Faster, Please! — The Podcast

Farmer is the Baillie Gifford Professor of Complex Systems at Oxford's Institute for New Economic Thinking. Before joining Oxford in 2012, he worked at Los Alamos National Laboratory and the Santa Fe Institute, where he studied complex systems and economic dynamics. During the 1990s, he took a break from academia to run a successful quantitative trading firm using statistical arbitrage strategies.

Farmer has been a pioneer in chaos theory and complexity economics, including the development of agent-based models to understand economic phenomena. His work spans from housing markets to climate change, and he recently authored Making Sense of Chaos exploring complexity science and economic modeling.

In This Episode

* What is complexity economics? (1:23)

* Compliment or replacement for traditional economics (6:55)

* Modeling Covid-19 (11:12)

* The state of the science (15:06)

* How to approach economic growth (20:44)

Below is a lightly edited transcript of our conversation.

What is complexity economics? (1:23)

We really can model the economy as something dynamic that can have its own business cycles that come from within the economy, rather than having the economy just settle down to doing something static unless it's hit by shocks all the time, as is the case in mainstream models.

Pethokoukis: What does the sort of economics that people would learn, let's say, in the first year of college, they might learn about labor and capital, supply-demand equilibrium, rational expectations, maybe the importance of ideas. How does that differ from the kind of economics you are talking about? Are you looking at different factors?

Farmer: We’re really looking at a completely different way of doing economics. Rather than maximizing utility, which is really the central conceptual piece of any standard economic model, and writing down equations, and deducing the decision that does that, we simulate the economy.

We assume that we identify who the agents in the and economy are, who's making the decisions, what information do they have available, we give them methods of making the decisions — decision-making rules or learning algorithms — and then they make decisions, those decisions have economic impact, that generates new information, other information may enter from the outside, they make decisions, and we just go around and around that loop in a computer simulation that tries to simulate what the economy does and how it works.

You've been writing about this for some time. I would guess — perhaps I'm wrong — that just having more data and more computer power has been super helpful over the past 10 years, 20 years.

It's been super helpful for us. We take much more advantage of that than the mainstream does. But yes, computers are a billion times more powerful now than they were when Herb Simon first suggested this way of doing things, and that means the time is ripe now because that's not a limiting factor anymore, as it was in the past.

So if you're not looking at capital and labor per se, then what are the factors you're looking at?

Well, we do look at capital and labor, we just look at them in a different way. Our models are concerned about how much capital is there to invest, what labor is available. We do have to assign firms production functions that tells, given an amount of capital and labor and all their other inputs, how much can the firms produce? That part of the idea is similar. It's a question of the way the decision about how much to produce is made, or the way consumers decide how much to consume, or laborers decide at what price to provide their labor. All those parts are different.

Another difference — if I'm understanding it correctly — is, rather than thinking about economies that tend toward equilibrium and focusing how outside shocks may put an economy in disequilibrium, you're looking a lot more at what happens internally. Am I correct?

We don't assume equilibrium. Equilibrium, it has two senses in economics: One is supply equals demand. We might or might not run a model where we assume that. In many models we don't, and if that happens, that's great, but it's an outcome of the model rather than an assumption we put in at the beginning.

There's another sense of equilibrium, which is that everybody's strategy is lined up. You've had time to think about what you're doing, I've had time to think about what I'm doing, we’ve both come to the optimal decision for each of us to make, taking the other one into account. We don't assume that, as standard models typically do. We really can model the economy as something dynamic that can have its own business cycles that come from within the economy, rather than having the economy just settle down to doing something static unless it's hit by shocks all the time, as is the case in mainstream models. We still allow shocks to hit our models, but the economy can generate dynamics even without those shocks.

This just popped in my head: To whom would this model make more intuitive sense, Karl Marx or Adam Smith?

Adam Smith would like these models because they really allow for emergent behavior. That is, Smith's whole point was that the economy is more than the sum of its parts, that we get far more out of specializing than we do out of each acting like Robinson Crusoes. Our way of thinking about this gets at that very directly.

Marx might actually like it too, perhaps for a different reason. Marx was insightful in understanding the economy as being like, what I call in the book, the “metabolism of civilization.” That is, he really did recognize the analogy between the economy and the metabolism, and viewed labor as what we put together with natural resources to make goods and services. So those aspects of the economy are also embodied in the kind of models we're making.

I think they both like it, but for different reasons.

Compliment or replacement for traditional economics (6:55)

There are many problems where we can answer questions traditional methods can't even really ask.

The way I may have framed my questions so far is that you are suggesting a replacement or alternative. Is what you're suggesting, is it one of those things, or is it a compliment, or is it just a way of looking at the world that's better at answering certain kinds of questions?

I think the jury is out to find the answer to that. I think it is certainly a compliment, and that we're doing things very differently, and there are some problems where this method is particularly well-suited. There are many problems where we can answer questions traditional methods can't even really ask.

That said, I think time will tell to what extent this replaces the traditional way of doing economics. I don't think it's going to replace everything that's done in traditional economics. I think it could replace 75 percent of it — but let me put an asterisk by that and say 75 percent of theory. Economists do many different things. One thing economists do is called econometrics, where they take data and they build models just based on the data to infer things that the data is telling them. We're not talking about that here. We're talking about theories where economists attempt to derive the decisions and economic outcomes from first principles based on utility maximization. That's what we're talking about providing an alternative to. The extent to which it replaces that will be seen as time will tell.

When a big Wall Street bank wants to make a forecast, they're constantly incorporating the latest jobless claims numbers, industrial production numbers, and as those numbers get updated, they change their forecasts. You're not using any of that stuff?

Well, no. We can potentially could ingest any kind of data about what's going on.

But they're looking at big, top-down data while you're bottom-up, you're sort of trying to duplicate the actual actors in the economy.

That is true, but we can adjust what's at the bottom to make sure we're matching initial conditions. So if somebody tells us, “This is the current value of unemployment,” we want to make sure that we're starting our model out, as we go forward, with the right level of unemployment. So we will unemploy some of the households in our model in order to make sure we're matching the state of unemployment right now and then we start our simulation running forward to see where the economy goes from here.

I would think that the advent of these large language models would really take this kind of modeling to another level, because already I'm seeing lots of papers on their ability to . . . where people are trying to run experiments and, rather than using real people, they're just trying to use AI people, and the ability to create AI consumers, and AI in businesses — it would have to be a huge advance.

Yes. This is starting to be experimented with for what we do. People are trying to use large language models to model how people actually make decisions, or let's say, to simulate the way people make decisions, as opposed to an idealized person that makes perfect decisions. That's a very promising line of attack to doing this kind of modeling.

Large language models also can tell us about other things that allow us to match data. For example, if we want to use patents as an input in our modeling — not something we're doing yet, but we've done a lot of studies with patents — one can use large language models to match patents to firms to understand which firms will benefit from the patents and which firms won't. So there are many different ways that large language models are likely to enter going forward, and we're quite keen to take advantage of those.

Modeling Covid-19 (11:12)

We predicted a 21.5 percent hit to UK GDP in the second quarter of 2020. When the dust settled a year later, the right answer was 22.1. So we got very close.

Tell me, briefly, about your work with the Covid outbreak back in 2020 and what your modeling said back then and how well it worked.

When the pandemic broke out, we realized right away that this was a great opportunity to show the power of the kind of economic modeling that we do, because Covid was a very strong and very sudden shock. So it drove the economy far out of equilibrium. We were able to predict what Covid would do to the UK economy using two basic ideas: One is, we predicted the shock. We did that based on things like understanding a lot about occupational labor. The Bureau of Labor Statistics compiles tables about things like, in a given occupation, how close together do people typically work? And so we assumed if they worked closer together than two meters, they weren't going to be able to go to their job. That combined with several other things allowed us to predict how big the shock would be.

Our model predicted how that shock would be amplified through time by the action of the economy. So in the model we built, we put a representative firm in every sector of the economy and we assumed that if that firm didn't have the labor it needed, or if it didn't have the demand for its product, or if it didn't have the inputs it needed, it wouldn't be able to produce its product and the output would be reduced proportional to any of those three limiting factors.

And so we started the model off on Day One with an inventory of inputs that we read out of a table that government statistical agencies had prepared for each sector of the economy. And we then just looked, “Well, does it have the labor? Does it have demand? Does it have the goods?” If yes, it can produce at its normal level. If it's lacking any of those, it's going to produce at a lower level. And our model knew the map of the economy, so it knew which industries are inputs to which other industries. So as the pandemic evolved day by day, we saw that some industries started to run out of inputs and that would reduce their output, which, in turn, could cause other industries to run out of their inputs, and so on.

That produced quite a good prediction. We predicted a 21.5 percent hit to UK GDP in the second quarter of 2020. When the dust settled a year later, the right answer was 22.1. So we got very close. We predicted things pretty well, industry by industry. We didn't get them all exactly right, but the mistakes we made averaged out so that we got the overall output right, and we got it right through time.

We ran the model on several different scenarios. At the time, this was in April of 2020, the United Kingdom was in a lockdown and they were trying to decide what to do next, and we tested several different scenarios for what they might do when they emerged from the full lockdown. The one that we thought was the least bad was keeping all the upstream industries like mining, and forestry, and so on open, but closing the downstream, customer-facing industries like retail businesses that have customers coming into their shop, or making them operate remotely. That was the one they picked. Already when they picked it, we predicted what would happen, and things unfolded roughly as we suggested they would.

The state of the science (15:06)

Mainstream models can only model shocks that come from outside the economy and how the economy responds to those shocks. But if you just let the model sit there and nothing changes, it will just settle down and the economy will never change.

I'm old enough to remember the 1990s and remember a lot of talk about chaos and complexity, some of which even made it into the mainstream, and Jurassic Park, which may be the way most people heard a little bit about it. It's been 30 years. To what extent has it made inroads into economic modeling at central banks or Wall Street banks? Where's the state of the science? Though it sounds like you're really taking another step forward here with the book and some of your latest research.

Maybe I could first begin just by saying that before Jurassic Park was made, I got a phone call and picked up the phone, and the other end of the line said, “Hi, this is Jeff Goldblum, have you ever heard of me?” I said, “Yeah.” And he said, “Well, we're making this movie about dinosaurs and stuff, and I'm going to play a chaos scientist, and I'm calling up some chaos scientists to see how they talk.” And so I talked to Jeff Goldblum for about a half an hour. A few of my other friends did too. So anyway, I like to think I had a tiny little bit of impact on the way he behaved in the movie. There were some parallels that it seemed like he had lifted.

Chaos, it's an important underlying concept in explaining why the weather is hard to predict, it can explain some forms of heart arrhythmias, we use it to explain some of the irregular behavior of ice ages. In economics, it was tossed around in the ’90s as something that might be important and rejected. As I described in the book, I think it was rejected for the wrong reasons.

I'm proposing chaos, the role it plays in here is that, there's a debate about business cycles. Do they come from outside? The Covid pandemic was clearly a business cycle that came from outside. Or do they come from inside the economy? The 2008 financial crisis, I would say, is clearly one that came from inside the economy. Mainstream models can only model shocks that come from outside the economy and how the economy responds to those shocks. But if you just let the model sit there and nothing changes, it will just settle down and the economy will never change.

In contrast, the kinds of models we build often show what we call endogenous business cycles, meaning business cycles that the model generates all on its own. Now then, you can ask, “Well, how could it do that?” Well, basically the only plausible way it can do that is through chaos. Because chaos has two properties: One is called sensitive dependence on initial conditions, meaning tiny changes in the present can cause large changes in the future; but the other is endogenous motion, meaning motion that comes from within the system itself, that happens spontaneously, even in very simple systems of equations.

Would something like consumer pessimism, would that be an external shock or would something more internal where everybody, they're worried about the futures, then they stop spending as much money? How would that fit in?

If the consumer pessimism is due to the fear of a nuclear war, I would say it's outside the economy, and so that's an external shock. But if it's caused by the fact that the economy just took a big nose dive for an internal reason, then it's part of the endogenous dynamics

I spent many years as a journalist writing about why the market's going up, the market's going down, and by the end of the day, I had to come up with a reason why the market moved, and I could — I wasn't always quite confident, because sometimes it wasn't because of a new piece of data, or an earnings report, they just kind of moved, and I had no real reason why, even though I had to come up . . . and of course it was when I was doing that was when people started talking about chaos, and it made a lot of intuitive sense to me that things seem to happen internally in ways that, at least at the time, were utterly unpredictable.

Yeah, and in fact, one of the studies I discuss in the book is by Cutler, Poterba, and Summers — the Summers would be Larry Summers — where they did something very simple, they just got the 100 largest moves of the S&P index, they looked up what the news was the next day about why they occurred in the New York Times, and they subjectively marked the ones that they thought were internally driven, versus the ones that were real news, and they concluded they could only find news causes for about a third of them.

There is always an explanation in the paper; actually, there is one day on the top 12 list where the New York Times simply said, “There appears to be no cause.” That was back in the ’40s, I don't think journalists ever say that anymore. I don't think their paper allows them to do it, but that's probably the right answer about two-thirds of the time, unless you count things like “investors are worried,” and, as I point out in the book, if the person who invests your money isn't worried all the time, then you should fire them because investors should worry.

There are internal dynamics to markets, I actually show some examples in the book of simple models that generate that kind of internal dynamics so that things change spontaneously.

How to approach economic growth (20:44)

I'm not saying something controversial when I say that technological change is the dominant driver of economic growth, at least for the economy as a whole.

You recently founded a company, Macrocosm, trying to put some of these ideas to work to address climate change, which would seem to be a very natural use for this kind of thinking. What do you hope to achieve there?

We hope to provide better guidance through the transition. We're trying to take the kind of things we've been doing as academics, but scale them up and reduce them to practice so they can be used day-in and day-out to make the decisions that policymakers and businesspeople need to make as the transition is unfolding. We hope to be able to guide policymakers about how effective their policies will be in reducing emissions, but also in keeping the economy going and in good shape. We hope to be able to advise businesses and investors about what investments to make to make a profit while we reduce emissions. And we think that things have changed so that climate change has really become an opportunity rather than a liability.

I write a lot about economic growth and try to figure out how it works, what are the key factors. . . What insights can you give me, either on how you think about growth and, since I work at a think tank, the kind of policies you think policy makers should be thinking about, or how should they think about economic growth, since that seems to be on top-of-mind in every rich country in the world right now?

I'm not saying something controversial when I say that technological change is the dominant driver of economic growth, at least for the economy as a whole. And we've spent a lot of time studying technological change by just collecting data and looking for the patterns in that data: What does the technology cost through time and how rapidly is it deployed? We've done this for 50 or 60 technologies where we look at past technological transitions, because typically, as a technology is coming in, it's replacing something else that's going out, and what we've seen are a couple of striking things:

One is, many technologies don't really improve very much over time, at least in terms of cost. Fossil fuels cost about the same as they did 140 years ago once you adjust for inflation. In fact, anything we mine out of the ground costs about the same as it did a hundred years ago.

In contrast, solar energy from solar photovoltaic panels costs 1/10,000th what it did when it was introduced in the Vanguard satellite in 1958. Transistors have been going down at 40 percent per year, so they cost about a billionth of what they did back in 1960. So some technologies really make rapid progress, and the economy evolves by reorganizing itself around the technologies that are making progress. So for example, photography used to be about chemistry and film. Photography now is about solid-state physics because it just unhitched from one wagon and hitched itself to another wagon, and that's what's happening through the energy transition. We're in the process of hitching our wagon to the technologies that have been making rapid progress, like solar energy, and wind energy, and lithium ion batteries, and hydrogen catalyzers based on green energy.

I think we can learn a lot about the past, and I think that when we look at what the ride should be like, based on what we understand, we think the transition is going to happen faster than most people think, and we think it will be a net saving of money

So then how do you deal with a wild card, which I think if you look at the past, nuclear power seems like it’s super expensive, no progress being made, but, theoretically, there could be — at least in the United States — there could be lots of regulatory changes that make it easier to build. You have all these venture capital firms pouring money into these nuclear startups with small reactors, or even nuclear fusion. So a technology that seems like it's a mature technology, it might be easy to chart its future, all of a sudden maybe it's very different.

I'm not arguing we should get rid of nuclear reactors until they run their normal lifetime and need to be gotten rid of, but I think we will see that that is not going to be the winning technology in the long run, just because it's going to remain expensive while solar energy is going to become dirt cheap.

In the early days, nuclear power had faced a very favorable regulatory environment. The first nuclear reactors were built in the ’50s. Until Three Mile Island and Chernobyl happened, it was a very regulatorily friendly environment and they didn't come down in cost. Other countries like France have been very pro-nuclear. They have very expensive electricity and will continue to do so.

I think the key thing we need to do is focus on storage technologies like green hydrogen. Long-term storage batteries have already come down to a point where they're beginning to be competitive; they will continue to do so. And in the future, I think we'll get solid-state storage that will make things quite cheap and efficient, but I don't think small modular reactors are going to ever be able to catch up with solar and wind at this point.

On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

Micro Reads

▶ Economics

* United States Economic Forecast - Deloitte

* The Hidden Threat to National Security Is Not Enough Workers - WSJ

▶ Business

* DOGE Can’t Do It All. Here’s What It Can Do. - Politico

* AI Startup Perplexity Closes Funding Round at $9 Billion Value - Bberg

▶ Policy/Politics

* US Homeland Security chief attacks EU effort to police AI - FT

* The Trump Bump: The Republican Fertility Advantage in 2024 - IFS

* House unveils AI ‘road map’ but punts on setting priorities - Wapo

* Did Tariffs Make American Manufacturing Great? - Cato

▶ AI/Digital

* Call ChatGPT from any phone with OpenAI’s new 1-800 voice service - Ars

* Homo-Silicus: Not (Yet) a Good Imitator of Homo Sapiens or Homo Economicus - SSRN

* Is AI finally ready to replace your doctor? - NS

* The Age of Quantum Software Has Already Started - WSJ

* This is where the data to build AI comes from - MIT

* The New AI Stock Pickers Are Destined to Disappoint - Bberg Opinion

▶ Clean Energy/Climate

* Fusion Start-Up Plans to Build Its First Power Plant in Virginia - NYT

* Will the World's First Nuclear Fusion Power Plant Be Built in Virginia? Here's Why We're Skeptical - SciAm

* The deepest hole on Earth: Inside the race to harness unlimited power from our planet's core - SF

* Dubai transforms into walkable city with air-conditioned paths - New Atlas

* Oklo inks record deal for using nuclear to power data centers - E&E

▶ Robotics/AVs

* AI Robots Are Coming, and They’ll Be Made in Asia - Bberg Opinion

▶ Space/Transportation

* Boeing Starliner crew’s long awaited return delayed to March - Wapo

▶ Up Wing/Down Wing

* What Could Go Right? The Best News of 2024 - The Progress Network

▶ Substacks/Newsletters

* Why Don’t EU Firms Innovate? The Hidden Costs of Failure - Conversable Economist

* Why Did the Industrial Revolution Happen? - Oliver Kim

* One Down, Many To Go - Hyperdimensional

* The Experience Curve - Risk & Progress

* The case for clinical trial abundance - Slow Borin

* Nuclear Waste: Yes, In (or Under) My Backyard - Breakthrough Journal

* Answer Time: Can We Imagine Pluralistic Futures? - Virginia’s Newsletter

* What just happened - One Useful Thing

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

The future will be built on the big ideas we dare to conjure up today. We know that the most groundbreaking ideas often seemed ludicrous or simply impossible when first dreamed up, from the telephone, to human flight, to artificial intelligence. The key was a willingness to be creative and test the limits.

While many of us might not consider ourselves creative people, Duncan Wardle assures us that we can take our ideas and brainstorms to the next level, no matter who we are or what we do. Today on Faster, Please! — The Podcast, Wardle and I explore some concrete tools for breaking down our own barriers to innovation and accessing the genius within all of us.

Wardle is the former Head of Innovation and Creativity at Disney and founder of ID8. He has delivered multipl eTED Talks and teaches innovation Master Classes at Yale,Harvard, and the University of Edinburgh. His interactive book, The Imagination Emporium: Creative Recipes for Innovation has just been released.

In This Episode

* Creativity is learnable (1:37)

* Building a career of creativity (8:09)

* Tools for unlocking innovation (13:50)

* Expansionist vs. reductionist tools (18:39)

* Gamifying learning (25:20)

Below is a lightly edited transcript of our conversation.

Creativity is learnable (1:37)

I believe we're all born creative with an imagination. We're all born curious. We're all born with intuition. We're all born with empathy. They may not have been the most employable skill of our entire careers. They are now.

Pethokoukis: One of my favorite economists, Paul Romer, loves to use recipes as a metaphor to explain how innovation works in an economy. Like cooking recipes, innovation and ideas can be used repeatedly without being used up, you can combine different ideas as ingredients and create something new. I love that idea, and I love the way you present the book as kind of a recipe book you can sort of dip in and out of to help you be more creative and innovative.

How should someone use this book, and who is it broadly for?

Wardle: Me. Seriously. When I say me, I mean the busy, normal, hardworking person who says 10 times a day, “I don't have time to think.” And often considered the number one barrier to innovation and creativity: “I don't have time to think.” And I thought, “Okay, when you walk into a business office and you will look around, where's the book?” It's on the bookshelf, it's on the coffee table — nobody reads them. I thought, “Well, that's a waste of their money.” So I thought, “What book have I ever read — nonfiction — that I could read one page, know exactly what I need to do, and don't have to read the rest of the book today?” I thought, “My mom's cookbook! You want shepherd's pie? You go to page 67.” So I've designed the contents page the same way. It says, “Have you ever been to a brainstorm where nothing ever happened? Go to page 14. Fed up with your boss, shooting your ideas down? Go to page 12.”

So it is designed to be hop in and hop out, but I also designed the principles around: take the intimidation out of innovation, make creativity tangible for people who are uncomfortable with ambiguity and gray, far more importantly, make it fun, give people tools they choose to use when you and I are not around. I also designed it around this principle and I'll see if this works: Close your eyes for me for a second. How many days are there in September?

31?

Well, we'll pretend it's 30.

Or 30! That's the one thing I always confuse, which is the 30 and the 31.

Close your eyes for a second. Just think about how you might have known there were 30 days in September. How might you have remembered? What might you have learned or what can you see with your eyes closed?

Well, if I was a more melodic, musical person, loved a good rhyme, I might've used that very famous rhyme, which apparently I don't know very

Well, that's okay, neither do I, but I'll attempt it. About 30 percent of people go, “30 days has September, blah, blah, blah, and November.” They've just told me they're an auditory learner. That's their preferred learning style. They probably read a lot. How do I know that? Because when they learned it, they were six. When I asked the question, they learned it because they'd heard it.

I'm sure you've seen somebody at some point in your life count their knuckles: January, February, March, April, May, June, July, et cetera. You may not remember this because you might not be a kinesthetic learner. Those are the people who learn by doing. Again, how do we know this? They learned it when they were six. How did they remember it? By doing it.

And then 40 percent of an audience would just go, “No, no, I could just see a calendar with a number 30.” They're your visual learners. So I've designed the book to appeal to all three learning styles. It has a QR code in each chapter with a Spotify playlist for the auditory learners, animated videos where Duncan is now an animated character (who knew?) who pops out with a bunch of characters to tell you how to use the tools. And then hopefully, as of next Tuesday, the QR code on the back for kinesthetic learners will allow you to engage with the book and learn kinesthetically through artificial intelligence and ChatGPT and actually ask the book questions.

The fundamental conceit of the book, though, is that being innovative, being creative, that can be learned. You can get better at it. Some people say, “I'm not a math person,” which I also don't believe. They'll say, “I'm not a super creative person. I'm not super innovative.” One, I'm assuming you think that's wrong; and two, you mentioned AI, if people are worried about robots doing more repetitive kinds of tasks, then having the tools to bring out or enhance that imagination seem more important now than ever.

There's one thing I firmly believe in: We were all born a human, shockingly enough, and when you were given a gift for a holiday, perhaps, it came in an enormous box and it took you ages of time to take the toy out of the box because the box was the same height as you were. What do you spend the rest of the week playing with?

I love a good box.

Right? It was your castle, it was your rocket.

Love a good box. Oh man, that box can be a time machine, anything.

It was anything you wanted it to be until you went to the number one killer of creativity in imagination: western education, and the first thing you were told to do was, “Don't forget the color in between the lines.” Children are very curious. They ask, “Why, why, why, why?” Again, because they're after the insight for innovation. The insight for innovation comes on the sixth or seventh, why not the first one?

If I were to survey you and ask you, “Why do you go to Disney on holiday?” People would say they go for the new attractions. But that's not strictly true, is it?

So if you say, “Well, why do you go for the new attractions?”

“Well, no, I like the classics.”

“Well, why do you like the classics?” Why?

“I like It's a Small World.”

“Well, why do you like It’s a Small World?”

“I remember the music.”

“Why the music?”

“Well, that's my mom's favorite ride. We used to go every summer.”

“Why is that important to you 25 years later?”

“Oh, I take my daughter now.”

There's your insight for innovation. It has nothing to do with the capital investment strategy whatsoever and everything to do with that person's personal memory and nostalgia. But then we go to the number one killer of curiosity: western education. And the next thing our teacher tells us to do is stop asking “why,” because there's only one right answer.

We know when somebody is staring at the back of our head. When you've stared at the back of the head of somebody that you think is really hot, a stranger, they turn around and look at you. You have to look away really quickly. It's okay, we've all done it. We have 120 billion neurons in our first brain and 120 million neurons in our second brain, the brain with which we say we make lots of our decisions, when we say “with our gut.” We are all empathetic.

I believe we're all born creative with an imagination. We're all born curious. We're all born with intuition. We're all born with empathy. They may not have been the most employable skill of our entire careers. They are now. Why? Because I've been working with Google on DeepMind with their chief programmer — this is the AI program — and I asked her, “How the hell am I going to compete with this? How will any of us compete with this?” She said, “Well, by developing the things which will be the hardest for her to program into AI.” And I asked her what they were. She said, “The ones with which you were born: creativity, imagination, curiosity, empathy, and intuition.”

Will they be programmed one day? Interestingly enough, she said intuition will go first. I was like, oh, that hurt. So I said, “Why intuition?” She said, “It's built on experience and we could build an algorithm that will give them experience.” I'm like, oh, so will they be programed one day? Perhaps. Anytime in the short term? No.

Building a career of creativity (8:09)

Your subconscious brain is 87 percent of the capacity. Every innovation you've ever seen, every creative problem you've ever solved, is back here to work as unrelated stimulus, but when the door is shut, you can't access it. So what do I do? I'm playful. I'm deliberately playful.

In a moment, I want to briefly roll through the book, but first I want to ask about your job as the former head of innovation and creativity at Disney, which sounds like a fake job. It sounds like the kind of job someone would dream up and they wish there was such a job. It sounds like a dream job, but that was a real job. And what did you do there? Because it sounds fairly awesome.

I finished as Head of Innovation — I didn't start that way. I started as a coffee boy in the London office. In 1986, I used to go and get my boss six cappuccinos a day from Bar Italia, and about three weeks into the role, I was told I would be the character coordinator, the person that looks after the walk-around characters at the Royal Premier of Who Framed Roger Rabbit in the presence of the Princess of Wales, Diana. I was like, “What do I do?” They said, “Well you just stand at the bottom of the stairs, Roger Rabbit will come down the stairs, the princess will come in on the receiving line, she'll greet him or blow him off and move into the auditorium.” How could you possibly screw that up? Well, I could. That was the day when I found out what a contingency plan was, because I didn't have one.

A contingency plan would tell you, if you're going to bring a very tall rabbit with very long feet down a very large staircase towards the Princess of Wales, one might want to measure the width of the steps first before Roger trips on the top stair, is now hurdling like a bullet, head over feet at torpedo speed directly down the stairs towards Diana's head, whereupon he was taken out by two royal protection officers. There’s a very famous picture of Roger being taken out on the stairs and a 21-year-old PR guy in the background from Disney. “Oh s**t, I'm fired.” I got a call from somebody called a CMO — didn't know who that was, I thought I was going to tell me I'm fired. He goes, “That was great publicity.” I was like, “Wow, I can make a career out of this.”

So for the first 20 years I had some of the more mad, audacious, outrageous ideas for Disney, and then Disney purchased Pixar, then they purchased Marvel, then they purchased Lucasfilm, and we found that we all had different definition of creativity and different innovation models. I tried four models of innovation.

Number one, I hired an outside consultant and said, “Make me look good.” They were very good at what they did, but they weren't around for execution and they weren't going to show us how they did what they did. They were worried we wouldn't hire them again.

Model number two, innovation team. Duncan will be in charge. What could possibly go wrong? Well, when you have a legal team, nobody outside of legal does legal. When you have a sales team . . . So when you have an innovation team, the subliminal message you've sent to the rest of the organization is: You are off the hook, we've got an innovation team.

Third model was an accelerator program where we were bringing some young tech startups and take a 50-50 stake in their business. They could help us bring it to market much quicker than we could. We could help them scale it. But we had failed in the overall goal that Bob Iger had set for us: How might we embed a culture of innovation and creativity into everybody's DNA? So I set out to create a toolkit. A toolkit that takes the intimidation out of innovation, makes creativity tangible, and the process fun. And essentially, that's what the book is. It's not a book, it's a toolkit. Why? Because I want you to use it. It's broken up into creative behaviors, which I think if you don't get the creative behaviors right, the tools won't matter. They'll just be oblivious. I think the creative behaviors are the engine, and I'll explain what I mean by that.

Let me ask you a question. Close your eyes if you would?

I've done very poorly on the questions. Very poorly, but I will continue to answer them.

Where are you usually, and what are you doing when you get your best ideas?

I would say either on walks or, I think a lot of people say, in the shower, one of the two.

There we go. Alright. But here's the thing. I've done it with 20,000 people in the audience. Do you know how many people say at work? Nobody ever says at work. Why do we never have our best ideas at work?

Well, think about that last argument you were in. You turn to walk away from that argument, now you're still a bit angry, but you're beginning to relax, you're 10 seconds away, 20 seconds, and what pops into your brain? The killer one liner, that one perfect line you wish you'd used during but you didn't, did you? No. Why? Because when you are in an argument, your brain is moving at a thousand miles an hour defending yourself.

When you're in the office, you're doing emails, reports, quarterly results, and meetings. And I hear myself say, “I don't have time to think.” When you don't have time to think, the door between your conscious and subconscious brain is firmly closed. You're in the brain state called beta, and you're only working with your conscious brain. 90 percent of your working day — you can look this up — your conscious brain is 13 percent of the capacity of your brain. Your subconscious brain is 87 percent of the capacity. Every innovation you've ever seen, every creative problem you've ever solved, is back here to work as unrelated stimulus, but when the door is shut, you can't access it. So what do I do? I'm playful. I'm deliberately playful. There's a chapter of energizers in the book. They’re 60-second exercises. What are they for? To make you laugh, laughter with purpose.

What's an example of one of those?

Okay, I'll tell you what then, you are the world's leading designer of parachutes for elephants. I will now interview you about your job. So question, “How did you get into this industry in the first place?”

I was actually interviewing for a different job, I walked in the wrong door, and I ended up interviewing for that job.

Okay, and do you have to use different material for the parachutes? What are the parachutes made of? How big are they? Do you have to make bigger ones for elephants with smaller ears and smaller ones for elephants with big ears, the African and Indian elephants?

Thankfully the kind of material is changing all the time. A lot of advances: graphene, nanotechnology materials. So the kind of material is changing, which actually gives us a lot more flexibility for the kind of material and the sizes, depending, of course, on the size of the elephants and perhaps even their ears, and tails, and tusks.

So we'll stop there. You do that in a room full of people and you'll hear laughter. And the moment I hear laughter, I've opened the door between your conscious subconscious brain and placed you metaphorically back in the shower where you are when you have your best idea. I don't expect people to be playful every minute of every day. I do expect, particularly leaders, to be playful when they're trying to get other people to open up their brains and have big ideas.

Tools for unlocking innovation (13:50)

If you like breaking rules, this tool is for you. It's about breaking rules metaphorically. So step one, you list the rules of your challenge. Step two, you take one and ask the most audacious question. Step three, you land a big idea.

In the book, you sort of create these three animated characters representing . . . there's Spark who represents creative behaviors; Nova, innovation tools; and then Zing for these energizing exercises. But you sort of need all three of those?

You do, but you don't have to know them all at the same time, and that's the beauty of the book. But here's the thing: I created a character called Archie. Archie was a direct descendant of Archimedes, because when I ask people where they are when they get the best ideas, they say the shower. Archimedes was in the bath. And my daughter, who’s about 25, walks in the room and she goes, “Dad, he's an old white guy. You are an old white guy. You can't do that s**t anymore.” So I created three new characters. Spark is male, introduces creative behaviors; Zing, gender-neutral, introduces the energizers; and Nova, the brains of the organization, introduces innovation tools. The tools are split between what I call expansionist tools and reductionist tools. The more expertise and the more experience we have, the more reasons we know why the new idea won't work.

But here's the challenge: Up until 2020, we pretty much got away with doing what we did, and then came a global pandemic, enormous climate change, generation Z entering the workplace who don't want to work for us, and here comes AI. We don't get to think the way we thought four years ago. So the tools are designed specifically to stop you thinking the way you always do and give you permission to think differently.

I'll give you an example of one, it's called “What If.” A lot of people will say, “Oh, but we work in a very heavily regulated industry.” If you like breaking rules, this tool is for you. It's about breaking rules metaphorically. So step one, you list the rules of your challenge. Step two, you take one and ask the most audacious question. Step three, you land a big idea. So for example, it was created by Walt, but that's in the book, I won't go through the whole Walt Disney story because I want people to understand that this tool can work for them too.

There was a very tiny company in Great Britain in the late ’60s, before the days of mass automation, that used to make glasses that we drink out of, and they found too much breakage and not enough production when the glasses were being packaged and shipped. So they went down to the shop floor, observed the process for eight hours, and just wrote down the rules. Don't think about them, because then you'll think of all the reasons you can't break them, just write them down. So they wrote them down. 26 employees convey about cardboard box, six glasses on the top, six on the bottom, separated by corrugated cardboard, glasses wrapped in newspaper, employees’ reading newspaper. So somebody asked these somewhat provocative “what if” question, “What if we poke their eyes out?” Well, that's against the law and it's not very nice, but because they had the courage to ask the most audacious “what if” question of all, the lady sitting next to them immediately got out of her river of thinking — her expertise and experience — and said, “Well, hang on a minute, why don't we just hire blind people?” So they did. Production up 26 percent, breakage down 42 percent, and the British government gave them a 50 percent salary subsidy for hiring people with disabilities. Simple, powerful, fun.

You just mentioned briefly this notion of the river of thinking, which is sort of your thoughts and the assumptions that really come from your lifetime of experience. People obviously really, when evaluating ideas, they really value their own personal experience. You could have a hundred studies saying this will work, but if something about their personal experience says it won't, they won't listen to it. Now, I believe experience is important, it helps you make judgments, but sometimes I think you're right, that it's an absolute trap that leads us to say no when we should say yes, and yes when we should say no.

So that was one of the expansionist tools. One of the reductive tools is ideas. Ideas are the most subjective thing on the planet. You like pink, I like green, our boss likes yellow, there's a very good chance we're going to be doing the yellow idea. Well, wait a minute, was that the right one targeted for our consumer? Was it aligned with our brand? So there's a tool called stargazer. I borrowed it with pride from Richard Branson of Virgin. Virgin is the most elastic brand on the planet, right? They've done condoms, they've done space travel, and everything in between. Disney is a non-elastic brand. They do family magical experiences. So how does Virgin decide, of all these ideas they get pitched, how do they decide which ones to bring to market?

They have a tool, I call it stargazer, it looks like a starfish, it's got five prongs on it, you'll see it in the book, and each one has three criteria, and you can make up your own criteria at the beginning of the project. Let's say, is this a strategic brand fit? Is this aligned with who we stand for as a brand? Is this embedded in consumer truth? Is it relevant to our consumer? Can I get this into the market the next 18 to 24 months? Is it going to hit my financial goals? And is it socially engaging? Is it going to get people excited? And all you do with all of your ideas at the end is go around those five criteria and ask, does this do a poor job, a good job, or an outstanding job of being aligned with our brand, a poor job, a good job, or an outstanding job of being targeted at our consumer, relevant to our consumer? And then guess what? With different colors for each idea, you join the dots just as you did when you were a kid. And one idea will rise to the top as to meeting your criteria, objectives, the most, not the one you like the best.

Expansionist vs. reductionist tools (18:39)

I define creativity as the ability to have an idea. We all have hundreds a day. I define innovation is the ability to get it done. That's the hard part, and that's what the tools are designed and helping you with.

Do you think that the book and your approach is most helpful in helping people be more creative and come up with ideas or helping other people judge ideas as being good ideas and being open to ideas and closed to the wrong ideas?

I think people use confusing terms just to make themselves more intelligent. The amount of times I've been in a meeting and somebody used an acronym, nobody knows what it is, but nobody's going to put their hand up. I call it expansionist and reductionist, the official name is divergent and convergent, who cares? Expansionist tools are the ones that help you get out of your river of thinking and help you think differently, and the reductionist tools are okay, now we've got all of these ideas, which one goes to market, how do we take it to market, how do we actually get it done?

A lot of people say, as you said at the beginning, “I'm not creative.” Well, if you define yourself as a musician or an artist, then guess what? I'm not creative either. I define creativity as the ability to have an idea. We all have hundreds a day. I define innovation is the ability to get it done. That's the hard part, and that's what the tools are designed and helping you with.

If you're running a business and you're like, “I want to implement this,” how do you . . . I'm sure you would love this, buy everybody the book, buy everybody three copies of the book. How do you implement it? I mean, I'm just curious how you do that job.

How do I do the job? Or how does the business?

How would someone do that job if they're like, I'm trying to make my workforce more creative, I'm trying to make sure that we are open to good ideas. How do you institute that at an existing business?

Here's a tool that can change a culture overnight: Now you and I have been tasked with coming up with an idea for a birthday party. We've been given a $100,000, which is a reasonable budget for a birthday party. The theme could be Star Wars or Harry Potter. What would you like it to be?

I'd probably go with Star Wars.

Okay, so I'm going to come at you some amazing ideas for a Star Wars birthday. I'd like you to start each and every response with the words “No, because.” They'll be the first two words you use in each response, and then you'll tell me why not.

So I was thinking of coming to your house, painting your kitchen dark, turn it into the Death Star canteen, and we'll have a food and wine festival from Hoth and Naboo and Tatooine.

No, no, no. We can't do that because I like the way it looks now, I'm worried about repainting it and matching those colors. That's too significant of a change.

What if, then, we just turn the lights out, we do a glow-in-the dark lightsaber fight full of our favorite alcoholic liquid?

Well, that sounds like a better idea. Am I still supposed to say “no, because?”

“No, because.” Stay on the “no, because.”

No, can't do it. Listen, I worry about those lightsabers breaking, I'll be honest with you, and that alcohol flying over the place. Also, there are going to be kids there, and I just worry about the alcohol aspect. Because I’m an American, and we're very tight.

So perhaps if there's kids there, we could do a cosplay party, and all the tall people could come as Vader and all the little people could come as ewoks.

No, because I think some of the tall people would like to be the good guy, and I think some of the people who are not quite as tall might feel we were infantilizing them by turning them into ewoks.

I’ll tell you what, then, we'll do a movie marathon and we’ll show all seven films back-to-back with some popcorn and coke. What do you say?

No, because that would be a really long event. I think people would be super sick of even watching their favorite movies after about two movies, so can't do it.

Alright, so we'll stop there. When somebody's constantly saying “no, because” to you, how does that make you feel?

Like I really don't feel like coming up with any more ideas and like they will just not get to “yes.”

And we started there with a food and wine festival and we ended up with showing the movies. Would you say the idea was getting bigger as we were going, or was it getting smaller? Which direction was it?

It was getting progressively smaller and less imaginative.

So let's try that again. Can we do Harry Potter?

Well, I don't know as much, but I'll do my best.

Okay, so have you seen a couple of the films?

Kind of?

You pick the theme, then. What do you want?

Marvel. A beautifully licensed property. Yes, Marvel.

I'm going to come at you with some ideas for a Marvel party. I'd like you to start each and every response this time with the words, “yes, and,” and we'll just build it together, okay?

I tell you what, we could do a Spider-Man party where everybody gets those little web things that they could shoot out of their hands, but are actually made out of cotton candy, so we could eat it, we could eat the webs.

Oh yes, and perhaps we could have villain-themed targets the shoot at?

Oh, yes, and we could have a room full of superheroes and a room full of villains, and we have cosplay party and there'll even be a make-your-own Iron Man suit!

Yes, we can have an Iron Man suit, obviously, and we can have the other costumes, and perhaps some of their other tools, like Thor’s hammer, those could somehow also be candy-related.

Oh yes, and we could actually invite the stars of the film, we could have Chris Hemsworth, Robert Downey, Jr., and Chris Pratt, and Rocket, and Groot.

Yes. Love the idea. And perhaps if that's not quite possible —

— That was a “no, because!”

Oh that sounded like a “no.”

Come on, come on.

We've reached the limits of my creativity.

We'll stop there. A couple of observations: a lot more laughter, a lot more energy.

Bigger or smaller?

We're taking our steps into an ever-wider world!

We work in big organizations, we work in small organizations, we have colleagues, we have constituencies, we have bosses, we have local regulators, et cetera, to bring on board with our ideas. By the time we just finished building that idea together, whose idea was it by the time we'd finished?

That is lost to the fog of history. It is now a collaborative idea that we both can take credit for when it's a huge success.

Ours. Two very simple words from the world of improv that have the power to turn a small idea into a big one really quickly. You can always value-engineer a big idea back down again, but you can't turn a small idea into a big idea. Far more importantly, it transfers the power of “my idea,” which we know never goes anywhere outside an organization, to “our idea” and accelerate its opportunity to get done.

For people listening today, I'll give you one word of advice to take away: Don't let the words “no, because” be the first two words you use when somebody comes bouncing into your office with an idea you are not thinking of. They may have genius two seconds from now, two weeks from now — they ain't coming back.

Just remind yourselves: I know you have responsibilities, I know you've got deadlines, I know you've got quarterly results. We are not green-lighting this idea for execution today, we are mainly green-housing it together using “yes, and.”

Gamifying learning (25:20)

Gaming is the future of education, there's no question.

So now I have one more question I think that's super valuable advice, actually. As you were talking about western education squashing the creativity. . . Do you have you any thoughts about how to change that, keeping the best of what we do?

Gamify. Gamify everything. Gaming is the future of education, there's no question. Universities will fall, but why will universities fall? That's a fairly outrageous statement. Well, let me think. Blue-collar workers, the white collar workers laughed at them because they didn't go to university. Let me think — people who use their hands, artificial intelligence, probably not taking them out anytime soon. White collar workers, not so much. Goodbye. Not quite, that's a slight exaggeration, but universities are teaching the same thing that we learned.

So I walk into a classroom, a professor says, “In the year 3 AD, Brutus stabbed Julius Caesar in the back on the steps of the Senate of Rome.” Okay, well I'm asleep already. However, if I could walk into the Senate in Rome, in virtual reality, or in Apple Vision Pro — hello, thank you very much — walk right up to Julius Caesar and Brutus debating with the senators and say, “Hey Julius, look behind you!”

I tell you for why: My son sat down at the breakfast table many years ago, he was probably about 13 or 14 at the time, and he said, “Do you know the Doge’s Palace in Venice was built in 14 . . .” And he went on this whole diatribe. I was like, where the hell did you learn that? He goes, “Oh, Assassin's Creed.” Gaming will annihilate.

See, when you say online training, the first words out of somebody's mouth are, “Boring!” So, what I aim to develop within a year from today is to gamify the Imagination Emporium and actually help people, train them how to be more imaginative using gaming.

On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

Micro Reads

▶ Economics

* AI and the Future of Work: Opportunity or Threat? - St. Louis Fed

* Industrial policies and innovation in the electrification of the global automobile industry - CEPR

▶ Business

* What Is Venture Capital Now Anyway? - NYT

* When IBM Built a War Room for Executives - IEEE

▶ Policy/Politics

* How U.S. Firms Battled a Government Crackdown to Keep Tech Sales to China - NYT

* Was mocking Musk a mistake? Democrats think about warmer relationship with the billionaire - Politico

* Recent Immigration Surge Has Been Largest in U.S. History - NYT

* The DOJ’s Misguided Overreach With Google Is An Opportunity for Trump - AEI

* Harding, Coolidge and the Forerunner of DOGE - WSJ Opinion

* We Are All Mercantilists Now - WSJ Opinion

* Exclusive: Trump transition recommends scrapping car-crash reporting requirement opposed by Tesla - Reuters

* Trump’s Treasury Pick Is Poised to Test ‘Three Arrows’ Economic Strategy - NYT

* This Might Be the Last Chance for Permitting Reform - Heatmap

▶ AI/Digital

* Are LLMs capable of non-verbal reasoning? - Ars

* Google’s new Project Astra could be generative AI’s killer app - MIT

* The Mystery of Why ChatGPT Couldn’t Say the Name ‘David Mayer’ - WSJ

* OpenAI’s ChatGPT Will Respond to Video Feeds in Real Time - Bberg

* Google and Samsung’s first AI face computer to arrive next year - Wapo

* Why AI must learn to admit ignorance and say 'I don't know' - NS

* AI Pioneer Fei-Fei Li Has a Vision for Computer Vision - IEEE

* Broadcom soars to $1tn as chipmaker projects ‘massive’ AI growth - FT

* Chip Cities Rise in Japan’s Fields of Dreams - Bberg Opinion

* Tetlock on Testing Grand Theories with AI - MR

* The mysterious promise of the quantum future - FT Opinion

▶ Biotech/Health

* RFK Jr.’s Lawyer Has Asked the FDA to Revoke Polio Vaccine Approval - NYT

* Designer Babies Are Teenagers Now—and Some of Them Need Therapy Because of It - Wired

* The long shot - Science

▶ Clean Energy/Climate

* What has four stomachs and could change the world? - The Economist

* Germany Sees Huge Jump in Power Prices on Low Wind Generation - Bberg

▶ Space/Transportation

* NASA’s boss-to-be proclaims we’re about to enter an “age of experimentation” - Ars

* Superflares once per Century - MPI

* Gwynne Shotwell, the woman making SpaceX’s moonshot a reality - FT Opinion

▶ Substacks/Newsletters

* The Changing US Labor Market - Conversable Economist

* How we'll know if Trump is going to sell America out to China - Noahpinion

* Can RFK Kneecap American Agriculture? - Breakthrough Journal

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Washington’s initial thinking about AI regulation has evolved from a knee-jerk fear response to a more nuanced appreciation of its capabilities and potential risks. Today on Faster, Please! — The Podcast, I talk with technology policy expert Neil Chilson about national competition, defense, and federal vs. state regulation in this brave new world of artificial intelligence.

Chilson is the head of AI policy at the Abundance Institute. He is a lawyer, computer scientist, and former chief technologist at the Federal Trade Commission. He is also the author of “Getting Out of Control: Emergent Leadership in a Complex World.”

In This Episode

* The AI risk-benefit assessment (1:18)

* AI under the new Trump Administration (6:31)

* An AGI Manhattan Project (12:18)

* State-level overregulation (15:17)

* Potential impact on immigration (21:15)

* AI companies as national champions (23:00)

Below is a lightly edited transcript of our conversation.

The AI risk-benefit assessment (1:18)

Pethokoukis: We're going to talk a bit about AI regulation, the future of regulation, so let me start with this: Last summer, the Biden administration put out a big executive order on AI. I assume the Trump administration will repeal that and do their own thing. Any idea what that thing will be?

We have a lead on the tech, we have the best companies in the world. I think a Trump administration is really going to amp up that rhetoric, and I would expect the executive order to reflect the need to keep the US and the lead on AI technology.

Chilson: The Biden executive order, repealing it is actually part of the GOP platform, which does not say a lot about AI, but it does say that it's definitely going to get rid of the Biden executive order. I think that's the first order of business. The repeal and replace process . . . the previous Trump administration actually had a couple of executive orders on AI, and they were very big-picture. They were not nearly as pro-regulatory as the Biden executive order, and they saw a lot of the potential.

I'd expect a shift back towards a vision of AI as a force for good, I'd expect to shift towards the international dynamics here, that we need to keep ahead of China in AI. We have a lead on the tech, we have the best companies in the world. I think a Trump administration is really going to amp up that rhetoric, and I would expect the executive order to reflect the need to keep the US and the lead on AI technology.

That emphasis differs from the Biden emphasis in what way?

The Biden emphasis, when you read the executive order, it has some nice language up top about how this is a great new technology, it's very powerful, but overwhelmingly the Biden executive order is directed at the risk of AI and, in particular, not existential risk, more the traditional risks that academics who have talked about the internet have had for a long time: these risks of bias, or risks to privacy, or risks to safety, or deepfakes. And to be honest, there are risks to all of these technologies, but the Biden executive order to really pounded that home, the emphasis was very much on what are the problems that this tech could cause and what do we as the federal government need to do to get in here and make sure it's safe for everybody?

I would expect that would be a big change. I don't see, especially on the bias front, I don't see a Trump administration emphasizing that as a primary thing that the federal government needs to fix about AI. In fact, with people like Elon Musk having the ear of the president, I would expect maybe to go in the opposite direction, that these ideas around bias are inflated, that these risks aren't really real, and, to the extent that they are, that it's no business of the federal government to step in and tell companies how to bias or de-bias their products.

One thing that sort of confuses me on the Elon Musk angle is that it seemed that he was — at least used to be — very concerned about these somewhat science-fictional existential risks to AI. I guess my concern is that we'll get that version of Musk again talking to the White House and maybe he says, “I'm not worried about bias, but I'm still worried about it killing us all.” Is there any concern there, that that theme, which I think seems to have faded a little bit from the public conversation (maybe I'm wrong) that that will reemerge.

I agree with you that I think that theme has faded. The early Senate hearings were very much in that vein, they were about the existential risk, and some of that was the people who were up there talking. This is something that's been on the mind of some of the leaders of the cutting edge of the tech space, and it's part of the reason why they got into it. There's always been a tension there. There is some sort of dynamic here where they're like, “This stuff is super dangerous and super powerful, so I need to be the one creating it and controlling it.” I think Musk still kind of falls in that bucket, so I share a little bit of that concern, but I think you're right that Congress has said, “Oh, those things seem really farfetched. That's not how we're going to focus our time.” I would expect that to continue even with a Musk-influenced administration.

I actually don't think that there is necessarily a big tension between that and a pushback against the sort of red-tape regulatory approach to AI that was kind of the more traditional pessimistic, precautionary approach to technology, generally. I think Musk is a guy who hates red tape. I think he's seen it in his own businesses, how it's slowed down launches of all sorts. I think you can hate red tape and be worried about this existential risk. It's not necessarily in intentioned, but it'll be interesting to see how those play out, how Musk influences the policy of the Trump administration on AI.

AI under the new Trump Administration (6:31)

One issue that seemed to be coming up over and over again is differing opinions among technologists, venture capitalists, about the open-source issue. How does that play out heading into a Trump administration? When I listen to the Andreessen Horowitz podcast, those guys seem very concerned.

They're going to get this software. They're going to develop it themselves. We can't out-China China. We should lean into what we're really good at, and that is a dynamic software-development environment, of which open source is a key component.

So there's a lot of disagreements about how open source plays out. Open source, it should be pointed out first, is a core technology across everything that people who develop software use. Most websites run on open source software. Most development tools have a huge open source component, and one of the best ways to develop and test technology is by sharing it with people and having people build on it.

I do think it is a really important technology in the AI space. We've seen that already, people are building smaller models, doing new things in open source that it costs a lot of money to do in the first instance, maybe in a closed source.

The concerns that people raise is that this, especially in the national security space or the national competition, that this sort of exposes our best research to other countries. I think there's a couple of responses to that.

The first one is that closed source is no guarantee that those people don't have that technology as well. In fact, most of these models fit on the thumb drive. Most of these AI labs are not run like nuclear facilities, and it's much easier to smuggle a thumb drive out than it is to smuggle a gram of plutonium or something like that. They're going to get this software. They're going to develop it themselves. We can't out-China China. We should lean into what we're really good at, and that is a dynamic software-development environment, of which open source is a key component.

It also offers, in many ways, an alternative to centralized sources of artificial intelligence models, which can offer a bunch of user interface-based benefits. They're just easier to use. It's much easier to log into OpenAI and use their ChatGPT than it is to download and build your own model, but it is really nice as a competitive gap filler to have thousands and thousands of other that might do something specific, or have a specific orientation, which you can train on your own. And those exist because of the open source ecosystem. So I think it solves a lot of problems, probably a lot more than it creates.

So what would you expect — let's focus on the federal level — for this congress, for the Trump administration, to do other than broadly affirm that we love AI, we hope it continues? Will there be any sort of regulatory rule, any sort of guidance, that would in any way constrain or direct this technology? Maybe it's in the area of the frontier models, I don't know.

I think we're likely to see a lot of action at the use level: What are the various uses of various applications and how does AI change that? So in transportation and healthcare . . . this is a general purpose technology, and so it's going to be deployed in lots of spaces, and a lot of these spaces already have a lot of regulatory frameworks in place, and so I think we'll see lots of agencies looking to see, “Hey, this new technology, does it really change anything about how we regulate medical devices? If it does, how do we need to accommodate that? What are the unique risks? What are the unique opportunities that maybe the current framework doesn't really allow for?”

I think we'll see a lot of that. I think, once you get up to the abstract model level, it's much harder to figure out what problem both are we trying to solve at the model level and do we have the capability to solve at the model level. If we're worried about people developing bio weapons with this technology, is making sure the model doesn't allow that, is that useful? Is it even possible? Or should we focus those attentions maybe down on, people can't secure the components that they need to execute a biohazard? Would that be a more productive place? I don't see a lot of action, honestly, at the model level.

Maybe there'll be some reporting requirements or training requirements. The executive order had those, although they used something called the Defense Production Act — I think probably unconstitutionally, how they use that. But that's going to go away. If that gets filled in by Congress, that there's some sort of reporting regime — maybe that's possible, but Congress doesn't seem to be able to get those types of really high-level tech regulations across the line. They haven't done it with privacy legislation for a long time and everybody seems to think that would be a good idea.

I think we'll continue to see efforts at the agency level. One thing Congress might do is they might spend some money in this space, so maybe there will be some new investment or maybe the national laboratories will get some money to do additional AI research. That has its own challenges, but most of them are financial challenges, they're not so much whether or not it's going to impede the industry, so that's kind of how I think it'll likely play out at the federal level.

An AGI Manhattan Project (12:18)

A report just came out (yesterday, as we're recording this) from the outside advisory group on US-China relations that advises the government, and they're calling for a Manhattan Project to get to an artificial general intelligence, I assume before China or anybody else.

Is that a good idea? Do you think we'll do that? What do you make of that recommendation, which caused quite a stir when it came out?

For the most part, artificial general intelligence, I don't understand what the appeal of that is, frankly . . . Why not train something that could do something specific really well?

Yeah, it's a really interesting report. If you read through the body of the report, it's pretty standard international competitiveness analysis that says, “What are the supply chains for chips? How does it look? How do we compare on talent development? How do we compare on the industry backing investment?” Things like that. And we compare very well, overall, the report says.

But then, all of a sudden at the top level, the first recommendation talks about artificial general intelligence. This is the kind of AI that doesn't exist yet, but it's the kind that could basically do everything a human could do at the intellectual level that a human could do it. It's interesting because that recommendation, it doesn't seem to be founded on anything that's actually in the report. There's no other discussion in the report about artificial general intelligence, or how important it is strategically, or anything like that, and yet, they want to spend Manhattan Project-level amounts of money — I think in today's dollars, that'd be like $30 billion to create this artificial general intelligence. I don't know what to make of that, and, more than that, I think it's very unlikely to move the policy discussion. Maybe it moves the Overton window, so people are talking like, “Yeah, we need a Manhattan Project,” but I don't think that it's likely to do anything.

For the most part, artificial general intelligence, I don't understand what the appeal of that is, frankly. It has a sort of theoretical appeal, that we could have a computer that could do all the things that a person could do, but in the modern economy, it's actually better to have things that are really good at doing a specific set of things rather than having a generalist that you can deploy lots of different places, especially if you're talking about software. Why not train something that could do something specific really well? I think that would slot into our economy better. I think it's much more likely to be the most productive value of the intense computation time and money that it takes to train these types of models. So it seems like a strange thing to emphasize in our federal spending, even if we're talking about the national security implications. It would seem like it'd be much better to train a model that's specifically built for some type of drone warfare or something rather than trying to make it good at everythi ng and then say, “Oh, now we're going to use you to fly drones.” That doesn't seem to make a ton of sense.

State-level overregulation (15:17)

We talked about the federal level. Certainly — and not that the states seem to need a nudge, but if they see the Washington doing less, I'm sure there'll be plenty of state governments saying, “Well then we need to do more. We need to fill up the gap with our state regulation.” That already seems to be happening. Will that continue to happen and can the Trump administration stop that?

I think it will continue to happen, the question is what kind of gap is left by the Trump administration. I would say what the Biden administration left was a vision gap. They didn't really have an overarching vision for how the US was going to engage with this technology at the federal level, unlike the Clinton administration which set out a pretty clear vision for how the federal government planned to engage on the early version of the internet. What it said was, for some really good reasons, we're going to let the commercial sector lead on development here.

I think sending a signal like that could have sort of bully-pulpit effect, especially in redder states. You'll still see states like California and New York, they're listening to Europe on how to do stuff in this space.

Still? Are we still listening to . . . Who are the people out there who think, “They've got it figured out”? I understand that maybe that's your initial impulse when you have a new technology and you're like, “I don't know what to do, so who is doing something on it?” But we've had a little bit of time and I just don't get anybody who would default to be like, “Man, we're just going to look at a couple of EU white papers and off to the races here in our state.”

I think we're starting to see . . . the shopping of bills that look a lot like the way privacy has worked across the states, and in some cases are being pushed by the same organizations that represent compliance companies saying, “Hey, yeah, we need to do all this algorithmic bias auditing, or safety auditing, and states should require it.”

I think a lot of this is a hangover of the social media fights. AI, if you poll it just at that level, if you're like, “Hey, do you think AI is going to be good or bad for your job or for the economy?” Americans are somewhat skeptical. It's because they think of AI in the cultural context that includes Terminator, and automation, and so they think of it that way. They don't think about the thousands of applications on their phones that use artificial intelligence.

So I think there's a political moment here around this. The Europeans jumped in on and said, “Hey, we're the first to regulate in this space comprehensively.” I think they're dialing that back since some of their member states are like, “Hey, this is killing our own homegrown AI industry.” But for some reason, you're right, California and New York seem to be embracing that, and I think they probably will continue to. At the very local level, at the state level, there's just weird incentives to do something and then you don't really pay a lot of consequences down the road.

Having said that, there was a controversial bill that was very aggressively pushed, SB 1047, in California over the summer, and it got killed. It got canned by Gavin Newsom in the end. And I think that's a sort of a unique artifact of California's “go along to get along” legislature process where even people who don't support bills vote for them, kind of knowing that Gavin, or that the governor, will bring down the veto when it doesn't make political sense.

All of this is to say, California's going to California. I think we're starting to see, and what concerns me is, we're starting to see the shopping of bills that look a lot like the way privacy has worked across the states, and in some cases are being pushed by the same organizations that represent compliance companies saying, “Hey, yeah, we need to do all this algorithmic bias auditing, or safety auditing, and states should require it.”

There's a Texas draft bill that has been floated right now, and you wouldn't think that Texas would be on the frontier of banning differential effects in bias from AI. It doesn't really sound particularly red-state-y, but these things are getting shopped around and if it moves in Texas, it'll move other places too. I worry about that level of red tape coming at the state level, and that's just going to be ground warfare on the legislative front at the state level.

So federal preemption, what is that and how would that work? And is that possible?

It's really hard in this space because the technology is so general. Congress could, of course, write something that was very broad and preempted, certain types of regulation of models, and maybe that's a good idea, I've seen some draft language around that.

On the other hand, I do believe in federalism and these aren't quite the same sort of network-based technologies that only make sense in a national sweep. So maybe there's an argument that we should let states suffer the consequences of their own regulatory approaches. That hurts my heart a little bit just to think about the future because there are a lot of talented people in those states who are going to find out it's the lawyers who are their main constraint. Those types of transaction costs, they will slow us down. I think if it looks like we're falling behind in the US because we can't get out of our own way regulatorily, I think there will be more impulse to fix things.

There are some other creative solutions such as interstate compacts to try to get people to level up across multiple states about how they're going to treat AI and allow innovation to flourish, and so I think we'll see more of those experiments, but it is really hard at the federal level to preempt just because there's so many state-based interests who are going to push back against that sort of thing.

Potential impact on immigration (21:15)

As far as AI influencing what we do elsewhere — one thing you wrote about recently in a really great essay, which I've already drawn upon in some of these questions is — thinking about immigration and AI talent coming to the United States — what I think is now a widely accepted understanding, that this is an important technology and we certainly want to be the leader in this technology — does that change how we think about immigration, at least very high-skilled immigration?

We should be wanting the most talented people to come here and stay here.

I think it should. Frankly, we should have changed our minds about some of this stuff a long time ago. We should be wanting the most talented people to come here and stay here. The most talented people in the world already come here for school often. When I was in computer science grad school, it was full of people who really desperately wanted to stay in the US and build companies and build products, and some of them struggled really hard to figure out a way to do it legally.

I think that making it easier for those people to stay is essential to keeping not just our lead in the world, I don't want to say it that way — I mean that's important, I think national competitiveness is sort of underrated, I think that is valuable — but those people are the most productive in the US system where they can get access to venture capital that's unlike any other part of the planet. They can get access to networks of talent that are unavailable on other parts of the planet. Keeping them here is good for the US, but I think it's good overall for technological development, and we should really, really, really focus on how to make that easier and more attractive.

AI companies as national champions (23:00)

This isn't necessarily a specific AI issue, but again, as you said earlier, it seems like a lot of the debate, initially, is really a holdover from the social media debates about moderation, and bias, and all that, and a lot of those sorts of people, in many cases, and frameworks just got globed onto AI.

Another aspect is the antitrust, and now we’re worried about these big companies owning these platforms, and they're biased.

Do we begin to look at issues of how we look at our big companies who have been leading in AI, doing a lot of R&D — does the politics around Big Tech change if we begin to see them as our vanguard companies that will keep us ahead of China?

. . . in contrast to the Biden sort of “big-is-bad” rhetoric that they sort of leaned into entirely, I think a Trump administration is going to bring more nuance to that in some ways. And I do think that there will be more of a look towards our innovative companies as being the vanguard of what we do in the US.

I think it already has, honestly. You saw early on, the Senate hearings around AI were totally inflected with the language of social media and that network-effects type of ecosystem. AI does not work like that. It doesn't work the same way. In fact, the feedback loops are so much faster from these models, we saw things like Google Gemini that had ahistorical renderings of the founding fathers, and that got so much shouting on Twitter, and on X, and lots of other places that Google very quickly adjusted, tweaked its path. I think we're seeing the toning down of that rhetoric and the recognition that these companies are creating a lot of powerful, useful products, and that they are sort of national champions.

Trump, on the campaign trail, when asked about breaking up Google for an ongoing antitrust litigation was like, “Hold on guys, breaking up these companies might not be in our best interest. There might be other ways we can solve these types of problems.” I think that that level of, in contrast to the Biden sort of “big-is-bad” rhetoric that they sort of leaned into entirely, I think a Trump administration is going to bring more nuance to that in some ways. And I do think that there will be more of a look towards our innovative companies as being the vanguard of what we do in the US.

Now, having said that, obviously I think there's tons of AI development that is not inside of these largest companies in the open source space, and especially in the application layer, building on top of some of these foundation models, and so I think that ecosystem is also extremely important. Things that sort of preference the big companies over the small ones, I would have a lot of concerns about, and there have been regulatory regimes proposed that, even while opposed by some of the bigger companies, would certainly be possible for them to comply with in a way that small companies would struggle to comply with, and open-source developers just don't have any sort of nexus with which to comply, since there is no actual business model that's propping that type of approach up. So I'd want to keep it pretty neutral between the big companies, the small companies, and open source, while having the cultural recognition that big companies are extremely valuable to the US innovation ecosystem.

If you had some time with, I don’t know, somebody, the president, the vice president, the Secretary of Commerce, someone in an elevator going from the first to the 10th floor, and you had to quickly say, “Here's what you need to be keeping in mind about AI over the next two to four years,” what would you say?

I think the number one thing I would say is that, at the state level, we're wrapping a lot of red tape around innovative companies and individuals, and that we need to find a way to clear that thicket or stop it from growing any further. That's the number one challenge that I see facing this.

Secondary to that, I would say the US government needs to figure out how to take advantage of these tools. The federal government is slow to adopt new technologies, but this technology has a lot of applications to the types of government work that hundreds of thousands of federal employees do every day, and so finding ways to streamline using AI to do the job better I think is really valuable, and I think it would be worth some investment at the federal level to think about how to do that well.

On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

Micro Reads

▶ Economics

* Productivity During and Since the Pandemic - San Francisco Fed

* The Effect of COVID-19 Immigration Restrictions on Post-Pandemic Labor Market Tightness - St. Louis Fed

* Trump Plans Tariffs on Canada, China and Mexico That Could Cripple Trade - NYT

▶ Business

* Nvidia’s new AI audio model can synthesize sounds that have never existed - Ars

* Europe’s Mistral expands in Silicon Valley in hunt for AI staff - FT

▶ Policy/Politics

* Musk Wants $2 Trillion of Spending Cuts. Here’s Why That’s Hard. - WSJ

* AI Governance: From Fears and Fearmongering to Risks and Rewards - AEI

* Newsom says California to offer EV subsidies if Trump kills federal tax credit - Wapo

▶ AI/Digital

* A new golden age of discovery - AI Policy Perspectives

* How Do You Get to Artificial General Intelligence? Think Lighter - Wired

* Is Creativity Dead? - NYT Opinion

* The way we measure progress in AI is terrible - MIT

* AI's scientific path to trust - Axios

* AI Dash Cams Give Wake-Up Calls to Drowsy Drivers - Spectrum

▶ Biotech/Health

* Combining AI and Crispr Will Be Transformational - Wired

* Neuralink Plans to Test Whether Its Brain Implant Can Control a Robotic Arm - Wired

* Scientists are learning why ultra-processed foods are bad for you - Economist

▶ Clean Energy/Climate

* Taxing Farm Animals’ Farts and Burps? Denmark Gives It a Try. - NYT

* These batteries could harness the wind and sun to replace coal and gas - Wapo

▶ Robotics/AVs

* On the Wings of War - NYT

▶ Up Wing/Down Wing

* ‘Genesis’ Review: Rise of the New Machines - WSJ

* The Myth of the Loneliness Epidemic - Asterisk

▶ Substacks/Newsletters

* The Middle Income Trap - Conversable Economist 

* America's Productivity Boom - Apricitas Economics

* The Rise of Anthropic powered by AWS - AI Supremacy

* Data to start your week - Exponential View

* Trump's economic team is on a collision course with reality - Slow Boring

* Five Unmanned SpaceX Starships to Mars in 2026 with Thousands of Teslabots - next BIG future

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Housing in the United States has come to be known as a panacea problem. Gone are the days when tossing the graduation cap meant picking up the keys to a front door, and the ripple effects of unaffordable housing stretch across society: poor social mobility, smaller families, worse retirement-readiness, just to name a few.

Today on Faster, Please — The Podcast, I talk to Bryan Caplan about the seemingly obvious culprit, government regulation, and the growing movement to combat it.

Caplan is a professor of economics atGeorge Mason University. His essays have been featured in the New York Times, Wall Street Journal, Washington Post, and TIME Magazine. He is editor and chief writer of theBet On It Substack, and is the author of several books, including Build, Baby, Build: The Science and Ethics of Housing Regulation.

In This Episode

* America’s evolving relationship with housing (1:31)

* The impact of regulation (3:53)

* Different regulations for different folks (8:47)

* The YIMBY movement (11:01)

* Homeowners and public opinion (13:56)

* Generating momentum (17:15)

* Building new cities (23:10)

Below is a lightly edited transcript of our conversation.

(Note: This was recorded just before the presidential election.)

America’s evolving relationship with housing (1:31)

The main thing that changed is that we've seen a long-run runup of housing prices.

Pethokoukis: What was going on with housing prices and housing affordability from the war to the 1970s? Was it kind of flattish? People were recovering from the Great Depression; what was going on then?

Caplan: Yeah, it was quite flat, so there were decades where we had rapidly expanding population, the Baby Boom, and markets were working the way that markets normally do: You get demand going up, raises prices in the short run, but then that means the prices are above the cost of production, and so you get entry, and you build more until prices come back down to the cost of production. That's the way markets are supposed to work!

I don't know how people thought about their homes in the late ’40s, ’50s, and ’60s, but did they view them as, “This is our primary investment,” or did they view them more as a place to live? Were there any expectations that this was their retirement plan?

I honestly don't know. I don't remember reading anything about that. I grew up in Los Angeles where in the ’70s and ’80s people already had some sense of, “Your home is an important retirement vessel,” but it is plausible that when you are going back to earlier decades, people did have a different view.

I've often heard Americans say that Japanese don't think about their homes as retirement vessels, but I've never talked to anyone in Japan to assure me this is so, so I don't know.

But that scenario changed.

It did.

How did it change and are we confident we know why it changed?

The main thing that changed is that we've seen a long-run runup of housing prices. Depending upon what series you're looking at, the runup might be starting in the early ’70s or the early ’80s, but in any case, there was what economists would call a structural break where a series that was generally flat over the long term started rising over the long term. There have been a few times when prices fell back down, like after the Great Recession, but now, inflation adjusted, we are higher than the peak right before the Great Recession.

Now, is that the same as affordability? Because I assume incomes could be going up, so has it outpaced median income over that period?

Probably not, although it's in the right ballpark, and maybe.

One thing you can say is, well, there's regulation before, there's regulation after, so how can you go and blame the rise on the regulation?

The impact of regulation (3:53)

I would like to blame regulation. Intuitively, that makes sense to me, but I suppose we need more than intuition here.

. . . there's a lot of regulation almost everywhere a lot of people live.

I would say that we do have very good evidence that regulation is indeed to blame. If you look at it very quickly, you might say, “Well, there was regulation before; it didn't seem to matter that much.” The answer to this really was death by a thousand cuts, where we just piled regulation on regulation, but also where regulations that have been interpreted mildly before started being interpreted strictly afterwards.

How do we know that it really is regulation? The easiest thing to do is just to look at the strictness of regulation in different parts of the country, and you can see that there are some places that are crazy strict and the prices are crazy high. There's other places where the regulation is a lot lighter and even though they're getting plenty of population increase, they nevertheless do not have these long-run rises.

So the contrast between the Bay Area and the Texas Triangle is very strong. So these are both areas that, in some sense, they are growth areas, a lot of tech there, but the Bay Area has seen very little rise in the amount of housing and massive increase in prices, whereas Texas has, in contrast, seen a large rise in the number of houses and very low rises in the price of housing.

The main method that economists have used in order to disentangle all this is it really starts with trying to figure out: What is land that you are not allowed to build anything on worth? So just think about whatever your excess land is in a single-family area, you're not allowed to put another structure there, you can put a volleyball court or something like that. So you just find out, well, what is land where you can't build anything worth? And usually, even in a good area, that land is not worth much. If you can't build on it, it's like, I guess we can put some grass, but that's not that good. Then the next step is to just go to a construction manual and to see what the cost of construction is in a given area and then compare it to the price. This is a quite reasonable approach and it has gotten better over time because data has gotten better.

The main thing is that Joe Gyourko, who's been working on this for about 20 years, in his last big paper, he got data on actual vacant lots, and so you can see, this is a vacant lot, usually because you just can't build anything on it, can't get the permission, and as a result of this, he's also able to find out, how bad does the regulation get as you move away from the city center. We've got details like Los Angeles looks like it's regulated out to the horizon. You’ve got 50 miles away from downtown LA and it's still pretty bad regulation. On the other end, a city like Chicago is very regulated in the downtown, but 30 miles out, then there's not that much effect anymore.

The punchline of all this work is that there's a lot of regulation almost everywhere a lot of people live. If you want to go and build a skyscraper in the middle of nowhere in Kansas, you could probably do it, but you wouldn't want to build a skyscraper in the middle of nowhere in Kansas, that defeats the whole purpose of building a skyscraper.

That leads to two questions: The first question is, just to be clear, when we're talking about regulation, is it single-family homes versus multifamily? Is it also the coding, what the home has to be made out of? Do the walls have to be so thick, or the windows? What are we talking about?

The honest answer is that most economists’ estimates are just giving you an estimate of all regulation combined with a considerable agnosticism about what actually are the specific regulations that matter. There are other papers that look at specific kinds of regulation and come up with at least very credible claims that this is a big part of the puzzle.

The main things that matter a lot in the US: We've got height restrictions — those matter in your biggest, most expensive cities; you can just look at a place like Central Park or get a helicopter shot of San Francisco and say, don't tell me you can't build more stuff here. There's endless room to build more stuff here as long as you can go vertically.

It's also very standard to say that you are only allowed to have single-family homes in most residential land in the US, it's just zoned single family only, so you just are not legally allowed to squeeze in a larger number of dwellings.

Then you've got, even with single-family regulation, it's very standard to have minimum lot sizes, which just says that you've got to have at least like an acre of land per house, which, whenever I'm speaking in metric countries, I'm always telling, what is that . . .? It's a lot. It's a lot of land, and the amount of land that's normally required has gone up a lot. One-acre zoning in the past would've seemed crazy. Now plenty of places have five-acre zoning. You could obviously just squeeze way more houses in that space. And what is clear is that builders normally build the absolute maximum number they're allowed to build. Anytime someone is going up to the very border of a rule, that is a strong sign the rule is changing behavior.

Different regulations for different folks (8:47)

Very rarely did someone sit around saying, “You know what's great about Texas? Our lack of housing regulation.”

Why are these rules different in different places? That may be a dumb question. Obviously San Francisco is very different from Texas. Is the answer just: different places, different people, different preferences? Do we have any idea why that is?

Matt Kahn, who is based in Los Angeles, he's been I think at UCLA and USC, he's got a very good paper showing, at least in California, it's the most progressive left-wing places that have the worst regulation, and it just seemed to be very philosophical. On the other hand, I spent a lot of time during Covid in Texas. Very rarely did someone sit around saying, “You know what's great about Texas? Our lack of housing regulation.” It’s not so much that they are opposed to what's going on in California, it just doesn't occur to them they could be California.

In a way, you might actually get them to be proud about what they're doing if you could remind them, “Oh, it's really different in California,” and just take them on a tour, then they might come back and say, “God bless Texas.” But it's more of, there's the places where people have an ideological commitment to regulation, and then the rest of the country is more pragmatic and so builders are able to get a lot more done because there just aren't fanatics that are trying to stop them from providing the second most basic necessity for human beings.

Now, this is all striking because the YIMBY [Yes In My Backyard] movement, and my book Build, Baby, Build — I definitely think of that as a YIMBY book. My goal is to make it the Bible of YIMBY, and it's in comic book form, so it's a Bible that can be read by people starting at age five.

In any case, the YIMBY movement is definitely left-coded. People that are in that movement, they think of themselves as progressives, usually, and yet they are just a small piece of a much broader progressive coalition that is generally totally hostile to what they're doing. They are punching above weight and I want to give them a lot of credit for what they've been able to accomplish, and yet, the idea that YIMBYs tend to be left-wing and therefore they are the main people that are responsible for allowing housing is just not true. Most places in the country basically don't have a lot of pro- or anti-housing activism. They just have apathy combined with a construction industry that tries to go and build stuff, and if no one stops them, they do their job.

The YIMBY movement (11:01)

Who the hell decided that was a good idea that everybody should have an acre of land?

I want to talk a bit more about the economic harms and benefits of deregulation, but if I was a center-left YIMBY, I would think, “Oh, I have all kinds of potential allies on the right. Conservatives, they hate regulation.” I wonder how true that is, at least recently, it seems to me that when I hear a lot of conservatives talking about this issue of density, they don't like density either. It sounds like they're very worried that someone's going to put up an apartment building next to their suburban home, YIMBY people want every place to look [the same] — What's the home planet in Star Wars?

Coruscant.

Yeah Coruscant, that that's what the YIMBYs want, they want an entire planet to look like a city where there's hundreds of levels, and I'm not sure there's the level of potential allyship on the right that center-left YIMBYs would want. Is that a phenomenon that you've noticed?

I actually I have a whole chapter in Build, Baby, Build where I try to go and say we can sell these policies to very different people in their own language, and if they actually believe their official philosophy, then they should all be coming down to very similar conclusions.

I think the main issue of center-left YIMBYs talking to people who are right wing or conservative, it's much more about polarization and mutual antipathy than it is about the people on the right would actually object to what they're hearing. What I say there is there are certain kinds of housing regulation that I think the conservatives are going to be sympathetic to. In particular, not liking multifamily housing in suburbs, but I don't really think there is any conservative objection to just allowing a lot more skyscrapers in cities where they don't even go. There's not going to be much objection there and it's like, “Yeah, why don't we go and allow lots of multifamily in the left-wing parts of the country?”

But I think the other thing is I don't think it's really that hard to convince conservatives that you shouldn't need to have an acre of land to go and have a house. That one, I think, is just so crazy, and just unfair, and anti-family, you just go and list all the negative adjectives about it. Did you grow up in a house on a one-acre lot? I didn't! Who the hell decided that was a good idea that everybody should have an acre of land? Wouldn't you like your kids to be able to walk to their friends' houses?

A lot of it seems to be that government is just preventing the development of something that people would actually want to live in. I remember when my daughter finally made a friend within walking distance, I wanted to light a candle, hallelujah! A child can walk to be friends with a child! This has not happened in all my years! But that was the normal way things were when you'd be on a quarter-acre or a third of acre when I was growing up.

Homeowners and public opinion (13:56)

People generally favor government policies because they believe . . . the policies are good for society.

If someone owns a house, they like when that price goes up, and they might see what you're saying as lowering the price of homes. If we were to have sort of nationwide deregulation, maybe deregulation where the whole country kind of looks like wherever the lightest-regulated place is. People are going to say, “That's bad for me! I own a home. Why would I want that?”

Lots of people think this, and especially economists like this idea of, of course we have all this regulation because it's great for homeowners; homeowners are the main wants to participate in local government. Sounds likely, but when we actually look at public opinion, we see that tenants are strong advocates regulation too, and it's like, gee, that really doesn't make any sense at all. They're the ones that are paying for all this stuff.

But it does make sense if you switch to a much simpler theory of what's going on, which fits the facts, and that is: People generally favor government policies because they believe —underscore believe — the policies are good for society. So many people from the earlier decades say, “Oh, all those Republicans, they just want tax cuts.” Now we're finally at the level where Republicans are poorer than Democrats. It's like, “Yeah, I guess it's getting a little bit hard to say that people become Republicans to get tax cuts when they're the ones paying lower taxes.” How about there's an actual disagreement about what policies are good for society, which explains why people belong to different parties, support different policies.

So most of what I'm doing in Build, Baby, Build is trying to convince people, look, I'm not impugning your motives, I don't think that you're just favoring whatever policies are selfishly best for you. I think that whatever policies you're into are ones that you think are genuinely good for your community, or your area, or your country, but we are not thinking very well about everything that's going on.

So part of it is that a lot of the complaints are just overblown or wrong, but another thing is that generally we base a regulation purely on complaints without any thought of any good thing that we might be losing. I make a big deal in the book about how, if you don't want to have noise, and traffic, and pollution, it's really easy — just move to some remote part of the country and you solve all those problems; yet hardly anybody wants to do that.

Why are people staying in congested areas with all these problems and paying a lot of extra money for them? Many of these people now have telework jobs, they don't even have a job reason to stay there. And the answer's got to be, there's just a bunch of really good things about living near other people that we hardly ever talk about and which have no political voice. There's almost no one's going to show up in a meeting and [say], “I favor this because I want there to be more commercial opportunities. I favor this because I want there to be more social opportunities, more cultural opportunities, more economic opportunities,” and yet these are all the reasons why people want to live near other people. So we have a set of regulation just based upon complaints: complaints which are generally out of context, not quantified. So we just see that people are willing to pay a lot of money for the package of living in an area with a bunch of other people, so that's got to mean that the good of other people exceeds the bad of the other people; otherwise, why aren't you living out in the middle of nowhere?

Generating momentum (17:15)

The sad truth is that symbolic issues are much more likely to get people excited, but this is something that determines the quality of life for most people in this country.

When I read the book, and I read a really good New York Times essay —

Would that be my essay, Jim?

I think it is your essay! In fact, it was, I should have been clearer on the author of that essay. The brilliant Bryan Caplan was the author of that essay.

If you look at the potential benefits on inequality, there's environmental impact, maybe people are really worried about birth rates, it really seems like housing really is sort of the “everything problem.”

Panacea problem, or the “housing theory of everything.”

It really does. I think the current election season, it's probably the most I've heard it talked about, and not really talked about very much.

And thoughtlessly. Spoken of thoughtlessly.

To me there seems to be a lot more — I'll use a nice think tank word — there's been a lot more ideation about the issue in recent years, and maybe it's only now kind of breaking through that filter where politicians start talking about it, but boy, when you look through what you've written about it, it seems like it should be a top three issue that politicians talk about.

The sad truth is that symbolic issues are much more likely to get people excited, but this is something that determines the quality of life for most people in this country. It's the difference between: Are you going to keep living with your parents until you're 30, or are you going to be able to afford to get your own place, start your own family? And again, it's one where older people remember how things used to be, and the idea of, well, why can't things just be like that? Why can't it be that a person who gets out of college can go and immediately afford to get a pretty good house?

At AEI, Mark Perry, for example, who is one of your colleagues, I think probably a remote colleague, he has done stuff on how new houses are better and so on, and that's also true, so I don't want to go and act like there's been no progress at all. But still, of course a lot of people are not moving into those new houses, they’re moving into old houses, which are the same as they were in the past, but just way more expensive if you want to go and live in that area

The other thing that is worth pointing out is that it's really temping to say, well, of course housing naturally gets more expensive as population rises. The period after World War II that we were mentioning, that's the Baby Boom era, population was rising at a much faster rate then than it did now, even counting immigration, and yet prices were much flatter because we were able to just go and legally build way more stuff.

I feel like you feel like you need to drive home the point about demand not being met by supply for this artificial reason: regulation. Even though, to me, it seems utterly natural and a classic case, people struggle to come up with alternative reasons that it's really not that. That it's because of . . . there’s private equity firms buying up all the homes, or the reason apartment rents go up is because there’s a cabal of apartment owners . . . They look for these other reasons, and I don’t quite get that when there seems to be a pretty obvious reason that we theoretically know how to fix.

Some of these other stories, they are half-truths, but they're not helpful. So the thing of, “Gee, if we just shut down tourism and letting foreign buyers buy stuff here, then demand will be lower, and prices will be lower, and we won't need to build anything new.” And it's like, do you realize what you're saying? You're basically saying that you want to destroy one of your best export industries.

If people around the world want to go and buy houses in your area, why do you want to turn them away instead of saying, cha-ching, let's capitalize on this by building a ton of housing for them? If there's a lot of tourists that want to go and rent a place in your area, why is it you want to go and strangle the market, which obviously it's a great industry — Build stuff and rent it to people, and it's not like there's some fixed amount unless the law says it must be fixed.

One benefit I didn't mention was social mobility where we need people, if they want to be able to move towards high-wage, high-productivity cities, to find good jobs, and then not have the wages of those good jobs mostly gobbled up by housing costs. That kind of circulation system, if that's the right phrase.

Certainly in some parts of the country, that has just been stopped and that has been a traditional way people move up the ladder.

We’ve got very good data on this. In earlier periods of US history, there was basically a foolproof way for someone in a low-income part of the country to get a big raise, and that was just to move. Steinbeck’s Grapes of Wrath not withstanding, this almost always works. It wasn't normally the case that you starve to death on your way to California from Oklahoma. Instead, normally, it's just a simple thing: You move from a low-wage area to a high-wage area and you get a lot more money, and you get a much higher take-home salary. But then in those days, there was not much difference in housing prices between different areas of the country, and therefore you would actually have a rise in not just your paycheck, but your standard living.

Now it's still true that you can get a rise in your paycheck by moving to the Bay Area. The problem is your standard of living, if you're coming from Mississippi, will generally crash because the housing cost eats up much more than 100 percent of the raise.

I remember I had a colleague who had a son who was an investment banker in the Bay Area. He and his wife were sharing a small apartment with two roommates, and it's like investment bankers can't afford apartments! Things have gotten out of hand, I think we can say with great confidence now.

Building new cities (23:10)

. . . politics is an area where there's a lot of ideas where it's like no one's trying it, it must be because it wouldn't work if tried, and then someone tries it with a little panache, or a little twist, and it catches on, and you're like, alright, maybe that's the real story.

Should we be building new cities somewhere? I think former President Trump has talked about this idea that we, is that something you've thought about at all?

Yes. I didn't put it into the book, but when I was writing up some follow-up posts on things that I wished I would've talked about, or just more speculative things, I do have some friends who are involved in that project to go and build a new city in the Bay Area. I hope it works.

There is always the problem of there's almost always going to be some existing people where you want to build your new city, and then what do you do about them? You can try buying them out. There is this holdout problem, a few people are going to stay there and say, “I'm not going to sell.” Or you could just go and do what happened in the movie Up: We'll buy everybody around you, and if you don't like it, too bad.

But on the other hand, it may be that activists will put a stop to your plan before you can get it off the ground. So in that case, it was going and selling off empty federal or state land, which we have in abundance. If I remember, I think that 23 percent of the land of the United States is owned by the federal government. Another 10 percent is owned by state governments. And even if you subtract out Alaska, there's still a ton. If you look at the map, it's really cool because you might think, “Oh, it's just that the government owns land no one in the right mind would want.” Not true.

Desert land in Nevada next to Area 51 or something.

Virtually all of Texas, even those western deserts, are privately owned. I've driven through them. Have you ever driven through West Texas?

I have.

Alright, so you're there and you're like, “Who wants to own this stuff?” And it's like, well, somebody at whatever the market price is considers this worth owning, and as to whether it's for mineral extraction, or for speculation on one day it'll be worth something when the population of Texas is greater, or they're going to do ranching there, I don't know. But it is at a price someone is willing to go and own almost every piece of land.

What the map really shows is it was ideology that led all this land to be held by the government. It's basically the ideology of conservation that we hear about. You get John Muir and Teddy Roosevelt, and as a result, they didn't just wind up protecting a few really beautiful national parks, they wind up putting millions of square miles of land off-limits for most human use.

Again, when the population of the country is lower, maybe it didn't even matter that much, but now it's like, “Hey, how about you go and sell me a hundred square miles so I can put a new city here?” The idea that an Elon or Zuckerberg couldn't go and just say, “I'm putting a pile of money into this. I'm going to build a new city and have a decent chance of it working.” Maybe it would be just a disaster and they waste their money. Then more likely I think it's going to be like Seward’s Folly where it's like, “What's the point of buying Alaska?” Oh, actually it was fantastic. We got a great bargain on Alaska and now it is an incredible, in hindsight, investment.

As we were talking, I started thinking about Andrew Yang who ran for president, I think that was in 2020, and he had one issue, really: Universal Basic Income. He thought that he had found an issue that was going to take him to the White House. It did not.

I kind of think if you were going to have a candidate focus a lot on one issue, this would not be a bad issue, given how it touches all these concerns of modern American society.

As an economist, I always hesitate to say that anyone who is a specialist in an area and is putting all their resources into it is just royally screwing up. At the same time, politics is an area where there's a lot of ideas where it's like no one's trying it, it must be because it wouldn't work if tried, and then someone tries it with a little panache, or a little twist, and it catches on, and you're like, alright, maybe that's the real story.

Just to give Trump credit where credit is due, there's just a lot of things that he said that you would think would've just destroyed his candidacy, and instead it seemed like he came out and he was more popular than ever. Maybe he just saw that there were some ideas that are popular that other people didn't realize would be popular.

Now I'm not optimistic about what he's going to do about housing, although anytime he says one good thing, it's like, I don’t know, maybe he'll just get fixated on that, but more likely ADHD will kick in, unfortunately.

But just to go and allow one new laissez-faire city to be built on federal land in some non-crummy area of the country — just as a demonstration project, the value of that would be enormous, just to see, hey, there's no reason why you can't have spacious, cheap homes in a really nice area that is not that remote from the rest of the country. Just imagine the airport you could build there, too — before all the noise complaints. You probably know about the noise complaints against Reagan Airport and how one single guy filed over half the complaints. It's like, how are we going to build anything? Let's build it all before that guy shows up!

On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

Micro Reads

▶ Economics

* Trump Could Win the Contest With China Once and for All - NYT Opinion

▶ Business

* Nvidia’s message to global chipmakers - FT Opinion

* The Great American Microchip Mobilization - Wired

* ASML Sticks to Long-Term Growth Targets Amid AI Frenzy - WSJ

▶ Policy/Politics

* Trump and the future of AI regulation - FT

* Silicon Valley eyes a windfall from Trump’s plans to gut regulation - Wapo

* Environmental Policy Act Ruling Casts Doubt On White House Authority - Forbes

* How Elon Musk could disrupt Washington - Politico

* Semiconductors and Modern Industrial Policy - Journal of Economic Perspectives

▶ AI/Digital

* Google DeepMind has a new way to look inside an AI’s “mind” - MIT

▶ Biotech/Health

* Why we now think the myopia epidemic can be slowed – or even reversed - NS

* Canada Detects Its First Human Case of Bird Flu - NYT

▶ Clean Energy/Climate

* Climate Summit, in Early Days, Is Already on a ‘Knife Edge’ - NYT

▶ Robotics/AVs

* Nvidia Readies Jetson Thor Computers for Humanoid Robots in 2025 - WSJ

▶ Space/Transportation

* Former Officials Warn Lawmakers of Alleged Secret UAP Programs Operating Beyond Congressional Oversight - The Debrief

▶ Up Wing/Down Wing

* Stand-Up, Drama and Spambots: The Creative World Takes On A.I. - NYT

* Is Europe running out of chemistry teachers? - C&EN

▶ Substacks/Newsletters

* Here's What I Think We Should Do - Hyperdimensional

* What is OpenAI's Operator and Blueprint? History and Tips of Prompt Engineering from 2020 to 2025 - AI Supremacy

* People want competence, seemingly over everything else - Strange Loop Canon

Please check out the website or Substack app for the latest Up Wing economic, business, and tech news in this edition of the newsletter.

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

In this episode of Faster, Please! — The Podcast, I talk with economist Robin Hanson about a) how much technological change our society will undergo in the foreseeable future, b) what form we want that change to take, and c) how much we can ever reasonably predict.

Hanson is an associate professor of economics at George Mason University. He was formerly a research associate at the Future of Humanity Institute at Oxford, and is the author of the Overcoming Bias Substack. In addition, he is the author of the 2017 book, The Elephant in the Brain: Hidden Motives in Everyday Life, as well as the 2016 book, The Age of Em: Work, Love, and Life When Robots Rule the Earth.

In This Episode

* Innovation is clumpy (1:21)

* A history of AI advancement (3:25)

* The tendency to control new tech (9:28)

* The fallibility of forecasts (11:52)

* The risks of fertility-rate decline (14:54)

* Window of opportunity for space (18:49)

* Public prediction markets (21:22)

* A culture of calculated risk (23:39)

Below is a lightly edited transcript of our conversation

Innovation is Clumpy (1:21)

Do you think that the tech advances of recent years — obviously in AI, and what we're seeing with reusable rockets, or CRISPR, or different energy advances, fusion, perhaps, even Ozempic — do you think that the collective cluster of these technologies has put humanity on a different path than perhaps it was on 10 years ago?

. . . most people don't notice just how much stuff is changing behind the scenes in order for the economy to double every 15 or 20 years.

That’s a pretty big standard. As you know, the world has been growing exponentially for a very long time, and new technologies have been appearing for a very long time, and the economy doubles roughly every 15 or 20 years, and that can't happen without a whole lot of technological change, so most people don't notice just how much stuff is changing behind the scenes in order for the economy to double every 15 or 20 years. So to say that we're going more than that is really a high standard here. I don't think it meets that standard. Maybe the standard it meets is to say people were worried about maybe a stagnation or slowdown a decade or two ago, and I think this might weaken your concerns about that. I think you might say, well, we're still on target.

Innovation's clumpy. It doesn't just out an entirely smooth . . . There are some lumpy ones once in a while, lumpier innovations than usual, and those boost higher than expected, sometimes lower than expected sometimes, and maybe in the last ten years we've had a higher-than-expected clump. The main thing that does is make you not doubt as much as you did when you had the lower-than-expected clump in the previous 10 years or 20 years because people had seen this long-term history and they thought, “Lately we're not seeing so much. I wonder if this is done. I wonder if we're running out.” I think the last 10 years tells you: well, no, we're kind of still on target. We're still having big important advances, as we have for two centuries.

A history of AI advancement (3:25)

People who are especially enthusiastic about the recent advances with AI, would you tell them their baseline should probably be informed by economic history rather than science fiction?

[Y]es, if you're young, and you haven't seen the world for decades, you might well believe that we are almost there, we're just about to automate everything — but we're not.

By technical history! We have 70-odd years of history of AI. I was an AI researcher full-time from ’84 to ’93. If you look at the long sweep of AI history, we've had some pretty big advances. We couldn't be where we are now without a lot of pretty big advances all along the way. You just think about the very first digital computer in 1950 or something and all the things we've seen, we have made large advances — and they haven't been completely smooth, they've come in a bit of clumps.

I was enticed into the field in 1984 because of a recent set of clumps then, and for a century, roughly every 30 years, we've had a burst of concern about automation and AI, and we've had big concern in the sense people said, “Are we almost there? Are we about to have pretty much all jobs automated?” They said that in the 1930s, they said it in the 1960s — there was a presidential commission in the 1960s: “What if all the jobs get automated?” I jumped in in the late ’80s when there was a big burst there, and I as a young graduate student said, “Gee, if I don't get in now, it'll all be over soon,” because I heard, “All the jobs are going to be automated soon!”

And now, in the last decade or so, we've had another big burst, and I think people who haven't seen that history, it feels to them like it felt to me in 1984: “Wow, unprecedented advances! Everybody's really excited! Maybe we're almost there. Maybe if I jump in now, I'll be part of the big push over the line to just automate everything.” That was exciting, it was tempting, I was naïve, and I was sucked in, and we're now in another era like that. Yes, if you're young, and you haven't seen the world for decades, you might well believe that we are almost there, we're just about to automate everything — but we're not.

I like that you mentioned the automation scare of the ’60s. Just going back and looking at that, it really surprised me how prevalent and widespread and how serious people took that. I mean, you can find speeches by Martin Luther King talking about how our society is going to deal with the computerization of everything. So it does seem to be a recurrent fear. What would you need to see to think it is different this time?

The obvious relevant parameter to be tracking is the percentage of world income that goes to automation, and that has been creeping up over the decades, but it's still less than five percent.

What is that statistic?

If you look at the percentage of the economy that goes to computer hardware and software, or other mechanisms of automation, you're still looking at less than five percent of the world economy. So it's been creeping up, maybe decades ago it was three percent, even one percent in 1960, but it's creeping up slowly, and obviously, when that gets to be 80 percent, game over, the economy has been replaced — but that number is creeping up slowly, and you can track it, so when you start seeing that number going up much faster or becoming a large number, then that's the time to say, “Okay, looks like we're close. Maybe automation will, in fact, take over most jobs, when it's getting most of world income.”

If you're looking at economic statistics, and you're looking at different forecasts, whether by the Fed or CBO or Wall Street banks and the forecasts are, “Well, we expect, maybe because of AI, productivity growth to be 0.4 percentage points higher over this kind of time. . .” Those kinds of numbers where we're talking about a tenth of a point here, that's not the kind of singularity-emergent world that some people think or hope or expect that we're on.

Absolutely. If you've got young enthusiastic tech people, et cetera — and they're exaggerating. The AI companies, even they're trying to push as big a dramatic images they can. And then all the stodgy conservative old folks, they're afraid of seeming behind the times, and not up with things, and not getting it — that was the big phrase in the Internet Boom: Who “gets it” that this is a new thing?

I'm proud to be a human, to have been part of the civilization to have done this . . . but we've seen that for 70 years: new technologies, we get excited, we try them out, we try to apply them, and that's part of what progress is.

Now it would be #teamgetsit.

Exactly, something like that. They're trying to lean into it, they're trying to give it the best spin they can, but they have some self-respect, so they're going to give you, “Wow 0.4 percent!” They'll say, “That's huge! Wow, this is a really big thing, everybody should be into this!” But they can't go above 0.4 percent because they've got some common sense here. But we've even seen management consulting firms over the last decade or so make predictions that 10 years in the future, half all jobs would be automated. So we've seen this long history of these really crazy extreme predictions into a decade, and none of those remotely happened, of course. But people do want to be in with the latest thing, and this is obviously the latest round of technology, it's impressive. I'm proud to be a human, to have been part of the civilization to have done this, and I’d like to try them out, and see what I can do with them, and think of where they could go. That's all exciting and fun, but we've seen that for 70 years: new technologies, we get excited, we try them out, we try to apply them, and that's part of what progress is.

 The tendency to control new tech (9:28)

Not to talk just about AI, but do you think AI is important enough that policymakers need to somehow guide the technology to a certain outcome? Daron Acemoglu, one of the Nobel Prize winners, has for quite some time, and certainly recently, said that this technology needs to be guided by policymakers so that it helps people, it helps workers, it creates new tasks, it creates new things for them to do, not automate away their jobs or automate a bunch of tasks.

Do you think that there's something special about this technology that we need to guide it to some sort of outcome?

I think those sort of people would say that about any new technology that seemed like it was going to be important. They are not actually distinguishing AI from other technologies. This is just what they say about everything.

It could be “technology X,” we must guide it to the outcome that I have already determined.

As long as you've said, “X is new, X is exciting, a lot of things seem to depend on X,” then their answer would be, “We need to guide it.” It wouldn't really matter what the details of X were. That's just how they think about society and technology. I don't see anything distinctive about this, per se, in that sense, other than the fact that — look, in the long run, it's huge.

Space, in the long run, is huge, because obviously in the long run almost everything will be in space, so clearly, eventually, space will be the vast majority of everything. That doesn't mean we need to guide space now or to do anything different about it, per se. At the moment, space is pretty small, and it's pretty pedestrian, but it's exciting, and the same for AI. At the moment, AI is pretty small, minor, AI is not remotely threatening to cause harm in our world today. If you look about harmful technologies, this is way down the scale. Demonstrated harms of AI in the last 10 years are minuscule compared to things like construction equipment, or drugs, or even television, really. This is small.

Ladders for climbing up on your roof to clean out the gutters, that's a very dangerous technology.

Yeah, somebody should be looking into that. We should be guiding the ladder industry to make sure they don't cause harm in the world.

The fallibility of forecasts (11:52)

I'm not sure how much confidence we should ever have on long-term economic forecasts, but have you seen any reason to think that they might be less reliable than they always have been? That we might be approaching some sort of change? That those 50-year forecasts of entitlement spending might be all wrong because the economy's going to be growing so much faster, or the longevity is going to be increasing so much faster?

Previously, the world had been doubling roughly every thousand years, and that had been going on for maybe 10,000 years, and then, within the space of a century, we switched to doubling roughly every 15 or 20 years. That's a factor of 60 increase in the growth rate, and it happened after a previous transition from forging to farming, roughly 10 doublings before.

It was just a little over two centuries ago when the world saw this enormous revolution. Previously, the world had been doubling roughly every thousand years, and that had been going on for maybe 10,000 years, and then, within the space of a century, we switched to doubling roughly every 15 or 20 years. That's a factor of 60 increase in the growth rate, and it happened after a previous transition from forging to farming, roughly 10 doublings before.

So you might say we can't trust these trends to continue maybe more than 10 doublings, and then who knows what might happen? You could just say — that's 200 years, say, if you double every 20 years — we just can't trust these forecasts more than 200 years out. Look at what's happened in the past after that many doublings, big changes happened, and you might say, therefore, expect, on that sort of timescale, something else big to happen. That's not crazy to say. That's not very specific.

And then if you say, well, what is the thing people most often speculate could be the cause of a big change? They do say AI, and then we actually have a concrete reason to think AI would change the growth rate of the economy: That is the fact that, at the moment, we make most stuff in factories, and factories typically push out from the factory as much value as the factory itself embodies, in economic terms, in a few months.

If you could have factories make factories, the economy could double every few months. The reason we can't now is we have humans in the factories, and factories don't double them. But if you could make AIs in factories, and the AIs made factories, that made more AIs, that could double every few months. So the world economy could plausibly double every few months when AI has dominated the economy.

That's of the magnitude doubling every few months versus doubling every 20 years. That's a magnitude similar to the magnitude we saw before from farming to industry, and so that fits together as saying, sometime in the next few centuries, expect a transition that might increase the growth rate of the economy by a factor of 100. Now that's an abstract thing in the long frame, it's not in the next 10 years, or 20 years, or something. It's saying that economic modes only last so long, something should come up eventually, and this is our best guess of a thing that could come up, so it's not crazy.

The risks of fertility-rate decline (14:54)

Are you a fertility-rate worrier?

If the population falls, the best models say innovation rates would fall even faster.

I am, and in fact, I think we have a limited deadline to develop human-level AI, before which we won't for a long pause, because falling fertility really threatens innovation rates. This is something we economists understand that I think most other people don't: You might've thought that a falling population could be easily compensated by a growing economy and that we would still have rapid and fast innovation because we would just have a bigger economy with a lower population, but apparently that's not true.

If the population falls, the best models say innovation rates would fall even faster. So say the population is roughly predicted to peak in three decades and then start to fall, and if it's falls, it would fall roughly a factor of two every generation or two, depending on which populations dominate, and then if it fell by a factor of 10, the innovation rate would fall by more than a factor of 10, and that means just a slower rate of new technologies, and, of course, also a reduction in the scale of the world economy.

And I think that plausibly also has the side effect of a loss in liberality. I don't think people realize how much it was innovation and competition that drove much of the world to become liberal because the winning nations in the world were liberal and the rest were afraid of falling too far behind. But when innovation goes away, they won't be so eager to be liberal to be innovative because innovation just won't be a thing, and so much of the world will just become a lot less liberal.

There's also the risk that — basically, computers are a very durable technology, in principle. Typically we don't make them that durable because every two years they get twice as good, but when innovation goes away, they won't get good very fast, and then you'll be much more tempted to just make very durable computers, and the first generation that makes very durable computers that last hundreds of years, the next generation won't want to buy new computers, they'll just use the old durable ones as the economy is shrinking and then the industry that commuters might just go away. And then it could be a long time before people felt a need to rediscover those technologies.

I think the larger-scale story is there's no obvious process that would prevent this continued decline because there's no level at which, when you get that, some process kicks in and it makes us say, “Oh, we need to increase the population.” But the most likely scenario is just that the Amish and [Hutterites] and other insular, fertile subgroups who have been doubling every 20 years for a century will just keep doing that and then come to dominate the world, much like Christians took over the Roman Empire: They took it over by doubling every 20 years for three centuries. That's my default future, and then if we don't get AI or colonize space before this decline, which I've estimated would be roughly 70 years’ worth more of progress at previous rates, then we don't get it again until the Amish not only just take over the world, but rediscover a taste for technology and economic growth, and then eventually all of the great stuff could happen, but that could be many centuries later.

This does not sound like an issue that can be fundamentally altered by tweaking the tax code.

You would have to make a large —

— Large turn of the dial, really turn that dial.

People are uncomfortable with larger-than-small tweaks, of course, but we're not in an era that's at all eager for vast changes in policy, we are in a pretty conservative era that just wants to tweak things. Tweaks won't do it.

Window of opportunity for space (18:49)

We can't do things like Daylight Savings Time, which some people want to change. You mentioned this window — Elon Musk has talked about a window for expansion into space, and this is a couple of years ago, he said, “The window has closed before. It's open now. Don't assume it will always be open.”

Is that right? Why would it close? Is it because of higher interest rates? Because the Amish don't want to go to space? Why would the window close?

I think, unfortunately, we've got a limited window to try to jumpstart a space economy before the earth economy shrinks and isn't getting much value from a space economy.

There's a demand for space stuff, mostly at the moment, to service Earth, like the internet circling the earth, say, as Elon's big project to fund his spaceships. And there's also demand for satellites to do surveillance of the earth, et cetera. As the earth economy shrinks, the demand for that stuff will shrink. At some point, they won't be able to afford fixed costs.

A big question is about marginal cost versus fixed costs. How much is the fixed cost just to have this capacity to send stuff into space, versus the marginal cost of adding each new rocket? If it's dominated by marginal costs and they make the rockets cheaper, okay, they can just do fewer rockets less often, and they can still send satellites up into space. But if you're thinking of something where there's a key scale that you need to get past even to support this industry, then there's a different thing.

So thinking about a Mars economy, or even a moon economy, or a solar system economy, you're looking at a scale thing. That thing needs to be big enough to be self-sustaining and economically cost-effective, or it's just not going to work. So I think, unfortunately, we've got a limited window to try to jumpstart a space economy before the earth economy shrinks and isn't getting much value from a space economy. Space economy needs to be big enough just to support itself, et cetera, and that's a problem because it's the same humans in space who are down here on earth, who are going to have the same fertility problems up there unless they somehow figure out a way to make a very different culture.

A lot of people just assume, “Oh, you could have a very different culture on Mars, and so they could solve our cultural problems just by being different,” but I'm not seeing that. I think they would just have a very strong interconnection with earth culture because they're going to have just a rapid bandwidth stuff back and forth, and their fertility culture and all sorts of other culture will be tied closely to earth culture, so I'm not seeing how a Mars colony really solves earth cultural problems.

Public prediction markets (21:22)

The average person is aware that these things, whether it's betting markets or these online consensus prediction markets, that they exist, that you can bet on presidential races, and you can make predictions about a superconductor breakthrough, or something like that, or about when we're going to get AGI.

To me, it seems like they have, to some degree, broken through the filter, and people are aware that they're out there. Have they come of age?

. . . the big value here isn't going to be betting on elections, it's going to be organizations using them to make organization decisions, and that process is being explored.

In this presidential election, there's a lot of discussion that points to them. And people were pretty open to that until Trump started to be favored, and people said, “No, no, that can't be right. There must be a lot of whales out there manipulating, because it couldn't be Trump's winning.” So the openness to these things often depends on what their message is.

But honestly, the big value here isn't going to be betting on elections, it's going to be organizations using them to make organization decisions, and that process is being explored. Twenty-five years ago, I invented this concept of decision markets using in organizations, and now in the last year, I've actually seen substantial experimentation with them and so I'm excited to see where that goes, and I'm hopeful there, but that's not so much about the presidential markets.

Roughly a century ago there was more money bet in presidential betting markets than in stock markets at the time. Betting markets were very big then, and then they declined, primarily because scientific polling was declared a more scientific approach to estimating elections than betting markets, and all the respectable people wanted to report on scientific polls. And then of course the stock market became much, much bigger. The interest in presidential markets will wax and wane, but there's actually not that much social value in having a better estimate of who's going to win an election. That doesn't really tell you who to vote for, so there are other markets that would be much more socially valuable, like predicting the consequences of who's elected as president. We don't really have much markets on those, but maybe we will next time around. But there is a lot of experimentation going in organizational prediction markets at the moment, compared to, say, 10 years ago, and I'm excited about those experiments.

A culture of calculated risk (23:39)

I want a culture that, when one of these new nuclear reactors, or these nuclear reactors that are restarting, or these new small modular reactors, when there's some sort of leak, or when a new SpaceX Starship, when some astronaut gets killed, that we just don't collapse as a society. That we're like, well, things happen, we're going to keep moving forward.

Do you think we have that kind of culture? And if not, how do we get it, if at all? Is that possible?

That's the question: Why has our society become so much more safety-oriented in the last half-century? Certainly one huge sign of it is the way we way overregulated nuclear energy, but we've also now been overregulating even kids going to school. Apparently they can't just take their bikes to school anymore, they have to go on a bus because that's safer, and in a whole bunch of ways, we are just vastly more safety-oriented, and that seems to be a pretty broad cultural trend. It's not just in particular areas and it's not just in particular countries.

I've been thinking a lot about long-term cultural trends and trying to understand them. The basic story, I think, is we don't have a good reason to believe long-term cultural trends are actually healthy when they are shared trends of norms and status markers that everybody shares. Cultural things that can vary within the cultures, like different technologies and firm cultures, those we're doing great. We have great evolution of those things, and that's why we're having all these great technologies. But things like safetyism is more of a shared cultural norm, and we just don't have good reasons to think those changes are healthy, and they don't fix themselves, so this is just another example of something that’s going wrong.

They don't fix themselves because if you have a strong, very widely shared cultural norm, and someone has a different idea, they need to be prepared to pay a price, and most of us aren’t prepared to pay that price.

If we had a healthy cultural evolution competition among even nations, this would be fine. The problem is we have this global culture, a monoculture, really, that enforces everybody.

Right. If, for example, we have 200 countries, if they were actually independent experiments and had just had different cultures going different directions, then I'd feel great; that okay, the cultures that choose too much safety, they'll lose out to the others and eventually it'll be worn out. If we had a healthy cultural evolution competition among even nations, this would be fine. The problem is we have this global culture, a monoculture, really, that enforces everybody.

At the beginning of Covid, all the usual public health efforts said all the usual things, and then world elites got together and talked about it, and a month later they said, “No, that's all wrong. We have a whole different thing to do. Travel restrictions are good, masks are good, distancing is good.” And then the entire world did it the same way, and there was strong pressure on any deviation, even Sweden, that would dare to deviate from the global consensus.

If you look about many kinds of regulation, it's very little deviation worldwide. We don't have 200, or even 100, independent policy experiments, we basically have a main global civilization that does it the same, and maybe one or two deviants that are allowed to have somewhat different behavior, but pay a price for it.

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Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Micro Reads

▶ Economics

* The Next President Inherits a Remarkable Economy - WSJ

* The surprising barrier that keeps us from building the housing we need - MIT

* Trump’s tariffs, explained - Wapo

* Watts and Bots: The Energy Implications of AI Adoption - SSRN

* The Changing Nature of Technology Shocks - SSRN

* AI Regulation and Entrepreneurship - SSRN

▶ Business

* Microsoft reports big profits amid massive AI investments - Ars

* Meta’s Next Llama AI Models Are Training on a GPU Cluster ‘Bigger Than Anything’ Else - Wired

* Apple’s AI and Vision Pro Products Don’t Meet Its Standards - Bberg Opinion

* Uber revenues surge amid robust US consumer spending - FT

* Elon Musk in funding talks with Middle East investors to value xAI at $45bn - FT

▶ Policy/Politics

* Researchers ‘in a state of panic’ after Robert F. Kennedy Jr. says Trump will hand him health agencies - Science

* Elon Musk’s Criticism of ‘Woke AI’ Suggests ChatGPT Could Be a Trump Administration Target - Wired

* US Efforts to Contain Xi’s Push for Tech Supremacy Are Faltering - Bberg

* The Politics of Debt in the Era of Rising Rates - SSRN

▶ AI/Digital

* Alexa, where’s my Star Trek Computer? - The Verge

* Toyota, NTT to Invest $3.3 Billion in AI, Autonomous Driving - Bberg

* Are we really ready for genuine communication with animals through AI? - NS

* Alexa’s New AI Brain Is Stuck in the Lab - Bberg

* This AI system makes human tutors better at teaching children math - MIT

* Can Machines Think Like Humans? A Behavioral Evaluation of LLM-Agents in Dictator Games - Arxiv

▶ Biotech/Health

* Obesity Drug Shows Promise in Easing Knee Osteoarthritis Pain - NYT

* Peak Beef Could Already Be Here - Bberg Opinion

▶ Clean Energy/Climate

* Chinese EVs leave other carmakers with only bad options - FT Opinion

* Inside a fusion energy facility - MIT

* Why aren't we driving hydrogen powered cars yet? There's a reason EVs won. - Popular Science

* America Can’t Do Without Fracking - WSJ Opinion

▶ Robotics/AVs

* American Drone Startup Notches Rare Victory in Ukraine - WSJ

* How Wayve’s driverless cars will meet one of their biggest challenges yet - MIT

▶ Space/Transportation

* Mars could have lived, even without a magnetic field - Big Think

▶ Up Wing/Down Wing

* The new face of European illiberalism - FT

* How to recover when a climate disaster destroys your city - Nature

▶ Substacks/Newsletters

* Thinking about "temporary hardship" - Noahpinion

* Hold My Beer, California - Hyperdimensional

* Robert Moses's ideas were weird and bad - Slow Boring

* Trading Places? No Thanks. - The Dispatch

* The Case For Small Reactors - Breakthrough Journal

* The Fourth Industrial Revolution and the Future of Work - Conversable Economist

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

On October 13, SpaceX and Elon Musk successfully launched their Starship rocket into low-Earth orbit. Then, in a milestone moment for space technology, they successfully captured the rocket’s Super Heavy booster with “chopstick” arms on the launch tower upon reentry, marking the first time a booster was ever caught in mid-air.

The achievement is a mind-blowing feat of human engineering — one that hasn’t gotten nearly the recognition that it deserves. Today on Faster, Please! — The Podcast, I talk with must-read space journalist Eric Berger about the role of SpaceX in the new, 21st-century Space Race, the significance of the company’s achievements, and our potential to become a spacefaring, inter-planetary species.

Berger is the senior space editor at Ars Techica, and is the author of both Liftoff: Elon Musk and the Desperate Early Days that Launched SpaceX and his most recent excellent book, Reentry: SpaceX, Elon Musk, and the Reusable Rockets that Launched a Second Space Age.

In This Episode

* Starship’s big reentry (1:43)

* Race (back) to the moon (8:54)

* Why Starship? (11:48)

* The Mars-shot (18:37)

* Elon in the political area (22:10)

* Understanding SpaceX (24:06)

Below is a lightly edited transcript of our conversation

Starship’s big reentry (1:43)

James Pethokoukis: After the launch tower caught that booster stage of the rocket, I saw someone on Twitter a day later say, “Hey, do you guys remember over the weekend when SpaceX sent a Statue-of-Liberty-sized object to space and then caught it when it came back down? That was amazing!”

So two things: First, as a space guy, what was your reaction? Two, beyond the sheer coolness of it, why was this an important thing to happen?

It seemed inconceivable a few years ago, but now, all of a sudden, it's the future of rocketry, just like that.

Eric Berger: Just from a space perspective, it’s epic to see, to use your adjectives, the Statue of Liberty comparison. I mean, it's a small skyscraper, but they essentially launch that thing to space at thousands of miles per hour, then it slows down, it comes back right where it took off from, hovers, and it falls precisely into these two arms that are designed to catch it. The cool thing is that we'd never seen anything like that before. It seemed inconceivable a few years ago, but now, all of a sudden, it's the future of rocketry, just like that.

the significance of this, of course, is SpaceX has shown that with the reusability of the Falcon 9 rocket, it can really change the economics of launch. This year they've launched 101 times. No country had ever done that many launches before in a year. They're going to launch 95 percent of all the mass into orbit this year with primarily the Falcon 9 Rocket, and all that's because the first stage is entirely reusable, they're flying them more than 20 times now, and so they're just taking that and scaling it.

What was amazing about the tower catch this weekend was the fact that it really removes the need for landing legs. You may think, “Well, what's the big deal about that?” Well, there's a lot of mass involved with those landing legs: You need powerful actuators to drive them, you need hydraulic fluid, and that's a lot of dead mass in the vehicle. Also, it's not insignificant to transport the rocket from wherever it lands, either on a boat or on land, to the factory and to refurbish the rocket and launch again. Ideally, with this step, they're eliminating days from that process of reuse and ideally, in the future, they're literally going to be catching the rocket, setting it back on the launch mount and then potentially flying again.

So it's not just the Starship, right? So for the other launches, is this is going to become the landing procedure?

No, it will be just for Starship. They will continue to fly Falcon 9 as is. That's a mature product, everyone's pretty comfortable with that vehicle. But, look, other companies have tried different things. When Rocket Lab was trying to reuse its small Electron vehicle, its plan was to have the first stage come back under a parachute and then basically swoop in with a helicopter and catch it so that the rocket didn't fall into the ocean. That ended up not working.

It seems very whimsical.

Well, it made sense from an engineering standpoint, but it was a lot more difficult to snag the rocket than they ended up finding out. So, up until now, the only way to get a rocket back vertically was on a drone ship or landing straight up, and so this is a brand new thing, and it just creates more efficiencies in the launch system.

What is the direction now, as far as launch costs and the continued decline of launch costs if this will be the new landing procedure for Starship?

It's impossible to say that, of course. We can look to a Falcon 9 for an analog. SpaceX sales started out selling Falcon 9 for $60 million, it's upped that price to about $67 or $68 million — still the lowest-cost medium-lift launch vehicle in the world, but that's the price you or I or NASA would pay for a rocket. Internally, the estimate is that they're re-flying those vehicles for about $15 million. So, in effect, SpaceX has taken the cost of the lowest-price vehicle on the market and divided it by four, basically.

Starship, of course, can lift much more payload to orbit than Falcon 9. By some measures, five to 10 times as much, eventually. And so if they can get the cost down, if they can make the first and second stage reusable, I think you're talking about them bringing the cost down potentially another order of magnitude, but they've got a lot of work to get there.

I think the second most common comment I saw on social media — the first one being like, “This is amazing, I'm crying, this is so cool” — the second one is, “Why is NASA not using this Starship to get to the moon?” It seems like progress is being made quickly, and you mentioned the costs, I think people are just befuddled. It's a question you must get a lot.

The reality is that if we want to go to the moon before 2030, we probably need to do it with a combination of NASA's Space Launch System rocket and Starship.

It's a complicated answer, but the reality is that NASA, in conjunction with Congress, has basically, over the last quarter of a century, pivoted away from reusable launch vehicles, and at one point in the early 2000s, they were actually funding three different reusable launch vehicles. The most famous of those, of course, was the Space Shuttle. It stopped funding the Space Shuttle in 2011 and it went back to developing this large, expendable rocket called the Space Launch System. That was the tried and true pathway, and no one really had faith in what SpaceX is doing. And so now here we are, almost 15 years later, and SpaceX has gone out and proved it with the Falcon 9, the Falcon Heavy, and now Starship.

The reality is that if we want to go to the moon before 2030, we probably need to do it with a combination of NASA's Space Launch System rocket and Starship. In 2021, NASA did select Starship as its lunar lander. So Starship is a critical part of the architecture. Probably the most challenging part, actually, is getting down to the lunar surface and then getting back up reliably. And so Starship plays a key role, and I just really think that it's inevitable that Starship and potentially Blue Origin’s architecture will be how humans get to the moon and back, but we're kind of in an interim period right now.

Is it just sort of too late to switch?

Yeah, it is. It's too late to switch. You could conceive of scenarios in which humans launch in Crew Dragon, transfer over to a Starship, and then come back in Crew Dragon, but even then you've got some challenges. And the problem — problem is the wrong word, but one of the major issues with Starship is that it has no redundancy when you come back and land. It has got to nail the landing or people inside of it die. So you're going to want to see hundreds of Starship launches and many, many successful landings in a row before you put people on the vehicle. And to have the idea of launching humans from Earth to the moon at this point, we're pretty far from that. I would think a decade from now, at least, and by then China will be on the moon. And so it's really a matter of, do you want to sort of continue to delay the human return of the moon, or do you want to take the tools that you have now and make your best run for it?

Race (back) to the moon (8:54)

Since you brought it up, are we going to beat China to the moon with the SLS?

Very much an open question. The SLS Rocket is basically ready. In its current form, it performed very well during Artemis I. It's obviously super expensive. You may have seen the Europa Clipper launch on Monday of this week, that launched on a Falcon Heavy. For almost a decade, Congress mandated NASA that it launched on the SLS rocket, and that would've cost 10 times as much. NASA paid about $200 million for the Clipper launch on Falcon Heavy, SLS would've been in excess of $2 billion, so it's a very expensive rocket, but it does work, it worked well during Artemis I. The best way we have right now, Jim, to get astronauts from Earth out to lunar orbit is SLS and the Orion deep spacecraft vehicle. That will change over time, but I think if we want to put humans on the moon this decade, that's probably the best way to do it.

Is it going to be a close call? I don't want to overemphasize the competition aspect, but I guess I would like to see America do it first.

It's going to be close. NASA's current date is 2026 for the Artemis III moon landing. There's no way that happens. I think 2028 is a realistic no-earlier-than date, and the reality is SpaceX has to make a lot of progress on Starship. What they did this past weekend was a great step. I think the key thing about the fact of this weekend's launch is that it was a success. There were no anomalies, there's going to be no investigation, so SpaceX is going to launch again. As long as they continue to have success, then they can start popping these off and get to some of the really key tests like the in-space propellant transfer tests, which they hope to do sometime next year.

[W]hen you're on the moon, there's no launch tower, there's no launch crew, you’ve just got the astronauts inside Starship, and if that vehicle doesn't take off on the moon, the crew's going to die. So it's got to work.

What Starship will do is it'll launch into low-earth orbit, and then it'll be refueled, and it'll go to the moon, and you need lots of launches to refuel it. And then really the key test, I think, is landing on the moon, because the South Pole is pretty craterous, you've got to have high confidence in where you land, and then the big challenge is getting back up to lunar orbit safely.

Think about it: When you watch any rocket launch, you see this very detailed, very intricate launch tower with all these umbilicals, and all of these cables, and power, and telemetry, and stuff, and humans are looking at all this data, and if there's any problem, they abort, right? Well, when you're on the moon, there's no launch tower, there's no launch crew, you’ve just got the astronauts inside Starship, and if that vehicle doesn't take off on the moon, the crew's going to die. So it's got to work. And so that's really a big part of the challenge, as well, is getting all that to work. So I think 2028, for all that to come together, is a realistic no-earlier-than date, and China's pretty consistently said 2030, and they're starting to show off some hardware, they recently demonstrated that suggests they have a chance to make 2030.

On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

Why Starship? (11:48)

What is the commercial case for Starship, assuming that these next launches continue to go off well? What is it supposed to be doing here on Earth and in Earth orbit?

The next big race is to deliver internet, not to a dish that you set up, but actually to your mobile phone. It's called direct-to-cell, and you need much bigger satellites for this. And so SpaceX needs the Starship to launch these satellites, so that will really be the commercial use case for Starship in the near term.

Its primary function, and I think the most important function for SpaceX in the near term, is launching these much larger Starlink satellites. I think it's been pretty well proven that there's a large demand for broadband internet from low-earth orbit. Starlink has now up to four million customers and they're actually signing almost at an exponential rate. Then growth, the business is profitable. So that's been super impressive. The next big race is to deliver internet, not to a dish that you set up, but actually to your mobile phone. It's called direct-to-cell, and you need much bigger satellites for this. So SpaceX needs the Starship to launch these satellites, so that will really be the commercial use case for Starship in the near term.

I think once the vehicle starts flying reliably, we're going to see where the commercial customers go because we've never really been in a launch environment where you're not really constrained by mass and, more importantly, by volume. You can just build bigger, less-efficient things. Instead of hyper-managing your satellite to be small, and light, and compact, you can kind of make trades where maybe you have a lower-cost vehicle that's bigger. The capability of Starship with its voluminous payload fairing and being able to lift a hundred or more tons to low-earth orbit for low cost — entirely new regime. And so I think it's a case of Field of Dreams, “If you build it, they will come,” and in the near term, Starship will be the business case, and longer-term we'll see some unique opportunities.

You've been covering this for quite a while, documenting, books, including your most recent book. Really an amazing ride as a space journalist for you here.

I've been covering space now for two decades, and really with a focus on commercial space over the last decade because I think that's where a lot of the excitement and innovation is coming from. But the reality is that you've got this whole ecosystem of companies, but the 800-pound gorilla is SpaceX. They're the company that has consistently had success. They are the only provider of crew transportation services for NASA, still, even five years after their initial success, and they're the only provider right now that's launching cargo missions to the space station. They've got huge Starlink satellites, constellation. As a journalist, you really want to understand the biggest, most dominating force in the industry, and that's clearly SpaceX, and so that's why I've chosen to dedicate a lot of time to really understand where they started out and how they got to where they are, which is at the top of the heap.

The story that you lay out in your book, which came out last month — Reentry: SpaceX, Elon Musk, and the Reusable Rockets that Launched a Second Space Age — to me, it’s still a story people mostly don’t know, and one that I think a lot of non-space reporters don’t understand. What are some common misunderstandings that you come across that make you feel like you need to tell this story?

I think, until recently, one of the things that people might say about SpaceX is, “Well, what's the big deal? NASA's launched humans to orbit in the past, NASA's launched cargo, they had a reusable space vehicle in the Space Shuttle.” What's different is that SpaceX is doing this at scale, and they're building for a long-term plan that is sustainable.

I'll give you an example: The Space Shuttle was reusable. Everything was reusable except the external tank. However, you needed a standing army of thousands of people to pour over the Space Shuttle after it came back from space to make sure that all of its tiles and every piece of equipment was safe. Now, when it was originally sold to Congress back in the 1970s, the program manager for the space shuttle, George Mueller said that the goal was to get the cost of payload-to-orbit for the Space Shuttle down to $25 a pound, which sounded great because then they were saying dozens of people could fly on the vehicle at a time. Well, of course, at the end of the day, it only ever flew at a maximum of seven people, and the cost of payload-to-orbit was $25,000. So yes, it was reusable, but it was the kind of thing that was super expensive and you couldn't fly very often. You could do limited things.

It's really the first vehicle we ever developed to go to Mars. SpaceX is doing some of the same things that NASA did, but it's doing them better, faster, and a lot cheaper.

SpaceX is proposing kind of an order-of-magnitude change. We went to the moon in the 1960s with the Lunar Module, and everyone remembers it carried two astronauts down to the lunar surface. And that whole thing launched on a giant stack, the Saturn V rocket. So if you were to take the Lunar Module and replace the astronauts and just use it to deliver cargo to the moon, it could take five tons down to the lunar surface. Starship, in a reusable mode, can take a hundred tons. If you send an expendable version of Starship, it's 200 tons. And oh, by the way, even if you're not bringing that Starship back, you're getting the whole first stage back anyway.

And so that's really the promise here, is you're building a sustainable system in space where it doesn't cost you $6 billion to go to the moon, it costs you half a billion dollars or to go to the moon, and you can then go on and do other things, you can fill your Starship up with methane repellent and go further. It's really the first vehicle we ever developed to go to Mars. SpaceX is doing some of the same things that NASA did, but it's doing them better, faster, and a lot cheaper.

That $25-a-pound number you gave for Space Shuttle, where are we with SpaceX? Where is SpaceX, or where are they and what's their goal in that context?

They're getting down in a couple of thousand dollars a pound with a Falcon 9, and the idea is, potentially, with Starship, you get down to hundreds of dollars a pound or less. They have a big challenge too, right? They're using tiles on Starship as well. They showed some of them off during the webcast this weekend, and I think we have yet to have any kind of information on how reusable, or how rapidly reusable Starship will be, and we'll have to see.

The Mars-shot (18:37)

To the extent the public understands this company — this is my understanding — the point here is to build Starship, to further this satellite business, and then that satellite business will fund the eventual Mars mission and the Mars colonization. I think that's the public perception of what is happening with this business. How accurate is that? Is that how you look at it? I mean, that's how I look at it from my uninformed or less-informed view, but is that really what we're talking about here?

Yeah, fundamentally, I think that is accurate. There is no business case right now to go to Mars. AT&T is not going to pay $5 billion to put an AT&T logo on a Starship and send a crew to Mars. There are no resources right now that we really can conceive of on Mars that would be profitable for humans to go get and bring back to Earth. So then the question is: How do you pay for it?

Financially, the business case for Mars is not entirely clear, so you’ve got to figure out some way to pay for it. That was one reason why Elon Musk ultimately went with Starlink. That would pay for the Mars vision.

Even when settlers went to the New World in the 1500s, 1600s, in United States, they were exporting tobacco and other products back to Europe, and there's no tobacco that we know of on Mars, right? Financially, the business case for Mars is not entirely clear, so you’ve got to figure out some way to pay for it. That was one reason why Elon Musk ultimately went with Starlink. That would pay for the Mars vision.

I think that's still fundamentally the case. It's effectively going to be paying for the entire development of Starship, and then if it becomes highly profitable, SpaceX is not a public company, so they can take those revenues and do whatever they want with them, and Elon has said again and again that his vision is to settle Mars, and he's building the rockets to do it, and he's trying to find the funding through Starlink to accomplish it. That is the vision. We don't know how it's all going to play out, but I think you're fundamentally correct with that.

I think when he mentions Mars, there are some people that just give it a roll of the eye. It just sounds too science fictional, despite the progress being made toward accomplishing that. It sounds like you do not roll your eyes at that.

Well, it's interesting. He first really talked publicly about this in 2016, eight years ago, back when there was no Starship, back when they just were coming off their second Falcon 9 failure in about a year, and you kind of did roll your eyes at it then . . . And then they got the Falcon 9 flying and they started re-flying it and re-flying it. They did Falcon Heavy, and then they started building Starship hardware, and then they started launching Starship, and now they're starting to land Starship, and this is real hardware.

And yes, to be clear, they have a long, long way to go and a lot of technical challenges to overcome, and you need more than just a rocket in a spaceship to get to Mars, you need a lot of other stuff, too: biological, regulatory, there's a lot of work to go, but they are putting down the railroad tracks that will eventually open that up to settlement.

So I would not roll my eyes. This is certainly the only credible chance, I think, for humans to go to Mars in our lifetimes, and if those early missions are successful, you could envision settlements being built there.

Elon in the political arena (22:10)

Given SpaceX's accomplishments and their lead, is that company politics-proof? Obviously there's always going to be controversy about Elon, and Twitter, and who he gives money to, and things he says, but does any of that really matter for SpaceX?

I think it does. We've already seen a couple examples of it, especially with Elon's very public entree into presidential politics over the last several months. I think that does matter. In his fight with Brazil over what he termed as free speech, they were confiscating Starlink, and so they were trying to shut Starlink down in their country, and that directly affects SpaceX. In California, over the last week we have seen a commission vote to try to limit the number of launches Falcon 9 launches from Vandenberg Space Force Base, and they clearly did that because they were uncomfortable with Elon's behavior publicly. So yeah, this is going to bleed over.

Now, in the near term, there will be limited impacts because the US Department of Defense clearly needs SpaceX rockets. They need SpaceX’s Starlink, they use a branded version of it called Starshield for military communications. The launch and Starlink capabilities are essential for the military. NASA is even more reliant on SpaceX for the International Space Station and beyond; the entire moon program runs through Starship, so it's not going to change in the near term, but longer term you could see this having impacts, and it's not clear to me exactly what those would be — I don't think you could really nationalize SpaceX, and I think if you did try to nationalize SpaceX, you would sort of destroy its magic, but I do think there will ultimately be consequences for the Elon's political activity.

Understanding SpaceX (24:06)

About Reentry, is there a particular story in there that you think just really encapsulates, if you want to understand SpaceX, and what it's doing, and where it's come from, this story kind of gets at it?

The point of the book was to tell the story behind the story. A lot of people knew, generally, what SpaceX has accomplished over the last decade, or the last 15 years, but this really takes you behind the scenes and tells the stories of the people who actually did it.

It's a company that's moving so fast forward that, like I said, there are all these challenges they're facing and they're just tackling them one-by-one as they go along.

I think one of the best stories of the book is just how they were making this up as they went along. The very first time they were going to try to land on the barge was in January of 2015, the drone ship landing, and the night before that barge was going to set out to sea, the guy who had developed the barge realized that, wait a minute, if we come back with a rocket this week, we have nowhere to put it in the port of Jacksonville, because they were staging out of Jacksonville at the time. And there had been this whole discussion at SpaceX about where to put these pedestals, but no one had actually done it. That night, he and another engineer stayed up all night drinking red wine and CADing out designs for the pedestals, and they met the concrete pores the next morning and just built these pedestals within 24 hours. It's a company that's moving so fast forward that, like I said, there are all these challenges they're facing and they're just tackling them one-by-one as they go along.

Elon has spoken about there's sort of this window of opportunity open for space. In the United States, at least, it was open and then it kind of closed. We stopped leaving Earth orbit for a while, we couldn't even get our people into Earth orbit; we had to use another country's rockets.

Is this window — whether for space commerce, space exploration — is it sort of permanently open? Are we beyond the point where things can close — because satellites are so important, and because of geopolitics, that window is open and it's staying open for us to go through.

I think he's talking about the window for settlement of Mars and making humans a multi-planetary species. And when he talks about the window closing, I think he means a lot of different things: One, the era of cheaper money could end — and that clearly did happen, right? We've seen interest rates go way up and it's been much more difficult to raise money, although SpaceX has been able to still do that because of their success. I think he's thinking about his own mortality. I believe he's thinking about a major global war that would focus all of our technological efforts here on planet Earth trying to destroy one another. I think he's thinking about nuclear weapons — just all the things that could bring human progress to a screeching halt, and he’s saying, “Look, the window may be 100 years or it may be 20 years.” So he's like, “We should seize the opportunity right now when we have it.”

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Micro Reads

▶ Economics

* Larry Summers on the Economics of AI - Conversable Economist

* Landing Softly Is Just the Beginning - San Francisco Fed

* More Babies Aren’t the Only Solution to Falling Birthrates - NYT Opinion

* Generative AI at work: Survey evidence from three Central Banks - SSRN

▶ Business

* Nvidia Chief Makes Case for AI-First Companies - WSJ

* Apple Intelligence Isn’t Very Smart Yet—and Apple’s OK With That - WSJ

* Andreessen Horowitz Backs Infinitus to Bring AI to Medical Calls - Bberg

* Breaking Up Google Is a Fool’s Game - WSJ Opinion

▶ Policy/Politics

* The US is the world’s science superpower — but for how long? - Nature

* Can A.I. Be Blamed for a Teen’s Suicide? - NYT

* Former OpenAI Researcher Says Company Broke Copyright Law - NYT

* The tragedy of a 50-50 America - FT Opinion

* Both Harris and Trump pose problems for U.S. energy producers. - AEI

* Why Harris and Trump Are Pandering to Crypto Plutocrats - NYT Opinion

* Trump’s Tariffs and Economic Risk - WSJ Opinion

* China asks: what is an e-bike? - FT Opinion

* This Startup Shows Why the U.S. CHIPS Act Is Needed - Spectrum

▶ AI/Digital

* Big frontier AI systems will emerge from global, distributed efforts, not just big tech: Meta’s Yann LeCun - Techcircle

* Does ChatGPT Have a Poetic Style? - arXiv

▶ Biotech/Health

* Danes to Use New Nvidia AI Supercomputer for Drug Discovery - Bberg

▶ Clean Energy/Climate

* Averting Climate Catastrophe Requires Economic Growth - PS

* The Energy Transition We Really Should Be Focusing On - RealClearScience

* To Fight Climate Change, Clean Up Carbon Markets - Bberg Opinion

* A Mexican Electric Car? Only If Private Firms Lead the Way - Bberg Opinion

▶ Robotics/AVs

* Crop-spraying robot is designed to reduce emissions and use less herbicide - Atlas

▶ Space/Transportation

* Beetlejuice, Betelgeuse, Betelbuddy? Astronomers Find Something Unexpected Orbiting Infamous “Doomed Star” - Debrief

▶ Up Wing/Down Wing

* Meet Hollywood’s AI Doomsayer: Joseph Gordon-Levitt - WSJ

* Here’s What the Regenerative Cities of Tomorrow Could Look Like - Wired

* Archimedes Rediscovered: Technology and Ancient History - JSTOR Daily

* Energy expert Vaclav Smil on how to feed the world without trashing it - NS

▶ Substacks/Newsletters

* Yes, You’re Still Imagining a Migrant Crime Spree - Alex Nowrasteh's Immigration Insights and Other Deep Dives

* How long can we sustain economic growth? - Noahpinion

* What is Anthropic's AI Computer Use? - AI Supremacy

* An AI intern in your pocket - Exponential View

* Industrial Policy’s Inescapable Uncertainty Problem - The Dispatch

* NEPA Nightmares IV: Tule Wind - Breakthrough Journal

* When you give a Claude a mouse - One Useful Thing

* Larry Summers on the Economics of AI - Conversable Economist

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Eli Dourado is on a mission to end the Great Stagnation, that half-century period of economic and technological disappointment that began in the 1970s (what I refer to in my 2023 book, The Conservative Futurist, as the Great Downshift). If we want to turn the page on this chapter of slow progress and deserved skepticism, we’re going to have to accept some creative destruction.

Dourado believes that the courage to embrace major change is key to meeting our potential. Today on Faster, Please! — The Podcast, I talk with Dourado about the future of the US job market and energy production in a world of AI.

Dourado is chief economist at the Abundance Institute, and author of his own Substack newsletter.

In This Episode

* The dawn of a productivity boom? (1:26)

* Growing pains of job market disruption (7:26)

* The politics of productivity growth (15:20)

* The future of clean energy (23:35)

* The road to a breakthrough (30:25)

* Reforming NEPA (35:19)

* The state of pro-abundance (37:08)

Below is a lightly edited transcript of our conversation

The dawn of a productivity boom? (1:26)

Pethokoukis:  Eli, welcome to the podcast.

Dourado: Thanks for having me on, Jim.

I would like to think that what we are experiencing here in the 2020s is the beginnings of an extended productivity boom. We have some good economic data over the past year and a half. I know this is something that you care about, as I do . . . What's your best guess?

I think the seeds of a boom are there. There's plenty of low-hanging fruit, but I'd say the last few quarters have not been that great for TFP growth, which is what I followed most closely. So we actually peaked in TFP in the US in Q4, 2021.

Now what is that, what is TFP?

Total factor productivity. So that's like if you look at inputs and how they translate into outputs.

Capital, labor . . .

Capital and labor, adjusting for quality, ideally. We've gotten less output for the amount of inputs in the last quarter than we did at the end of 2021. So slight negative growth over the last three years or so, but I think that you're right that there is room for optimism. Self-driving cars are coming. AI has immense potential.

My worry with AI is other sociopolitical limits in the economy will hold us back, and you kind of see the news breaking today as we're recording this, is there's a strike at the ports on east coast, and what's at issue there is are we allowed to automate those jobs? Are the owners of the ports allowed to automate those jobs? And if the answer ends up being “no,” then you can say goodbye to productivity gains there. And so I really think the technology is there to do a lot more to kick off a productivity boom, but it's the sociopolitical factors that are slowing us down.

And I definitely want to talk about those sociopolitical factors, and the port strike is hopefully not a harbinger. But before I leave this topic, I suppose the super bullish case for productivity is that AI will be so transformative, and so transformative throughout the economy, both automating some things, helping us do other things more efficiently, and creating brand new high-productivity things for us to do that we will have maybe an extended 1990s, maybe more, I might hope?

What is your bullish case, and does that bullish case require what they call artificial general intelligence, or human-level, or human-level plus intelligence? Is that key? Because obviously some people are talking about that.

Can we have an important productivity boom from AI without actually reaching that kind of science-fictional technology?

I don't actually think that you need one-to-one replacement for humans, but you do need to get humans out of the loop in many, many more places. So if you think about the Baumol effect, the idea here is if there are parts of the economy that are unevenly growing in productivity, then that means that the parts of the economy where there is slow productivity growth, perhaps because you have human labor still being the bottleneck, those parts are going to end up being massive shares of the economy. They're going to be the healthcares, the educations, the parts of the economy where we have lots of inflation and increased costs. So the real boom here, to me, is can you replace as many humans as possible? Over the short run, you want to destroy jobs so that you can create a booming economy in which the jobs are still available, but living standards are much higher.

If you think about these big chunks of GDP like health, housing, energy, transportation, that's what you need to revolutionize, and so I can think of lots of ways in health that we could use AI to increase productivity. And I also have very little doubt that even current levels of AI could massively increase productivity in health. I think the big question is whether we will be allowed to do it.

So you don't need AGI that is as good as a human in every single thing that a human might do to limit the number of humans that are involved in providing healthcare. Housing, I think there's construction robots that maybe could do it, but I think the main limits are, like land use regulation, more sociopolitical. In energy, it's kind of the same thing, NIMBYism is kind of the biggest thing. Maybe there's an R&D component that AI could contribute to. And then in transportation, again, we could automate a lot of transportation. Some of that's happening with autonomous cars, but we are having trouble automating our ports, for example, we're having trouble automating cargo railroads for similar make-work reasons.

I think the bull case is you don't need AGI, really, really sophisticated AI that can do everything, but you do need to be able to swap out human workers for even simpler AI functions.

I don't actually think that you need one-to-one replacement for humans, but you do need to get humans out of the loop in many, many more places.

Growing pains of job market disruption (7:26)

I'm sure that some people are hearing you talk about swapping out human workers, replacing human workers. They're thinking, this is a world of vast technologically-driven unemployment; that is what you are describing. Is that what you're describing?

Not at all. If we had the kind of productivity boom we're talking about, the economy would be so incredibly hot, and you need that hot market. People have all kinds of fantasies about how good AI could get. Can it substitute for a human in every single thing? And I'm not even positing that. I'm saying if we could just get it good enough to substitute in some things, the economy's going to be booming, it's going to be hot, there will still be things that humans can do that AIs can’t. There's lots of things that maybe we want a human to do, even if the AI can do it, and we will be able to afford that a lot better.

I think that the world I'm thinking about is one where living standards are way higher for everybody — and higher levels of equality, even. If you have the sort of uneven productivity gains that we've had for the last several decades, where tech does really well, but every other part of the economy does badly, well, that drives a lot of regional inequality, that drives a lot of different kinds of demographic inequality, and if we had broad-base productivity growth, that means better living standards for everybody, and I think that's what we should aim for.

When I talk about what you've been referring to as these sociopolitical factors or how we might slow down progress, slow down automation, the whimsical example I use is there being a law saying that yes, you can have kiosks in every McDonald's, but you have to have an employee standing next to the kiosk to actually punch the buttons.

As you mentioned with this port worker strike, we don't need my scenario. That is kind of what's happening on these ports, where there could be a lot more automation, but because of both unions and our acquiescence to these unions, we don't have the kind of automation — forget about sci-fi — that doesn't exist in other places in the world. And I wonder if that doesn't sort of encapsulate, at least in this country, the challenge: Can we get our heads around the idea that it's okay in the long run, that there will be some downsides, and some people might be worse off, and we need to take care of those people, but that's the disruption we need to tolerate to move forward?

You can't have a growing economy where there's no churn, where there's no displacement, where it's complete, where there's no dynamism. You need to be able to accept some level of change. I sympathize with people whose jobs get destroyed by automation. It is hard, but it's much less hard if the economy is super hot because we've been prioritizing productivity growth, and if that were the case, I think we'd find new jobs for those people very quickly. The process is not automatic, but it's much slower when you have low productivity growth and a stagnant economy than it is when you have high productivity growth and a booming economy.

The question I always get is, what about the 60-year-old guy? What's he going to do? And I'm not sure I have a much better answer. Maybe there's other jobs, but it's tough to transition, so maybe the answer there is you cut him a check, you cut that 60-year-old a check, and if you have a high-productivity economy, you have the resources for that to be an option.

Right! So that's the other thing is that we can afford to be generous with people if we have a really rapidly growing economy. It’s that we don't have the resources if we're stagnating, if we're already overextended fiscally, that's a terrible position to be in because you can't actually afford to be generous. And if there are people that truly, like you said, maybe they're very old and it doesn't make sense to retrain, or something like that, they’re near retirement, yeah, absolutely, we can afford that much better when GDP is much higher.

Where do you think, as a nation, our head is at as far as embracing or not being fearful of disruption from technological change? If I only looked at where our head was at with trade, I would be very, very worried about entering a period of significant technological disruption, and I would assume that we will see lots and lots of pushback if AI, for instance, is the kind of important, transformative, general purpose technology that I hope it is.

Again, if I look at trade, I think, “Boy, there's going to be a lot of pushback.” Then again, when I think about risk broadly, and maybe it's not quite the same thing, I think, “Well, then again, we seem to be more embracing of nuclear energy, which shows maybe — it's not the same thing, but it shows a greater risk tolerance.” And I'm always thinking, what's our societal risk tolerance? Where do you think we're at right now?

I think most people, most Americans, don't actually think in those terms. I think most Americans just think about, “How are things going for me?” They kind of evaluate their own life, and if their communities, or whatever, have been struggling due to trade stuff, or something like that, they'll be against it. So I think the people who think in these more high-level terms, it’s like societal elites, and I think normal people who have just lived under 50 years of stagnation, they're kind of distrustful of the elites right now: “I don't pay attention to policy that closely, and my life is bad, at least in some dimensions is not as good as I wanted it to be, it's hasn't had the increase that my parents' generation had,” or something like that. And they're very distrustful of elites, and they're very mad, and you see this nihilistic populism popping up.

You see kind of a diverse array of responses to this nihilistic populism. Some people might say, “Well yeah, elites really have messed up and we need to do what the common people want.” And then the other people are like, “No, we can't do that. We need to stay the course.” But I think that there's a hybrid response, where it's like, the elites really have done bad, but we don't just want to do what the populists want, we want to just have better elite-led policies, which include things like, we have to take productivity growth seriously, we can't just paper over a lot of the tensions and the conflicts that arise from that, we need to embrace them head-on and do everything we can to produce an economy that is productive, that works for everybody, but maybe not in the way that the populists think it will work.

You can't have a growing economy where there's no churn, where there's no displacement, where it's complete, where there's no dynamism. You need to be able to accept some level of change.

The politics of productivity growth (15:20)

I would love to see what American politics looks like if the rest of this decade we saw the kind of economic productivity and wage growth that we saw in the fat part of the 1990s. We act like the current environment, that's our reality, and that's our reality as far as the eye can see, but I'll tell you, in the early ’90s, there was a lot of gloom and doom about the economy, about productivity, how fast we could grow, the rise and fall of great powers, and America was overstretched, and after really three or four years of strong growth, it's like America Triumphant. And I’m wondering if that would be the politics of 2030 if we were able to generate that kind of boom.

Yeah, I think that's totally right. And if you look at total factor productivity, which is my KPI [key performance indicator] or whatever, if you look at 1995 to 2005, you were back to almost two percent growth, which is what we had from 1920 to 1973. So you had a slow period from 1973 to 1995, and an even slower period since 2005, and you get back to that two percent. That's the magic number. I think if we had TFP at two percent, that changes everything. That's a game-changer for politics, for civility, for social stability, we'd really be going places if we had that.

I was mentioning our reaction to trade and nuclear power. The obvious one, which I should have mentioned, is how we are reacting to AI right now. I think it's a good sign that Congress has not produced some sort of mega regulation bill, that this recent bill in California was not signed by Governor Newsom. Congress has spent time meeting with technologists and economists trying to learn something about AI, both the benefits and risks.

And I think the fact that it seems like, even though there was this rush at some point where we needed to have a pause, we needed to quickly regulate it, that seems to have slowed down, and I think that's a good sign that perhaps we're able to hit a good balance here between wanting to embrace the upside and not utterly panicking that we're producing the Terminator.

Absolutely. I think AI is something where the benefits are very clear, we're starting to see them already. The harms are extremely hypothetical, it's not evidence-based, it’s really a lot of sci-fi scenarios. I think the right attitude in that kind of world is to let things ride for a while. If there are harms that arise, we can address them in narrowly tailored ways.

I think government is sometimes criticized for being reactive, but reactive is the right approach for a lot of issues. You don't want to slow things down preemptively. You want to react to real facts on the ground. And if we need to react quickly, okay, we'll react quickly, but in a narrowly tailored way that addresses real harms, not just hypothetical stuff.

I love what you're saying there about reaction. I'm a big preparer. I love preparation. If I'm going to go anywhere, I over-prepare for all eventualities, I will bring a messenger bag so if the world should end while I'm out, I'll be okay. I love to prepare. But one lesson I draw from the pandemic is that only gets you so far, preparation, because before the pandemic, there were a gazillion white papers about the possibility of a pandemic, all kinds of plans as a culture, we were sort of marinating in pandemic apocalypse films, maybe about turning us into zombies rather than giving us a disease.

And then when we finally have a pandemic, it's like, “Where's the respirators? Where's this, where's that? We didn't have enough of this.” And so, while I'm sure preparation is great, what really helped us is we reacted. We reacted in real time because we're a rich country, we're a technologically advanced country, and we came up with a technological fix in a vaccine. To me — and again, I'm not sure how this is you meant it — but the power of being able to react effectively, boy, that's a pretty good capability of a well-functioning country.

Yeah, and a slight difference between the pandemic and AI is it was not the first pandemic. AI is just such a unique set of theorized risks that people are like, nothing like this has ever happened before. This is like the introduction of a brand new super-intelligent species to the planet. This is the first time two intelligent species — if you want to count humans as an intelligent species — two intelligent species will the planet at the same time. And the theorization here is just so far out of the spectrum of our experience that it is hard to even see how you could prepare if those risk materialize. The only intelligent thing that is likely to do any good is to have our eyes open, and let's see what the harms are as they materialize.

The problem with coming up with remedies for theorized harms is that the remedies never go away once they're implemented. Safety regulation never gets laxer over time. And so if you're implementing safety regulations because of real safety problems, okay, fair play, to some extent. I think in some dimensions we're too safe, but it kind of makes sense. But if you're doing it to just theorized harms that have never materialized, I think that's a big mistake.

And you've written about this fairly recently. To me, there's a good kind of complexity with an economy that you have a high-functioning economy where people can connect, and colleges and universities, and businesses, and entrepreneurs, these networks work together to produce computer chips or large language models. That's a good kind of complexity.

But then there's the other kind of complexity, in which you just have layer after layer of bureaucracy, and programs meant to solve a problem that was a problem 20 years ago and is no longer a problem, and that kind of complexity, that's not the kind we want, right?

Yeah, I think you want the sophistication in the economy, but in a way that works for everybody. There have to be benefits to it. If you increase the burden of complexity without producing any net benefits, then people start to rebel against it, they start to be indifferent to or apathetic about the health of society. And there's an anthropologist, Joseph Tainter, who wrote this book, The Collapse of Complex Societies, and his theory is that once you have complexity without the marginal benefits of complexity, you're in for a shock, at some point, when people start becoming apathetic or hostile to the current order. And the complexity grows and shrinks as a system, you can't ever just control like, “Oh, let's do more, or let's do one percent less complexity.” Once people start to rebel against it, it snowballs and you could end up with a very bad situation.

The problem with coming up with remedies for theorized harms is that the remedies never go away once they're implemented. Safety regulation never gets laxer over time.

The future of clean energy (23:35)

Nuclear versus solar versus geothermal: What do you like there?

Solar panels have massively come down in cost, and we're not that far away from — in sort of number of doublings of deployment, and sort of long-deployment space — we're not that far away from the cost being so low that . . . you could almost round the panels cost to free. It almost makes sense. And the problem is, if you look at the solar electricity costs on utility-scale farms, they have not really moved in the last few years. And I think this is in large part because we're designing the solar farms wrong, we're not designing them for the era of cheap panels, we're designing them, still, to track the sun, and complex mechanisms, and too much space between the panels, and too much mowing required, and all that. So as we adapt to the new paradigm of very, very cheap panels, I think that you'll get lower solar costs.

I think the other thing that is obviously complimentary to all of these sources actually is battery innovation. I'm very excited about one particular new cathode chemistry that maybe could drive the cost way, way down for lithium ion batteries. And so you're in a world where solar and batteries is potentially very, very cheap. And so for nuclear and geothermal, they have some advantages over solar.

If batteries get cheap, the advantage of not the firmness . . . I think people think that the advantage of these sources versus solar is just that solar is variable and the other sources are constant, but that's less of an advantage if batteries are cheap, and I think you also want batteries to be able to respond to the fluctuations in demand. If we had an entirely nuclear-powered economy, the nuclear plants actually want to run at constant speed. You don't want to ramp them up and down very quickly, but demand fluctuates. And so you still want batteries to be a buffer there and be the lowest-cost way to balance the network.

So the things that nuclear and geothermal can really compete on is land density — even gigawatt-scale nuclear where you have these giant exclusion zones and tons of land around them and so on, they're still more dense per acre than solar, and geothermal is maybe even denser because you don't need that exclusion zone, and so they could be much, much better in terms of density.

There's an advantage — if you want a lot of power in a city, you probably want that to be supplied by nuclear. If you're more rural, you could do solar. Another possibility is portability. So there's future versions of nuclear that are more mobile. People have talked about space-based nuclear for being able to go to Mars or something like that, you want thermonuclear propulsion and you can't do that with solar. Or powering submarines and stuff. So I think there's always a place for nuclear.

And then the other advantage for both nuclear and geothermal is if you don't need to produce electricity. So if you're producing just the heat — it turns out a big part of the cost of any sort of thermal source is converting it to electricity. You have to have these giant steam turbines that are very capital intensive. And so, if you just need heat, say up to 600 degrees C heat for nuclear and maybe 400 degrees C heat for deep geothermal, those are really good sources for doing that, and maybe if we had continued advances in drilling technology for geothermal or if we could figure out the regulatory stuff for nuclear, I think you could have very cheap industrial thermal energy from either of those sources.

Nuclear and geothermal are competing against a backdrop where we'll probably have pretty cheap solar, but there's still some advantages and these sources still have some utility and we should get good at both of them.

What do you think that energy mix looks like in 25 years, the electrical generation mix for this country?

It would be surprising if it wasn't a lot of solar. My friend Casey Handmer thinks it's going to be 90-plus percent solar, and I think that's a little crazy.

Do you happen to know what the percent is now?

Oh, I don't know. It's probably like three or four or something like that, off the top of my head, maybe less. The other question is, what's the base? I think a lot of people just want to replace the energy we have now with clean energy, and much more we need to be thinking about growing the energy supply. And so I think there's a question of how much solar we could deploy, but then also how much other stuff are we deploying? Let's do a lot of everything. You do have to drive the cost of some of these sources down a bit for it to make sense, but I think we can.

And then the real gains happen when maybe some of these . . . what if you could do some sort of conversion without steam turbines? What if you had ways to convert the thermal energy to electricity without running a steam cycle, which is hundreds-of-year-old technology? Essentially

You're just finding a new way to heat it up.

Yeah, so you look at why has solar come down so much? It's because it’s solid-state, easy to manufacture, any manufacturing process improvements just move forward to all future solar panels. If we had thermoelectric generators or other ways of converting the heat to electricity, that could be really great, and then there's other kinds of nuclear that are like solid-state conversion, like alpha voltaics and things like that. So you could have a box with cobalt 60 in it that's decaying and producing particles that you're converting to electricity, and that would be solid state. It's sometimes called a “nuclear battery,” it's not really a battery, but that would be a way to power cars maybe with something like that. That would be awesome.

Nuclear and geothermal are competing against a backdrop where we'll probably have pretty cheap solar, but there's still some advantages and these sources still have some utility and we should get good at both of them.

The road to a breakthrough (30:25)

When, if ever, this century, do you think we get AGI, and when, if ever, this century, do you think we get a commercial fusion reactor?

AGI, I'm still not really a 100 percent clear on how it's defined. I think that AI will get increasingly more capable, and I think that's an exciting future. Do we even need to emulate every part of the human brain in silicon? I don't think so. Do we need it to have emotions? Do we need it to have its own independent drive? We definitely don't need it to be a perfect replica of a human brain in terms of every capability, but I think it will get more capable over time. I think there's going to be a lot of hidden ways in which AGI, or powerful AI, or highly capable AI is going to happen slower than we think.

I think my base reasoning behind this is, if you look at neurons versus transistors, neurons are about a million times more energy efficient. So six orders of magnitude is kind of what we have to traverse to get something that is equally capable. And maybe there's some tricks or whatever that you can do that means you don't have to be equally capable on an energy basis, but you still need to get four orders of magnitude better. And then the other thing about it is that, if you look at current margins that people are working on, things like the ChatGPT o1 model, it's a lot slower, it does a lot of token generation behind the scenes to get the answer, and I think that that's the kind of stuff that could maybe drive progress.

Let's say we have a world where you ask an AI for a cure for cancer, and you run it on a big data center, and it runs for six months or a year, and then it spits out the answer, here's the cure for cancer, that's still a world where we have very, very powerful AI, but it's slow and consumes a lot of resources, but still ultimately worth it. I think that might be where we're headed, in a way, is that kind of setup. And so is that AGI? Kind of. It's not operating the same way as humans are. So this is different.

You're not going to fall in love with it. It's nothing like that.

I’m pretty uncertain about AGI: A) what it means, but what does it even look like in the end?

Fusion, I'll give you a hot take here, which is, I think there will be net energy gain fusion developed in this decade. I think that someone will have it. I think that probably the first people to get it will be doing it in a completely uneconomical way that will never work economically. Most of the people that are working on fusion are working on DT fusion, which is another one of these sources that basically produces heat, and then you use a steam turbine, and then that produces electricity. I think that the steam turbine is just a killer in terms of the added costs.

So all these sources are basically fancy ways of boiling water and then running a steam turbine. So what you want to look at is: What is the cheapest way to boil water? With fission, you just hold two magic rocks together and they boil water. With geothermal, you drill a hole in the ground and send water down there and it boils. With these DT fusion reactors, you build the most complex machine mankind has ever seen, and you use that to boil water — that's not going to be as cheap as fission should be. So I think that we'll struggle to compete with fission if we can ever get our act together.

There's other kinds of fusion called aneutronic fusion. That's harder to do. I think it’s still possible, maybe this decade, that someone will crack it, but that's harder to do. But the nice thing about that is that you can harvest electricity from those plasmas without a steam turbine. So if it's going to be economical fusion, I think it's plausible by 2030 somebody could crack it, but it would be that aneutronic version, and it is just technically a bit harder. You'll see some reports in a couple of years, like, “Oh, these people, they got net energy out of a fusion reactor.” It's like, okay, it's a scientific breakthrough, but look for the cost. Is it going to be competitive with these other sources?

Do we even need to emulate every part of the human brain in silicon? I don't think so . . . We definitely don't need it to be a perfect replica of a human brain in terms of every capability, but I think it will get more capable over time.

Reforming NEPA (35:19)

Do you think we've sort of got a handle, and we've begun to wrangle the National Environmental Policy Act [NEPA] to the ground? Where are we on reforming it so that it is not the kind of obstacle to progress that you've written so much about and been a real leader on?

My base scenario is we're going to get reforms on it every two years. So we had some a year and a half ago with the Fiscal Responsibility Act, I think we were possibly going to get some in the lame duck session this year in Congress. None of these reforms are going to go far enough, is the bottom line. I think that the problem isn't going to go away, and so the pressure is going to continue to be there, and we're just going to keep having reforms every two years.

And a lot of this is driven by the climate movement. So say what you will about the climate movement, they're the only mainstream movement in America right now that's not complacent, and they're going to keep pushing for, we’ve got to do something that lets us build. If we want to transform American industry, that means we've got to build, and NEPA gets in the way of building, so it's going to have to go.

So I think my baseline case is we get some reforms this year in the lame duck, probably again two years later, probably again two years later, and then maybe like 2030, people have kind of had enough and they just say, “Oh, let's just repeal this thing. We keep trying to reform it, it doesn't work.” And I think you could repeal NEPA and the environment would be fine. I am pro-environment, but you don't need NEPA to protect the environment. I think it's just a matter of coming to terms with, this is a bad law and probably shouldn't exist.

I am pro-environment, but you don't need NEPA to protect the environment. I think it's just a matter of coming to terms with, this is a bad law and probably shouldn't exist.

The state of pro-abundance (37:08)

What is the state of, broadly, a pro-abundance worldview? What is the state of that worldview in both parties right now?

I think there's a growing, but very small, part of each party that is thinking in these terms, and I think the vision is not really concrete yet. I think they don't actually know what they're trying to achieve, but they kind of understand that it's something in this general direction that we've been talking about. My hope is that, obviously, the faction in both parties that is thinking this way grows, but then it also develops a little bit more of a concrete understanding of the future that we're trying to build, because I think without that more-concrete vision, you're not actually necessarily tackling the right obstacles, and you need to know where you're trying to go for you to be able to figure out what the obstacles are and what the problems you need to address are.

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Some signs of tech progress are obvious: the moon landing, the internet, the smartphone, and now generative AI. For most of us who live in rich countries, improvements to our day-to-day lives seem to come gradually. We might (might), then, forgive some of those who claim that our society has not progressed, that our lives have not improved, and that a tech-optimist outlook is even naïve.

Today on Faster, Please! — The Podcast, I talk with economist Noah Smith about pushing the limits in areas like energy technology, how geopolitical threats spur innovation, and why a more fragmented industrial policy might actually be an advantage.

Smith is the author of the popular Noahpinion Substack. He was previously an assistant finance professor at Stony Brook University and an economics columnist for Bloomberg Opinion.

In This Episode

* Recognizing progress (1:43)

* Redrawing the boundaries of energy tech (12:39)

* Racing China in research (15:59)

* Recalling Japanese economic history (20:32)

* Regulating AI well (23:49)

* Rethinking growth strategy in the EU (26:46)

Below is a lightly edited transcript of our conversation

Recognizing progress (1:43)

Pethokoukis: Noah, welcome to the podcast.

Smith: Great to be here!

Not to talk about other podcast guests, but I will very briefly — Last year I did one with Marc Andreessen and I asked him just how tech optimistic he was, and he said, “I'm not sure I'm an optimist at all,” that the most reasonable expectation is to expect the future to be like the past, where we have a problem building things in the real world, that some of our best ideas don't necessarily become everything they could be, and I think a perfectly reasonable baseline forecast is that, for all our talk about optimism, and “let's go,” and “let's accelerate,” that none of that happens. Does that sound reasonable to you or are you more optimistic?

I'm optimistic. You know, a few years ago we didn't have mRNA vaccines. Now we do. And now we have a magical weight loss drug that will not only make you lose weight, but will solve half your other health problems for reasons we don't even understand yet.

So much inflammation.

Right. We didn't even have that a few years ago. That did not exist. If you told someone that would exist, they would laugh at you. A magic pill that not only makes you thin, but also just solves all these other health issues: They would laugh at you, Scott Alexander would laugh at you, everyone would laugh at you. Now it's real. That's cool.

If you had told someone a few years ago that batteries would be as insanely cheap as they are, they would've been like, “What? No. There's all these reasons why they can't be,” but none of those reasons were true. I remember because they did actually say that, and then batteries got insanely cheap, to the point where now Texas is adding ridiculous amounts of batteries for grid storage. Did I predict that was going to happen? No, that surprised me on the upside. The forecasters keep forecasting sort of a leveling off for things like solar and battery, and they keep being wrong.

There's a lot of other things like reusable rockets. Did you think they'd get this good? Did you think we'd have this many satellites in the low-earth orbit?

AI just came out of nowhere. Now everyone has this little personal assistant that's intelligent and can tell them stuff. That didn't exist three years ago.

So is that, perhaps, growing cluster of technologies, that's not just a short-term thing. Do you think all these technologies — and let's say particularly AI, but the healthcare-related stuff as well — that these taken together are a game-changer? Because people always say, “Boy, our lives 30 years ago didn't look much different than our lives today,” and some people say 40 years ago.

But that’s wrong!

Yes, I do think that is wrong, but that people's perception.

When I was a kid, people didn't spend all day looking at a little screen and talking to people around the world through a little screen. Now they do. That's like all they do all day.

But they say that those aren't significant, for some reason, they treat that as a kind of a triviality.

Like me, you're old enough to remember a thing called “getting bored.” Do you remember that? You’d just sit around and you're like, “Man, I’ve got nothing to do. I’m bored.” That emotion just doesn't exist anymore — I mean, very fleetingly for some people, but we've banished boredom from the world.

Remember “getting lost?” If you walk into that forest, you might get lost? That doesn't happen unless you want to get lost, unless you don't take your phone. But the idea that, “Oh my God, I'm lost! I'm lost!” No, just look at Google Maps and navigate your way back.

Being lost and being bored are fundamental human experiences that have been with us for literally millions of years, and now they're just gone in a few years, just gone!

Remember when you didn't know what other places looked like? You would think, “Oh, the Matterhorn, that’s some mountain in Switzerland, I can only imagine what that looks like.” And then maybe you'd look it up in an encyclopedia and see a picture of it or something. Now you just type it into Google Images, or Street View, or look at YouTube, look at a walking tour or something.

Remember not knowing how to fix things? You just had no idea how to fix it. You could try to make it up, but really what you'd do is you'd call someone who was handy with stuff who had this arcane knowledge, and this wizard would fix your cabinet, or your dresser, or whatever, your stereo.

Being lost and being bored are fundamental human experiences that have been with us for literally millions of years, and now they're just gone in a few years, just gone!

So why does that perception persist? I mean, it's not hard to find people — both of us are probably online too much — who just will say that we've had complete and utter stagnation. I don't believe that, yet that still seems to be the perception, and I don't know if things haven't moved fast enough, if there are particular visions of what today should look like that haven’t happened, and people got hung up on the flying-car, space-colony vision, so compared to that, GPS isn’t significant, but I think what you have just described, not everybody gets that.

Because I think they don't often stop to think about it. People don't often stop to think about how much the world has changed since they were young. It's like a gradual change that you don't notice day-to-day, but that adds up over years. It's like boiling the frog: You don't notice things getting better, just like the frog doesn't notice the water getting hotter.

Do you think it's going to get hotter going forward, though? Do you think it's going to boil faster? Do you think that AI is such a powerful technology that it'll be indisputable to everybody that something is happening in the economy, in their everyday lives, and they look a lot different now than they did 10 years ago, and they're going to look a whole lot different 10 years from now?

Utility, remember — back to econ class — utility is concave. A utility of wealth, utility of consumption, is concave, which means that if you get 10,000 more dollars of annual income and you're poor, that makes a hell of a lot of difference. That makes a world of difference to you. But if you're rich, it makes no difference to you. And I think that Americans are getting rich to the point where the new things that happen don't necessarily increase our utility as much, simply because utility is concave. That's how things work.

In the 20th century, people escaped material poverty. They started out the century with horses and buggies, and wood-burning stoves, and freezing in the winter, and having to repair their own clothes, and having food be super expensive, and having to work 60-hour weeks, 80-hour weeks at some sweatshop, or just some horrible thing, and horrible conditions with coal smoke blackening the skies; and then they ended in nice, clean suburbia with computers and HDTVs —I guess maybe we didn't get those till the 2000s — but anyway, we ended the 20th century so much richer.

Basically, material poverty in rich countries was banished except for a very few people with extreme mental health or drug problems. But then for regular people, material want was just banished. That was a huge increment. But if you took the same increment of wealth and did that again in the next century, people wouldn't notice as much. They'd notice a little bit, but they wouldn't notice as much, and I think that it's the concavity of utility that we're really working against here.

In the 20th century, people escaped material poverty. They started out the century. . . having to work 60-hour weeks, 80-hour weeks at some sweatshop. . . and then they ended in nice, clean suburbia with computers and HDTVs . . .

So is economic growth overrated then? That kind of sounds like economic growth is overrated.

Well, no. I don't know that it's overrated. It's good, but I don't know who overrates it. Obviously it's more important for poor countries to grow than for rich countries to grow. Growth is going to make a huge difference to the people of Bangladesh. It's going to be life-changing, just as it was life-changing for us in the 20th century. They're going to have their 20th century now, and that's amazing.

And, to some extent, our growth sustains their growth by buying their products; so that helps, and contributing to innovations that help them, those countries will be able to get energy more easily than we were because they're going to have this super-cheap solar power, and batteries, and all this stuff that we didn't have back in the day. They're going to have protections against diseases, against malaria, and dengue fever, and everything. We didn't have those when we were developing, we had to hack our way through the jungle.

So growth is great. Growth is great, and it's better for the people in the poor countries than for us because of concavity of utility, but it's still good for us. It's better to be advancing incrementally. It's better to be feeling like things are getting better slowly than to be feeling like things aren't getting better at all.

So many things have gotten better, like food. Food has gotten immeasurably better in our society than it was in the ’90s. The food you can eat at a regular restaurant is just so much tastier. I don't know if it's more nutritious, but it's so much tastier, and so much more interesting and varied than it was in the ’90s, and people who are in their 40s or 50s remember that. And if they stop to think about it, they'll be like, “You know what? That is better.” We don't always stop to remember what the past was. We don't remember what food was like in the ’90s — I don't. When I'm going out to a restaurant to eat, I don't think about what a restaurant was like in 1994, when I was a kid. I don't think about that. It just doesn't come to mind. It's been a long time.

In Japan I noticed it a lot, because Japan had, honestly, fairly bland and boring food up until about 2010 or so. And then there was just this revolution where they just got the most amazing food. Now Japan is the most amazing place to go eat in the world. Every restaurant's amazing and people don't understand how recent that is. People don't understand how 20 years ago, 25 years ago, it was like an egg in a bowl of rice and sort of bland little fried things. People don't remember how mediocre it was, because how often did they go to Japan back in 2005?

It's better to be feeling like things are getting better slowly than to be feeling like things aren't getting better at all.

Redrawing the boundaries of energy tech (12:39)

Your answer raised several questions: One, you were talking about solar energy and batteries. Is that enough? Is solar and batteries enough? Obviously I read about nuclear power maybe too much, and you see a lot of countries trying to build new reactors, or restart old reactors, or keep old nuclear reactors, but over the long run, do we need any of that other stuff or can it really just be solar and batteries almost entirely?

Jesse Jenkins has done a lot of modeling of this and what would be the best solutions. And of course those models change as costs change. As battery costs go down and battery capabilities improve, those models change, and we can do more with solar and batteries without having to get these other things. But the current models that the best modelers are making right now of energy systems, it says that we're probably looking at over half solar and batteries, maybe two thirds, or something like that. And then we'll have a bunch of other solutions: nuclear, wind, geothermal, and then a little bit of gas, we'll probably never completely get rid of it.

But then those things will all be kind of marginal solutions because they all have a lot of downsides. Nuclear is very expensive to build and there's not much of a learning curve because it gets built in-place instead of in a factory (unless it's on a submarine nuclear plant, but that's a different thing). And then wind takes too much land, really, and also the learning curve is slower. Geothermal is only certain areas. It's great, but it's only certain areas. And then gas, fossil fuel, whatever.

But the point is that those will all be probably part of our mix unless batteries continue to get better past where we even have expected them to. But it's possible they will, because new battery chemistries are always being experimented with, and the question is just: Can we get the production cost cheap enough? We have sodium ion batteries, iron flow batteries, all these other things, and the question is, can we get the cost cheap enough?

Fortunately, China has decided that it is going to pour untold amounts of capital and resources and whatever into being the Saudi Arabia of batteries, and they're doing a lot of our work for us on this. They're really pushing forward the envelope. They're trying to scale every single one of these battery chemistries up, and whether or not they succeed, I don't know. They might be wasting capital on a lot of these, or maybe not, but they're trying to do it at a very large scale, and so we could get batteries that are even better than we expect. And in that case, I would say the share of solar and batteries would be even higher than Jesse Jenkins and the other best modelers now predict.

But you don't know the future of technology. You don't know whether Moore's Law will stop tomorrow. You don't know these things. You can trace historical curves and forecast them out, and maybe come up with some hand-wavy principles about why this would continue, but ultimately, you don't really know. There's no laws of the universe for technological progress. I wish there were, that'd be cool. But think solar and batteries are on their way to being a majority of our total energy, not just electricity, but total energy.

Racing China in research (15:59)

Does it concern you, in that scenario, that it's China doing that research? I understand the point about, “Hey, if they want to plow lots of money and lose lots of money,” but, given geopolitical relations, and perhaps more tariffs, or war in the South China Sea, does that concern you that that innovation is happening there?

It absolutely does concern me. We don't want to get cut off from our main sources of energy supply. That's why I favor policies like the Inflation Reduction Act. Basically, industrial policy is to say, “Okay, we need some battery manufacturing here, we need some solar panel manufacturing here in the country as a security measure.” Politicians always sell it in terms of, “We created this many jobs.” I don't care. We can create jobs anyway. Anything we do will create jobs. I don't care about creating specific kinds of jobs. It is just a political marketing tactic: “Green jobs, yes!” Okay, cool, cool. Maybe you can market it that way, good for you.

But what I do care about is what you talked about, which is the strategic aspect of it. I want to have some of that manufacturing in the country, even if it's a little inefficient. I don't want to sacrifice everything at the altar of a few points of GDP, or a few tenths of a percent of points of GDP at most, honestly. Or sacrifice everything in the altar of perfect efficiency. Obviously the strategic considerations are important, but, that said, what China's doing with all this investment is it's improving the state of technology, and then we can just copy that. That's what they did to us for decades and decades. We invented the stuff, and then they would just copy it. We can do that on batteries: They invent the stuff, we will copy it, and that's cool. It means they're doing some of our work, just the way we did a lot of their work to develop all this technology that they somehow begged, borrowed, or stole.

. . . what China's doing with all this investment is it's improving the state of technology, and then we can just copy that. That's what they did to us for decades and decades. We invented the stuff, and then they would just copy it. We can do that on batteries. . .

The original question I asked about: Why should we think the future will be different than the recent past? Why should we think that, in the future, America will spend more on research? Why do we think that perhaps we'll look at some of the regulations that make it hard to do things? Why would any of that change?

And to me, the most compelling reason is, it's quite simple just to say, “Well, what about China? Do you want to lose this race to China? Do you want China to have this technology? Do you want them to be the leaders in AI?” And that sort of geopolitical consideration, to me, ends up being a simple but yet very persuasive argument if you're trying to argue for things which very loosely might be called “pro-progress” or “pro-abundance” or what have you.

I don't want to whip up any international conflict in order to stimulate people to embrace progress for national security concerns. That wouldn't be worth it, that’s like wagging the dog. But, given that international conflict has found us — we didn't want it, but given the fact that it found us — we should do what we did during the Cold War, during World War II, even during the Civil War, and use that problem to push progress forward.

If you look at when the United States has really spent a lot of money on research, has built a lot of infrastructure, has done all the things we now retrospectively associate with progress, it was for international competition. We built the interstates as part of the Cold War. We funded the modern university system as part of the Cold War. And a lot of these things, the NIH [National Institutes of Health], and the NSF [National Science Foundation], and all these things, of course those came from World War II programs, sort of crash-research programs during and just before World War II. And then, in the Civil War, of course, we built the railroads.

So, like it or not, that's how these things have gotten done. So now that we see that China and Russia have just decided, “Okay, we don't like American power, we want to diminish these guys in whatever way we can,” that's a threat to us, and we have to respond to that threat, or else just exceed to the loss of wealth and freedom that would come with China getting to do what it wants to us. I don't think we should exceed to that.

I don't want to whip up any international conflict in order to stimulate people to embrace progress. . . But, given that international conflict has found us. . . we should do what we did during the Cold War, during World War II, even during the Civil War, and use that problem to push progress forward.

Recalling Japanese economic history (20:32)

You write a lot about Japan. What is the thing you find that most people misunderstand about the last 30 years of Japanese economic history? I think the popular version is: Boom, in the ’80s, they looked like they were ahead in all these technologies, they had this huge property bubble, the economy slowed down, and they've been in a funk ever since — the lost decades. I think that might be the popular economic history. How accurate is that?

I would say that there was one lost decade, the ’90s, during which they had a very protracted slowdown, they ameliorated many of the effects of it, but they were very slow to get rid of the root cause of it, which was bad bank debts and a broken banking system. Eventually, they mostly cleaned it up in the 2000s, and then growth resumed. By the time per capita growth resumed, by the time productivity growth and all that resumed, Japan was aging very, very rapidly, more rapidly than any country has ever aged in the world, and that masked much of the increase in GDP per worker. So Japan was increasing its GDP per worker in the 2000s, but it was aging so fast that you couldn't really see it. It looked like another lost decade, but what was really happening is aging.

And now, with fertility falling all around the world right now in the wake of the pandemic, probably from some sort of effect of social media, smartphones, new technology, whatever, I don't know why, but fertility's falling everywhere — again, it looked like it had bottomed out, and then now it's falling again. We're all headed for what happened to Japan, and I think what people need to understand is that that's our future. What happened to Japan in the 2000s where they were able to increase productivity, but living standards stagnated because there were more and more old people to take care of. That is something that we need to expect to happen to us, because it is. And, of course, immigration can allay that somewhat, and it will, and it should. And so we're not because of immigration

Will it in this country? In this country, the United States, it seems like that should be something, a major advantage going forward, but it seems like it's an advantage we seem eager to throw away.

Well, I don't know about eager to throw away, but I think it is in danger. Obviously, dumb policies can wreck a country at any time. There's no country whose economy and whose progress cannot be wrecked by dumb policies. There's no country that's dumb-proof, it doesn't exist, and it can't exist. And so if we turn off immigration, we're in trouble. Maybe that's trouble that people are willing to accept if people buy the Trumpist idea that immigrants are polluting our culture, and bringing all kinds of social ills, and eating the pets, and whatever the hell, if people buy that and they elect Trump and Trump cracks down hard on immigration, it will be a massive own-goal from America. It will be a self-inflicted wound, and I really hope that doesn't happen, but it could happen. It could happen to the best of us.

There's no country whose economy and whose progress cannot be wrecked by dumb policies. There's no country that's dumb-proof, it doesn't exist, and it can't exist.

Regulating AI well (23:49)

Do you think what we're seeing now with AI, do you think it is an important enough technology that it is almost impossible, realistically, to screw it up through a bad regulation, through a regulatory bill in California, or something on the national level? When you look at what's going on, that if it's really as important as what perhaps the most bullish technologists think it is, it's going to happen, it's going to change businesses, it's going to change our lives, and unless you somehow try to prohibit the entire use of the technology, there's going to be an Age of AI?

Do people like me worry too much about regulation?

I can't say, actually. This is not something I'm really an expert on, the potential impact of regulation on AI. I would never underestimate the Europeans' ability to block new technologies from being used, they seem to be very, very good at it, but I don't think we'll completely block it, it could hamper it. I would say that this is just one that I don't know.

But I will say, I do think what's going to happen is that AI capabilities will outrun use cases for AI, and there will be a bust relatively soon, where people find out that they built so many data centers that, temporarily, no one needs them because people haven't figured out what to do with AI that's worth paying a lot of money for. And I have thoughts on why people haven't thought of those things yet, but I'll get to that in a second. But I think that eventually you'll have one of those Gartner Hype Cycles where eventually we figure out what to do with it, and then those data centers that we built at that time become useful. Like, “Oh, we have all these GPUs [graphics processing units] sitting around from that big bust a few years ago,” and then it starts accelerating again.

So I predict that that will happen, and I think that during the bust, people will say, just like they did after the Dot-com bust, people will say, “Oh, AI was a fake. It was all a mirage. It was all useless. Look at this wasted investment. The tech bros have lied to us. Where's your future now?” And it's just because excitement about capabilities outruns end-use cases, not all the time, obviously not every technology obeys this cycle, for sure . . . but then many do, you can see this happen a lot. You can see this happen with the internet. You can see this happen with railroads, and electricity. A lot of these things, you've seen this pattern. I think this will happen with AI. I think that there's going to be a bust and everyone's going to say, “AI sucks!” and then five, six years later, they'll say, “Oh, actually AI is pretty good,” when someone builds the Google of AI.

Rethinking growth strategy in the EU (26:46)

To me, this always gets a lot of good attention on social media, if you compare the US and Europe and you say, the US, it's richer, or we have all the technology companies, or we're leading in all the technology areas, and we can kind of gloat over Europe. But then I think, well, that's kind of bad. We should want Europe to be better, especially if you think we are engaged in this geopolitical competition with these authoritarian countries. We should want another big region of liberal democracy and market capitalism to be successful.

Can Europe turn it around? Mario Draghi just put out this big competitiveness report, things Europe can do, they need to be more like America in this way or that way. Can Europe become like a high-productivity region?

In general, European elites’ answer to all their problems is “more Europe,” more centralization, make Europe more like a country. . . But I think that Europe's strength is really in fragmentation . . .

I think it can. I wrote a post about this today, actually, about Mario Draghi's report. My bet for what Europe would have to do is actually very different than what the European elites think they have to do. In general, European elites’ answer to all their problems is “more Europe,” more centralization, make Europe more like a country. You know, Europe has a history of international competition. France, and Germany, and the UK, and all these powers would fight each other. That's their history. And for hundreds of years, it's very difficult to change that mindset, and Mario Draghi's report is written entirely in terms of competitiveness. And so I think the mindset now is “Okay, now there's these really big countries that we're competing with: America, China, whatever. We need to get bigger so we're a big country too.” And so the idea is to centralize so that Europe can be one big country competing with the other big countries.

But I think that Europe's strength is really in fragmentation, the way that some European countries experiment with different institutions, different policies. You've seen, for example, the Scandinavian countries, by and large, have very pro-business policies combined with very strong welfare states. That's a combination you don't see that in Italy, France, and Germany. In Italy, France, and Germany, you see policies that specifically restrict a lot of what business can do, who you can hire and fire, blah, blah, blah. Sweden, and Denmark, and Finland, and Norway make it very easy for businesses to do anything they want to do, and then they just redistribute. It's what we in America might even call “neoliberalism.”

Then they have very high taxes and they provide healthcare and blah, blah, and then they basically encourage businesses to do business-y things. And Sweden is more entrepreneurial than America. Sweden has more billionaires per capita, more unicorns per capita, more high-growth startups per capita than America does. And so many people fall into the lazy trap of thinking of this in terms of cultural essentialism: “The Swedes, they're just an entrepreneurial bunch of Vikings,” or something. But then I think you should look at those pro-business policies.

Europeans should use Sweden as a laboratory, use Denmark, use Norway. Look at these countries that are about as rich as the United States and have higher quality of life by some metrics. Look at these places and don't just assume that the Swedes have some magic sauce that nobody else has, that Italy and Greece and Spain have nothing to learn from Sweden and from Denmark. So I think Europe should use its fragmentation.

Also, individual countries in Europe can compete with their own local industrial policies. Draghi talks about the need to have a Europe-wide industrial policy to combat the industrial policies of China and America, but, often, when you see the most effective industrial policy regimes, they're often fragmented.

So for example, China until around 2006, didn't really have a national industrial policy at all. At the national level, all they did was basically Milton Friedman stuff, they just privatized and deregulated. That's what they did. And then all the industrial policy was at the provincial and city levels. They went all out to build infrastructure, to attract FDI [foreign direct investment], to train workers, all the kinds of things like that. They did all these industrial policies at the local level that were very effective, and they all competed with each other, because whichever provincial officials got the highest growth rate, you'd get promoted, and so they were competing with each other.

Now, obviously, you don't want to go for growth at the expense of anything else. Obviously you'd want to have things like the environment, and equality, and all those things, especially in Europe, it's a rich country, they don't just want to go for growth, growth, growth only. But if you did something like that where you gave the member states of the EU more latitude to do their local policies and to set their local regulations of things like the internet and AI, and then you use them as laboratories and copy and try to disseminate best practice, so that if Sweden figures something out, Greece can do it too, I think that would play to Europe's strength, because Draghi can write a million reports, but Europe is never going to become the “United States of Europe.” Its history and ethno-nationalism is too fragmented. You'll just break it apart if you try.

The European elites will just keep grousing, “We need more Europe! More Europe!” but they won't get it. They'll get marginally more, a little bit more. Instead, they should consider playing to Europe's natural strengths and using the interstate competitive effects, and also laboratory effects like policy experimentation, to create a new development strategy, something a little bit different than what they're thinking now. So that's my instinct of what they should do.

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Micro Reads

▶ Business/ Economics

* Behind OpenAI’s Audacious Plan to Make A.I. Flow Like Electricity - NYT

* OpenAI Pitched White House on Unprecedented Data Center Buildout - Bberg

* OpenAI Executives Exit as C.E.O. Works to Make the Company For-Profit - NYT

* OpenAI to Become For-Profit Company - WSJ

* Mark Zuckerberg’s AI Vision Makes Metaverse a Slightly Easier Sell - WSJ

* Intel’s Foundry Shake-Up Doesn’t Go Far Enough - WSJ

* OpenAI CTO Mira Murati Is Leaving the Company - Wired

* Meta unveils augmented reality glasses prototype ‘Orion’ - FT

▶ Policy/Politics

* The Schumer Permitting Exception for Semiconductors - WSJ Opinion

* Biden breaks with environmentalists, House Dems on chip bill - Politico

* Mark Zuckerberg Is Done With Politics - NYT

▶ AI/Digital

* I Built a Chatbot to Replace Me. It Went a Little Wild. - WSJ

* Meta's answer to ChatGPT is AI that sounds like John Cena or Judi Dench - Wapo

* Want AI that flags hateful content? Build it. - MIT

* The Celebrities Lending Their Voices to Meta’s New AI - WSJ

▶ Biotech/Health

* Why do obesity drugs seem to treat so many other ailments? - Nature

* Antimicrobial resistance is dangerous in more ways than one - FT Opinion

* Who’s Really Keeping Ozempic and Wegovy Prices So High? - Bberg Opinion

▶ Clean Energy/Climate

* Microsoft’s Three Mile Island Deal Is Great News - Bberg Opinion

* China’s accelerating green transition - FT

* Microsoft’s Three Mile Island Deal Isn’t a Nuclear Revival — Yet - Bberg Opinion

* A Faster, Cheaper Way to Double Power Line Capacity - Spectrum

* A Public Path to Building a Star on Earth - Issues

▶ Space/Transportation

* Hypersonic Weapons — Who Has Them and Why It Matters - Bberg

▶ Up Wing/Down Wing

* Trump Offers Scare Tactics on Housing. Harris Has a Plan. - Bberg Opinion

* The Sun Will Destroy the Earth One Day, Right? Maybe Not. - NYT

* How supply chain superheroes have kept world trade flowing - FT Opinion

* Can machines be more ‘truthful’ than humans? - FT Opinion

▶ Substacks/Newsletters

* America's supply chains are a disaster waiting to happen - Noahpinion

* The OpenAI Pastiche Edition - Hyperdimensional

* The Ideas Anticommons - Risk & Progress

* Sam Altman Pitches Utopian impact of AI while Accepting UAE Oil Money Funding - AI Supremacy

* The Government’s War on Starter Homes - The Dispatch

* NEPA Nightmares III: The Surry-Skiffes Creek-Whealton Transmission Line - Breakthrough Journal

* Dean Ball on AI regulation, "hard tech," and the philosophy of Michael Oakeshott - Virginia’s Newsletter

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

When it comes to sports, everybody is basically aligned that the goal here is helping every kid reach their potential. We celebrate talent, we give athletes the resources and personalized support they each need to develop their skills. We have varsity leagues, we have junior varsity leagues. We make sure that kids are challenged at the appropriate level for their current level abilities. And for some reason, when it comes to academics, we throw all of that out the window.

Our progress as a society depends a lot on the brilliant ideas of our greatest thinkers. To improve our way of life, we should be promoting our best and brightest to the highest heights of their potential. Instead, we seem to be stemming the flow of great minds at the source: in our public schools. With a one-size-fits-all, equality-of-outcome model, we rob our kids, and our society, of their potential.

Today on Faster, Please — The Podcast, I talk with Niels Hoven, founder and CEO of Mentava, an educational software company. Hoven’s goal: to help kids learn at their own pace, whether that includes additional support, or simply the resources to excel beyond expectations.

Hoven is the father of four, former product manager at Cloudflare, and was VP of product development at Pocket Gems.

In This Episode

* Treating academics like athletics (1:35)

* School as childcare and instruction (5:44)

* The role of parents (8:04)

* Mentava’s mission (10:04)

* Reframing the public school (15:20)

* The San Francisco algebra ban (17:50)

* Investing in our future (20:05)

Below is a lightly edited transcript of our conversation

Pethokoukis: Niels, welcome to the podcast.

Hoven: Thank you so much. I appreciate you having me here.

Treating academics like athletics (1:35)

You argue that the current American education system is fundamentally flawed.

I do think it has some issues.

How does closing achievement gaps hurt our education system? How does it hold students back?

So obviously my problem is not with closing achievement gaps, my problem is what happens when you set up policies with that as the only goal. I think what we've seen is that the goal of today's modern education policy is closing the gaps between high achievers and low achievers, which is, of course, wonderful, but the way that has actually manifested in schools is by slowing down high achievers and not giving them the opportunity to achieve their potential. In San Francisco, you're literally not allowed to teach material above grade level, which I think is crazy.

Most school systems have gifted programs. Doesn't that meet your concern?

So those gifted programs, I think they don't go far enough to support the learning needs of students who are really capable of achieving dramatically more, and, in a lot of places they're very, very hard to get into. So in our school district right now, in order to qualify for the gifted program, you have to take a series of tests and you basically have to score 99th percentile on all of those tests. All of those tests are basically grade-level tests, so they're not really teaching seeing how far above grade level you are, so it's really, “Are you really, really good at taking the tests, so well that three times in a row you can score 99th percentile on grade level stuff?” That's not really getting the kids who need their learning needs supported by these special programs, and these programs really only operate a single grade above grade level. What about the kids who could be doing calculus in middle school, or want to be moving much faster than that: Two years of math a year, every single year — we aren't supporting them.

You've proposed treating academics more like sports. What does that look like in practice and how might that change how we approach education and how we think about education more broadly?

When it comes to sports, everybody is basically aligned that the goal here is helping every kid reach their potential. We celebrate talent, we give athletes the resources and personalized support they each need to develop their skills. We have varsity leagues, we have junior varsity leagues. We make sure that kids are challenged at the appropriate level for their current level abilities.

And for some reason, when it comes to academics, we throw all of that out the window. We just say, “Okay, everybody must progress at the same speed, learn the same thing at the same time.” To me that's like saying, “Okay LeBron, you are not allowed to dunk until everybody else can dunk also.” And so I want to see us treat academics more like sports, where we encourage students to pursue their interests, to develop their talents to the fullest potential, and respect the diversity of kids' ability and motivations.

To what do you attribute the staying power of this — I don’t know if it's a one-size-fits-all system, but of a system that, in many key ways, isn't different than it was a hundred years ago?

It is a government-sponsored monopoly, so I guess that would be my answer. How did the taxi cab medallion system last so long, even though it was dramatically underserving everybody who wanted to take a taxi? There's no competition.

What does that more sports-like environment look like? It sounds like there'd be more freedom, there'd be less regimentation. What does that world look like?

What I'm really pushing for is I would like to see students receiving instruction appropriate for their current level. I talk a lot about high-achieving students, but this is also true for struggling students. Right now we have a very one-size-fits-all model of education, and that means students who are struggling and need extra attention to get caught up aren’t given the opportunity that they need to perhaps move at a slower pace or get extra support, and kids who want to be moving faster and maybe learning two years of math a year, every single year, so that they can be doing college-level math in middle school, they're also not getting that support. We managed to do that in sports, we have lots of different leagues so that kids can find the level of competition that is appropriate for them, but for some reason, when it comes to academics, we refuse to allow that amount of differentiation.

School as childcare and instruction (5:44)

You advocate reducing instruction time to two hours a day. One, is that enough? And two, what are the kids doing for the other . . . are they getting into mischief? What are they doing for the rest of the day if they're not studying?

I think we've really conflated the role of school, and I think an important question to ask is: Is school as we provide it now, is it childcare or is it academics? And I think it is both. An interesting fact about school is, despite all of the problems that we all understand our schools have, schools have like an 80 percent approval rating from parents, and that's because the job that schools do for most parents is actually childcare. It is free childcare for while the parents are at work, it is finding a place where your children are entertained and loved, and that is super important.

But somehow we have also layered this layer of academic theater on top of that childcare instead of saying, “Okay, these kids can play in the woods for eight hours a day, or they can play dodgeball or grow their social-emotional skills and build their friendships with a friend.” We had to say, “No, they have to be learning something – but not too fast at this very, very slow pace.” And if you look at things like homeschoolers, you see most homeschoolers do two hours of academics a day, and they have the same outcomes as kids who are going to public schools, so we really don't need that much more time doing academics as long as that time is being spent efficiently.

Is this new world possible within a mostly public school system as it exists today? Can you do this, or are you talking about private school, homeschooling, but does this have anything to do with the public school system, which seems to me fairly resilient? Certainly, I think the changes of the sort of magnitude you're talking about.

I like the public school system. I went to public school, I had a really positive experience in public school. My own kids go to public school. And I think the difference is that when I was in public school, people were much more accepting of the idea of kids who wanted to move at their own pace. And so Mentava, certainly we're happy to support kids who are homeschoolers, who are in private school, but the real vision is to allow kids to be part of, essentially, their local public school community, go to school with friends from the neighborhood, but still have the opportunity to progress at their own pace

The role of parents (8:04)

Tell me a little bit about your personal educational experience and how that shaped your views and how it eventually led to your company.

Education has always been very important to my family. My dad taught me to read early, when I arrived at kindergarten, I could already read, I was roughly a year ahead in math. And so he negotiated with my school to just let me, during math class, just for an hour a day, could I just go to the next grade up and sit in on their math class and then come back to my own class for the rest of the day. And we did that, and that worked great until third grade, because my school only went up to third grade, so there wasn't a class for me. So at that point, I just started doing independent study. Just during math class, for an hour a day, I would go to the back of the classroom, I would study out of a math book, and then at the end of that hour I would come back and rejoin my friends for the rest of the day.

And I did that for the next four years, and basically, thanks to that accelerated support, I ended up taking calculus in eighth grade. There are kids who can be moving that fast if you just kind of get out of their way. My own son — he goes to a public school — we also got permission for him to do independent study last year, and now in fourth grade he'll probably be ready to start pre-algebra.

This is doable now. This was doable when I was a kid with textbooks, this is doable now with off-the-shelf software, but it's harder than it needs to be. And so our vision is: We can make this easier. I think a lot of kids could have done what I did, but they weren't given the opportunity. We want to make sure that more kids have this opportunity to have their learning needs supported.

Do you think parents underestimate what their kids are capable of doing?

Parents have no idea what their kids are capable of doing, especially parents of high-achieving kids. We've seen this over and over again with the families who are entering in Mentava’s learn-to-read software now. We target our software at kids as young as two, but often age three and four, we're trying to teach them to read, trying to get them to about a second grade reading level in maybe six to 12 months. We just had a three-year-old complete our entire curriculum, which gets us close to a second grade reading level, in about six months. So it is doable, it can move fast, and we have parents who say, “I had no idea that my kid was capable of doing this at this point!”

Mentava’s mission (10:04)

So walk me through what your company does, the service it provides, how it all works.

The long-term vision for our company is to support the learning needs of kids who are not being supported in school. If you have a child who wants to learn two years of math in a year, the real gating factor of that is, a lot of times it's teacher availability, or it's school policy that says there's no one available to give them that instruction. But imagine that they had the opportunity to just go open a math book.

It's a resource issue. We'd love to do it, but we don't have the resources.

We don’t have the resources. Sometimes that's true, sometimes that's not true, sometimes it's policy, but whatever. But they could go get a math book, they could just study that book and go as fast as they wanted — but that's boring. Not every kid is going to have that motivation. And so, to some extent, we're not really solving for curriculum, we are solving for motivation. We want to build software that can deliver that same curriculum — we know how to teach math, we know how to teach reading — deliver it in a more sort of fun, entertaining, motivating way, and allow kids to essentially continue to progress at their own pace without being gate-kept by the availability of teachers to essentially unlock that knowledge for them. And so we are starting at a very young age by teaching kids to read with software.

What I really want to teach is math. I want to get kids to learn math as fast as possible, but in order for kids to be able to teach themselves math, they have to be able to read, and so that is our first piece of software: learn-to-read software for preschoolers.

And obviously preschoolers, these are young kids, so is your expectation that software will be done at home? Are there schools trying to incorporate in some way? How's that working?

We've started talking to schools about pilots, but I think, right now, we get a lot of attention from parents. Incentives are just better aligned that way. Schools right now are not particularly concerned with, “Are we supporting our kids achieving their fullest potential or are we ensuring our kids can learn as fast as possible?” But parents really care about that. And so right now we have a lot of customers who are basically parents at home who realize, “Oh, my three- or four-year-old is ready to start reading, what can I do to best support them now?”

How long has the company been in business?

We kind of accidentally launched about six months ago.

Was this a pandemic-related idea?

This was. I have four kids. I had three kids during the pandemic and the fourth one arrived during the pandemic. They were at home, doing school at home, and I also had a job at the time, so did my wife, we had two working parents trying to take care of three kids at home, we were trying to figure out how to help them learn, and really the only way to make that work was to give them the skills that they needed to teach themselves. And at that time, my kids were five and three. And so how can I get my five-year-old teaching themselves math? How do I get my three-year-old teaching themselves to read? And the solution to that is software. We know the curriculum, we know if you want to teach reading, it's phonics, but how do you get the kid to sit down and memorize the 44 sounds in the English language? Well, turns out that software and games are really, really good at solving motivation, so we just needed to package that all together and that was how Mentava was started.

So during this exact period that you've thought of this idea, you're putting together a company, putting together the software, we have sort of a new stage in software happening with chatbots and large language models. Are those technologies that compliment what you're doing? Are you going to have to do something different to use those technologies? How's that going to work out for you?

It's very complimentary. So we're not using AI right now, but we see it coming. There is kind of this perfect storm of timing right now where, I think because of Covid, parents started to realize that, “Oh, my kid is not learning as much in school as I thought. This is what they're doing in school?” We had all that visibility when our kids were doing homeschool in front of screens at home.

Technology has gotten to a point where we can give screens to every kid, and iPads, and other tablets. Touchscreens make learning much more accessible. We're seeing the effectiveness of some learning software — a lot of learning software is really, really bad, but some of it is good, and people are seeing that. And then, at the same time, like you see AI coming out and getting people very excited about the potential of software to affect education.

It’s funny, when we were raising money, the idea that software could be a teacher was a very contrarian perspective. Everybody said, “How could software possibly be a teacher? You’re going to need a human there.” And then about 12 months later, AI came out, people said, “Oh, of course you're going to have software teachers. We've always believed that.”

But my take on AI is that the power of AI is really in its adaptability, and you actually don't need that much adaptation for teaching reading or teaching math. You memorized the 26 letters, the 44 sounds in the English language, you learn addition, and then you learn subtraction, then you learn multiplication, then you learn division. It's pretty linear. It's pretty sequential. And so my belief is that there's actually this core learning pathway that you can really, really optimize, and we should focus on that. And it's fairly sequential, and it's fairly deterministic. And then the power of AI is to catch the kids who fall off of that and get confused and ask, “Okay, what are you confused about? I see you're confused about this thing. Let me give you some custom instruction and then get you back on that main pathway.”

Reframing the public school (15:20)

In an ideal world — and let's just stick with, I think it's reasonable to think that, for the time being, most kids are going to be educated by public schools. That's a lot of kids, a magnitude difference in how many kids are in private school or are homeschooled. What should that public school day look like, ideally, given what you've learned going through this process?

The biggest challenge for public school is that there's such a diversity of student needs there. Public schools are simultaneously academics, but they're also childcare, and they're also a social support network. They're a safety net for a lot of kids, and they're trying to provide all those services to all these different kids by giving them all the exact same thing. To me that makes no sense, and what I would really love to see in our public schools is just more differentiation, more acceptance of diversity of needs, diversity of motivations, diversity of abilities, and saying, “Okay, these children need this particular service from our public schools. Let's make sure that they're in a place where they can get those services. But we have these other kids who want to learn two years of math every year. They can do that in two hours a day, and then they want to spend the rest of the day playing in the forest.” That would be amazing.

Should that actual classroom time look markedly different? I'm sure that if I went into most classrooms — I had kids, one currently in high school and ones who were in high school not that long ago — that those classrooms, blackboards, teachers, lecturing: That's the classroom experience. That's in 2024, that was the classroom experience in 1924. Should that classroom experience look fundamentally different?

I think that's an interesting question. I think it's going to look different for different kids. I think there is a sense that some of the rigor I would say of the old days has been lost, and I think that there's good and bad to that. I think a lot of that is a result of conflating childcare with academics. You can't do rigorous academics for eight hours a day. It’s sort of like weightlifting; you can't do squats for eight hours a day, but you can do them very effectively for half an hour. But if you want to pretend that you're exercising for eight hours a day, then you, by definition, have to remove a lot of that rigor. So I would like to get rid of the academic theater and be very clear about, “Okay, this time is play time, this is childcare time, and this time is academic time, and we're really going to buckle down and focus here.”

The San Francisco algebra ban (17:50)

A few years back, there was a ban on teaching middle school algebra in San Francisco. Can you give me some background on that?

So this was passed about 10 years ago. The way it used to work is that most kids took algebra in eighth grade. If you were ready earlier, you could take algebra in seventh grade, but essentially in San Francisco, because some kids were not prepared to take algebra in eighth grade, they said across the board, all kids must take algebra in ninth grade. So even the kids who used to take it in seventh grade, the kids who used to take it in eighth grade, “Sorry, we're not doing it in middle school anymore. You all have to take it in ninth grade.”

Usually these sorts of educational decisions, they're just lost in the noise, parents don't have time to focus on the nitty and gritty of curriculum, but this was a big problem for parents because this meant that you could not get through calculus in high school without essentially taking summer school or getting private tutoring. And for a lot of competitive colleges, you need to be in calculus, have taken calculus, in high school. And so parents had a real problem with this particular curriculum change.

The irony of all of this is that this was enacted with the hope of increasing equity, of driving more equal outcomes, and it had the opposite effect because now it’s just the parents with the resources who are able to go out and do summer school, and private tutors, and then get their kids the math support that they needed. So this happened a decade ago, and it has been a battle for 10 years to get algebra back into middle schools in San Francisco, and it actually went the other way: California statewide nearly got rid of algebra in their statewide middle school curriculum because of the quote-unquote “success of San Francisco,” which is basically, if you look into it, it's just San Francisco cooking the books, literally lying about their outcomes.

And so finally, this past year, parents essentially had enough and they put it on the ballot and said, “We're going to take a vote about, should middle schoolers be allowed to learn algebra.” It's funny because a lot of times people think that this cuts along party lines: Conservatives versus Democrats, red versus blue, but even in San Francisco, the most progressive city in the United States, 80 percent of families were like, “Yes, we should support all kids learn these. Yes, if a kid is ready to take algebra in middle school, we should allow them to do that.”

Investing in our future (20:05)

I'll tell you the one thing I kept thinking of as I was learning more about your company and your outlook was it seems to me like it'd be really important, as a country, that every kid can reach their potential, but especially the very smartest kids, that we get everything out of them that we can, right? That's pretty important. These are people who are going to be designing the next stage of AI, they're going to be designing the new computer chips, they're going to be in biotechnology. If we can get more out of those kids, there's a huge multiplier there.

I believe that very deeply. I believe leaders are important. I believe in the power of single individuals to create huge amounts of change, but not everybody agrees with that. I was at a school the other day, and a bench outside the school literally has carved into it —a bench that every student sees as they go into the school — it says, “Strong people do not need strong leaders.” And I fundamentally disagree with that. I think we need strong people and we also need strong leaders, and the way we get both of those is ensuring that every student has the opportunity to have their learning needs supported and have the opportunity to achieve their potential.

What's the direction of the company? Where are you going to be in five years? What's the dream?

Right now, we are in the process of officially launching our learn-to-read app, targeted at preschoolers, and then what I really want to do is start transitioning into math. So once we have taught kids to read, we have essentially unlocked their ability to teach themselves. And so our goal is to keep up with this earliest cohort of kids who are learning to read and support them as they continue through their K–12 career. If they want to learn two years of math a year, then I would love to build two years of math curriculum each year so that they continue using Mentava to support their K–12 experience, and then they discovered that, I don't know, they're done with math in middle school, and then they get to figure out what's next after that. Do I go start a company? Do I do internships? Do I go learn marine biology? I don't know.

What about computer science? Does that play a role here?

When I say math, I would say specifically math and computer science are what I'm most passionate about. I think of it almost as vocational school. Those are the skills that we can teach that directly contribute to, okay, this person is able to create more value in the world because they know these two fundamental skills now.

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American global leadership is due in great part to its innovators — visionaries who drive society beyond the preconceived limits. Historically, government-led initiatives like the Manhattan Project or the Apollo Project pushed boundaries. Today, too often, government lags behind technologically.

Today on Faster, Please! — The Podcast, I talk with Katherine Boyle about American Dynamism, the spirit of pro-progress innovation, and how a new generation of Silicon Valley startups is spurring government to break out of its old habits.

Boyle is a general partner at VC giant Andreessen Horowitz, having previously been a partner at General Catalyst and a general assignment reporter at The Washington Post. She primarily invests in national security, aerospace and defense, and public safety companies, among others.

In This Episode

* American Dynamism (1:25)

* From software to the physical world (7:23)

* Government collaboration: challenges & opportunities (11:29)

* Playing the long-game in Washington (21:16)

* Building the American Dream (24:35)

Below is a lightly edited transcript of our conversation

American Dynamism (1:25)

Let's just start with a little bit of definition about American Dynamism. Broadly, what challenges or problems is this effort directed toward?

It's a bit of a long story as to what American Dynamism is, how it arrived to be a category of innovation, but the short definition is American Dynamism is built for companies that support the national interest. So a very broad category of companies, everything from aerospace, defense, national security, companies that sell directly to the US government and to our allies, but also things like housing, education, transportation, infrastructure, things that are built in the physical world where Washington or states usually like to regulate those things.

So one of the things that we saw in our own portfolio is that there are a lot of companies that we used to be classifying as “enterprise” or “consumer,” and really what they were were government companies because they had to interface with a regulator much earlier in their trajectory, or they saw government as a potential buyer of the product. So in cases of things like aerospace and defense, those are very obvious government buyers, but things like public safety, where we have companies like Flock Safety, for example, that started out selling to homeowners associations thinking they were a consumer company, but ultimately got extraordinary pull from local governments and from public safety officials because of how good the technology was. So the companies, in some ways, they were these N-of-One companies, really solving really important civic problems, but over time it became very clear that this was a growing category of technology.

But the broader underlying thesis, I'd say, of where the movement came from, and when we really started seeing this as an area where founders, in particular, were excited to build, I think it did come out of “It’s Time to Build,” my partner Mark Andreessen's canonical post where he basically said during Covid that we have to be able to build things in the physical world. And there was sort of this realization that technology has solved many, many problems in the digital realm that I think, in some ways, the last 15 years of the Silicon Valley technology story has really been about changes in consumer technology or changes in the workplace, but now we're finally seeing the need for changes in government and civic goods, and there's just an extraordinary amount of momentum from young founders who really want to build for their country, build for the needs of the citizenry.

Does it change what you do, or maybe the kinds of expertise that are needed, to think about these things as a category, rather than different companies scattered in these other kinds of categories. Thinking of them as like, “Oh, there's some sort of commonality,” how is that helpful for you?

The thing that's interesting is that there's sort of a “yes” and “no” part to that question. The yes is that the founders are coming from different places. So the companies that have led to this sort of, I would say, extraordinary wealth of engineering talent where people are not afraid to tackle these problems, there's a handful of the companies that have scaled: it's companies like SpaceX, companies like Palantir, where, 20 years ago, they were banging their heads against the wall trying to figure out, “How do we sell to government?” In many cases, they had to sue the government in order to be able to sell and compete against the larger incumbents that have been around for, in many cases, 50, 70 years. But now you have these talented engineers who've sort of seen those playbooks, both in terms of, they understand what good engineering looks like, they understand the pace of innovation, how quickly you have to bring new products to market, and they also understand that you have to be in touch with your customer, constantly iterating.

And so you now have companies that have scaled in these categories where there is this nice thing that happens in Silicon Valley, and I always say it's a mark of a really successful company when three, four, five years into the journey, you start seeing the early people at that company say, “Well, I want to solve this problem,” or “I want to go be a founder, myself,” and they start building more companies. So I think that, in some ways, the natural order of how Silicon Valley progresses, in terms of, do you need to have different expertise, or are there different talent pools? Yes, they're coming from different companies, but it's the same story of Silicon Valley Dynamism, which is, someone comes in, I always joke, they go to the University of Elon Musk and they learn how to manufacture, and then they say, “Well, actually, I don't want to just work on rockets anymore, I'd like to work on nuclear.” And so then you have companies like Radiant Nuclear that have spun out of SpaceX several years ago that are building in a totally different category for the built world, but have that sort of manufacturing expertise, that engineering expertise, and also know what it's like to work in a highly regulated environment.

Does it require a different expertise, then, to advise these companies because of that government interface?

I think in some ways it does, yes, the types of people who are investing in this category, maybe there's a number of investors where they got their start at Palantir, for example, or they understand the early journey of SpaceX. But at the same time, the thing that I think has been most surprising to us is just how quickly this movement caught on among the broader Silicon Valley ecosystem. And I think that's a very good thing, because, at its core, these are software companies in many cases. Yes, they're building hardware, but software is the lever that's allowing these companies to scale. So you are seeing the traditional venture capital firms that used to say, “Oh, I would never touch anything that is operating in the physical world,” or the meme you had five years ago, which is, “You'll never be able to sell anything to the US government, I'm not wasting my money there.” You've seen a complete 180 in the Silicon Valley ecosystem in terms of venture firms where they're now willing to take bets on these types of companies.

And you're also seeing, there's a number of founders where their first company, for example, might've done very well, and it might've just been pure software, or in a consumer enterprise, sort of a more classical Silicon Valley domain, and now you're seeing those founders say, “Actually, I want to build for the civic need. I want to build for the national interests. These are issues I care about.” And so you're seeing those founders actually decide to build in the category and team up with founders who maybe have a little bit more experience in government, or maybe have a little more experience in terms of how they're building in the physical world.

From software to the physical world (7:23)

That period you referred to, which seems like a lot of what Silicon Valley was doing with the first 15 years or so of this century: they're doing internet, social media, very consumer-facing. How valuable was that period? Because that is a period that, here in Washington, is much criticized as trivial, “Why wasn't Silicon Valley solving these huge problems like we did in the ’60s?” Again, there were some critics who just looked at it as a waste of brainpower. To what extent is that a fair criticism, and do you think, is that unfair? That stuff was valuable, people valued the kinds of products that were produced

You would actually be better able to speak to this than me, but I'll say, the graph or the chart that's going viral today, as we speak, is the comparison of 2009 US GDP versus Eurozone GDP, which were roughly equal in 2009, coming right off the Great Recession, to today, which I actually think it was tweeted something like, I think it's. . .  the US is 77 percent greater in terms of GDP than the Eurozone countries, which means that, for some reason, the Silicon Valley ecosystem — and it is largely attributed to Silicon Valley. When I first wrote the thesis on American Dynamism, I looked actually at 1996, because it was 25 years when I published it, but 1996, if you looked at the top US companies by market cap, all six of them were outside of technology as an ecosystem. They were energy companies, I would say almost archaic industries that had grown over a long period of time, but if you look at those six companies today, they are all tech companies. And so something has happened in the 21st century. You could say the new American Century is actually built off the back of software. It's built off of these large tech companies that were built in California, in many cases. And so the 15-year period that you're talking about, which is this sort of, it was a zero-interest-rate environment, cost of capital was very low, there was a lot of experimentation going on, it was, in many ways, the canonical example of American Dynamism broadly, that you had risk capital going after many new ideas in many different areas, but they were particularly really focused on the areas that government was not interested in regulating.

And that's always been the theme of innovation in Silicon Valley is, “Let's go where they're not necessarily paying attention.” Maybe you had some one-offs in terms of, you'll always have to meet with your regulator at some point—in the case of Uber or Airbnb—but these companies were really born of the needs that founders understood. They were built off the back of a platform shift in terms of, 2007, 2008, the iPhone becomes the thing that everyone wants to build on, it becomes the mobile era. And so you really did have this focus of software, and enterprise software, and consumer, and companies were able to grow to extraordinary heights. And if you just look at what it has done for US GDP in comparison to even something like Europe, it is really extraordinary. So that is a story that I think we should be celebrating and telling.

But what has happened, I think, since Covid is this new shift, which is, we've explored many of the digital frontiers that we can. And of course there's always a new digital frontier. Every time we think it's over, we get hit with a new one — in the case of AI. But the thing that I think has really changed is that entrepreneurs now are not afraid of the physical world, and they are realizing — and I hate to use the word “inevitable,” but in some ways this is an inevitability — that you are going to have to interface with government at a certain point if you are going to build in the physical world. And there are so many opportunities, there are so many different places where founders can build, that that really did take on new meeting post- this slew of black swan events, in the case of Covid, and then of course Russia invaded Ukraine, where I think it did wake up a lot of founders who said, “I want to work on these really hard problems.” And thankfully we have companies that have scaled during that time, that have trained these manufacturing capabilities, they've trained engineers how to do these things. So it is our view that that 15-year period was extraordinary for software, but the next 10 years are going to be extraordinary for these American Dynamism companies, as well.

Government collaboration: challenges & opportunities (11:29)

When you talk about interfacing with government, what popped into my head was a bit of video of a congressional hearing, and they were trying to decide, do we want to bring the private sector and SpaceX into the space program, and so not just have it be a government effort by NASA? And I just remember these senators just lambasting the idea. And I think they might've brought in some astronauts, too. And if I was interested in interfacing with government and I had seen that video, I'm like, “Boy, oh boy, I hope the attitude of government has changed since then, because it seems like that's a wall.” What is the attitude on the other side? You said the attitude of the entrepreneurs has changed, of funders, but what about on the other side? What is the openness to the kinds of solutions that your companies are presenting?

I think it's changed because it has to, and I always point to the late former Secretary of Defense Ash Carter, who in 2015 started DIUx [Defense Innovation Unit Experimental] as an innovation unit for the DoD [Department of Defense], recognizing that there's a talent problem that US government has had; and it didn't start in the last 10 years. When I was exploring this talent problem, I actually realized that there had been a commission on the lack of talent going into the bureaucracy at the federal level.

In the 1990s, Paul Volcker actually chaired the commission, it was called a “Quiet Crisis.” Basically that young people today, unlike in the ’50s and the ’60s where government was seen as this extraordinary job that you could have or that you could go into one of these companies and work in a company for 30 years and then draw a pension, that young people today want to go work in the private sector, and the growth and dynamism of the private sector has actually been an issue for government, and that is not a new issue. It was explored in the late ’80s, early ’90s, and it has gotten precipitously worse because of tech. I would say that the technological innovation risk capital going to Silicon Valley and saying, “We're going to fund young people as they come out of college because they understand this new type of engineering.” You're seeing some of the best and brightest young people decide not to go to traditional companies, which has been a huge issue for the prime contractors that supply 40 percent of the government programs for the DoD, but what has happened is you're seeing this extraordinary engineering talent go to startups. And so I think what even — this is 10 years ago now — DIU saw, if all of our best and brightest software talent is avoiding government, or much of it is avoiding government, they're avoiding traditional companies that we work with, we have to meet them where they are.

And so the DoD I actually think was the first government organization to really recognize this crisis and to decide, we're going to need to have new interfaces. Now, whether that means new procurement, that's always going to be a debate, and that's a Washington issue that I think we've been fighting for several years now in order to change how these companies are able to work with the DoD on these big programs, but I think even just recognizing that this was an issue 10 years ago was a huge step for government.

And over time now, we've seen a handful of what we would call “defense 1.0” companies, in terms of startups, many of them kind of built off the back of a company like SpaceX, now realizing that you can build for USG [US Government], you can build hardware-software hybrid that you can then sell into production contracts, and it's companies like Anduril that were started in 2017 when people said, “This is impossible to do. You're never going to be able to sell to USG,” and this year was chosen for a massive program, the CCA [Collaborative Combat Aircraft] program with the Air Force, over many prime contractors.

And so I think that is the story now that Silicon Valley has seen, and I always joke that, particularly investors and founders, they really only need to see a handful of winners to know that something is a category, and so you're going to see more and more of these companies being founded, scaling, and I think that circuitous cycle and that virtuous cycle actually leads more to the DoD saying, “Okay, this is a real ecosystem now.” It's not as risky to take a chance on a startup, which is what government is always worried about, if we take a chance on anything innovative, are we going to look foolish? And so I think, in some ways, you are seeing the government respond to what's happened in the private sector, but this is not something that's a year old, two years old, or three years old, this is something that's been talked about for almost 10 years now, and of course SpaceX now is an over-20-year-old company.

Is this still primarily a Defense Department-focused effort? Are there other areas of government who are looking at what's happening with DoD and they're drawing lessons? How diverse of an effort has this become?

We see this across every sector that government cares about. So it's not just defense, it's aerospace, it's energy, it's logistics, it's transportation. We always joke, if there is a department in Washington that exists to regulate a sector, that is American Dynamism, and you are seeing innovation in those sectors. But it's happening at different rates. I'd say the DoD is one of the largest spenders. The largest private US company right now is SpaceX, so there's success in those categories, so you're seeing a lot of interest in it now, but then there's companies in public safety. That's an area where I think there's just been an extraordinary explosion of innovation in the last few years, largely driven by the fact that there is a labor crisis happening in public safety across America, but it is a different sale, it's not selling to federal government, selling to state and local.

One of our companies, Flock Safety, which I mentioned at the beginning of our chat, they now are involved in solving 10 percent of vehicular crimes in America.

What do they do?

So, it's a great story about a company that was founded in Atlanta in 2017, and they built a very small modular license plate reader that only tracks cars, not people, and started building for homeowners associations with the recognition that most crimes in America are committed with a car, and so if you can put these in areas of high traffic, areas to augment the work of law enforcement, crime will go down. And they started selling to homeowners associations and immediately got pull around Atlanta and suburban Atlanta from police chiefs who said, “I need 10 of these in areas where we don't have enough people who can look at different areas.”

So now this company is operating across America, they're in all 50 states, and what's extraordinary about what they've been able to do as a technology company, just putting up cameras in different sectors and following cars, is one of the hardest problems for law enforcement is when a car that has committed at theft or — one of the most extraordinary stories they've told us recently was there was a young girl kidnapped, a young child kidnapped in Atlanta, and the car went into a different county. And so when that happens, for law enforcement it's often one of the most difficult things, if a car goes into a different county, to do data sharing across these places. But if you have a network of cameras that can track the car, you find that kidnapped child, or you find that stolen vehicle much, much faster. In many ways, catching the cars at the moment where they've moved from county to county has actually solved one of the bigger data issues that law enforcement has.

What's interesting about this example — and it provides a nice lead-in to my next question — is, in that situation, the solution wasn't to help the various databases communicate better, it was a completely different sort of solution. So, are what these companies doing — it seems like what they're not doing is taking existing operations and improving efficiency, but providing a new way to approach the problem that they're trying to tackle.

Yes. And what's incredible about that story is it was not started as a company that was supposed to support law enforcement. It was started for homeowners associations, it was a consumerization of a civic problem. And I think that's what's really interesting is, one of the biggest issues, and this is why I think you're now seeing really interesting technology companies enter government at all levels is, you have a population that has grown up with consumer technology now. So as the boomers retire, the boomers remember what it was like to be in government, or to be in office places without Zoom, without the consumer internet, and without the things that make life much easier and tangible, as those people retire, you have young people demanding, “We have to use better technology.”

And so the solutions are not, “Okay, let's iterate on the existing systems that we've used for the last 10 or 20 years,” it's, “Why can't my experience when I walk into my job in government feel exactly the same way that it does when I walk into my home and I experience the consumerization of everything around me?”

So I think that is part of it, that you have this millennial generation that's now coming into leadership. In many cases, you have people who don't necessarily remember the world before the internet or didn't have formative experiences in the workplace or in government before the internet. And that is shaping and reshaping all of how government functions, and likely will for the next 20 years. The thing that, especially when we talk about the Department of Defense and the warfighter, the thing that has always been tragic is that you have more technology in your phone than you do when you go onto the battlefield. And so I think there's this understanding that young people are demanding to have the same level of technology and the same ease-of-use in all aspects of governance, in all aspects of civic goods.

Playing the long-game in Washington (21:16)

You seem like a very upbeat, positive person. My experience as people from Silicon Valley — or now, in your case, from Miami, a new startup hotbed — they come through Washington, they bring that optimism with them, then after a few days of dealing with people on Capitol Hill, the optimism is drained out of them, they go back shells of their former selves, because if you've dealt with a lot of people on Capitol Hill and staffers, what they're really good at saying is, “That will never pass . . . that will take 20 years . . . three of my predecessors worked on it, it didn't work . . .” How have you been able to maintain a fairly upbeat attitude, given that this is the world that your companies have to deal with?

I agree with you that one of the biggest problems that we see, and which we joke about, is that the only reason why people in Silicon Valley 10 years ago were going to Washington was to apologize for the things that they did. They would get hauled in front of Congress, say they're sorry, and so I think what we've seen in these sectors, in particular, is it's a specific type of founder and person who knows that this is very mission-driven. They are called to build these companies. They care about these companies. They're passionate about the national interest. And so they know they have to go to Washington repeatedly, and I think some of the mistakes that, say, founders who had no exposure to Washington, or have no exposure to regulated industries, when they would go to Washington, they'd say, okay, maybe I go once a year, shake some hands, it's kind of fun, and then I go back and I build, and they would be surprised when they got nowhere. And of course, I think that the most sophisticated companies recognize that they have to learn to play the game that Washington cares about. And there is a totally different culture in Washington, there's a totally different set of incentives. I say it's really the difference between, Silicon Valley is a positive-sum culture: Everyone helps everyone, knowing that the pie can always get bigger, and you always want a piece of that bigger pie as it's growing, and so the more things that you're doing, the better. It's why we have this beautiful angel investing network. It's why we have all of these things that make no sense to people in Washington where it's elections, where 10,000 votes in a state could decide the election, and it's a zero-sum game, and that is what decides who is in office and who is in think tanks. And so it's a very different way of thinking about things.

The thing that I think has changed the most about Silicon Valley is recognizing, we might not be good at zero-sum games and zero-sum thinking, but that is the people that we are interfacing with, and we need to understand their incentive systems when they decide to make a purchasing decision, when they decide whether they're going to vote on a bill in a certain way, when they think about, what do their constituents care about back home in a place that has nothing to do with Silicon Valley or California. So I think that level of empathy for what Washington does, which is very different than what Silicon Valley does, is important.

Is it hard to stay optimistic? There are times where you're banging your head against the wall, we're on very short time horizons, Washington can go in perpetuity doing what it does without necessarily seeing much change. But having those points of connection, and constantly having the conversation, and recognizing that it is a long game and not a short game, I think has been very beneficial, and now there are success stories: Palantir, Anduril, Shield AI, these companies that have been around for 10 years now, that have really shown that it is possible to do good work and to support the needs of the DoD, and to speak the language of the DoD, as well, I think has really led to this next generation of founders understanding what they need to do to be successful as well.

Building the American Dream (24:35)

What kind of world are you trying to create? I'm sure it's intellectually challenging, I'm sure it's well-paying, but, fundamentally, why are you doing this? And I would think it's to create some world that is better than the one we're currently living. What is the world you're trying to create?

I think there is a recognition post-Covid, in particular, for a lot of young people, a lot of engineers, that things were broken, things are broken in this country. The physical world has not kept up with the digital world, and there's been extraordinary changes, technology is moving as fast as it possibly can, and a lot of the things that people care the most about have been left out of that story: Education, which is something we haven't necessarily talked about yet, but education needs to be completely transformed in an era where technology is at our fingertips and where people who are good at learning learn faster than they ever possibly could, and people who are not good at learning don’t, and so you have a disparity between those people.

But there's an extraordinary amount of change that has happened in the last 25 years where the things that American citizens care most about have not changed in the way that they need to keep up with, again, the changes in the consumer internet and what we've seen in the enterprise.

And so the story of, how do we make America strong? How do we continue to be the most dynamic country in the world? How do we make sure that all American citizens and the things they care about most in terms of the American Dream are part of that story? I think that is something that the founders who work in American Dynamism care deeply about. They recognize, and I always point this out, but there are so many founders now who are working at companies like Anduril, like Saronic, where they don't necessarily even remember September 11th — they weren't old enough — but they care deeply about the idea that America needs to be a strong country, and that we need to have a mode of deterrence, and we need to have a strong national defense that keeps America the most dynamic country so that people can build inside of it. The same thing with recognizing that there needs to be changes in housing, needs to be changes in education, these are things that were part of the American Dream when our parents were growing up and feel a little bit distant for a lot of other young people growing up today. So I think there is a recognition that technology has to be a part of those big sectors in order to support the American Dream that many of us grew up with and that many of us aspire to.

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In our highly globalized economy, exogenous shocks and unsettling headlines are everywhere. It makes sense that market forecasters should be biting their nails, but so often their prophecies of doom prove completely false. Philipp Carlsson-Szlezak is a proponent of “rational optimism.” He believes there’s a calmer, more measured way of going about financial and economic analysis that sets us up to be more flexible to the highs and lows of the economic events. Today on Faster, Please! — The Podcast, I talk with Carlsson-Szlezak about why an overreliance on models — and a tendency to assume the worst — can impair our ability to roll with unexpected events and make the best of them.

Carlsson-Szlezak is the global chief economist at Boston Consulting Group, and leads the Center for Macroeconomics at their Henderson Institute. He is the co-author of the new book, Shocks, Crises and False Alarms: How to Assess True Macroeconomic Risk.

In This Episode

* Optimism during a polycrisis (1:39)

* AI employment panic (7:47)

* Risk-assessment strategy (13:08)

* Federal Reserve predictions (19:44)

* Impending shocks? (23:41)

Below is a lightly edited transcript of our conversation

Pethokoukis: Philipp, welcome to the podcast.

Carlsson-Szlezak: Thanks for having me.

Optimism during a polycrisis (1:39)

It seems as if there are multiple challenges facing the world and the global economy simultaneously. People described it as a “polycrisis,” and it could be everything from trying to navigate economies to a soft landing after a bout of inflation; part of it, I guess, is the big rise in debt; we have war in Europe; maybe, eventually, war in Asia over Taiwan; and, of course, climate change; aging population; falling birth rates; and some people seem to view AI as more of a threat than a positive, it's going to take jobs, and perhaps other bad things. If I've given a sensible description of the world, how can one be a “rational optimist” in a world of polycrisis?

Just taking maybe two of your examples: The soft landing that was supposed to be impossible, remember that? We need, what was it, six percent unemployment for how many years to bring inflation down? So clearly that didn't pan out like the pessimists said. Or think about the war in Ukraine that you mentioned, which, of course, is the tragedy, but the fact is that there is no recession in the Eurozone so far. The fact is that industrial production has held up rather well, even in the heartland of industrial production in Germany. So real industrial output is actually remarkably resilient. Overall, there's little doubt that there are many, many risks. There are crises, but, more often than not, we're focusing on the tail ends of the distribution and pretend that those risks are at the very center of the risk distribution.

It sort of reminds me — it's not a perfect analogy — of where we were in the early 1990s. I suppose you can always point to, and maybe this is part of your point, if you want to focus on bad news, the world will give you plenty of bad news to focus on. But I remember at the beginning of the 1990s, very bad recession here in the United States, a lot of concerns about the ability for rich economies to grow quickly. Again, debt was an issue, and though, looking back, it may seem like, wow, people should have been really excited: end of the Cold War, there was a lot of uncertainty what would happen to the former Soviet Union, a lot of talk back then about suitcase nukes, who knew what was going to happen in the world? And of course, all of this kind of concern and uncertainty led right into a big economic boom.

So to kind of get back to what you were saying, it seems to me that, rather than being rational optimists, we’re sort of naturally irrational pessimists.

Yeah, but we shouldn't be. I think your example of the ’90s and what the mid- and late ’90s delivered, I think is not a bad analogy for what I think will play out in the 2020s, the rest of the decade. We're in an “era of tightness,” is what we call it in the book, which is really a structural condition of the labor market. Lots of people think that shortages in the labor market are a byproduct of Covid, but that's not true. The labor market turned tight already in 2017, so, in technical language, that's when unemployment dropped below U*. Covid was an interruption of this tightness. Unemployment went to almost 15 percent, and then it came down just as fast, but we are in this era of tightness, and I think it will persist.

To be clear, even if and when you get another recession, you will return to a tight stance. And there are a lot of silver linings that come with eras of tightness: It translates into better real wage growth, it nudges and forces firms do capital-for-labor substitution, it pushes them towards the technological frontier in their respective areas, and all of that should lead into some boost of productivity growth. I'm not of the kind where we're predicting this big jump in productivity growth, I think that's too hyped, but I do believe that the structural tightness, which is almost like a spark to the fuel of technology, I think that will push gradually and measurably over the years to come.

And the driving forces of that tightness are what?

We have a number of things going. Essentially, you had a mismatch of demand of supply already in the late ’10s, as I described, so there's a supply issue, we don't have enough labor supply. You have certain forces on the demographic side that constrained that. And I think often we hear the story that AI is going to produce so much unemployment that there will be mass unemployment, and I don't believe any of this. I think that will play out very differently. Historically, technology has never given us structural or technological unemployment. On the contrary, technology is the deflationary force in the medium- and long-run. Firms that can deliver cost savings, they can lower prices, they will do so to grab market share. That is a real income boost for consumers. So when their real incomes grow, they redeploy that gained real income to new services, new goods purchase and consumption, and that leads to new employment. And so I think, essentially, you will remain with a story where labor is tight, and that is the defining underpinnings of what's coming.

Today people don't remember that even in the 2010s, I think it was Bill Gates, he wanted a robo-tax, a robot tax. Because why? Because automation was taking over the assembly lines and we're going to have to provide for all these people who are going to lose their jobs! Well, where are we today? Near record-low unemployment. And this is in a line of a long tradition where Nobel Prize winners, and technologists, and politicians, they've all predicted technological unemployment.

AI employment panic (7:47)

I wanted to talk a bit about AI labor, since you brought it up. If you don't think mass-unemployment is a valid concern, could there be other downsides from deployment of generative AI in an economy? Could it be, instead of higher employment, might it just be greater inequality? Maybe, before, we had technology hurting blue-collar workers; certainly there's a lot of white collars worried about it. I was just reading a story in the New York Times — all of these people in Hollywood are just terrified, whether they're doing special effects, or they're sound editors, they're all terrified that their white-collar jobs are going away. So do you see, in the near term, any downside from AI?

In macro there's always this tension between the aggregate, which is what macroeconomics is about, and then the distribution of experiences under the hood of macro, if you will. So there will be winners and losers, and there will be those that are harder hit than others, but I think when you look at the aggregate, you add it all up the net-net, I don't anticipate this being a structural or technological unemployment situation.

To go to the micro level, you can take the other side of that argument, too. This is not a big area of research for me, so I'm straying outside of my field of expertise here, but plenty of people have argued that perhaps AI will give a lift to those least-skilled. Why? Because AI is a companion for them that makes them more productive and allows them to create more value, and therefore to be paid better. So I think the jury is out on that.

I don't anticipate a smooth ride where everyone will be a winner and everything will be just plain sailing. Of course this is disruptive, of course there will be gyrations, but the story about technological unemployment's been told for so long. Today people don't remember that even in the 2010s, I think it was Bill Gates, he wanted a robo-tax, a robot tax. Because why? Because automation was taking over the assembly lines and we're going to have to provide for all these people who are going to lose their jobs!

Well, where are we today? Near record-low unemployment. And this is in a line of a long tradition where Nobel Prize winners, and technologists, and politicians, they've all predicted technological unemployment.

There's a nice story with Wassily Leontief, a Nobel Prize winner in economics. He said in the ’70s that human labor was going to go the way of the horse after the introduction of the automobile. Well, 50 years on, we're here with very tight labor markets. And Kennedy was worried about it, too, and others before him. And so I think we have to point to something that's truly different about AI to tell that story. I think we can potentially find some reasons that are genuinely different about AI, but before we all become hysterical about it, I think we should take a deep breath.

Does it strike you as odd that, in a world of low unemployment and, if you're correct, perhaps a longer-term structural tightness, that it's at this moment that people are very worried about technological unemployment, it's at this very moment that they're very worried about immigration coming in and taking jobs. You would think these would be concerns at periods of very high unemployment: people standing in line around the block to get a job, but that's not where we're at. Yet the public mood seems to not be in sync with that.

I think that's a good observation, I don't have a great explanation for it. The technology that's on display is impressive, it is novel, and what's different, generally, is that it makes a credible promise to impact the service economy. In our book, the way we position the slump of productivity growth has little to do with high debt and all those explanations that are occasionally fashionable. It has a lot to do with the fact that the US economy transitioned from being a physical economy to a service economy. And in the physical economy, the production of goods, you always had pretty respectable productivity growth, including the last few decades. But because of this mix shift into services where you did not have the technology to make progress on the productivity side, this mix shift dragged down aggregate productivity growth. If you have zero or very little productivity growth in services, which is like 65, 70 percent of the economy, and you have very high productivity growth and the part that is 30 or 35 percent of the economy, well the blended average is going to be low. And so, as we now have productivity growth promises from AI and services, I think a lot can change there. Again, not in a step change way, this is not like flipping a switch, it's going to be hard slog, and incremental, and cumulative, but something will happen there.

There's plenty of risk out there. New crises will come and happen, but for every true crisis, there are many false alarms, and that is something that I think we need to internalize more, and that is something that can help us see risk a little more calmly and in a measured way.

Risk-assessment strategy (13:08)

Just to take a quick step back: Describe your process for assessing risk. Where do you begin? What are the factors? Do you have a fundamental baseline model of the way the world works? How does that process start and work for you?

The way we go about risk in the book is to say macroeconomic risk should be viewed both as the downside, which is how we commonly view risk, like a recession, or even a structural downside like a deflationary depression — these are downsides. But for practitioners, risk is also hidden in potential upside if you miss out on it. And both the downside and the upside, they come in two flavors: tactical, short-term stuff, cyclical stuff; and the more structural strategic kind, like shifts that happen over longer periods of time. And so we like to think of macro risk in those four flavors: the short, the long term, and the upside and the downside, if you will

Generally when we look at risk, it's very seductive and tempting to focus on bad outcomes and then start analyzing how bad will it be and how quickly they're going to happen. In most situations, it pays off to take a step back, and take a deep breath, and say, “Well, how is the system constructed? What are the drivers? What is the history of this thing?” and an important question, “What would it take to get that outcome from the edges of the risk distribution? What does it take to get there?” Too often in public discourse, we jump straight to the tails of the risk distribution. We're immediately obsessing with the cliff edge and the fall into economic death, and then we're pretending that that risk outcome, which is part of the distribution, so we can't ignore it, but we're pretending that the edges of the distribution are the very center.

And so what we do in the book for a number of areas of risk in the real economy, the financial economy, and the global economy, we go over and over again into these approaches of asking, “How is this thing constructed? What are the drivers? What do you have to believe for the truly bad outcome?” There's plenty of risk out there. New crises will come and happen, but for every true crisis, there are many false alarms, and that is something that I think we need to internalize more, and that is something that can help us see risk a little more calmly and in a measured way.

How well did markets, investors, economists — how well was their risk-assessment process in 2020, given where we are today? My guess is that the global economy is better in 2024 than people thought in February, or March, or April of 2020 as the pandemic was kicking in. Did we do a good job assessing risk and reward back then?

No. Public discourse did a terrible job at that. The conventional wisdom and received wisdom in March and April, May, even June, July, and even August, the summer, when you had the first signs of recovery, the conventional wisdom was: This is worse than 2008, and this could be as bad as the Great Depression. And we have a great collection of headlines that we keep, there are lots of them in the book as well. It was, in my mind, a prediction failure. Why? Because what happens is that a lot of the commentary, a lot of the thinking, was too model-based, what we call “master-model mentality” in the book.

So how do you project a recovery, typically? You look at the unemployment rate as a proxy for the health of the economy, and if you have a high unemployment rate and a recession, well, it can take a long time to bring that down. After 2008, it took the better part of the 2010s to bring unemployment down, and you had “only” (in quotation marks) unemployment of 10 percent after the Global Financial Crisis. Now with Covid, you almost went to 15 percent. So the models extrapolated outside their empirical range. They said, “Well, if it took almost a decade to bring down this unemployment rate after 10 percent unemployment, then after 15 percent unemployment, well it's going to take even longer.” Hence, the narrative of “worse than 2008,” “as bad as the 1930s,” and blah, blah, blah.

Even at the time, you could ask exactly these questions, and I'm not saying this with hindsight bias. We did a piece on March 28th, 2020 in Harvard Business Review where we did exactly that thought experiment. We said, “What does it take for this to be a structural downgrade for the US economy? What does it take for to be worse than 2008?” You're going to need to see damage on the supply side of the economy. You're going to need to see the downgrading of the labor market of a window of capital investment that isn't happening, and the loss of skills, et cetera. And we asked, “Well, how likely is that?” And, of course, it comes down to stimulus. Of course it does, and it comes down to how innovative, fast, and big are we in backstopping the real economy? And we were. And so even in March — and this is shelter-in-place phase, right? This is not even sort of the full lockdown. Even then, you could ask sober questions about very bad risks. And if you did that, you arrived at answers that weren't predictive in “this will happen” at a point forecast level of accuracy. But there was clearly a path and a narrative in March 2020 that was consistent with what actually happened: the tightest recovery on record, and a US economy that was not pushed off its trend path. So after 2008, the US economy was actually pushed off its prior trend path, never made it back in terms of what the trend was, did make it back in terms of growth rates after 2008, but it never made this levels recovery in that sense. All of that was avoided in 2020, and you didn't have to be a magician to at least entertain the possibility that that was a meaningful part of the outcome distribution.

Federal Reserve predictions (19:44)

Speaking of models, how has the Fed's model performed? Which is another way of saying, how has the Fed performed, and continues to perform?

In the recent inflation surge, et cetera? I think the Fed has taken too much flak for what happened in the inflation spike. The inflation spike, by the way, again, was immediately spun into a structural inflection point, the 1970s narrative, off to the races, wage price spirals, all that nonsense. It was an idiosyncratic mismatch of demand and supply. It was an overshoot in consumption following stimulus, and you had the supply chain crunch, and then you had a number of exogenous shocks that nobody could foresee, and those who like to take credit for having predicted the spike, they didn't foresee the Ukraine war, the shock in oil that followed, and many other of the things that played into the spike. The bigger story, though, is quite simply that, as this mismatch of demand and supply unwound, inflation also came down pretty fast.

Now, back to the Fed: Yes, there were slow in responding. Would it have been better for them to go early, perhaps, yes, let's say yes. But at the same time, the idea that they would fail to step up and act, and reign this in, and stand by and watch this whole thing go to hell. I mean that was never credible. And they did step up, and they did what they had to do, and I think also attempting the soft landing was the right thing. People at the time did say, “We need a draconian recession right now to remove all the risk of a regime break in inflation!” Well, you would've cut short a really tight labor market that has a lot of real wage gain that delivers a lot of good things for particularly the bottom of the labor market. So it was the right call to attempt a soft landing rather than saying, “Look, we're going to cut this cycle short right now to remove any risk of inflation spiraling out of control.” They did the right thing. They're successful at it. The soft landing is a success. We're well into it. And so I give them more credit.

Is that what you think is the biggest mistake people are making, that they're still asking, “What about the soft landing?” And what you're saying is, “We're already into it. You sort of missed it. It happened. You're still looking for it.”

Every so often you still see the headline, “Are we going to get a soft landing?” And I'm like, “Well, let's just take a step back.” What is a soft landing? The task was to cool down the labor market, best seen through the eyes of job openings, to cool that down without pushing up the unemployment rate. These two are mirror images of each other. When firms stop hiring, they usually also start firing, so we had to pull off this trick: You stop hiring, but you don't start firing.

That was the soft landing. That's the definition of a soft landing, nothing else. And that is what happened: Job openings are down more than three-and-a-half million or so — don't nail me on the decimal — and the unemployment rate is up a little, but, as you and I know, the unemployment rate is not up because of firings. The unemployment rate is up for compositional and participation reasons. So if that is not a soft landing, at least, I would call it the second of three stages, if you will, I don't know what it is. And back to the topic of headlines, most of them are just confusing people more than they're helping them. It's always nice to write something clickbaity that people will be scared of and think this is the cliff edge. How about a headline: “Wow, this is a really great soft landing! This is remarkably good!” Why don't we acknowledge that for a moment?

You can always speculate. You can speculate on, for example, exogenous shocks. Covid is an exogenous shock, and there are others: There are solar flares, and there are new pandemics, and there are things that can do immediate damage, and you can spend millions of dollars on models, and they simply won't capture that exogenous risk.

Impending shocks? (23:41)

Yeah, I mean, the name of the book is Shocks, Crises and False Alarms. As I look over the rest of this decade, if you take the most bullish and extravagant predictions about AI, it’s not clear to me what the economy looks like a decade from now. Again, if you take the most bullish kind of [view]: we get the human-level AI and all that. So there's that.

I also am not quite sure what the world looks like if some of these worst-case scenarios with Taiwan, and the US, and China, because that seems to me to be so potentially bad, I don't want to think about it. I don't know what the global economy looks like on the other side.

What are the big risks, or the things which you believe pose the greatest risk of disruption? Disruptions are going to be good and bad. If you're really worried about AI, that must mean AI is very powerful, it can do a lot of good things, too. So what out there do you really worry about that the disruption will be just bad and have far more downside?

You can always speculate. You can speculate on, for example, exogenous shocks. Covid is an exogenous shock, and there are others: There are solar flares, and there are new pandemics, and there are things that can do immediate damage, and you can spend millions of dollars on models, and they simply won't capture that exogenous risk. So that's one story.

Geopolitics, since you mentioned it, a third of the book, roughly, the third part is about those types of risks, and they can be devastating, there's no doubt about it; but would you build a central case around this and make that the base case and expectation of how to view the future? Geopolitics is extremely treacherous when it comes to translating its impact on the economy. It's fascinating to me often how little the complexity is acknowledged and understood, and, in the book, we use an example juxtaposing a start of World War I and World War II.

So when World War I breaks out, the Dow is down 10 percent, they close it for 136 days, and when they reopen it, it's down another 20 percent. Exactly as you would expect, right? It makes a lot of sense, a world war and the market's in the gutter. Yet, when World War II breaks out in ’39, the market jumps 10 percent and stays up. Why? It ends the Great Depression, it puts to use labor, it has capital expenditure and investment, and it singlehandedly ends a decade of malaise.

And there is a silver lining to this, and all of this doesn't sit well with how we want to think and should also think about geopolitics, which is in humanitarian terms, and also values and idealistic views. All of this is true and correct, but if we are to assess the impact on the economy, we are going to have to restrain some of these instincts, and we're going to have to say, what are the transmission channels from geopolitics to the real economy, to the financial economy, and to the institutions that we have in place that govern our economy? What are those transmission channels? And often, the bar is higher than you think.

Just think about it, the Ukraine war. It's left no mark on the US economy at all, virtually. Why? Because the real linkages weren't there; virtually no trade into this part of the world, either Ukraine or Russia. The financial linkages weren't really there; it's not like balance sheets of US banks were impaired by shutting off that part of the world. And on the institutional side, we can discuss sanctions, and we can discuss using the US dollar as a means of punishing Russia, and all that. But essentially, once you think soberly about, well, how is that shock supposed to transmit to the economy? Well, it looks a lot different.

The same could be said about the tragedy in the Middle East. The oil price is lower than before the attack on Israel, right? If you look at futures and forward pricing, or the price of insurance against swings in the oil price, it’s lower today than before the attack on Israel and before the retaliation that Israel enacted. So any of these geopolitical risks and hotspots, they are to be taken seriously. I'm not saying they don't matter, but when we extrapolate from them straight to the economy, it more often goes wrong than it goes right.

And a final thought: I’m not a Taiwan and China watcher, but one thing that's also clear to me, since you mentioned the unthinkable and the worst-case scenario, my next question would be, okay, what shape would that take? Would that be a blockade? Would that be an actual invasion? Would it be something that involves airlifting semiconductors out of the island? Would that be . . . There's a myriad ways of how such a thing could play out. It'd be a big shock, and terrible, but I can't say with confidence what it would do linearly to an economy like the US economy. It would come down to the details of that.

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In a world of Artificial General Intelligence, machines would be able to match, and even exceed, human cognitive abilities. AGI might still be science fiction, but Séb Krier sees this technology as not only possible, but inevitable. Today on Faster, Please! — The Podcast, I chat with Krier about how our public policy should facilitate AGI’s arrival and flourishing.

Krier is an AI policy expert, adviser, and attorney. He currently works in policy development and strategy at Google DeepMind. He previously served as Head of Regulation for the UK Government’s Office for Artificial Intelligence and was a Senior Tech Policy Researcher at Stanford’s Cyber Policy Center.

In This Episode

* The AGI vision (1:24)

* The risk conversation (5:15)

* Policy strategy (11:25)

* AGI: “if” or “when”? (15:44)

* AI and national security (18:21)

* Chatbot advice (20:15)

Below is a lightly edited transcript of our conversation

Pethokoukis: Séb, welcome to the podcast.

Krier: Thank you. Great to be here.

The AGI vision (1:24)

Let's start with a bit of context that may influence the rest of the conversation. What is the vision or image of the future regarding AI — you can define it as machine learning or generative AI — that excites you, that gets you going in the day, that you feel like you're part of something important? What is that vision?

I think that's a great question. In my mind, I think AI has been going on for quite a long time, but I think the aim has always been artificial general intelligence. And in a sense, I think of this as a huge deal, and the vision I have for the future is being able to have a very, very large supply of cognitive resources that you can allocate to quite a wide range of different problems, whether that's energy, healthcare, governance, there's many, many ways in which this technology can be applied as a general purpose technology. And so I guess my vision is seeing that being used to solve quite a wide range of problems that humans have had for decades, centuries, millennia. And I think you could go into so many different directions with that, whether it's curing diseases, or optimizing energy grids, and more. But I think, broadly, that’s the way I think about it. So the objective, in a sense, is safe AGI [Artificial General Intelligence], and from that I think it can go even further. And I think in many ways, this can be hugely beneficial to science, R&D, and humanity as a whole. But of course, that also comes with ways in which this could be misused, or accidents, and so on. And so huge emphasis on the safe development of AGI.

So you're viewing it as a tool, as a way to apply intelligence across a variety of fields, a variety of problems, to solve those problems, and of course, the word in there doing a lot of lifting is “safely.” Given the discussion over the past 18 months about that word, “safely,” is, one, I think someone who maybe only pays passing attention to this issue might think that it's almost impossible to do it safely without jeopardizing all those upside benefits, but you're confident that those two things can ultimately be in harmony?

Yeah, absolutely, otherwise I wouldn't be necessarily working on an AGI policy. So I think I'm very confident this can be done well. I think it also depends what we mean by “safety” and what kind of safety we have in mind. Any technology, we will have costs and trade-offs, but of course the upside here is enormous, and, in my mind, very much outweighs potential downsides.

However, I think for certain risks, things like potentially catastrophic risks and so on, there is an argument in treading some careful path and making sure this is done scientifically with a scientific method in mind, and doing that well. But I don't think there's fundamentally a necessary tension, and I think, in fact, what many people sometimes underestimate is how AI itself, as a technology, will be helpful in mitigating a lot of the risks we're foreseeing and thinking about. There's obviously ways in which AI can be used for cyber offense, but many ways in which you can also use that for defense, for example. I'm cautiously optimistic about how this can be developed and used in the long run

The risk conversation (5:15)

Since these large language models and chatbots were rolled out to public awareness in late 2022, has the safety regulatory debate changed in any way? It seems to me that there was a lot of talk early on about these existential risks. Now I seem to hearing less about that and more about issues about, maybe it's disinformation or bias. From your perspective, has that debate changed and has it changed for the better, or worse?

I think it has evolved quite a lot over the past — I've been working in AI policy since 2017 and there's been different phases, and at first a lot of skepticism around AI even being useful, or hype, and so on, and then seeing more and more of what these general models could do, and I think, initially, a lot of the concerns were around things like bias, and discrimination, and errors. So even things like, early-on, facial-recognition technologies were very problematic in many ways: not just ways in which they were applied, but they would be prone to a lot of errors and biases that could be unfair, whereas they're much better now, and therefore the concern now is more on misuse than it accidentally misidentifying someone, I would say. So I think, in that sense, these things have changed. And then a lot of the discourse around existential risk and so on, there was a bit of a peak a bit last year, and then this switched a bit towards more catastrophic risks and misuse.

There's a few different things. Broadly, I think it's good that these risks are taken seriously. So, in some sense, I'm happy that these have taken more space, in a way, but I think there's also been a lot of alarmism and unnecessary doomerism, of crying wolf a little bit too early. I think what happens is that sometimes people also conflate a capability of a system and how that fits within a wider risk or threat model, or something; and the latter is often under-defined, and there's a tendency for people to often see the worst in technology, particularly in certain regions of the world, so I think sometimes a lot has been a little bit exaggerated or overhyped.

But, having said that, I think it’s very good there's lots of research going on on the many ways in which this could potentially be harmful, certainly on the research side, the evaluation side, there’s a lot of great work. We've published some papers on sociotechnical evaluations, dangerous capabilities, and so on. All of that is great, but I think there has also been some more polarized parts calling for excessive measures, whether regulatory, or pausing AI, and so on, that I think have been a little bit too trigger-happy. So I'm less happy about these bits, but there's been a lot of good as well.

And much of the debate about policy has been about the right sort of policy to prevent bad things from happening. How should we think about policy that maximizes the odds of good things happening? What should policymakers do to help promote AI to reshape science, to help promote AI diffusing as efficiently as possible throughout an economy? How do we optimize the upside through policy rather than just focusing on making sure the bad things don't happen?

I think the very first thing is not having rushed regulation. I'm not personally a huge fan of the Precautionary Principle, and I think that, very often, regulations can cause quite a lot of harm downstream, and they're very sticky, hard to remove.

The other thing that you can do beyond avoiding bad policy is I think a lot of the levers to making sure that the development goes well aren't necessarily all directly AI-related. So it'll be things like immigration: attracting a lot of talent, for example, I think will be very important, so immigration is a big one. Power and energy: you want there to be a lot more — I'm a big fan of nuclear, so I think that kind of thing is also very helpful in terms of the expected needs for AI development in the future. And then there are certain things governments could potentially do with some narrow domains like Advance Market Commitments, for example, although that's not a panacea.

Commitments to do what?

Oh, Advance Market Commitments like pull mechanisms to create a market for a particular solution. So like Operation Warp Speed, but you could have an AI equivalent for certain applications, but of course there's a lot of parameters in doing that well, and I wouldn't want a large industrial-policy-type approach to AI. But I think generally it's around ensuring that all the enablers, all the different ingredients and factors of a rich research and development ecosystem continue to thrive. And so I think, to a large extent, avoiding bad regulation and ensuring that a lot of things like energy, immigration, and so on go well is already a huge part of the battle.

How serious of a potential bottleneck is the energy issue? It seems to me like it's a serious issue that's coming fast, but the solutions seem like they'll take more time, and I'm worried about the mismatch between the problem and finding a solution to the problem.

I suspect that, over the coming years, we will see more and more of these AI systems being increasingly useful, capable, and then integrated into economic systems, and I think as you start seeing these benefits more and more, I think it'll be easier to make the case for why you need to solve some of these kind of policy issues a bit faster.

And I also think these solutions aren't that difficult, ultimately. So I think there’s a lot that can be done around nuclear, and wind, and solar, and so on, and many regulatory processes that could be simplified, and accelerated, and improved to avoid the vetocracy system we're in at the moment. So I don't think the solutions are that difficult, I think mustering the political will might be right now, but I expect that to be less of a challenge in the coming years with AI showing more and more promise, I think.

Policy strategy (11:25)

Speaking of vetocracy, whatever the exact substance of the regulation, I am concerned, at least in the United States, that we have 50 states, and perhaps even more bodies if you look at cities, who all have a lot of ideas about AI regulation, and I'm extremely concerned that that sort of fractured policy landscape will create a bottleneck.

Can we get to where we need to go if that's the regulatory environment we are looking at, at least in the United States? And does, ultimately, there need to be a federal . . . I think the technical word is “preemption” of all those efforts? So there's a federal approach, and there aren't a federal approach, plus a 50-state approach, plus a 175-city approach to regulation. Because if it's going to be what I just described, that seems like a very difficult environment to deal with.

 I'm not wildly optimistic around a patchwork of different state-level regulatory systems. I think that will come with various externalities, you'll have distortionary effects. It will be a very difficult environment, from a commercial perspective, to operate in smoothly. I think I'm a lot more open to something at a federal level at some point, rather than a big patchwork of city-level or state-level regulation. Now, it depends on exactly what we're talking about. There might be specific domain, and context, and application-specific regulations that might make sense in some state and not another, but in general, from a first principles level at least, I think that would probably not be desirable.

A second regulatory concern — and maybe this is dissipating as policy makers learn more, especially at the federal level, maybe, learn more about AI — is that, at least initially, it seems to me that whatever your policy idea was for social media, or about content moderation or what have you, you just kind of took that policy framework and applied it to AI because that was what you had. You pulled that baby right off the shelf. Are we still seeing that, or are people beginning to think, “This is its own thing, and my ideas for social media may be fine for social media, but I need to think differently about AI”? Obviously the technology is different; also, I think both the risks and potential rewards are very different.

Yeah, totally. I think that has been an issue. Now, I wouldn't say that's the case for everyone. There's been some groups and some institutions doing some very careful work that really think about AI, and AGI, and so on in careful, more calibrated ways; but also I’ve seen quite a lot of reports where you could have easily imagined the same text being about social media platforms, or some kind of other policy issue, or blockchain, or something just being repurposed for AI. And there's a lot of stuff out there that's just very high level, and it's hard to disagree with at a high level, but it’s far harder to apply and look at from an operational or practical perspective.

So I've been seeing quite a lot of that; however, I think over time, the field is maturing more and more, and you're seeing better thinking around AI, what it really is, what's appropriate at the model level versus at the application level and the existing landscape of laws and regulation and how these might apply as well, which is often that's something that's forgotten, or you have lots of academics coming in and just trying to re-regulate everything from first principles, and then you're like, “Well, there's tort law, and there's this and that over there.” You got to do your gap analysis first before coming out with all this stuff.

But I think we are seeing the field of AI governance and policy maturing in that space, and I expect it to continue, but I still, of course, see a lot of bad heuristics and poor thinking here, and particularly an underestimation of the benefits of AI and AGI. I think there's a tendency to always think of the worst for everything, and it's necessary, you need to do that too, but few are really internalizing how significant AGI would be for growth, for welfare, and for solving a lot of the issues that we've been talking about in the first place.

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AGI: “if” or “when”? (15:44)

Is AGI an “if” issue, or is it a “when” issue, and if it's a “when,” when? And I say this with the caveat that predictions are difficult, especially about the future.

In my mind, it's definitely a “when” question. I see no real strong reason why it would be an “if,” and that being completely impossible. And there's been many, many, many examples over the last 10 years of people saying, “Well, this is not possible with neural networks,” and then 10 minutes later, it is proven to be possible. So that's a recurring theme, and that may not be sufficient to think that AGI is feasible and possible, but I'm pretty confident for a variety of reasons. About AGI, by the way, I think there's an excellent paper by Morris and others on Levels of AGI [for] Operationalizing Progress on the Path of AGI, and I think it's a very good paper to [frame one’s thinking about AGI].

And that goes back to one point I made earlier in that, at some point, you'll have systems that will be capable of quite a lot of things and can do probably anything that your average human can do, starting at least virtually, remotely, to start with, and eventually to the physical world, but I think they'll be capable in that sense. Now, there's a difference between these systems being capable in an individual lab setting or something and then them being actually deployed and used in industrial processes, commercial applications, in ways that are productive, add value, create profits, and so on, and I think there's a bit of a gap here. So I don't think we'll have a day where we'll wake up and say, “Oh, that's it, today we have AGI.” I think it'll be more of a kind of blurry spectrum, but gradually I think it'll be harder and harder people to deny that we have reached AGI, and as this stuff gets integrated into production systems, I think the effects on growth and the economy will speak for themselves.

As to when exactly, I would think that, at least the capabilities, I would expect that in the next five years you could easily see a point where people could make a very confident claim that, yeah, we've got systems now that are AGI-level. They’re generally capable, and they are pretty competent, or even expert-level to at least 90th percentile of skilled adults, and then the challenge will be then operationalizing that and integrating that into a lot of systems. But in my mind, it's definitely not an “if,” and I would say the next five to 10 years is the kind of relevant period I have in mind, at least. It could be longer, and I think the tech community has a tendency to sometimes over-index, particularly on the R&D side.

AI and national security (18:21)

Do you have any thoughts, and maybe you don't have any thoughts, about the notion that, as perhaps AGI seems closer, and maybe the geopolitical race intensifies, that this becomes more of a national security issue, and the government takes a greater role, and maybe the government makes itself a not-so-silent partner with tech companies, and it really becomes almost like a Manhattan Project kind of deal to get there first. Leopold Aschenbrenner wrote this very long, very long paper — is that an issue that you have any thoughts on? Is it something that you discuss, or does it seem just science fictional to you?

Yeah, I do do a lot of thinking on that, and I've read Leopold’s report, and I think there's a lot of good things in there. I don't necessarily agree with everything. I think things like security are really critical, I think thinking about things like alignment, and so on, is important. One thing I really agree with with Leopold’s report that I'm glad he emphasized was the need to secure and cement liberal democracy, “the free world must prevail” kind of thing. I think that is indeed true, and people tend to underestimate the implication on that front. Now, what that looks like, what that means and requires in practice is not fully clear to me yet. I think people talk about a Manhattan Project, but there are many other potential blueprints or ways to think about that. There could be just normal procurement partnerships, there could be different models for this. At some point, something like that could be defensible, but it's very hard to predict that in advance, given particularly. . . well, how hard it is to predict anything with AI to start with. And secondly, there's loads of trade-offs with all these different options, and some might be a lot better than others, so I think certainly more work might be needed there. But, in principle, the idea doesn't seem completely crazy or science fiction to me.

Chatbot advice (20:15)

You recently posted on X that you were baffled at how many people don't use these language models or chatbots daily. I think a lot of people don't know what they would use them for. Do you have any recommendations for ways that people who are not in your line, who are not coders, that people can use them? Do you use them in ways that are applicable to the way regular people might use them?

Yeah, I think so, and under the post, I gave a few examples of how I use it. Now admittedly, most of these wouldn't be something that anyone would do, but I thought about this last weekend when I was seeing my parents and I was trying to get them to understand what Claude or Gemini is and how to think about it, what kind of questions are worth asking, and what kind of questions are not worth asking, and it's very hard to come up with a very crisp way of sharing these intuitions. I think the first piece of advice I'd give is probably to just take one of these models and have a very long conversation with it about some sort of topic, like try to poke holes, try to contradict, and I think that starts giving you maybe a few better intuitions about what this can do, as opposed to just treating it as some sort of question-and-answer Oracle-type search engine, which I think is not the right use case.

That is probably the most unsatisfying way to look at it, and just treat it as a better Google search engine. I mean really that sort of conversational, curious aspect, rather than saying like, “Find me a link.” “Find me a link” isn't a great use.

Exactly, and people will often do that. We'll do a thing, we'll get some incorrect answer, or hallucination, or whatever, and then we'll say, “Oh, these things are not good, they're not accurate,” and we'll stop using it, and to me, that is just crazy. It is very fundamentally incurious, and I think there's ways of using them and thinking of them that is very useful. So what have I done recently? I'm trying to think of an example. . .

I had some papers that I couldn't understand very well, and I would just ask it for better analogies, explanations, try to dig into certain concepts and ideas and just play around with them until the insights and intuitions were easier for me to internalize and understand. And I think you could do that at different levels, and regular people also want to understand things, so I think that might be potentially an example. But the very first thing I would do is simply long, protracted conversations to really get a sense of how far the model can really go, and then, as you do that, you'll find things that are a bit more creative than, “Can you please rewrite this email for me? Can you find typos?” or “Can you fill in my tax report?” or something. I think one way a friend used it — and of course, there are obvious limitations to that, get a lawyer and everything — but he had a legal contract that someone sent to him, and he couldn't afford a lawyer straight away, so he just said, “Can you help me find potential issues and errors in here? Here's who I am in this kind of contract. Here's what I'm concerned with.” And it's a first starting point. It can be useful. It gives you interesting insights. It doesn't mean it replaces a lawyer straight away, but it is one potential interesting way that everyday people could use.

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

✈ A quick note: I will be traveling through the middle of the month and will be posting a bit less than usual and perhaps a bit shorter than usual.

These days, it seems that critics of capitalism are more prevalent and more vocal than ever. But Ruchir Sharma, author of What Went Wrong with Capitalism, argues that the free market never let us down; our government did. Today on Faster, Please! — The Podcast, Sharma and I discuss the American addiction to “pain management” — unnecessary economic intervention aimed at dulling the effects of the natural ups and downs of a free market, and how it crippled American capitalism.

Sharma is chairman of Rockefeller International and the founder and chief investment officer of Breakout Capital. He previously served as head of emerging markets and chief global strategist at Morgan Stanley.

In This Episode

* Disillusionment (1:20)

* Economic booms (6:12)

* Pain management (8:49)

* Populist policy (14:38)

* Catalyzing change (17:32)

Below is a lightly edited transcript of our conversation

Disillusionment (1:20)

Pethokoukis: In the book, you write with some concern about the declining faith in capitalism, really among all Americans, especially Democrats and the young. It may be worrisome, but is it really surprising, given we had a financial crisis . . . hard to believe it was, what, 14 years ago? 15? Well, I guess 16, 2008 . . . Financial crisis, slow recovery. So, for a lot of people, there's a pretty good chunk of their lives where the economy didn't seem to be really zipping along very quickly and making a big change in their lives, so if people are skeptical of capitalism, can you really blame them?

Sharma: Well, as I argue in the book, Jim, that the current system we have in place is very far from capitalism. It's a very distorted form of capitalism that we have in place, and the surprise, I think, has to be the fact that, at the headline level, the numbers from the American economy look pretty good, which are the fact that the economy is growing at above two percent, the stock market is booming, America is seen as the center of all the tech innovation, AI, and, compared to its major rivals such as Europe, America seems to be in a much better place. And I think that a lot of people in the Biden administration try to put that out, which is that, “What's the problem, given how well the American economy is doing?”

And I think that the polling data is obviously very different. It shows a persistent and consistent decline in faith in the American economy, that the voters and people have, and, as you pointed out at the outset, that a lot of young people, in fact, say that now they prefer socialism to capitalism. So I guess that's the surprise, which is the fact that, at the headline level, the numbers look fine, and especially when you compare it to other countries, and yet, if you look beneath the hood, both the numbers, in terms of polling numbers and then a deeper look at capitalism, which is what I've done in the book, reveal that something is wrong with the system. The general feeling that the average American has, that the system is almost rigged against them, and rigged in favor of Big Business.

Clearly one reason people are sort of unhappy is because we had a big surge of inflation, and, even though the rate of inflation has come down, prices are still a lot higher than they remember. But that seems to me to be a temporary aberration. As every day, and month, and year goes by, we'll be a little further from this inflation surge. And then you mentioned all those positive things: in every sort of emerging technology, America seems to be the leader. Is there really a deep problem that will be more or less solved on its own the further we get away from the pandemic and that pandemic-era economy?

Well, anything can happen, but I wouldn't bet on that because, as you said, that the decline in the faith in America's brand of capitalism and the number of people who feel that the country's moving in the wrong direction, all that data predates the pandemic. So it's not as if there was a surge in inflation and that suddenly changed people's thinking about the economy and they're feeling much worse off because their real wages got wiped out by inflation. This happened even before that. Through the last 10 or 20 years, you've seen a consistent decline in American faith in the economy, in American faith in government. So this is not just about the near-term inflation data, or even in terms of what's happened in the post-pandemic world, and to bet, therefore, that, with the passage of time, as the pandemic sort of becomes more and more of a distant memory that this is going to change. I think the problems are much deeper, and it shows up in the fact that, as I argue in the book, that economic and social mobility in America today is close to record lows. Only 35 percent of Americans feel today that they're going to be better off than their parents, and when the American Dream was really flowering, that number used to be 70 to 80 percent of people felt that they'd be better off than their parents. So there's a whole host of data to show here that the problem and the disaffection with the economic system is much deeper than just the pandemic-driven surge in inflation.

Economic booms (6:12)

Is there anything about this economy that four or five years of above-average economic growth won't solve? I sort of recall that in the early ’90s, you could have made a very similar case that we had a nasty recession in the early ’90s. Some people have forgotten about it, but it was a bad recession. And then we had the Gulf War, and there were a lot of newspaper articles saying that the era of fast growth was over, America just couldn't grow fast anymore, and just as people were convinced that the good days were over, the economy took over, internet boom, tech boom, and we had very rapid growth—and, interestingly, it was also a period of high inequality, but people didn't seem to care so much because the economy was cooking and real wages were rising. So is there anything wrong that a little bit of faster growth couldn't solve?

In terms of the fact that I remember living through that era, and I think that if you compare the polling data, it shows the fact that the problems are much deeper now, and the disaffection is much deeper than what was there, in terms of the fact that what solved it back then — even back then, the basic faith in American capitalism was never lost. I think that what's happened now is a feeling that we don't have an equality of opportunity anymore, and that inequality levels now have risen much further than back then. So I think that it's always possible for some hopeful turn to take place, but I'd say that the problems this time are much deeper, and that's what I try and say: Why has this happened? The book is a deep investigation of why has this happened systematically over time. We've gotten to a point now where, across the Western world, leaders are universally, almost, unpopular, and they are also struggling to get reelected. This is happening in Europe, and I argue in the book that capitalism is in worse shape in Europe: much more statist, much more bureaucratic, much more intrusive, and Europe's an even greater regulatory hegemon than America is. So something which is going on across Western societies for this disaffection and feeling that the American government is more pro-business than it is pro-competition, which should be the essence of capitalism.

Pain management (8:49)

But where do you think it all went wrong?

That’s the crux of the argument. As the tagline of the book goes, that capitalism did not fail, it was ruined. What ruined it? As I show, that it is the suite of government habits, that how the government's role in American society has come to resemble that of pain management, which is the fact that every time there is the slightest hint of pain, we administer opiates. That's one of the reasons we have the opiate crisis, where people are just hooked to opiates, because at the slightest pain, you give them opiate to relieve the pain without quite solving the underlying cause of the problem. I think, in a similar way, what's happened with American capitalism is the fact that the government has been trying to socialize risk and take risk out of the system to try and mitigate pain, and in doing so, it's got the economy hooked to constant stimulus, constant government intervention, which is leading to a lot of perverse consequences.

What are those purpose consequences? One of them, as I've argued in the book, is that productivity has declined. Now remember, capitalism is supposed to generate lots of competition, lead to more creative destruction, lead to an increase in productivity, and productivity is the key to economic growth. But in the last 30 to 40 years, we have seen a big decline in productivity growth across the western world, including in the United States.

On the other hand, we have seen a lot of deadwood being kept alive due to all these interventions. The culture of bailouts, the culture of regulation, has kept a lot of deadwood alive in the system, which is not only dampening productivity growth, but it's preventing the entry of new businesses and new firms to come. As a result, the pace of startups in this country today has gone down significantly. It's picked up a bit after the pandemic, but for the last 30 to 40 years, the rate of new startups in this country has declined.

So I think that the systematic increase in the government's involvement in the economy has led to these perverse consequences, and those changes are quite recent. The American government was never this involved at a very basic level. The share of government spending in the economy was just three percent a hundred years ago. It has gone up over time, now we're closing in on 40 percent, the government spending, the share of the economy.

But it's not just that. The culture of bailouts: America never believed that it should be bailing out private sector enterprises. And yet, from the 1980s onwards, it's been an increased culture of bailouts. Before that, America did not do bailouts of private-sector companies, but once the precedent was set with the large financial sector bailout of 1984 of Continental Illinois, you've seen one bailout after another, and get bigger and bigger with each crisis.

And then, of course, you have the entire role that the Fed has played the, US Central Bank, in the way it has tried to micromanage the cycle and always try to act with policies where, on the upside, it's fine if markets rise, but on the downside, it's there to protect and socialize risk, which, once again, has undermined productivity and kept a lot of deadwood and possibly zombie companies alive.

So it's this suite of government habits that I think has corroded capitalism and brought us to this position today where capitalism is so distorted.

Famously, during the financial crisis, President Bush said, in his own colloquial way, “This sucker is going down.” Would you just have “let this sucker go down” rather than bail out banks back in 2008?

Each bailout seems justifiable because, at that point in time, you're in the midst of a crisis, and there's always this fear that if you don't bail out, we will end up being like the liquidationists of the 1929s and lead to a Great Depression. And I think that

“Liquidate farmers! Liquidate labor!” Andrew Mellon.

Totally correct. But I think that the impulse now is the opposite, which is, “liquefy, liquefy, liquefy.” So even in 2008, if you needed to intervene to prevent a financial crisis, they can argue that was justifiable. But after that, look at what happened: the Fed continued to do quantitative easing, to lift asset prices, thinking that high asset prices will be good for economic growth, whereas it only increased inequality because the owners of asset prices tend to be the rich, and put many aspirants of the property market, or buyers of the property market, it put those things out of reach.

And then also the fact that you had, in terms of the last year, when you had the Silicon Valley Bank problems, you intervened again to try and prevent it. And again, the fear is raised that if you don't intervene, you'll have the Great Depression. So I think we need to find a balance here, which is that you've gone from “liquidate, liquidate, liquidate” to now “liquefy, liquefy, liquefy.” And I think that we need to get back to some balance and, yeah, there is a role for government, like in a terrible crisis, but you can't have a government always be there to intervene at this slightest hint of trouble. That is what causes problems.

Populist policy (14:38)

If we indeed live in a populist political age, I would assume that I would see more intervention, and more bailouts, and more pain-prevention, because that's what populism is. Populism is saying that you've been taken advantage of by the elites, it's not your fault, and if it's not your fault, you shouldn't feel any pain, therefore we will intervene to help you. Government will help you. So wouldn’t you expect in the near future just to have more of this kind of thing: more pain-management public policy?

I think that you're right that this trend can continue, because the default path of politicians is to keep doing what they've been doing unless there's a crisis which forces them to reverse course and forces, I'd say, American society then to wake up and say, “This is not working.” But to say that this is a populist thing, I'm not sure, because this is the strategy which has been pursued for the last few years, if not decades, which is what I've argued in the book. So if you're going to keep pursuing the same strategy, then you should not expect different outcomes. If the strategy of so-called populism of more intervention was working, then why should so many people be upset with what's going on?

I've been in the last few days talking about this book. I'm surprised at how receptive people have been to the idea that it's not the government's business to be bail out private sector companies. It's not the government's business to be instituting 3,000 new regulations a year. The average number of new regulations that the government would put into a year has gone up dramatically over the last couple of decades. Now, again, it is not the job of the government to be putting in so many regulations because the more regulations you put in, the harder it is for small and midsize businesses to thrive, and it creates a barrier to entry, because the cost of regulation has gone up significantly, it can be borne only by big businesses, the average business finds it more difficult. And also the lobbyists, then, are able to rewrite regulations in their favor, and they're hired typically by the Big Tech firms or the people with all the money.

I think a populist agenda would favor deregulation. A populist agenda would say that you can't have the Fed run monetary policy which keeps on inflating asset prices, particularly property prices, and makes it harder and harder for Americans to afford a home. And similarly, a populist agenda should be against bailouts, because bailouts typically help the entrenched powerful companies rather than the average person. And as I said, it's time to try something different also because what's been tried so far is clearly not working in terms of making Americans happy.

Catalyzing change (17:32)

Let me ask you this, then: What do you see, then, that makes you think we're going to do something differently?

I don't see anything as yet in terms of that, just because, as I said, the politicians will keep doing the same thing unless there's a crisis. What forces countries to change course, including the countries which are held by liberals as these great paragons of economic virtue like Sweden or the other Nordic countries?

The bond market? Is that the action-forcing entity here? Would it be the bond market?

Eventually, yes. I think that that's it, which that only when the markets stop financing these incredible deficits do you begin to see a course-correction. But what my book tries and does here is, as I said, the first step to a cure is to at least diagnose the problem correctly. So far, the diagnosis that the Biden administration offered was, “Oh, the government needs to double down because we have had this era of small government for the last 30 to 40 years. We need to double down on what the government's been doing to correct all these problems.” But the problem is this, that we never had an era of small government! So to say that now we need to reverse that era is just wrong. As I demonstrate in the book, capitalism has been about just expanding the government over the last 30 to 40, at least the capitalism practiced by the Western societies in the last few decades.

So I would say that you're right that the bond market, eventually, is obviously the ultimate disciplinarian. It did that to Greece, it did that to Sweden, and other countries before that. But we don't seem to be at that point yet, but we could be, because the next time you have an economic downturn in the US, the budget deficit will widen to nine, 10 percent of GDP. As revenues fall, more and automatic spending kicks in, and, after that's done, the ability for interest rates to come down, which typically do to help a country go through a recession, I think will be quite limited in countries such as the United States, because your government spending would've been so high already by then.

If I were to put together a short-but-sweet economic agenda to deal with some of these, I might say, “Boy, you're worried about debt and deficits?” I would say, “What we need is a value-added tax and we need to at least lower the projected pace of spending on social security and Medicare.” So Medicare reform, social security reform, a value-added tax—and if I tried running on that agenda, I think they would run me out of town.

Since we don't have politicians generally calling for that, isn't the revealed preference of American voters for more of the same: “Don't tax me, but also don't take away my benefits,” and off we go. If there was this deep swell for any change that you think might be there, based on maybe your conversations with folks, wouldn't it be already reflected by our politicians? But I don't see that.

Yeah, you're absolutely correct that politicians don't live in a vacuum, they react to a societal chain. But my point is that no one seems to be doing . . . I just pointed out to you that outside of this so-called “tough medicine,” which you just highlighted, there are other things which can be done in terms of drawing the line on bailouts, drawing the line on instituting new regulations. Even Trump came to par, he spoke about the fact that he's going to withdraw two regulations for every one that he puts into place. In the end, though, he ended up putting out as many regulations per year as the Obama administration had done, so there was no change in that.

So I think this tough medicine, which is hard to administer, and societies only bear tough medicine once they see an apparent crisis, not something more insidious, like what I'm describing in the book, maybe yes, but there are things, as I said, whether it's got to do with the conduct of monetary policy, or it's got to do with regulation, or the culture of bailouts, I think these things can change, and the American voter will be much more receptive to it.

What's the option? That the politicians keep doing what they're doing today, the person in office will keep being unpopular and keep losing elections. As I pointed out in the book, as well, and in one of my FT [Financial Times] columns, that if you look at it, the number of politicians across the Western world who are getting reelected is declining. Typically, if you were in office, you had the platform, that if you stood for reelection, you'd get reelected. In the last few years, being an incumbent has become a disadvantage rather than an advantage. So clearly the people are unhappy, and if the politicians are going to keep doing the same thing, they should be more prepared to lose elections once in office.

Well, I think maybe they should be prepared to lose elections. Maybe they all should pray for an AI-driven productivity boom, that'll cover up a lot of bad policy.

Yes, we got that briefly in the late ’90s and early 2000s when you had a big tech productivity boom, which took place with the internet, but that has faded over time, and as I argue in the book that you can keep doing all this great technological stuff, but if you're going to undermine the fabric of capitalism, the creative-destructive fabric of capitalism with much more government intervention and more statist policies, then you should be prepared also to see a decline in productivity, and that will offset the gains coming from technology like AI.

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Micro Reads

▶ Business/ Economics

* ChatGPT Maker OpenAI Goes Smaller and Cheaper With New AI Tech - WSJ

* The Mysterious Slowdown in US Manufacturing Productivity - SSRN

* Can the returns from Big Tech’s staggering capex live up to the hype? - FT Opinion

* Trapped! China and the ‘middle-income trap’ - CEPR

* The Economic Populists Have a Point - WSJ Opinion

* Pandemic Layoffs and the Role of Stay-At-Home Orders - San Francisco Fed

* Is Greece’s Six-Day Work Week a Harbinger? - Project Syndicate

▶ Policy/Politics

* Trump's Tariffs Will Send Prices Up Mount McKinley for Americans - Bberg 

* California is a battleground for AI bills, as Trump plans to curb regulation - Wapo

* Trump Is Wrong About Taiwan's Chip Industry - Bberg Opinion

* Why planetary problems need a new approach to politics - Aeon

* Political chaos rattles clean energy investors - E&E

▶ AI/Digital

* Data for A.I. Training Is Disappearing Fast, Study Shows - NYT

* Generative AI Can Harm Learning - SSRN

* The Push to Develop Generative A.I. Without All the Lawsuits - NYT 

▶ Biotech/Health

* Retinol's anti-ageing effects may work by changing your skin microbes - NS

▶ Clean Energy/Climate

* AI Is Already Wreaking Havoc on Global Power Systems - Bberg

* Our Understanding Of How To Modulate Climate Change Is Ballooning – Issues & Insights 

▶ Space/Transportation

* Advanced Propulsion Researchers from GE Aerospace Successfully Test Cutting-Edge Dual-Mode Hypersonic Ramjet - The Debrief

▶ Substacks/Newsletters

* Bad and good arguments for industrial policy - Noahpinion

* Forget Adapting to Climate Change - Breakthrough Journal

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

✈ A quick note: I will be traveling through the middle of the month and will be posting a bit less than usual and perhaps a bit shorter than usual.

After decades of resistance to nuclear power, growing concern over climate change, rising electricity needs, and a desire for greater energy independence are spurring renewed public interest in a future powered by atomic fission (perhaps fusion, too). Today on Faster, Please! — The Podcast, I talk to Dr. Mike Goff about the state of US nuclear power, the developing advancements in nuclear technology, and what it will take to reach our vast potential.

Goff is the acting assistant secretary and the principal deputy assistant secretary for the Department of Energy’s Office of Nuclear Energy. He previously spent over 30 years at Idaho National Laboratory, including a major advisory and management role. He has written over 70 publications on the nuclear fuel cycle.

In This Episode

* Atomic Age 2.0 (1:31)

* Major concerns (7:37)

* Out of practice (11:04)

* Next-generation policy (17:38)

* Human capital (21:48)

* Fusion forecast (23:12)

Below is a lightly edited transcript of our conversation

Atomic Age 2.0 (1:31)

The Energy Secretary recently spoke about adding a lot more nuclear capacity, tripling it, I think, by 2050 or so. And before we get into whether that's possible, I wanted to ask you: As you understand it, what is the current consensus explanation for why the Nuclear and Atomic Age of the ’50s and ’60s, why that kind of ended? Because when the secretary spoke about building more capacity, I thought about the — and this is something maybe a lot of people are unaware of, that President Nixon had a plan to build a lot of more nuclear reactors in this country back in the ’70s during the oil crisis; that didn't happen, and we all know about Three Mile Island. But is there a consensus as to why Atomic Age 1.0 came to an end? Obviously we still get a lot of energy from nuclear, but not what people had imagined 40 years ago.

There are a variety of reasons. We did build a lot at one point, and we were building 10 plants a year, pretty extensive builds out there. We did then have Three Mile Island in the late ’70s, and then we got costs started going up, and schedules started increasing on the builds, and we ended up not having a lot of energy growth, in fact, we went for a long period where we weren't having a lot of energy growth, and we had a lot of other energy sources, natural gas, coal, and all. We had a lot of other energy sources out there as well. So yeah, we became pretty stagnated around 20 percent of the electricity. But now, like you say, yeah, there's been a big change in what we think the needs are for nuclear going forward, for a variety of reasons.

My background is journalism, and as a journalist I’ve written, I know, multiple stories in my life about a Nuclear Renaissance. So I'm wondering why this time looks to be different. You suggested in your previous answer that there might be some reasons. What are those reasons that we may be entering a new age where we will see an expansion in the nuclear sector?

I do think we will see that expansion, and, in fact, I think we have to see that expansion, and it's because of a lot of the positive attributes of nuclear right now. Obviously there's a lot of focus on trying to get more clean energy out there, and nuclear is a large base load source of clean energy. And it's not just CO2 emission, but it doesn't emit particulates and all, as well, so it's good air, good quality of life. So it has those key attributes. But there are other clean energy sources as well: renewables, hydro, and all that. But I think the recognition that, if you are going to go toward decarbonization, you need still base load electricity too. You need base load electricity to help intermittent sources like renewables to be able to expand more as well. So nuclear is very good at enabling decarbonization, not just by adding clean electricity to the grid, but enabling you to expand out other renewables like wind and solar and all, as well.

Additionally, nuclear is very reliable. Of the energy sources, it has the highest capacity factor of any of the energy sources. In the United States, we run 93 percent of the time, so the existing fleet that we have out there of 94 plants, they're producing a 100 percent of the power 93 percent of the time, which dwarfs what any other energy source does out there as well.

Nuclear is safe. At times people are concerned about safety, but, in reality, it's actually one of the safest energy sources out there and continues to demonstrate that.

It's resilient for different weather-related events. It can still produce electricity out there as well. It also has a lot of energy security. And as we've learned, unfortunately, from Russia's unprovoked and unjustified invasion of Ukraine, we recognize energy security is national security, so nuclear really does help us on that national security front. It provides an energy source that we can largely on-source from us and our allies. We’ve got assured fuel supplies, and provides that long-term power. You can put fuel in it and it can last for two years or so.

And I guess one other thing I'll add out there as well, is it's a job creator. Of the different energy sources, the amount of jobs associated with nuclear are some of the highest on the amount of electricity produced. And when you actually start building nuclear, like we saw in Vogtle in Georgia where they were building the two plants, it creates huge amounts of jobs. In fact, I heard a stat recently that 35,000 union workers were trained as part of the construction of the Vogtle power plant, so it's a good job creator in all, as well. And again, the power density is great, it doesn't take up a lot of space, and with the advanced technologies that we've developed in the United States, you've continued to increase in the safety, you can have plants of a variety of different sizes that can be easily deployed to, say, retiring coal plants. It just has a lot of flexibility that it hasn't had in the past, but also it's that key recognition of its clean energy attributes, but its energy security attributes as well.

Major concerns (7:37)

I did not major in nuclear science, I majored in history and political science, but I remember I took a class as an undergraduate at Northwestern University on the nuclear fuel cycle, and I remember to this day that my professor — of course, this was obviously a while ago, and I think what most of the students knew about nuclear energy was probably Three Mile Island — and I remember to this day distinctly the professor saying, “If they wanted to build a nuclear reactor in my backyard, I would be totally fine with it.” He had zero fear on the safety issue. Now when you give that rap that you just gave me about the wonders of nuclear energy before regular people, what is their response? Do they worry about the nuclear waste? Do they worry about safety? Are they immediately sold, or what are the concerns that typically get raised to you?

You brought them up. I mean, safety is brought up because you do see these high profile accidents like Three Mile Island, Chernobyl, Fukushima, which were accidents. They weren't good things that you want to have happen, but the industry's also a very learning industry. The improvements that come out of those events have just made the industry even safer and safer. And again, it's still safer than most any other electricity-producing industry out there as well.

Waste does get brought up. We have not implemented a final disposal solution for the spent fuel from our reactors, but we have safely stored and managed the spent fuel over the last six decades, and the amount of fuel that's generated, I think the stat that gets tossed around, you could fit it all in a Walmart parking lot. This is not a lot of material because it's a high energy-density fuel. It's not a lot of material, and again, we safely manage that and store that. We have countries now that are moving forward with geological repositories, which we need to be doing in the United States. In fact, just last week, I went and visited the repository that hopefully will be operating next year in Finland for disposing of their spent fuel. We can do that, it’s not a technical issue, so we can safely manage the spent fuel.

The other issue that always comes up is still cost. We do have to demonstrate now that we can build these plants safely, and efficiently, and at a reasonable cost. On the Vogtle plant there were cost overruns and schedule overruns, but between Vogtle Unit 3 and Unit 4, there was about a 30 percent reduction in costs between those plants, so we are starting to get to where we can be deploying nth-of-a-kind cost plants out there as well. And hopefully with some of the small modular reactor designs and all that are going to rely more on modular construction, we can even get to nth-of-a-kind cost even quicker. It still takes some pushing and understanding to make sure that people do understand the advancements that have been made on nuclear technology, that it's not our parents' nuclear technology, there's a new round of technology out there.

Out of practice (11:04)

You raised two good points there. The cost issue, and that's a great stat about the Vogtle plant and the reduction between the two reactors. Is it your sense that the fact that we haven't been consistently building reactors and learning from the previous build, and having trained people who've worked on multiple reactors, that each one has become like this bespoke mega project? It’s my sense, and it seems logical, at least to me, that that has been a cost driver, that we haven't been able to churn these out like 10 a year, every year, decade after decade, because clearly, if that was the case, I don't see how we don't learn how to build them better, faster, and more efficiently. But that's not what we've been doing, obviously.

That's right. It's not. Even when I say with Vogtle, you had to stand back up the whole supply chain, you had to retrain the workforce, so there was a lot of learning in that process, even though, too, we did recognize on that plant you need to have designs very well finalized and standardized as well. One of the problems we realized from the buildout of the 90-something plants that we have now is no two plants were ever that similar. Everyone wanted to make a tweak in their plant, so we never got to where we had standardized designs.

So I think now that we're getting that trained workforce, getting the supply chain up there, and our vendors are really saying, “We're doing standardized plants. If someone else wants to make a tweak on this plant, they have to go somewhere else,” that people are going to go with standardized designs so we can really replicate these and get that cost benefit from it. The challenges that you brought up, we have to overcome, and I think we're set up now to be able to overcome that. I appreciate all the effort that went into building Units 3 and 4 at Vogtle. We've got enough benefit from that learning there and hopefully build very soon here.

There's a world where we have tripled our nuclear generating capacity, as Secretary Granholm said. Can that be a world where we get all our nuclear power from light water nuclear reactors, or must there be different kinds of reactors? You mentioned the small modular reactors, and I've interviewed startups doing microreactors, I don't know, maybe they'll be used to power data centers, but can that world of greatly increased nuclear generation, even with improvements in light water reactors, must there be different kinds of reactors?

I wouldn't say “must.” I think there will be. I think we will have that variability. I think we will still have large plants being built. I think maybe five years ago you wouldn't hear that people were talking about building gigawatt-sizes plants again. I think we'll have the gigawatt-size plants, we'll have the small modular reactors that are water-cooled, but I think we will get some of those advanced reactors out there: the Generation IV reactors, the sodium-cooled fast reactors that have the capacity to be able to burn waste better and also increase the sustainability of the amount of fuel they use. I think you’ll also have the high-temperature gas reactors that are helium-cooled, that use TRISO fuel. You'll have those because we need to not only decarbonize the electricity sector, we've got to decarbonize the industrial sector. That's much more challenging, and the high temperatures that can be provided from those reactors will help us in that decarbonization process.

So I think we will have a mixture out there. There are cases where the Gen IV systems are going to be better than the gigawatt-sized plants for the needs that are out there, but large power plants are going to be needed as well. Especially, like you say, you bring up the data centers, the amount of growth that we're hearing for electricity right now, I think again, we'll see gigawatt-sized plants will be needed to be able to meet that growth.

Yeah, I tell you, nothing frustrates me more than reading about what AI could perhaps do for our economy and then having people say, “Well, but we know we can't do it because we can't supply the power” or “We can't supply enough clean power,” I mean, well then it’d be sure great to have more nuclear energy. And I wonder, as you sort of tick off some of the potential advances and new kinds of reactors, maybe I look backward too much, but I can't help but wonder what nuclear reactors would be like today, where we would be today, maybe we would already have fusion reactors had we proceeded with this kind of momentum every decade since 1980. It drives me crazy, and you're a nuclear engineer, that must drive you crazy.

It does, I've been doing this . . . my first job in the nuclear industry was almost 40 years ago when I was still in college, and there have definitely been ups and downs in funding. In fact, there were some periods where there was almost zero research and development dollars spent in the government on nuclear energy. Luckily, though, the thing that we have is, under the four presidential administrations, there's been a real steady climb in the recognition of the importance of nuclear, and the funding to support it. So I'm happy that we have had this period that goes back to the early 2000s that's been really steady growth in recognition of nuclear. If we would've not had some of those laws in the late ’80s and ’90s, yeah, we could probably be further ahead, especially on some of the advanced technologies. Because yes, some of those advanced technologies started on research that was back in the ’50s, ’60s and ’70s: the sodium-cooled fast reactor, the molten salt reactor, all of those were based on R&D that we did back in the early days, as well.

Next-generation policy (17:38)

Which leads me to this question: You work for the government. I work for a public policy think tank, so of course I'm going to think about: Given where we are today, what government needs to do going forward, both on the R&D front and on the regulatory front, are we doing enough basic research for whatever the next, or the next next generation of nuclear is, and do we now have the kind regulatory framework we need for that next generation of reactors?

I'll go to the research one first—and I should note, my background is, I'm an R&D person, I came out of the national labs, so of course we always need more research and development. But that said, we have been blessed by funding from Congress and the administration that there's a significant amount of money for research and development in the United States. And I'll say that's good, because the one thing I will note, I do believe innovation in the US, as far as the nuclear technology, we are the best. The technologies that we're developing and our vendors are deploying it, really, it is the cutting edge technology, so it's good we have that R&D, and it's important, as you know, we need to continue to have it to move forward on that next generation of technologies and continue to make improvements on the technologies out there. So I think we have a good research base.

There's some infrastructure that we still need if we start deploying, say, when we mentioned that sodium-cooled fast reactor, we don't have a testing capability for that type of system. We shut down our last testing system on a fast reactor in 1994. We would probably need some additional infrastructure. But again, we have a pretty good base. And I'll say that also on the regulatory side. We do have a pretty good base as well. The Nuclear Regulatory Commission is obviously focused on light water reactors throughout its history, but they've actually been doing a good job at being able to work with some of the developers.

We have three entities out there that are working on Generation IV reactors. TerraPower did submit their construction authorization to the Nuclear Regulatory Commission, and they've accepted it, so they're working well with them, even though they have a water-based system. Hopefully X-energy, who's doing a high-temperature gas reactor, working with the government and all, as well, will be moving forward, as well. And we've had a third that's working in the molten salt space, a molten salt-cooled reactor that has already received a construction permit to go forward on a prototype reactor, a Kairos company.

I'm sure there's got to be reforms still on the Nuclear Regulatory Commission and make sure that we are timely and responding to license applications, but they are moving in the right direction. There's been a lot of interface with various laws, whether it's the NEICA (Nuclear Energy Innovation Capabilities Act), or NEIMA (Nuclear Energy Innovation and Modernization Act), two bills that were passed a little while back looking at reforming. And I think there still needs to be improvements and still need to be increase in the resource and capacity of the Nuclear Regulatory Commission, but they're heading in the right direction.

We have a good regulator, and that's one of the things that helps us make sure we feel that we can deploy this technology safely here, but also helps us in exporting our technology, where we can say, “Our technology has been licensed by the Nuclear Regulatory Commission,” which has such a high view externally in other countries, that helps us. So I want them to continue to be that safe regulator, but again, they are continuing to work to improve and streamline the process. Hopefully we get toward where we're standardizing, that we don't have to have a lot of interface and we don't — that'll come to the utilities, too — we don't make changes once we've got something approved, so we hopefully can speed up the process from the utility side, and all is well.

Human capital (21:48)

Are we going to turn out enough nuclear engineers? I imagine that, for a while, that probably seemed like a hard sell to someone who had an interest in science and engineering, to be in this industry versus some others. Probably a little easier sell; are we going to have enough people going into that to build all these reactors?

We are going to need to continue to increase it. We’re already seeing the uptick, though, in that area. I'll note: Our office, the office of Nuclear Energy, we've really — going back to the 2010 timeframe — really recognized that we needed to do more in that area, so we actually started investing almost 20 percent of our R&D budget to the universities to hopefully foster that next generation. And in fact, this year we just hit the mark where we've now spent $1 billion since the start of those programs on the universities to make sure we're doing R&D there and getting that next generation of folks out there. It’s something that we've got to continue to focus on to make sure that we do. Because yeah, if we triple, it's going to need a lot more nuclear engineers. But I also note, the thing I'm concerned about also is making sure we have the right trades and all, as well. If we're building these plants, making sure you have the welders, the pipe fitters, and all, that's going to be a big challenge, as well, especially if we're going to start building, say, 10 plants a year. That's a lot of people out there.

Fusion forecast (23:12)

I’m excited about the prospects for nuclear fusion, and I've talked to people at startups, and it has probably looked as promising as it ever has. How promising is it? How should I think about it as being part of our energy solution going forward, given where we're at? In fact, there are no commercial nuclear fusion reactors right now. Obviously people at startups give a lot of optimistic forecasts. How should I even think about that as being a partial solution in the coming decades? How do you look at it, at least?

I think it can be part of the solution in the coming decades. I think some of the changes that's taken place, especially over the last two years where there is more of a change to focus on, not fusion as a science program, but fusion as deployment, as an energy producer, you look at it as an applied energy. I think that's an important change that's occurred over the last two years, and the fusion programs within the Department of Energy are much more focused to that. It's similar to what's happened somewhat with fission. Fission, about 15 years ago, it was government-driven, and you pull along industry, until about 15 years ago you started having industry investing a lot of money and pulling along the government. You're now starting to see that happen in fusion, where people are doing a lot of a private investment, they're pulling along the government, and the government's working to see, how can we use the resources of the government to enable it?

So I think it will happen. I don't think fusion is going to be producing electricity to the grid this decade, but I think the vision that's been put forth by the government is their bold, decade-old vision to have a fusion pilot facility sometime within the decade. I think that is feasible. So maybe before the 2050s you can start having fusion generating some of our electricity. I'm a fission person at my heart, but I think fusion is, we're getting much more focused on moving it forward as an electricity source, and that'll help it be able to be deployed sometime here in our lifetime.

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Micro Reads

How Elon Musk and SpaceX Plan to Colonize Mars - NYT

What happened to the artificial-intelligence revolution? - Economist 

The EV trade war between China and the West heats up - Economist 

Defeated by A.I., a Legend in the Board Game Go Warns: Get Ready for What’s Next - NYT

Pfizer pins hopes on daily pill to crack market for weight-loss drugs - FT

Rise of the Restaurant Robots: Chipotle, Sweetgreen and Others Bet on Automation - WSJ

Saudi Arabia's Trillion-Dollar Makeover Faces Funding Cutbacks - Bberg

AI Spending: Goldman Strategists Say Big Tech’s Splurge Worries Investors - Bberg

It’s Time for AI to Start Making Money for Businesses. Can It? - WSJ

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Artificial intelligence may revolutionize the American economy, but whether we see that potential actualized depends on a few key factors: whether generative AI is a general purpose technology, whether the labor force makes a smooth pivot, how employers prioritize their resources, and whether the US chooses to take the lead in AI’s deployment. These are just a few of the topics I cover on the podcast today with Guy Ben-Ishai.

Ben-Ishai is the head of economic policy research at Google. He previously served as a principal at the Brattle Group and as chief economist in the office of the attorney general of the state of New York. He is also a co-author of the paper “AI and the Opportunity for Shared Prosperity: Lessons from the History of Technology and the Economy.”

In This Episode

* Is gen AI a general purpose tech? (1:22)

* Risks and benefits (7:46)

* Barriers to a boom (14:27)

* Investing in employees (19:16)

* Human-complimenting AI (25:29)

Below is a lightly edited transcript of our conversation

Is GenAI a general purpose tech? (1:22)

Pethokoukis: Do you have any doubt that generative AI, and perhaps machine learning more broadly, is an important general purpose technology that will eventually make a substantial and measurable impact in the economic statistics and productivity and economic growth?

Ben-Ishai; The immediate response is absolutely, but let me unpack that: Do I have doubts about the immense potential of the technology? No, and I'm saying that very confidently, which is uncommon for an economist. We put together the paper that you've initially cited at Google to look exactly at that question: When we say that AI marks a pivotal moment in human history, what does that actually mean for an economist? And I think the conclusion there that we're looking not in an ordinary technology, but rather at a general purpose technology, that is immense. That means that we're probably looking at the most transformative economic development of our generation. And to think, Jim, that the two of us are having a conversation about that today, that is historic. I feel incredibly privileged and lucky to think and work of these issues in our day and age.

But the second part of your question alluded to not the potential, but actually the actual impact. And if there's one takeaway from that exercise from the paper that we put together and from my conversation with so many academics and policymakers around the world, is that this is not just a watershed moment, it's not just a pivotal moment in human history, it's a fragile moment as well. This story can easily be a story of missed opportunity. I think that we so easily take for granted the fact that, yes, we will of course develop AI and deploy it and apply it very successfully. And it's so easy to get caught in the moment, particularly as the nation that advanced the science, I think somewhere in the back of the minds of all of us, there's that presumption that we will be the global leaders in deployment of AI. I am actually worried about that. To ensure that we are, it’s a tumultuous, fragile, and careful process that we’ve got to be really thoughtful about, with a lot of deliberate action about what we do, how do we proceed, and how do we ensure that we are indeed the ones that capitalize on the potential?

It's remarkable how quickly the narrative around American tech has shifted. Not long ago, Silicon Valley faced criticism for focusing on social media rather than groundbreaking innovations like the Apollo program or cancer cures. Now, they've unveiled generative AI, potentially the most significant technology of our era.

Regarding fragility, it's worth considering why AI might need special handling. Unlike the seamless diffusion of technologies like the internal combustion engine or electricity, AI seems more akin to nuclear power - a technology that was stifled by regulation. Do we need a proactive agenda to prevent AI's potential from being similarly constrained?

That's a great question, Jim. I'm so tempted to go back to your first part of the question about the importance of digital technologies, and economists get a really bad rap, but try to be a librarian these days. We tend to overlook the tremendous importance of information as a driver of economic growth in our economies. And even if you look just at small businesses and the tremendous opportunities that digital technologies have provided them. To think that a mom and shop store today can actually run a marketing campaign, analyze its customer base on large databases, export products to far markets, those are things that used to be the exclusive domain of just a few large companies that today are actually available broadly and widely through digital technologies. And maybe it's the fault of economists that we are not shouting off the tops of mountains frequently enough about the tremendous power of information and digital technologies and the accumulation of knowledge as a driver of economic growth.

The application of knowledge and intelligence — that seems to me to be pretty important.

I cannot agree more! And I think, to a great degree, it explains some of the tremendous optimism around AI as a technology that really reduces the barriers to interact with technology and democratizes its use in a way that we haven't seen before.

Risks and benefits (7:46)

We quickly shifted from marveling at AI's potential to fixating on its risks — existential threats, job losses, and disinformation. But let's step back for a moment. Can you elaborate on why you see this as an exciting technology with significant benefits? It seems many people aren't fully aware of its upside potential.

That's a great question, this is really the reason why we at Google, too, we paused for a minute and kind of wanted to think about this. We're at a sector where enthusiasm is in no short supply, so what does it actually mean when we say that this is a pivotal moment in human history? What does it mean for economists? I think it really boils down to this question of: Is AI an ordinary technology, or is it really a general purpose technology? That is the term of art that economists use, and I think it's actually important to pause for a minute and think about that, because it's critical. A general purpose technology is not just pervasive in use, it is a technology that enables productivity-enhancing applications to be applied across all segments and entire economies in ways that are not just advancing and accelerating economic growth, but are also expanding the frontier of innovation and technology. It's a source of ongoing and continual innovations.

And if you think about it for a minute, if you think about the prior general purpose technologies that we've had, if it's electricity, if it's personal computers, or it's the steam engine, their impact was tremendous. And at the time that they were launched, I think nobody had the perfect vision of where . . . we of course knew where we started, in the very same way that we do today about AI, but it's really difficult, if not impossible, to know where we will end. The compounding nature of these technologies is immense, particularly when you're looking at a general use technology and multi-domain technology that can lead to applications on such a broad basis. I don't think that today we can envision what new occupations, new applications, new sectors will emerge as a result of AI. And I think the fact that it's not an ordinary technology, but rather a general purpose technology, that is important, that does imply that we're probably looking at the most profound economic transformation in our generation. That is huge.

It's relatively straightforward to assess AI's ability to replicate current human tasks. But predicting the new possibilities it might unlock, like accelerating scientific discovery, is far more challenging. These potential upsides are difficult to quantify or model economically.

While we can more easily grasp potential downsides like job automation (which isn't necessarily negative), the upsides are less tangible. They depend on entrepreneurs creating new businesses and scientists leveraging AI for breakthroughs. This makes it harder to definitively argue that the benefits will outweigh any drawbacks.

Oh my God, Jim, I cannot agree more, and I think that there's two issues, and you have written about this just recently, and I think that there's really two issues that come up, at least in my mind, as a reaction to some of the studies that really focus on the measurement. We're trying to really drill this question of, “What will be the productivity gain from AI over the next five or 10 years?” I don't want to dismiss that question —

And can you give it to me within three decimal points, right?

Exactly! But we're doing such a huge disservice as economists when we focus on that. I think it really pertains to two reasons that you brought up. The first one relates to measurement. We are really looking, these studies are primarily based on occupational exposure of existing work streams. Little do we know today about what new work streams, occupations, tasks, creativity, or human endeavors will actually be triggered by this new technology. In a way, we're really just looking under a flashlight rather than thinking about the broader issue, the broader economic benefits that will emerge, kind of like the unknown unknowns that we know today about this technology.

Just to put it in perspective, think about the printing press that led to a scientific revolution. Think about the steam engine that led to an industrial revolution, to an electronic circuit that led to the digital age. We are at that point with AI today, and to think that we're looking at SOC, standard occupational codes, to look at the future impact on productivity, I think minimizes the value of our profession.

The other point that you touched on, which I think is so incredibly important: We're missing the point. It's really not about the third decimal point of our estimates. It's about the fact that we can reshape technology. Rather than measuring its benefit, let's actually make sure that we can capitalize on the potential. That is far more important than anything else. And at some point, we'll go back to your other question about fragility, but there are genuine barriers that we need to address collectively as a society. And if we are not going to do it, other countries will, right? And I think economists have a role in that conversation. I think that is the critical issue that we need to focus on.

Barriers to a boom (14:27)

We have a technology that seems, right now, it's fast evolving, but it seems pretty darn important. It's hard to believe that we've only really been having the specific conversation about generative AI for maybe a year and a half or so publicly. So what are the barriers? If this turns out not to be an important technology that's widely diffused throughout the American economy, what went wrong? What are the barriers that concern you?

I think there are three main categories that we focus on. First and foremost, you need digital infrastructure. I think it's a misconception, and I think we will learn that very quickly over the next few years, that AI or digital infrastructure is limited to broadband. It is increasingly becoming more so about access to data, large data centers, and compute power. And I think not just the US, but many other countries, will realize, or are in the process of understanding very soon, that those are the type of investments that one needs to make in order to deploy the technology. That's one category.

Another one is the regulatory environment and the legal standards. You know Jim, and this is something you've of course written about a lot, I don't think that no single country deliberately chooses to fall behind, and I think that we often fail to recognize the long-term impact and unintended consequences of regulations. We, of course, have a duty to protect, and there are areas that raise concern, but we have to balance that duty to protect with the desire to capitalize on the potential, to foster innovation, and to make sure, at the end of the day, that we emerge as the global leaders of this technology, that we lead its deployment. I think that the legal ecosystem is incredibly important in that respect and an important current dimension of competition between countries and the future over the deployment of AI.

And the third one is our workforce readiness. We need a workforce transition strategy. Let me pause here for a minute. If our workforce is not ready for an AI transition, our employers and our companies would find it very difficult to actually implement and adopt AI. It's simple as that. And if our companies do not adopt AI applications or technologies, we will quickly find out that we will fall behind. If you're looking at the history of our labor markets, we have been not just resilient, consistently resilient in our institutions and labor market operations, but we've also been highly effective at transitioning individuals from low-productivity to high-productivity occupations.

We used to be a primarily agrarian economy in the 19th century. We transitioned successfully to manufacturing, which at some point was about 27 percent of our workforce, now it's below 10 percent. From there, we switched on to services. We absorbed women into the workforce in an effective way. We have highly effective labor markets, which is a competitive advantage when we're thinking about global competition.

At the very same time, it's not without a cost. And in a lot of ways, I do think that it can be a double-edged sword, because the competitiveness of our labor markets also implies, at least factually, that the relationships that we have between employer and employee tend to be less permanent than they are in other economies, and that implies that employers have less of an incentive to actually invest in employees. That may put us at a relative disadvantage compared to other countries that have longer relationships between employers and employees and can afford for actually employers to participate, to take part, whether it's through apprenticeships or training programs, in making sure that their workforce is ready for an AI transition. That, Jim, worries me. I think it's more than just making sure that individuals that may lose their job get reinstated in the workforce, it's really an economic strategic objective for us. Unless we take care of our workforce, we will find it exceedingly difficult to implement AI on an economy-wide basis.

Investing in employees (19:16)

While Washington isn't dictating data center construction, companies are investing heavily in this infrastructure. Shouldn't the same logic apply to workforce development? If understanding and working with AI technology is crucial for business survival, there's a strong private incentive to invest in employees' skills. This holds true even considering the unique structure of the American labor market compared to, say, Europe's.

Let me pause for a minute, take it back one step so that we can think about why is investment in worker training and vocational programs are so difficult? Why are they so challenging, and why do they perhaps create externalities, the way that we just discussed, more broadly? Why are they ultimately a strategic concern for the US economy? So look, these programs are exceptionally difficult to get right in an ordinary course of business. And we at Google have invested a tremendous amount of resources on these programs, which are not a core product for us. They're not even a monetizable product for us. And we're not the only ones. A lot of other tech companies have done the same, to be honest.

Now, what are the challenges with these programs? First and foremost, they have to be relevant and they have to provide education, skills, programs that are actually relevant, that keep up to date with the advancements in technology. That is something that's really difficult to do. You have to make sure that employers are actually buying in. We may have the best program, but unless it enables the individuals who graduated from the program to signal to employers that these are individuals with high qualifications because they went through a program, let's say at Google, the program is simply not going to work.

And then the third thing, think about it from the employee perspective: For an individual, it's not about giving somebody a pamphlet, “Hey, let's participate in this great program.” It's really about, can you take time off, at a tremendous opportunity cost of time with your family, career, and work, to invest in a serious program that would end up in an outcome which actually lands you at a better career, more stable job, that is better paid. Those are tremendously difficult in the ordinary course of business, let alone when we're going through a transition where we don't even know today how tasks and occupations will evolve. Now, as I mentioned, private tech firms, because of also market expertise and access to occupational data that is far better, in a lot of ways, than what the government data that we have on occupations are perfectly positioned to carry out those programs. The question is whether they can be actually carried out independently, unilaterally, without the collaboration of federal agencies, whether it’s local governments, state or federal, without the participation of employers, colleges and other institutions —

It sounds to me like employers will have to be part of this.

For sure. Jim, maybe let me just mention one thing that we don't want to do. We've been in this movie before. Following NAFTA (North American Free Trade Agreement), we had the trade adjustment programs where we invested a lot of money in rescaling and training employees, and the results were very minimal, at best. So I do think that this is the type of a grand challenge, if you will, that no single actor can really solve independently. And I know that we're naturally, as economists, we're naturally hesitant about government intervention, but what better role for a government can you think of other than identifying a market failure that is of strategic importance to the US economy, and in a thoughtful way, collaborating with other relevant constituents to come up with solutions that are effective. Scaling those programs to a national level is going to be a real challenge. And I do think that there's a role for governments to actually lead, in collaboration with other constituents, those efforts.

And of course you are aware of the sort of deep skepticism among people about these programs.

Yes.

So obviously we talk about innovation, technological innovation, we also need program innovation, education innovation here.

Jim, I’ve got to be perfectly honest here — and this is just my individual experience — as economists, I would be lying if I wouldn't say that I share that skepticism and concern. At the very same time, I think that we need to consider the other ramifications and what is truly an issue. We are at a certain disadvantage because of the lower incentives that our businesses have, our employers have, to invest in employees, and we see it. Apprenticeship programs is one example that is working phenomenally well in other places, but not in the US. So I do worry about that. In the paper, we didn't offer any descriptive solutions, but we really highlight the challenge here: How do we find market-based, thoughtful solutions to scaling and vocational programs so that our workforce can be ready for an AI transition?

Human-complimenting AI (25:29)

I'm skeptical of the idea that we can guide AI development through policy to ensure it complements rather than just automates human work. It's unclear what policy levers could effectively achieve this — tweaking the tax code seems unlikely to produce specific AI outcomes.

But where we can make a difference is in human capital development. If we want AI that complements human skills and enables new business creation, we need to ensure people understand this technology. Currently, many don't, given its novelty. Focusing on education and skill development seems a more practical approach to shaping AI's impact.

You know, Jim, it’s really interesting, so Chris Pissarides, the Nobel Prize winner from London School of Economics, has a phenomenal paper about this question. He comes up with a very interesting finding that countries that actually invest in right regulatory environments and legal standards, that have the right infrastructure, that have the right environment to foster innovation, ultimately witness less concerns about substitution because the technology that's being advanced tends to be more complimentary, and as an economist, that makes a lot of sense to me.

Let me pause for a minute and explain why: There is a genuine concern about whether AI is being deployed or used to substitute labor. And I think if you think about the Turing Trap that Eric Brynjolfsson has written about, this notion that you can come up with the most myopic, plug-and-play, cheapest AI application, put that in some individual function in your business, and replace existing work streams that are being done by humans, that is a genuine concern, particularly for firms that are looking for the highest rate of return, at the lowest cost, without really investing and transforming their business.

As an economist, I can understand why that happens, but keep in mind that when that happens, those businesses are actually really failing to leverage and capitalize on the full potential of the technology. They're really going for the plug-and-play, cheapest applications. That's not good for labor because it leads to substitution. But certainly that's not good to the business, itself. In a competitive market—and I think one thing that we need to stress is the importance of competition in our markets—you'd anticipate that firms that actually go through the effort to invest, to reform, to transform their businesses, to reinvent themselves, are the ones that will prevail.

And I would think that would be a very powerful lesson for other businesses if that is indeed the case, right?

Exactly. And the question is, how can we promote this broader, more meaningful, more valuable application and adoption of AI? And I think it goes back to the fundamentals: You need the AI infrastructure, the right legal institutions and regulatory standards, and ultimately a workforce that is ready to transform. And I think once you put those together, I do believe (and I’m deliberately saying belief, because I don't know that we can really study this explicitly) that that will lead to more complementarity and augmentation, and less substitution.

Historical precedent suggests that extreme job loss scenarios, like robots taking all jobs, are unlikely. While AI will undoubtedly cause disruption, do you believe it will follow the pattern of past technologies? That is, replacing some tasks, enhancing others, and creating entirely new job categories. Given the policies we've discussed, are you confident that this balanced outcome is achievable with AI, or do you have doubts?

Oh my God, that's a tough question, Jim. You saved it for last.

I'll add an addendum, I'll add a qualifier: within the next 20 years. I don't know what it'll look like in 100 years from now, but within our immediate lifetimes as workers, you and me.

Let me address it in this way. Yes, absolutely, I am, I want to say, cautiously optimistic, because if we learned one thing from the last century, a period of time that reflects the most advanced technological progress in human history, is that we didn't witness an increase in unemployment and we didn't witness a decline in labor participation. That leads me to be optimistic about the future of AI as well. Having said that — I think you alluded to this — history doesn't always repeat itself, and we've never faced a technology that can automate such a wide range of human tasks and activities. So that should be concerning for us. We also should mention that, even if AI does not lead to mass unemployment or to net loss of jobs, there will be significant occupational and sectoral shifts if we get this right, which I am optimistic about us doing so. So that will be something that we will need to consider as well. So I would say, optimistic: absolutely. Cautiously optimistic: that's probably more correct.

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Micro Reads

Business/ Economics

* Supreme Court curtails Chevron deference - The Verge

* Here’s What the Court’s Chevron Ruling Could Mean in Everyday Terms - The New York Times

* America’s Frozen Housing Market Is Warping the Economy - The Wall Street Journal

* Startup Silicon Box to Build $3.4 Billion Chip Plant in Italy - The Wall Street Journal

* Trump’s Economic Policies Could Hinder His Campaign - The Washington Post

Policy/Politics

* Chips Act Could Fail Without More Visas for Skilled Immigrants - Bloomberg

* House Privacy Talks Implode in Spectacular Fashion - The Washington Post

* Big Tech investors should be paying more attention to EU’s regulatory strikes - Financial Times

AI/Digital

* This Viral AI Chatbot Will Lie and Say It’s Human - Wired

* A New Method for Evaluating AI Models - arXiv

* OpenAI’s CriticGPT Outperforms Humans in Catching AI-Generated Code Bugs - Ars Technica

Biotech/Health

* To cure disease, AI needs more of our data - Financial Times

* Challenges in the Global Health Landscape - Nature

Clean Energy/Climate

* Solar Power’s Expansion and Food Production Are Compatible - Bloomberg

* Maldives’ Climate Change Challenges - The New York Times

* Innovations in Carbon Removal Technologies - Financial Times

* Carbon Removal’s Existential Question - Heatmap

Robotics/AVs

* A New Approach to Robot Navigation Using Camera and Feet - IEEE Spectrum

Space/Transportation

* SpaceX Valuation Reaches Record $210 Billion - Bloomberg

* Amazon Delays Launch of Project Kuiper Broadband Satellites - Bloomberg

Up Wing/Down Wing

* Secrets of 2000-Year-Old Antikythera Mechanism Revealed with Help from Gravitational Wave Technology - The Debrief

Substacks/Newsletters

* Is AI Going to Make Us Rich or Kill Us? - Economic Forces

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

The image of the skyscraper is the hallmark of the modern city. Futuristic depictions of urban landscapes nearly always feature towering structures high above the clouds. Today, however, developing countries seem to be putting the greatest effort into building the most impressive skyscrapers, from the Burj Khalifa in the UAE, to the future Jeddah Tower in Saudi Arabia. Whether you love them or hate them, it’s worth asking why we build skyscrapers and what their role will be in future cities. Today on Faster, Please! — The Podcast, I sit down with Jason Barr, author of Cities in the Sky: The Quest to Build the World’s Tallest Skyscrapers.

Barr is a professor of economics at Rutgers University – Newark, and is a member of the Rutgers Global Urban Systems PhD program. He is also the author of Building the Skyline: The Birth and Growth of Manhattan’s Skyscrapers.

In This Episode

* Demand for the skyscraper (1:35)

* The end of the skyscraper (9:00)

* Pillars of commerce (14:05)

* The sky’s the limit (18:36)

* Manhattan extension (23:04)

* Trends and styles (24:23)

Below is a lightly edited transcript of our conversation

The image of the skyscraper is the hallmark of the modern city. Futuristic depictions of urban landscapes nearly always feature towering structures high above the clouds. Today, however, developing countries seem to be putting the greatest effort into building the most impressive skyscrapers, from the Burj Khalifa in the UAE, to the future Jeddah Tower in Saudi Arabia. Whether you love them or hate them, it’s worth asking why we build skyscrapers and what their role will be in future cities. Today on Faster, Please! — The Podcast, I sit down with Jason Barr, author of Cities in the Sky: The Quest to Build the World’s Tallest Skyscrapers.

Barr is a professor of economics at Rutgers University – Newark, and is a member of the Rutgers Global Urban Systems PhD program. He is also the author of Building the Skyline: The Birth and Growth of Manhattan’s Skyscrapers.

Demand for the skyscraper (1:35)

Pethokoukis: You obviously love skyscrapers, you're fascinated by them. You wrote a whole book on them. So I want to just start the very basic question: Why do skyscrapers fascinate you, and the people who aren't fascinated by them, what are they missing?

Barr: Great questions. Well, I grew up on Long Island, and so I was always really fascinated with Manhattan. I grew up in the ’70s, and so New York back then was a very dark, mysterious place for a youngster. So when I grew up, actually when I was in college, I started hanging out in the city. So to me, the skyline of Manhattan and New York City, they're just two sides of the same coin. I really developed an interest in tall buildings through my interest and fascination with Manhattan’s and New York City's history.

So when I came to Rutgers Newark, I just started doing research on tall buildings, especially in New York City: what was driving the heights of these buildings; there's all these interesting height cycles over the last 150 years. So I wrote my first book on the Manhattan skyline, that was called Building the Skyline, and then after that I thought, let's see what's happening around the rest of the world. So to me, the tall building is an interesting thing because it's part and parcel with urbanization, and I just personally don't think you could have one without the other.

I think some people might think that skyscrapers are, at least for rich countries, that they're kind of a 20th-century thing that we did as we were growing, and cities were getting bigger, and skyscrapers are a part of that, but now they're for other parts of the world, parts of the world which are still urbanizing, which are still getting richer. Are skyscrapers are still a thing for America?

The short answer is yes, but, given how dense cities are, tall buildings are just being added a lot more slowly. In New York, the population's kind of slowly growing, and so tall buildings are either replacing old buildings that are wearing out, or there's always this push by big global corporations to be in the newest and latest tall building. And obviously there's this international demand from people abroad to have an apartment — or national demand — global demand to have some kind of residential presence in New York. But the thing is, people in other countries: cities, planners, residents in other countries, they look to New York, they look to Chicago, and I think, for many of them, they see New York as something they want to emulate, and New York is, on just about almost any metric, it's probably the top global city. And so I think cities today, especially in China, and Asia more broadly, they're trying to kind of replicate that, what you might call “the Manhattan magic,” and I don't really think people in this country realize how much tall building construction is going on in other cities around the world. People in this country are a little bit more cynical about the role of the tall building in urban growth and in housing affordability and stuff like this, but other cities are basically going gangbusters, is a way to put it.

Is that driven by fundamental economic forces? Is it kind of a “national greatness” kinds of signaling projects? Are there fundamental reasons, not just to build skyscrapers, but to build very, very tall skyscrapers?

“All of the above” is the answer. Fundamentally, if there's many, many people who want to be working, living, playing in the center, the only way to accommodate the demand to be in the center is to make more land in the center, so the skyscraper, at its heart, is what I would say is “land in the sky.” You just go vertical because there's constraints on how much land there is in the center.

Having said that, definitely the skyscraper is seen as a kind of way to advertise, a way to increase confidence in the place, and so you boost foreign direct investment. Observatories are huge money makers, there’s a big tourism component. A lot of critics will say, “Oh, it's all about spectacle and ego.” But really, for the book, and just more broadly my research, when you drill down on the economics of these super tall buildings, not all of them are profitable or profit-maximizing, but they all have a strong economic rationale.

Now, I just also want to say, China has its own thing going on, which sort of compounds the skyscraper construction-building there because of their unique governance structure and land ownership structure, but China is building tall buildings because, at the end of the day, there's a kind of, what I call, a “tall building bling.” There's just something that says, “This city is growing, this city is drawing population.” So we build a tall building and we boost confidence in the city. And it works, really.

The pictures don't have to be too old, if you look at a picture of Shanghai, it looks a lot different not too long ago. It's almost as if a whole other city just kind of fell from the sky, a city of skyscrapers, and where there were once goats or something grazing, there's now a bunch of massive skyscrapers.

Yeah, absolutely, and there's a few reasons for this. One is, I think Chinese residents more broadly see tall building as a natural way to live. I've talked to many Chinese residents, whether it's Shanghai or other cities, and to them, to own an apartment in the sky is like the greatest thing. It's their equivalent of the single family home in the United States. Living in the clouds is something many people aspire to. The other aspect of it is, Shanghai, and the Pudong neighborhood in Shanghai, was chosen basically to become a financial hub. Basically, the leaders were looking at Hong Kong and they thought it was a, to quote, I forgot the author, but to quote him in the book, the Shanghai officials and the National Party officials saw Hong Kong as that frustratingly free city, and so they wanted to create a kind of a financial hub in Shanghai. And so the Shanghai Tower, for example, is part of that plan to really draw people's attention to Shanghai, itself. So it was part of a master plan.

The end of the skyscraper (9:00)

I certainly remember that, after 9/11, I heard about “the end of the skyscraper,” and then during the pandemic, I heard about “the end of the city.” Now I'm guessing that cities will continue to exist and we're going to continue to build tall buildings.

Absolutely. What 9/11 did was just make sure that we make our building safer with fire protection measures. In many Asian countries, every 20 floors, let's say, are mechanical floors, so you have the electric equipment, and the heating, and the cooling, and water tanks. They can also surround these in concrete, and so if something's on fire, if a floor is on fire, they can go to this hermetically sealed floor, a refuge floor, and stay there and be protected. And the elevator cores, they're made of concrete, and so you wouldn't have something like what happened on 9/11. So it didn't really impact the demand; 9/11 didn't impact the demand for the tall building, it just made us make tall buildings safer. And of course the downside is if you want to go into an office building, you have to have a swipe and you have to have an entry, so the negative of 9/11 was more about heightened security and increasing protections in a way that engenders a little bit more mistrust of us. But the demand didn't go away.

Same thing with Covid. For big cities like New York and San Francisco, I'm sure the empty-office problem is going to dissipate. It'll take a while. This may be an overly broad statement, but the truth is, our present and future is in cities. The funny thing about the internet and social media and all that, it was supposed to allow us to suburbanize more, or run away from these big, overcrowded cities, but the truth is, social media and internet technology has just made cities even more important. So, as long as cities are growing, there'll be a demand for tall buildings

Of the tallest, I don't know, half-dozen buildings, have you been to all of them?

That's a good question. I've been to the Shanghai Tower, which was the second-tallest building in the world, now is the third-tallest. The one that replaced it, I think it's [Merdeka 118] in Kuala Lumpur, I believe. I didn't go to that one yet because that just opened up recently. I've been to the Burj Khalifa, which is the world's tallest building. I'd have to look at the list. I've been to the Sears Tower, Empire State Building . . . Anyway, so I've been to a handful of them. I can't say I've been to every single one of the super-tall buildings in the world

And in any of those super-tall buildings, can you open a window? Why can't you open the windows in these skyscrapers?

Well, the wind forces are just tremendous! The biggest problem engineering tall buildings is making sure that the building doesn't sway so that people feel it. The really fascinating thing about engineering tall buildings is this question: How do you allow the building to sway enough so that you don't have to — you don’t want to over-engineer a building so that you make it perfectly stiff because that's just completely uneconomic to do that, but you want to make sure the building sways just enough so if you're sitting there reading a newspaper or drinking a cup of coffee on the top floor, you don't feel it. And so the wind forces high, a thousand feet in the air, are just so tremendous. I think if you open the window, everything would just would just blow away.

I was thinking about some of those very, super-skinny residential buildings, which I guess seem to be becoming more popular, and do those people really feel the motion?

From what I can tell, the short answer is no. There's one lawsuit in Manhattan, in particular, where the engineering wasn't exactly perfectly right, but I think that represents the exception that proves the rule. The building is safe, that's not the problem, it's just that, when you're dealing with these super-skinny buildings — these are kind of a new kind of breed of super-tall buildings, so sometimes the engineering isn't perfectly right, so they will figure out ways to kind of fix those problems. The problems are solvable, but sometimes if you don't get it 100 percent right, people complain, and obviously there's lawsuits and you have to go back in and tweak the engineering. But these things are selling for 70, 80, 100 million dollars for a penthouse on the 90th floor, so people still value them, and if motion sickness was a problem, they'd be worthless.

Pillars of commerce (14:05)

In the book, you run through a number of myths: tall buildings being only for the rich, that they drive up housing prices in cities, again, that you mentioned a little bit earlier, that they're somehow bad economic deals. All these myths all tend to be very negative.

I'm not going to rename your book, but I could call it “Cathedrals in the Sky,” I mean, I think these are beautiful buildings that say a lot about human aspiration and to create a sense of awe. Boy, but some people just do not see it that way.

I think there's a few strands; I've been thinking about this. There's a kind of a NIMBY strand, and sort of a NIMBY/gentrification strand. So people in the middle income, let's say, they see their housing prices going up, their rent going up, and then they see these billionaire condos, and so they, in my opinion, or based on my research, there's a confusion of correlation and causation. So the most visible manifestation in people's minds of gentrification and affordability problems are the super-slim buildings, but New York City has something like 3.6 million housing units, and if you look at the outlying areas of Queens and Staten Island, they're just covered in one- and two-family homes. Those neighborhoods have added barely any housing. So all of the housing — I'm exaggerating here when I say the word “all,” but the vast majority of new housing units happens in the center where either the zoning is more permissive, or old industrial sites come online and things like this, so people don't realize that the problem of housing affordability is citywide, it just looks naturally to be in their neighborhood where high rises are going up.

Then there's another strand, which I would say is kind of the “Jane Jacobs strand” / the anti-public-housing strand. Jane Jacobs has some great points in her book, The Death and Life of Great American Cities about walkability, about eyes on the street. She wasn't a big fan of tall buildings, and this has kind of given rise to this whole movement of “human scale,” where five-story Greenwich Village buildings, or 10-story Parisian mansard-roof-type buildings are perfect, and any other deviation from that is somehow destroying the city. So there's that part of it, that people see tall buildings as somehow destroying the feel or the perfect fabric of the city. And lastly, obviously, some of the failures with the public housing policy has made people convinced that it's unhealthy to live in these tall buildings. I think that gets at what you're inquiring about. I think there's those different strains.

I wonder if part of it stems for a confusion about what are cities for, and I mean cities are, for a large part, are where people to come together for jobs and to conduct commerce. And if you think of them that way, then certain things make sense; but if you think of them as, I don't know, some sort of urban retreat, where it's kind of like a garden or . . . I don't know, but it's a very different view, and perhaps it is not just about bike paths, but it's about what facilitates people to connect.

Without jobs, without a labor market, there's no purpose to have a city. Maybe in the 18th or 19th century, you can create a city for the king or the empire, as are many examples, or the Vatican or something like this; so you can have these sort of political capital cities, or even Washington DC, but, fundamentally, 99 percent of the world’s cities are places where people go to work, and so, if you don't allow the labor market to function properly, which means having a functioning housing market, then all these ideas about “the good city” and “the perfectly crafted city,” they kind of are irrelevant.

So you have to start with: what makes a city grow, what makes people productive, and then how do we accommodate that? To the extent that we can improve design, all the better. There's always a million ways to make things better for people design-wise. I think bike lanes are great, and I think pedestrian-friendly cities are better than car-centric cities, but you can't start with designing the city first and then seeing what happens. You have to start with “let's make an attractive place to live and work” first, and then work on the design feature second.

The sky’s the limit (18:36)

How tall are these buildings going to get?

Okay, well, the next world's tallest building is going to be one kilometer: The Jeddah Tower, which had started, I think back in 2013 or 2015, had been stalled, there was some sort of political turmoil in Saudi Arabia, and they've just restarted this Jeddah Tower in the city of Jeddah. And so when that's completed, that's going to be one kilometer. There were some plans floated to have a two-kilometer building in Riyadh. I don't think anyone really thinks that's going to happen.

How long does it take to get up to your office in a two-kilometer building?

Well, that's the thing. They're coming up with new ways to get people up there faster. The old conventional steel cables could maybe go 500 meters or something like that, which is maybe 80 floors or something. Maybe if you had a really good cable, you can get people to 80 floors and then they'd have to switch. Now they have these composite . . . it’s KONE UltraRope, which could go 1000 meters, which could go basically one kilometer continuously. So if you can get people from the ground floor to wherever their destination is within a minute, that's kind of like the golden rule here. People are not willing to wait more than a minute once they get in the elevator. The trick really is the ear pressure, and that's probably the hardest part because you're going up so quickly, the air pressure changes, so you have to figure out ways to make sure the cabin remains pressurized, and then there's the air pressure up on the highest floors. So that, I would argue, is the fundamental issue that's going to be coming next on the horizon is how to efficiently pressurize the highest floors. Let's say you're a mile high; if you're a mile high on the top floor, that's the equivalent of going from New York to Denver in a minute, or two minutes. So you have to figure out a way how to pressurize the entire building so it has a constant air pressure.

If I were to look at the skyline of major American cities 50 years from now, would you expect them to be radically different, futuristic looking, maybe not two-kilometer buildings, but a lot of very, very tall buildings? Or is it again, if they're not growing, if population isn't growing, then that won’t happen?

People are always asking me what I think about the doom loops and all that. Pick New York as one end of the spectrum: It's always going to be adding new buildings, that's just in its DNA, and so you're going to have this kind of collage of different building styles. But other cities, smaller cities, maybe where people are moving now because working from home, they'll add a few tall buildings here, they'll have mini-skylines. Then the other cities, like a St. Louis, that's just going to have to kind of figure out a plan for growth. So I don't see the world as a kind of Jetsons-type world.

I mean, you never know what's going to happen with the technology. There’s one company, TK or Thyssenkrupp elevators, they're working on Maglev elevators, and this can actually be a game changer because you have these shafts, so the Maglev elevator cars, they can go up or down or they can go horizontal. Part of the goal with that is that everybody has their own — if it's an apartment building, they have their own elevator car, it takes them up to their apartment, it becomes the door. So that could be a real game changer . . . And then you could run these things horizontally. So if you have these Maglev elevators, you can not only run them horizontally within the building, but, in principle, if you could work out property rights or whatever, you could connect these things across buildings. But at the end of the day, it's really about preferences and a kind of cultural perception of the tall building, and I just don't see us in the United States us having a dramatic, country-wide rethinking of where we live. There's always going to be this desire for the single-family home in the suburbs. Now maybe that'll diminish to some degree, but as long as people see their own little house as their own little castle . . .

Unlike China, where there seems to be a great desire to live in these kinds of buildings.

Manhattan extension (23:04)

Have you had any takers about your proposal to make Manhattan bigger?

No.

You would extend it by about 2000 acres and maybe build some tall buildings on that, I don't know.

The idea would be to create a new mini-Manhattan extending Manhattan into New York Harbor. Just briefly, the idea was both to add more housing and add more land, and to protect lower Manhattan against sea level rises and so forth. I proposed this in a New York Times op-ed piece, and, naturally, I would say the majority of commenters and people had this sort of kneejerk reaction against it.

I had a kneejerk reaction for it! I loved it!

You are part of a small, select core of appreciators, let's say. Having said that, in the 21st century it’s just not something I think most people are willing to wrap their heads around. So

To me, that's an idea with the future, and I think you should not be dejected that it was not initially well-received. I think that kind of idea might actually have some legs.

Trends and styles (24:23)

Finally, let me ask you, whether it's because of computers or new materials, would we expect skyscrapers in the future to look any differently? I think some people would love to go back to the 1930s style. They love that style of skyscraper, and they don't like the glass-and-steel, very rectangular skyscraper; they want it to look like Gotham City or something.

Actually, if you look in Manhattan, in Brooklyn there's one, I think they're calling it something like the “Dark Knight Tower” or the “Gotham Tower.” It's in Brooklyn and it has this almost art deco sort of —

It slipped my mind, I was thinking art deco, yes.

And there's a high rise apartment near Columbia University, which uses the same color masonry as the surrounding buildings. I think it's the Union Theological Seminary, which sold some of the land to build a high rise. It sort of blends in. So I guess the question is really architecturally speaking, and it's sort of hard to say. I think maybe there'll be some neo-historical buildings coming up here or there, but there's two things: One is that people like glass windows. People love to have light and views, and so that's really just pushing the glass buildings. I think developers like glass too, because it's easy to work with, and architects — if you're a developer and you want a super-tall building, you usually go to a handful of architects and you have some kind of design competition, and, chances are, you're going to get something that looks full of glass and has some funky geometry to it.

But they seem more twisty than they used to, so they're not just perfect rectangles.

Right, so you're creating a lot of illusion. The interesting thing is, at the end of the day, you can only have certain internal shapes because you need functional spaces, so you have to have illusion with the twisting and these sort of Jenga towers, and a lot of that is due to massive improvements in computer technology; so the rendering software has dramatically improved, the engineering know-how, the engineering technology improved, you can send your designs right to the manufacturer where they can then use the computer programs to design exactly the shapes and sizes.

So it's the learning curve of every building that you do adds to the knowledge of how to do something a little bit different, or some version of something before, and also just massive computer power. I think there'll be a lot more of these sort of funky architectural shape. How they hold up, only time tells. In the ’80s there was this massive postmodern boom with all kinds of pastiche-type buildings with all kinds of references to old buildings, and funky buildings, and some of those haven't held up as well.

Frankly, I'm from Chicago, and I know exactly what you're talking about. Also being from Chicago, I appreciate you calling that building the Sears Tower rather than what other name they try to put on it. Last question: Do you have a favorite skyscraper?

I’m from New York and I like the Empire State Building, and it's not just because architecturally a classic building, but it speaks to New York as a city of strivers. And the more research I did into the Empire State Building, the more I appreciate the sheer guts of these guys who built this building. And the thing is, when it was completed in 1931, Great Depression was really starting to kick into high gear, and so the building was unrented, and it kind of gave this whole mythology about how these guys didn't know what they were doing, but when you crunch the numbers, they knew exactly what they were doing. They knew what the landscape looked like for New York, and the costs, and the revenues. Nobody saw the Great Depression coming, and so to say that the Great Depression showed how foolish these were, I just think it's a bad standard to hold them to. And if you look at the revenues and them building value over its 90-whatever, 93-year history, it's been a money-maker for almost a century. After the Great Depression, it recovered and has become an icon and a moneymaker, so what's not to love about that?

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The media is full of dystopian depictions of artificial intelligence, such as The Terminator and The Matrix, yet few have dared to dream up the image of an AI utopia. Nick Bostrom’s most recent book, Deep Utopia: Life and Meaning in a Solved World attempts to do exactly that. Bostrom explores what it would mean to live in a post-work world, where human labor is vastly outperformed by AI, or even made obsolete. When all of our problems have been solved in an AI utopia . . . well, what’s next for us humans?

Bostrom is a philosopher and was founding director of the Future of Humanity Institute at Oxford University. He is currently the founder and director of research at the Macrostrategy Research Initiative. He also wrote the much-discussed 2014 book, Superintelligence: Paths, Dangers, Strategies.

In This Episode

* Our dystopian predisposition (1:29)

* A utopian thought experiment (5:16)

* The plausibility of a solved world (12:53)

* Weighing the risks (20:17)

Below is a lightly edited transcript of our conversation

Our dystopian predisposition (1:29)

Pethokoukis: The Dutch futurist, Frederik Polak famously put it that any culture without a positive vision of the future has no future. It's a light paraphrase. And I kind of think that's where we are right now, that despite the title of your book, I feel like right now people can only imagine dystopia. Is that what you think? Do I have that wrong?

Bostrom: It's easier to imagine dystopia. I think we are all familiar with a bunch of dystopian works of fiction. The average person could rattle off Brave New World, 1984, The Handmaid's Tale. Most people couldn't probably name a single utopian work, and even the attempts that have been made, if you look closely at them, you probably wouldn't actually want to live there. It is an interesting fact that it seems easier for us to imagine ways in which things could be worse than ways in which things could be better. Maybe some culture that doesn't have a positive vision has no future but, then again, cultures that have had positive visions also often have ended in tears. A lot of the times utopian blueprints have been used as excuses for imposing coercively some highly destructive vision on society. So you could argue either way whether it is actually beneficial for societies to have a super clear, long-term vision that they are staring towards.

I think if we were to ask people to give a dystopian vision, we would get probably some very picturesque, highly detailed visions from having sort of marinated in science fiction for decades. But then if you asked people about utopia, I wonder if all their visions would be almost alike: Kind of this clean, green world, with maybe some tall skyscrapers or something, and people generally getting along. I think it'd be a fairly bland, unimaginative vision.

That would be the idea of “all happy families are alike, but each unhappy family is unhappy in its own unique way.” I think it's easy enough to enable ways in which the world could be slightly better than it is. So imagine a world exactly like the one we have, except minus childhood leukemia. So everybody would agree that definitely seems better. The problem is if you start to add these improvements and you stack on enough of them, then eventually you face a much more philosophically challenging proposition, which is, if you remove all the difficulties and all the shadows of human life, all forms of suffering and inconvenience, and all injustice and everything, then you risk ending up in this rather bland future where there is no challenge, no purpose, no meaning for us humans, and it then almost becomes utopian again, but in a different way. Maybe all our basic needs are catered to, but there seems to be then some other part missing that is important for humans to have flourishing lives.

A utopian thought experiment (5:16)

Is your book a forecast or is it a thought experiment?

It's much more a thought experiment. As it happens, I think there is a non-trivial chance we will actually end up in this condition, I call it a “solved world,” particularly with the impending transition to the machine intelligence era, which I think will be accompanied by significant risks, including existential risk. In my previous book, Superintelligence, which came out in 2014, focused on what could go wrong when we are developing machine super intelligence, but if things go right—and this could unfold within the lifetime of a lot of us who are alive on this planet today—if things go right, they could go very right, and, in particular, all kinds of problems that could be solved with better technology could be solved in this future where you have superintelligent AIs doing the technological development. And we might then actually confront the situation where these questions we can now explore as a thought experiment would become pressing practical questions where we would actually have to make decisions on what kinds of lives we want to live, what kind of future we want to create for ourselves if all these instrumental limitations were removed that currently constrain the choices set that we face.

I imagine the book would seem almost purely a thought experiment before November 2022 when ChatGPT was rolled out by OpenAI, and now, to some people, it seems like these are questions certainly worth pondering. You talked about the impending machine superintelligence—how impending do you think, and what is your confidence level? Certainly we have technologists all over the map speaking about the likelihood of reaching that maybe through large language models, other people think they can't quite get us there, so how much work is “impending” doing in that sentence?

I don't think we are in a position any longer to rule out even extremely short timelines. We can't be super confident that we might not have an intelligence explosion next year. It could take longer, it could take several years, it could take a decade or longer. We have to think in terms of smeared out probability distributions here, but we don't really know what capabilities will be unlocked as you scale up even the current architectures one more order of magnitude like GPT-5-level or GPT-6-level. It might be that, just as the previous steps from GPT-2 to GPT-3 and 3 to 4 sort of unlocked almost qualitatively new capabilities, the same might hold as we keep going up this ladder of just scaling up the current architectures, and so we are now in a condition where it could happen at any time, basically. It doesn't mean it will happen very soon, but we can't be confident that it won't.

I do think it is slightly easier for people maybe now, even just with looking at the current AI systems, we have to take these questions seriously, and I think it will become a lot easier as the penny starts to drop that we're about to see this big transition to the machine intelligence era. The previous book, Superintelligence, back in 2014 when that was published—and it was in the works for six years prior—at that time, what was completely outside the Overton window was even the idea that one day we would have machine superintelligence, and, in particular, the idea that there would then be an alignment problem, a technical difficulty of steering these superintelligent intellects so that they would actually do what we want. It was completely neglected by academia. People thought, that’s just science fiction or idle futurism. There were maybe a handful of people on the internet who were starting to think about that. In the intervening 10 years, that has changed, and so now all the frontier AI labs have research teams specifically trying to work on scalable methods for AI alignment, and it's much more widely recognized over the last couple of years that this will be a transformative thing. You have statements coming out from leading policy makers from the White House, the UK had this global summit on AI, and so this alignment problem and the risks related to AI have sort of entered the Overton window, and I think some of these other issues as to what the world will look like if we succeed, similarly, will have to come inside the Overton window, and probably will do so over the next few years.

So we have an Overton window, we have this technological advance with machine intelligence. Are you as confident about one of the other pillars of your thought experiment, which is an equally, what might seem science-futuristic advance in our ability to edit ourselves, to modify ourselves and our brains and our emotions. That seems to hand-in-hand with the thought experiment.

I think once we develop machine superintelligence, then we will soon thereafter have tremendous advances in other technological areas as well because we would then not be restricted to humans trying to develop new technologies with our biological brains. But this research and development would be done by superintelligences on digital timescales rather than biological timescales. So the transition to superintelligence would, I think, mean a kind of telescoping of the future.

So there are all these technologies we can see are, in principle, possible. They don't violate the law of physics. In the fullness of time, probably human civilization would reach them if we had 10,000 years to work on it, all these science fiction like space colonies, or cures for aging, or perfect virtual reality uploading into computers, we could see how we might eventually . . . They're unrealistic given the current state of technology, but there's no (in principle) barriers, so we could imagine developing those if we had thousands of years to work on them. But all those technologies might become available quite soon after you have superintelligence doing the research and development. So I think we will then start to approximate the condition of technological maturity, like a condition where we have already developed most of those general purpose technologies that are physically possible, and for which there exists some in principally feasible pathway from where we are now to developing them.

 The plausibility of a solved world (12:53)

I know one criticism of the book is, with this notion of a “solved world” or technological maturity, that the combinatorial nature of ideas would allow for almost an unlimited number of new possibilities, so in no way could we reach maturity or a technologically solved state of things. Is that a valid criticism?

Well, it is a hypothesis you could entertain that there is an infinite number of ever-higher levels of technological capability such that you'd never be able to reach or even approximate any maximum. I think it's more likely that there will eventually be diminishing returns. You will eventually have figured out the best way to do most of the general things that need doing: communicating information, processing information, processing raw materials, creating various physical structures, et cetera, et cetera. That happens to be my best guess, but in any case, you could bracket that, we could at least establish lower bounds on the kinds of technological capabilities that an advanced civilization with superintelligence would be able to develop, and we can list out a number of those technologies. Maybe it would be able to do more than that, but at least it would be able to do various things that we can already sort of see and outline how you could do, it's just we can't quite put all the pieces together and carry it out yet.

And the book lists a bunch of these affordances that a technologically mature civilization would at least have, even if maybe there would be further things we haven't even dreamt of yet. And already that set of technological capabilities would be enough to radically transform the human condition, and indeed to present us with some of these basic philosophical challenges of how to live well in this world where we wouldn't only have a huge amount of control over the external reality, we wouldn't only be able to automate human labor across almost all domains, but we would also, as you alluded to earlier, have unprecedented levels of control over ourselves or our biological organism and our minds using various forms of bio technologies or newer technologies.

In this kind of scenario, is the purpose of our machines to solve our problems, or, not give us problems, but give us challenges, give us things to do?

It then comes down to questions about value. If we had all of these capabilities to achieve various types of worlds, which one would we actually want? And I think there are layers to this onion, different levels of depth at which one can approach and think about this problem. At the outermost layer you have the idea that, well, we will have increased automation as a result of advances in AI and robotics, and so there will be some humans who become unemployed as a result. At the most superficial layer of analysis, you would then think, “Well some jobs become unnecessary, so you need to maybe retrain workers to move to other areas where there is continued demand for human labor. Maybe they need some support whilst they're retraining and stuff like that.”

So then you take it a step further, like you peel off another layer of the onion and you realize that, well, if AI truly succeeds, if you have artificial general intelligence, then it's really not just some areas of human economic contribution that gets affected, but all areas, with a few exceptions that we can return to. But AIs could do everything that we can do, and do it better, and cheaper, and more efficiently. And you could say that the goal of AI is full unemployment. The goal is not just to automate a few particular tasks, but to develop a technology that allows us to automate all tasks. That's kind of what AI has always been about; it's not succeeded yet, but that's the goal, and we are seemingly moving closer to that. And so, with the asterisk here that there are a few exceptions that we can zoom in on, you would then get a kind of post-work condition where there would be no need for human labor at all.

My baseline—I think this is a reasonable baseline—is that the history of technology is a history of both automating things, but then creating new things for us to do. So I think if you ask just about any economist, they will say that that should be our guide for the future: that this exact same technology will think of new things for people to do, that we, at least up to this point, have shown infinite creativity in creating new things to do, and whether you want to call those “work,” there's certainly things for us to do, so boredom should not be an issue.

So there's a further question of whether there is anything for us to do, but if we just look at the work part first, are there ways for humans to engage in economically productive labor? And, so far, what has been the case is that various specific tasks have been automated, and so instead of having people digging ditches using their muscles, we can have bulldozers digging ditches, and you could have one guy driving the bulldozer and do the work of 50 people with a shovel or something. And so human labor is kind of just moving out of the areas where you can automate it and into other areas where we haven't yet been able to automate it. But if AIs are able to do all the things that we can do, then that would be no further place, it would look like, at least at first sight, for human workers to move into. The exceptions to this, I think, are cases were the consumer cares not just about the product, but about how the product

They want that human element.

You could have consumers with just a raw preference that a particular task was performed by humans or a particular product—just as now sometimes consumers play a little premium sometimes if a little gadget was produced by a politically favored group, or maybe handcrafted by indigenous people, we may pay more for it than if the same object was made in a sweatshop in Indonesia or something. Even if the actual physical object itself is equally good in both cases, we might care about the causal process that brought it into existence. So to the extent that consumers have those kinds of preferences, there could remain ineliminable demand for human labor, even at technological maturity. You could think of possible examples: Maybe we just prefer to watch human athletes compete, even if robots could run faster or box harder. Maybe you want a human priest to officiate at your wedding, even if the robot could say the same words with the same intonations and the same gestures, et cetera. So there could be niches of that sort, where there would remain demand for human labor no matter how advanced our technology.

Weighing the risks (20:17)

Let me read one friendly critique from Robin Hanson of the book:

Bostrom asks how creatures very much like him might want to live for eons if they had total peace, vast wealth, and full eternal control of extremely competent AI that could do everything better than they. He . . . tries to list as many sensible possibilities as possible . . .

But I found it . . . hard to be motivated by his key question. In the future of creatures vastly more capable than us I'm far more interested in what those better creatures would do than what a creature like me now might do there. And I find the idea of creatures like me being rich, at peace, and in full control of such a world quite unlikely.

Is the question he would prefer you answer unanswerable, therefore you cannot answer that question, so the only question you can answer is what people like us would be like?

No, I think there are several different questions, each of which, I think, is interesting. In some of my other work, I do, in fact, investigate what other creatures, non-human creatures, digital minds we might be building, for example, AIs of different types, what they might want and how one might think of what would be required for the future to go well for these new types of being that we might be introducing. I think that's an extremely important question as well, particularly from a moral point of view. It might be, in the future, most inhabitants of the future will be digital minds or AIs of different kinds. Some might be at scales far larger than us human beings.

In this book, though, I think the question I'm primarily interested in is: What if we are interested in it from our own perspective, what is the best possible future we could hope for for ourselves, given the values that we actually have? And I think that could be practically relevant in various ways. There could, for example, arise situations where we have to make trade-offs between delaying the transition to AI with maybe the risk going up or down, depending on how long we take for it. And then, in the meantime, people like us dying, just as a result of aging and disease and all kinds of things that currently result in people.

So what are the different risk tradeoffs we are willing to take? And that might depend, in part, on how much better we think our lives could be if this goes well. If the best we could hope for was just continuing our current lives for a bit longer, that might be a different choice situation than if there was actually on the table something that would be super desirable from our current point of view, then we might be willing to take bigger risks to our current lives if there was at least some chance of achieving this much better life. And I think those questions, from a prudential point of view, we can only try to answer if we have some conception of how good the potential outcome would be for us. But I agree with him that both of these questions are important.

It also seems to me that, initially, there was a lot of conversation after the rollout of ChatGPT about existential risk, we were talking about an AI pause, and I feel like the pendulum has swung completely to the other side, that, whether it's due to people not wanting to miss out on all the good stuff that AI could create, or worried about Chinese AI beating American AI, that the default mode that we're in right now is full speed ahead, and if there are problems we'll just have to fix them on the fly, but we're just not going to have any substantial way to regulate this technology, other than, perhaps,   the most superficial of guardrails. I feel like that's where we're at now; at least, that's what I feel like in Washington right now.

Yeah, I think that has been the default mode of AI development since its inception, and still is today, predominantly. The difficulties are actually to get the machines to do more, rather than how to limit what they're allowed to do. That is still the main thrust. I do think, though, that the first derivative of this is towards increased support for various kinds of regulations and restrictions, and even a growing number of people calling for an “AI pause” or wanting to stop AI development altogether. This used to be basically a completely fringe . . . there were no real serious efforts to push in this direction for almost all decades of AI up until maybe two years ago or so. And since then there has been an increasingly vocal, still minority, but a set of people who are trying hard to push for increased regulation, and for slowing down, and for raising the alarm of AI developments. And I think it remains an open question how this will unfold over the coming years.

I have a complex view on this, what would actually be desirable here. On the one hand, I do think there are these significant risks, including existential risks, that will accompany a transition. When we develop superintelligent machines, it's not just one cool more gadget, right? It's the most important thing ever happening in human history, and they will be to us as we are to chimpanzees or something—potentially a very powerful force, and things could go wrong there. So I do agree with the C.

So I've been told over the past two years!

And to the point where some people think of me as a kind of doomsayer or anti-AI, but that's not the full picture. I think, ultimately, it would be a catastrophe if superintelligence was never developed, and that we should develop this, ideally carefully, and it might be desirable if, at a critical point, just when we figure out how to make machines superintelligent, whoever is doing this, whether it's some private lab, or some government Manhattan Project, whoever it is, has the ability to go a little bit slow in that, maybe to pause for six months or, rather than immediately cranking all the knobs up to 11, maybe do it incrementally, see what happens, make sure the safety mechanisms work. I think that might be more ideal than a situation where you have, say, 15 different labs all racing together first, and whoever takes any extra precautions just immediately fall behind and become irrelevant. I think that would seem . . .

I feel like where we're at right now—I may have answered this differently 18 months ago—but I feel like where we're at right now is that second scenario. At least here in the United States, and maybe I'm too Washington-centric, but I feel we're at the “crank it up to 11,” realistically, phase.

Well, we have seen the first-ever real AI regulations coming on board. It's something rather than nothing, and so you could easily imagine, if pressure continues to build, there will be more demand for this, and then, if you have some actual adverse event, like some bad thing happening, then who knows? There are other technologies that have been stymied because of . . . like human cloning, for example, or nuclear energy in many countries. So it's not unprecedented that society could convince itself that it's bad. So far, historically, all these technology bans and relinquishments have probably been temporary because there have been other societies making other choices, and eventually, just like each generation is, to some extent, like a new role of the die, and eventually you get . . .

But it might be that we already have, in particular with AI technologies that, if fully deployed, could allow a society in a few years to lock itself in to some sort of permanent orthodoxy. If you imagine deploying even current AI systems fully to censor dissenting information—if you had some huge stigmatization of AI where it becomes just taboo to say anything positive about AI, and then very efficient ways of enforcing that orthodoxy by shadow banning people who dissent from it, or canceling them, or you could imagine surveilling anybody not to do any research on AI like that, the technology to sort of freeze in a temporary social consensus might be emerging. And so if 10 years from now there were a strong global consensus of some of these issues, then we can't rule out that that would become literally permanent. My probably optimal level of government oversight and regulation would be more than we currently have, but I do worry a little bit about it not increasing to the optimal point and then stopping there, but once the avalanche starts rolling, it could overshoot the target and result in a problem. To be clear, I still think that's unlikely, but I think it's more likely than it was two years ago.

In 2050, do you feel like we'll be on the road to deep utopia or deep dystopia?

I hope the former, I think both are still in the cards for what we know. There are big forces at play here. We've never had machine intelligence transition before. We don't have the kind of social or economic predictive science that really allows us to say what will happen to political dynamics as we change these fundamental parameters of the human condition. We don't yet have a fully reliable solution to the problem of scalable alignment. I think we are entering uncharted territories here, and both extremely good and extremely bad outcomes are possible, and we are a bit in the dark as to how all of this will unfold.

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While AI doomers proselytize their catastrophic message, many politicians are recognizing that the loss of America’s competitive edge poses a much more real threat than the supposed “existential risk” of AI. Today on Faster, Please!—The Podcast, I talk with Adam Thierer about the current state of the AI policy landscape and the accompanying fierce regulatory debate.

Thierer is a senior fellow at the R Street Institute, where he promotes greater freedom for innovation and entrepreneurship. Prior to R Street, he worked as a senior fellow at the Mercatus Center at George Mason University, president of the Progress and Freedom Foundation, and at the Adam Smith Institute, Heritage Foundation, and Cato Institute.

In This Episode

* A changing approach (1:09)

* The global AI race (7:26)

* The political economy of AI (10:24)

* Regulatory risk (16:10)

* AI policy under Trump (22:29)

Below is a lightly edited transcript of our conversation

A changing approach (1:09)

Pethokoukis: Let's start out with just trying to figure out the state of play when it comes to AI regulation. Now I remember we had people calling for the AI Pause, and then we had a Biden executive order. They're passing some sort of act in Europe on AI, and now recently a senate working group in AI put out a list of guidelines or recommendations on AI. Given where we started, which was “shut it down,” to where we're at now, has that path been what you might've expected, given where we were when we were at full panic?

Thierer: No, I think we've moved into a better place, I think. Let's look back just one year ago this week: In the Senate Judiciary Committee, there was a hearing where Sam Altman of OpenAI testified along with Gary Marcus, who's a well-known AI worrywart, and the lawmakers were falling all over themselves to praise Sam and Gary for basically calling for a variety of really extreme forms of AI regulation and controls, including not just national but international regulatory bodies, new general purpose licensing systems for AI, a variety of different types of liability schemes, transparency mandates, disclosure as so-called “AI nutritional labels,” I could go on down the list of all the types of regulations that were being proposed that day. And of course this followed, as you said, Jim, a call for an AI Pause, without any details about exactly how that would work, but it got a lot of signatories, including people like Elon Musk, which is very strange considering he was at the same time deploying one of the biggest AI systems in history. But enough about Elon.

The bottom line is that those were dark days, and I think the tenor of the debate and the proposals on the table today, one year after that hearing, have improved significantly. That's the good news. The bad news is that there's still a lot of problematic regulatory proposals percolating throughout the United States. As of this morning, as we're taping the show, we are looking at 738 different AI bills pending in the United States according to multistate.ai, an AI tracking service. One hundred and—I think—eleven of those are federal bills. The vast majority of it is state. But that count does not include all of the municipal regulatory proposals that are pending for AI systems, including some that have already passed in cities like New York City that already has a very important AI regulation governing algorithmic hiring practices. So the bottom line, Jim, is it's the best of times, it's the worst of times. Things have both gotten better and worse.

Well—just because the most recent thing that happened—I know with this the senate working group, and they were having all kinds of technologists and economists come in and testify. So that report, is it really calling for anything specific to happen? What's in there other than just kicking it back to all the committees? If you just read that report, what does it want to happen?

A crucial thing about this report, and let's be clear what this is, because it was an important report because senator Senate Majority Leader Chuck Schumer was in charge of this, along with a bipartisan group of other major senators, and this started the idea of, so-called “AI insight forums” last year, and it seemed to be pulling some authority away from committees and taking it to the highest levels of the Senate to say, “Hey, we're going to dictate AI policy and we're really scared.” And so that did not look good. I think in the process, just politically speaking—

That, in itself, is a good example. That really represents the level of concern that was going around, that we need to do something different and special to address this existential risk.

And this was the leader of the Senate doing it and taking away power, in theory, from his committee members—which did not go over well with said committee members, I should add. And so a whole bunch of hearings took place, but they were not really formal hearings, they were just these AI insight forum working groups where a lot of people sat around and said the same things they always say on a daily basis, and positive and negatives of AI. And the bottom line is, just last week, a report came out from this AI senate bipartisan AI working group that was important because, again, it did not adopt the recommendations that were on the table a year ago when the process got started last June. It did not have overarching general-purpose licensing of artificial intelligence, no new call for a brand new Federal Computer Commission for America, no sweeping calls for liability schemes like some senators want, or other sorts of mandates.

Instead, it recommended a variety of more generic policy reforms and then kicked a lot of the authority back to those committee members to say, “You fill out the details, for better for worse.” And it also included a lot of spending. One thing that seemingly everybody agrees on in this debate is that, well, the government should spend a lot more money and so another $30 billion was on the table of sort of high-tech pork for AI-related stuff, but it really did signal a pretty important shift in approach, enough that it agitated the groups on the more pro-regulatory side of this debate who said, “Oh, this isn't enough! We were expecting Schumer to go for broke and swing for the fences with really aggressive regulation, and he's really let us down!” To which I can only say, “Well, thank God he did,” because we're in a better place right now because we're taking a more wait-and-see approach on at least some of these issues.

A big, big part of the change in this narrative is an acknowledgement of what I like to call the realpolitik of AI policy and specifically the realpolitik of geopolitics

The global AI race (7:26)

I'm going to ask you in a minute what stuff in those recommendations worries you, but before I do, what happened? How did we get from where we were a year ago to where we've landed today?

A big, big part of the change in this narrative is an acknowledgement of what I like to call the realpolitik of AI policy and specifically the realpolitik of geopolitics. We face major adversaries, but specifically China, who has said in documents that the CCP [Chinese Communist Party] has published that they want to be the global leader in algorithmic and computational technologies by 2030, and they're spending a lot of money putting a lot of state resources into it. Now, I don't necessarily believe that means they're going to automatically win, of course, but they're taking it seriously. But it's not just China. We have seen in the past year massive state investments and important innovations take place across the globe.

I'm always reminding people that people talk a big game about America's foundational models are large scale systems, including things like Meta’s Llama, which was the biggest open source system in the world a year ago, and then two months after Meta launched Llama, their open source platform, the government of the UAE came out with Falcon 180B, an open source AI model that was two-and-a-half times larger than Facebook's model. That meant America's AI supremacy and open source foundational models lasted for two months. And that's not China, that's the government of the UAE, which has piled massive resources into being a global leader in computation. Meanwhile, China's launched their biggest super—I'm sorry, Russia's launched their biggest supercomputer system ever; you've got Europe applying a lot of resources into it, and so on and so forth. A lot of folks in the Senate have come to realize that problem is real: that if we shoot ourselves in the foot as a nation, they could race ahead and gain competitive advantage in geopolitical strategic advantages over the United States if it hobbles our technology base. I think that's the first fundamental thing that's changed.

I think the other thing that changed, Jim, is just a little bit of existential-risk exhaustion. The rhetoric in this debate, as you've written about eloquently in your columns, has just been crazy. I mean, I've never really seen anything like it in all the years we've been covering technology and economic policy. You and I have both written, this is really an unprecedented level of hysteria. And I think, at some point, the Chicken-Littleism just got to be too much, and I think some saner minds prevailed and said, “Okay, well wait a minute. We don't really need to pause the entire history of computation to address these hypothetical worst-case scenarios. Maybe there's a better plan than that.” And so we're starting to pull back from the abyss, if you will, a little bit, and the adults are reentering the conversation—a little bit, at least. So I think those are the two things that really changed more, although there were other things, but those were two big ones.

The political economy of AI (10:24)

To what extent do you think we saw the retreat from the more apocalyptic thinking—how much that was due from what businesses were saying, venture capitalists, maybe other tech . . . ? What do you think were the key voices Congress started listening to a little bit more?

That's a great question. The political economy of AI policy and tech policy is something that is terrifically interesting to me. There are so many players and voices involved in AI policy because AI is the most important general-purpose technology of our time, and as a widespread broad base—

Do you have any doubt about that? (Let me cut you off.) Do you have any doubt about that?

I don't. I think it's unambiguous, and we live in a world of “combinatorial innovation,” as Hal Varian calls it, where technologies build on top of the other, one after another, but the thing is they all lead to greater computational capacity, and therefore, algorithmic and machine learning systems come out of those—if we allow it. And the state of data science in this country has gotten to the point where it's so sophisticated because of our rich base of diverse types of digital technologies and computational technologies that finally we're going to break out of the endless cycle of AI booms and busts, and springs and winters, and we're going to have a summer. I think we're having it right now. And so that is going to come to affect every single segment and sector of our economy, including the government itself.

I think industry has been very, very scrambled and sort of atomistic in their approach to AI policy, and some of them have been downright opportunistic, trying to throw each other’s competitors under the bus

Now let me let you go return to the political economy, what I was asking you about, what were the voices, sorry, but I wanted to get that in there.

Well, I think there are so many voices, I can't name them all today, obviously, but obviously we're going to start with one that's a quiet voice behind the scenes, but a huge one, which is, I think, the National Security community. I think clearly going back to our point about China and geopolitical security, I think a lot of people behind the scenes who care about these issues, including people in the Pentagon, I think they had conversations with certain members of Congress and said, “You know what? China exists. And if we're shooting ourselves in the foot, we begin this race for geopolitical strategic supremacy in an important new general-purpose technology arena, we're really hurting our underlying security as a nation. I think that that thinking is there. So that's an important voice.

Secondly, I think industry has been very, very scrambled and sort of atomistic in their approach to AI policy, and some of them have been downright opportunistic, trying to throw each other’s competitors under the bus, unfortunately, and that includes OpenAI trying to screw over other companies and technologies, which is dangerous, but the bottom line is: More and more of them are coming to realize, as they saw the actual details of regulation and thinking through the compliance costs, that “Hell no, we won't go, we're not going to do that. We need a better approach.” And it was always easier in the old days to respond to the existential risk route, like, “Oh yeah, sure, regulation is fine, we'll go along with it!” But then when you see the devilish details, you think twice and you realize, “This will completely undermine our competitive advantage in the space as a company or our investment or whatever else.” All you need to do is look at Exhibit A, which is Europe, and say, if you always run with worst-case scenario thinking and Chicken-Littleism is the basis of your technology policy, guess what? People respond to incentives and they flee.

Hatred of big tech is like the one great bipartisan, unifying theme of this Congress, if anything. But at the end of the day, I think everyone is thankful that those companies are headquartered in the United States and not Beijing, Brussels, or anywhere else.

It’s interesting, the national security aspect, my little amateurish thought experiment would be, what would be our reaction, and what would be the reaction in Washington if, in November, 2022, instead of it being a company, an American company with a big investment from another American company having rolled out ChatGPT, what if it would've been Tencent, or Alibaba, or some other Chinese company that had rolled this out, something that's obviously a leap forward, and they had been ahead, even if they said, “Oh, we're two or three years ahead of America,” it would've been bigger than Sputnik, I think.

People are probably tired of hearing about AI—hopefully not, I hope they'll also listen to this podcast—but that would all we would be talking about. We wouldn’t be talking about job loss, and we wouldn't be talking about ‘The Terminator,’ we'd be talking about the pure geopolitical terms that the US has suffered a massive, massive defeat here and who's to blame? What are we going to do? And anybody at that moment who would've said, “We need to launch cruise missile strikes on our own data centers” for fear. . . I mean! And I think you're right, the national security component, extremely important here.

In fact, I stole your little line about “Sputnik moment,” Jim, when I testified in front of the House Oversight Committee last month and I said, “Look, it would've been a true ‘Sputnik moment,’ and instead it's those other countries that are left having the Sputnik moment, right? They're wondering, ‘How is it that, once again, the United States has gotten out ahead on digital and computational-based technologies?’” But thank God we did! And as I pointed out in the committee room that day, there's a lot of people who have problems with technology companies in Congress today. Hatred of big tech is like the one great bipartisan, unifying theme of this Congress, if anything. But at the end of the day, I think everyone is thankful that those companies are headquartered in the United States and not Beijing, Brussels, or anywhere else. That's just a unifying theme. Everybody in the committee room that day nodded their head, “Yes, yes, absolutely. We still hate them, but we're thankful that they're here.” And that then extends to AI: Can the next generation of companies that they want to bring to Congress and bash and pull money from for their elections, can they once again exist in the United States?

Regulatory risk (16:10)

So whether it's that working group report, or what else you see in Congress, what are a couple, three areas where you're concerned, where there still seems to be some sort of regulatory momentum?

Let’s divide it into a couple of chunks here. First of all, at the federal level, Congress is so damn dysfunctional that I'm not too worried that even if they have bad ideas, they're going to pursue them because they're just such a mess, they can't get any basic things done on things like baseline privacy legislation, or driverless car legislation, or even, hell, the budget and the border! They can't get basics done!

I think it's a big positive that one, while they're engaging in dysfunction, the technology is evolving. And I hope, if it's as important as I think you and I think, more money will be invested, we'll see more use cases, it'll be obvious—the downsides of screwing up the regulation I think will be more obvious, and I think that's a tailwind for this technology.

We're in violent agreement on that, Jim, and of course this goes by the name of “the pacing problem,” the idea that technology is outpacing law in many ways, and one man's pacing problem is another man's pacing benefit, in my opinion. There's a chance for technology to prove itself a little bit. That being said, we don't live in a legislative or regulatory vacuum. We already have in the United States 439 government agencies and sub-agencies, 2.2 million employees just at the federal level. So many agencies are active right now trying to get their paws on artificial intelligence, and some of them already have it. You look at the FDA [Food and Drug Administration], the FAA [Federal Aviation Administration], NHTSA [National Highway Traffic Safety Administration], I could go all through the alphabet soup of regulatory agencies that are already trying to regulate or overregulating AI right now.

Then you have the Biden administration, who's gone out and done a lot of cheerleading in favor of more aggressive unilateral regulation, regardless of what Congress says and basically says, “To hell with all that stuff about Chevron Doctrine and major questions, we're just going to go do it! We're at least going to jawbone a lot and try to threaten regulation, and we're going to do it in the name of ‘algorithmic fairness,’” which is what their 100-plus-page executive order and their AI Bill of Rights says they're all about, as opposed to talking about AI opportunity and benefits—it's all misery. And it's like, “Look at how AI is just a massive tool of discrimination and bias, and we have to do something about it preemptively through a precautionary principle approach.” So if Congress isn't going to act, unfortunately the Biden administration already is and nobody's stopping them.

But that's not even the biggest problem. The biggest problem, going back to the point that there are 730-plus bills pending in the US right now, the vast majority of them are state and local. And just last Friday, governor Jared Polis of Colorado signed into law the first major AI regulatory measure in Colorado, and there's a bigger and badder bill pending right now in California, there's 80 different bills pending in New York alone, and any half of them would be a disaster.

I could go on down the list of troubling state patchwork problems that are going to develop for AI and ML [Machine Learning] systems, but the bottom line is this: This would be a complete and utter reversal of the winning formula that Congress and the Clinton administration gave us in the 1990s, which was a national—a global framework for global electronic commerce. It was very intentionally saying, “We're going to break with the Analog Era disaster, we're going to have a national framework that's pro-freedom to innovate, and we're going to make sure that these meddlesome barriers do not develop to online speech and commerce.” And yet, here with AI, we are witnessing a reversal of that. States are in the lead, and again, like I said, localities too, and Congress is sitting there and is the dysfunctional soup that it is saying, “Oh, maybe we should do something to spend a little bit more money to promote AI.” Well, we can spend all the money we want, but we can end up like Europe who spends tons of money on techno-industrial policies and gets nothing for it because they can't get their innovation culture right, because they’re regulating the living hell out of digital technology.

So you want Congress to take this away from the states?

I do. I do, but it's really, really hard. I think what we need to do is follow the model that we had in the Telecommunications Act of 1996 and the Internet Tax Freedom Act of 1998. We've also had moratoriums, not only through the Internet Tax Freedom Act, but through the Commercial Space Amendments having to do with space commercial travel and other bills. Congress has handled the question of preemption before and put moratoria in place to say, “Let's have a learning period before we go do stupid things on a new technology sector that is fast moving and hard to understand.” I think that would be a reasonable response, but again, I have to go back to what we just talked about, Jim, which is that there's no chance of us probably getting it. There's no appetite in it. Not any of the 111 bills pending in Congress right now says a damn thing about state and local regulation of technology!

Is the thrust of those federal bills, is it the kinds of stuff that you're generally worried about?

Mostly, but not entirely. Some of it is narrower. A lot of these bills are like, “Let's take a look at AI and. . . fill in the blank: elections, AI and jobs, AI and whatever.” And some of them, on the merits, not terrible, others, I have concerns, but it's certainly better that we take a targeted sectoral approach to AI policy and regulation than having the broad-based, general-purpose stuff. Now, there are broad-based, general-purpose measures, and here's what they do, Jim: They basically say, “Look, instead of having a whole cloth new regulatory approach, let's build on the existing types of approaches being utilized in the Department of Commerce, namely through our NIST [National Institute of Standards and Technology], and NTIA [National Telecommunications and Information Administration] sub-agencies there. NIST is the National Standards Body, and basically they develop best practices through something called the AI Risk Management Framework for artificial intelligence development—and they're good! It's multi-stakeholder, it's bottom up, it's driven by the same principles that motivated the Clinton administration to do multi-stakeholder processes for the internet. Good model. It is non-regulatory, however. It is a consensus-based, multi-stakeholder, voluntary approach to developing consensus-based standards for best practices regarding various types of algorithmic services. These bills in Congress—and there's at least five of them that I count, that I've written about recently—say, “Let's take that existing infrastructure and give it some enforcement teeth. Let's basically say, ‘This policy infrastructure will be converted into a quasi-regulatory system,’” and there begins the dangerous path towards backdoor regulation of artificial intelligence in this country, and I think that's the most likely model we'll get. Like I said, five models, legislative models in the Senate alone that would do that to varying degrees.

AI policy under Trump (22:29)

Do you have any feel for what a Trump administration would want to do on this?

I do, because a month before the Trump administration left office, they issued a report through the Office of Management and Budget (OMB), and it basically laid out for agencies a set of principles for how it should evaluate artificial intelligence systems, both that are used by the government or that they regulate in the private sector, and it was an excellent set of principles. It was a restatement of the importance of policy, forbearance and humility. It was a restatement of a belief in cost-benefit analysis and identifying not only existing regulatory capacity to address these problems, but also non-regulatory mechanisms or best practices or standards that could address some of these things. It was a really good memo. I praised it in a piece that I wrote just before the Trump administration left. Now, of course, the Trump administration may change.

Yes, and also, the technology has changed. I mean, that was 2020 and a lot has happened, and I don't know where. . . . I'm not sure where all the Republicans are. I think some people get it. . .

I think the problem, Jim, is that, for the Republican Party, and Trumpian conservatives, in particular, they face a time of choosing. And what I mean by this is that they have spent the last four to six years—and Trump egged this on—engaging in nonstop quote-unquote “big tech bashing” and making technology companies in the media out to be, as Trumps calls them, “the enemy of the American people.” And so many hearings now are just parading tech executives and others up there to be beaten with a stick in front of the public, and this is the new thing. And then there's just a flood of bills that would regulate traditional digital technologies, repeal things like Section 230, which is liability protection for the tech sector, and so on, child safety regulations.

Meanwhile, that same Republican Party and Mr. Trump go around hating on Joe Biden in China. If it's one thing they can't stand more than big tech, it's Joe and China! And so, in a sense, they've got to choose, because their own policy proposals on technology could essentially kneecap America's technology base in a way that would open up the door to whether it's what they fear in the “woke DEI policies” of Biden or the CCP’s preferred policy agenda for controlling computation in the world today. Choose two, you don't get all three. And I think this is going to be an interesting thing to watch if Mr. Trump comes back into office, do they pick up where that OMB memo left off, or do they go right back to beating that “We’ve got to kill big tech by any means necessary in a seek-and-destroy mission, to hell with the consequences.” And I don't know yet.

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Project Apollo was a feat of human achievement akin to, and arguably greater than, the discovery of the New World. From 1962 to 1972, NASA conducted 17 crewed missions, six of which placed men on the surface of the moon. Since the Nixon administration put an end to Project Apollo, our extraterrestrial ambitions seem to have stalled along with our sense of national optimism. But is the American spirit of adventure, heroism, and willingness to take extraordinary risk a thing of the past

Today on the podcast, I talk with Charles Murray about what made Apollo extraordinary and whether we in the 21st century have the will to do extraordinary things. Murray is the co-author with Catherine Bly Cox of Apollo: The Race to the Moon, first published in 1989 and republished in 2004. He is also my colleague here at AEI.

In This Episode

* Going to the moon (1:35)

* Support for the program (7:40)

* Gene Kranz (9:31)

* An Apollo 12 story (12:06)

* An Apollo 11 story (17:58)

* Apollo in the media (21:36)

* Perspectives on space flight (24:50)

Below is a lightly edited transcript of our conversation

Going to the moon (1:35)

Pethokoukis: When I look at the delays with the new NASA go-to-the-moon rocket, and even if you look at the history of SpaceX and their current Starship project, these are not easy machines for mankind to build. And it seems to me that, going back to the 1960s, Apollo must have been at absolutely the far frontier of what humanity was capable of back then, and sometimes I cannot almost believe it worked. Were the Apollo people—the engineers—were they surprised it worked?

Murray: There were a lot of people who, they first heard the Kennedy speech saying, “We want to go to the moon and bring a man safely back by the end of the decade,” they were aghast. I mean, come on! In 1961, when Kennedy made that speech, we had a grand total of 15 minutes of manned space flight under our belt with a red stone rocket with 78,000 pounds of thrust. Eight years and eight weeks later, about the same amount of time since Donald Trump was elected to now, we had landed on the moon with a rocket that had 7.6 million pounds of thrust, compared to the 78,000, and using technology that had had to be invented essentially from scratch, all in eight years. All of Cape Canaveral, those huge buildings down there, all that goes up during that time.

Well, I'm not going to go through the whole list of things, but if you want to realize how incredibly hard to believe it is now that we did it, consider the computer system that we used to go to the moon. Jerry Bostick, who was one of the flight dynamics officers, was telling me a few months ago about how excited they were just before the first landing when they got an upgrade to their computer system for the whole Houston Center. It had one megabyte of memory, and this was, to them, all the memory they could ever possibly want. One megabyte.

We'll never use it all! We'll never use all this, it’s a luxury!

So Jim, I guess I'm saying a couple of things. One is, to the young’ins out there today, you have no idea what we used to be able to do. We used to be able to work miracles, and it was those guys who did it.

Was the Kennedy speech, was it at Rice University?

No, “go to the moon” was before Congress.

He gave another speech at Rice where he was started to list all the things that they needed to do to get to the moon. And it wasn't just, “We have these rockets and we need to make a bigger one,” but there was so many technologies that needed to be developed over the course of the decade, I can't help but think a president today saying, “We're going to do this and we have a laundry list of things we don't know how to do, but we're going to figure them out…” It would've been called pie-in-the-sky, or something like that.

By the way, in order to do this, we did things which today would be unthinkable. You would have contracts for important equipment; the whole cycle for the contract acquisition process would be a matter of weeks. The request for proposals would go out; six weeks later, they would've gotten the proposals in, they would've made a decision, and they'd be spending the money on what they were going to do. That kind of thing doesn't get done.

But I'll tell you though, the ballsiest thing that happened in the program, among the people on the ground — I mean the ballsiest thing of all was getting on top of that rocket and being blasted into space — but on the ground it was called the “all up” decision. “All up” refers to the testing of the Saturn V, the launch vehicle, this monstrous thing, which basically is standing a Navy destroyer on end and blasting it into space. And usually, historically, when you test those things, you test Stage One, and if that works, then you add the second stage and then you add the third stage. And the man who was running the Apollo program at that time, a guy named Miller, made the decision they were going to do All Up on the first test. They were going to have all three stages, and they were going to go with it, and it worked, which nobody believed was possible. And then after only a few more launches, they put a man on that thing and it went. Decisions were made during that program that were like wartime decisions in terms of the risk that people were willing to take.

One thing that surprises me is just how much that Kennedy timeline seemed to drive things. Apollo seven, I think it was October ’68, and that was the first manned flight? And then like two months later, Apollo 8, we are whipping those guys around the moon! That seems like a rather accelerated timeline to me!

The decision to go to the moon on Apollo 8 was very scary to the people who first heard about it. And, by the way, if they'd had the same problem on Apollo 8 that they'd had on Apollo 13, the astronauts would've died, because on Apollo 8 you did not have the lunar module with them, which is how they got back. So they pulled it off, but it was genuinely, authentically risky. But, on the other hand, if they wanted to get to the moon by the end of 1969, that's the kind of chance you had to take.

Support for the Program (7:40)

How enthusiastic was the public that the program could have withstood another accident? Another accident before 11 that would've cost lives, or even been as scary as Apollo 13 — would we have said, let's not do it, or we're rushing this too much? I think about that a lot now because we talk about this new space age, I'm wondering how people today would react.

In January, 1967, three astronauts were killed on the pad at Cape Canaveral when the spacecraft burned up on the ground. And the support for the program continued. But what's astonishing there is that they were flying again with manned vehicles in September 1967. . . No, it was a year and 10 months, basically, between this fire, this devastating fire, a complete redesign of the spacecraft, and they got up again.

I think that it's fair to say that, through Apollo 11, the public was enthusiastic about the program. It's amazingly how quickly the interest fell off after the successful landing; so that by the time Apollo 13 was launched, the news programs were no longer covering it very carefully, until the accident occurred. And by the time of Apollo 16, 17, everybody was bored with the program.

Speaking of Apollo 13, to what extent did that play a role in Nixon's decision to basically end the Apollo program, to cut its budget, to treat it like it was another program, ultimately, which led to its end? Did that affect Nixon's decision making, that close call, do you think?

No. The public support for the program had waned, political support had waned. The Apollo 13 story energized people for a while in terms of interest, but it didn't play a role.

 Gene Kranz (9:31)

500 years after Columbus discovering the New World, we talk about Columbus. And I would think that 500 years from now, we'll talk about Neil Armstrong. But will we also talk about Gene Kranz? Who is Gene Kranz and why should we talk about him 500 years from now?

Gene Kranz, also known as General Savage within NASA, was a flight director and he was the man who was on the flight director's console when the accident on 13 occurred, by the way. But his main claim to fame is that he was one of — well, he was also on the flight director's desk when we landed. And what you have to understand, Jim, is the astronauts did not run these missions. I'm not dissing the astronauts, but all of the decisions . . . they couldn't make those decisions because they didn't have the information to make the decisions. These life-and-death decisions had to be made on the ground, and the flight director was the autocrat of the mission control, and not just the autocrat in terms of his power, he was also the guy who was going to get stuck with all the responsibility if there was a mistake. If they made a mistake that killed the astronauts, that flight director could count on testifying before Congressional committees and going down in history as an idiot.

Somebody like Gene Kranz, and the other flight director, Glynn Lunney during that era, who was also on the controls during the Apollo 13 problems, they were in their mid-thirties, and they were running the show for one of the historic events in human civilization. They deserve to be remembered, and they have a chance to be, because I have written one thing in my life that people will still be reading 500 years from now — not very many people, but some will — and that's the book about Apollo that Catherine, my wife, and I wrote. And the reason I'm absolutely confident that they're going to be reading about it is because — historians, anyway, historians will — because of what you just said. There are wars that get forgotten, there are all sorts of events that get forgotten, but we remember the Trojan War, we remember Hastings, we remember Columbus discovering America. . . We will remember for a thousand years to come, let alone 500, the century in which we first left Earth.

 An Apollo 12 story (12:06)

If you just give me a story or two that you'd like to tell about Apollo that maybe the average person may have never heard of, but you find . . . I'm sure there's a hundred of these. Is there one or two that you think the audience might find interesting?

The only thing is it gets a little bit nerdy, but a lot about Apollo gets nerdy. On Apollo 12, the second mission, the launch vehicle lifts off and into the launch phase, about a minute in, it gets hit by lightning — twice. Huge bolts of lightning run through the entire spacecraft. This is not something it was designed for. And so they get up to orbit. All of the alarms are going off at once inside the cabin of the spacecraft. Nobody has the least idea what's happened because they don't know that they got hit by lightning, all they know is nothing is working.

A man named John Aaron is sitting in the control room at the EECOM’s desk, which is the acronym for the systems guide who monitored all the systems, including electrical systems, and he's looking at his console and he's seeing a weird pattern of numbers that makes no sense at all, and then he remembers 15 months earlier, he'd just been watching the monitor during a test at Cape Canaveral, he wasn't even supposed to be following this launch test, he was just doing it to keep his hand in, and so forth, and something happened whereby there was a strange pattern of numbers that appeared on John Aaron's screen then. And so he called Cape Canaveral and said, what happened? Because I've never seen that before. And finally the Cape admitted that somebody had accidentally turned a switch called the SCE switch off.

Okay, so here is John Aaron. Apollo 12 has gone completely haywire. The spacecraft is not under the control of the astronauts, they don't know what's happened. Everybody's trying to figure out what to do.

John Aaron remembers . . . I'm starting to get choked up just because that he could do that at a moment of such incredible stress. And he just says to the flight director, “Try turning SCE to auxiliary.” And the flight director had never even heard of SCE, but he just . . . Trust made that whole system run. He passes that on to the crew. The crew turns that switch, and, all at once, they get interpretable data back again.

That's the first part of the story. That was an absolutely heroic call of extraordinary ability for him to do that. The second thing that happens at that point is they have completely lost their guidance platform, so they have to get that backup from scratch, and they've also had this gigantic volts of electricity that's run through every system in the spacecraft and they have three orbits of the earth before they have to have what was called trans lunar injection: go onto the moon. That's a couple of hours’ worth.

Well, what is the safe thing to do? The safe thing to do is: “This is not the right time to go to the moon with a spacecraft that's been damaged this way.” These guys at mission control run through a whole series of checks that they're sort of making up on the fly because they've never encountered this situation before, and everything seems to check out. And so, at the end of a couple of orbits, they just say, “We're going to go to the moon.” And the flight director can make that decision. Catherine and I spent a lot of time trying to track down the anguished calls going back and forth from Washington to Houston, and by the higher ups, “Should we do this?” There were none. The flight director said, “We're going,” and they went. To me, that is an example of a kind of spirit of adventure, for lack of a better word, that was extraordinary. Decisions made by guys in their thirties that were just accepted as, “This is what we're going to do.”

By the way, Gene Kranz, I was interviewing him for the book, and I was raising this story with him. (This will conclude my monologue.) I was raising this story with him and I was saying, “Just extraordinary that you could make that decision.” And he said, “No, not really. We checked it out. The spacecraft looked like it was good.” This was only a year or two after the Challenger disaster that I was conducting this interview. And I said to Gene, “Gene, if we had a similar kind of thing happen today, would NASA ever permit that decision to be made?” And Gene glared at me. And believe me, when Gene Kranz glares at you, you quail at your seat. And then he broke into laughter because there was not a chance in hell that the NASA of 1988 would do what the NASA of 1969 did.

An Apollo 11 story (17:58)

If all you know about Apollo 11 is what you learned in high school, or maybe you saw a documentary somewhere, and — just because I've heard you speak before, and I've heard Gene Kranz speak—what don't people know about Apollo 11? There were — I imagine with all these flights — a lot of decisions that needed to be made probably with not a lot of time, encountering new situations — after all, no one had done this before. Whereas, I think if you just watch a news report, you think that once the rocket's up in the air, the next thing that happens is Neil Armstrong lands it on the moon and everyone's just kind of on cruise control for the next couple of days, and boy, it certainly doesn't seem like that.

For those of us who were listening to the landing, and I'm old enough to have done that, there was a little thing called—because you could listen to the last few minutes, you could listen to what was going on between the spacecraft and mission control, and you hear Buzz Aldrin say, “Program Alarm 1301 . . .  Program Alarm 1301 . . .” and you can't…   well, you can reconstruct it later, and there's about a seven-second delay between him saying that and a voice saying, “We're a go on that.” That seven seconds, you had a person in the back room that was supporting, who then informed this 26-year-old flight controller that they had looked at that possibility and they could still land despite it. The 26-year-old had to trust the guy in the back room because the 26-year-old didn't know, himself, that that was the case. He trusts him, he tells the flight director Gene Kranz, and they say, “Go.” Again: Decision made in seven seconds. Life and death. Taking a risk instead of taking the safe way out.

Sometimes I think that that risk-taking ethos didn't end with Apollo, but maybe, in some ways, it hasn't been as strong since. Is there a scenario where we fly those canceled Apollo flights that we never flew, and then, I know there were other plans of what to do after Apollo, which we didn't do. Is there a scenario where the space race doesn't end, we keep racing? Even if we're only really racing against ourselves.

I mean we've got . . . it's Artemis, right? That's the new launch vehicle that we're going to go back to the moon in, and there are these plans that somehow seem to never get done at the time they're supposed to get done, but I imagine we will have some similar kind of flights going on. It's very hard to see a sustained effort at this point. It's very hard to see grandiose effort at this point. The argument of, “Why are we spending all this money on manned space flight?” in one sense, I sympathize with because it is true that most of the things we do could be done by instruments, could be done by drones, we don't actually have to be there. On the other hand, unless we're willing to spread our wings and raise our aspirations again, we're just going to be stuck for a long time without making much more progress. So I guess what I'm edging around to is, in this era, in this ethos, I don't see much happening done by the government. The Elon Musks of the world may get us to places that the government wouldn't ever go. That's my most realistic hope.

Apollo in the Media (21:36)

If I could just give you a couple of films about the space program and you just… thought you liked it, you thought it captured something, or you thought it was way off, just let just shoot a couple at you. The obvious one is The Right Stuff—based on the Tom Wolfe book, of course.

The Right Stuff was very accurate about the astronauts’ mentality. It was very inaccurate about the relationship between the engineers and the astronauts. It presents the engineers as constantly getting the astronauts way, and being kind of doofuses. That was unfair. But if you want to understand how the astronauts worked, great movie

Apollo 13, perhaps the most well-known.

Extremely accurate. Extremely accurate portrayal of the events. There are certain things I wish they could include, but it's just a movie, so they couldn't include everything. The only real inaccuracy that bothered me was it showed the consoles of the flight controllers with colored graphics on them. They didn't have colored graphics during Apollo! They had columns of white numbers on a black background that were just kind of scrolling through and changing all the time, and that's all. But apparently, when their technical advisor pointed that out to Ron Howard, Ron said, “There are some things that an audience just won't accept, but they would not accept.”

That was the leap! First Man with Ryan Gosling portraying Neil Armstrong.

I'll tell you: First place, good movie—

Excellent, I think.

Yeah, and the people who knew Armstrong say to me, it's pretty good at capturing Armstrong, who himself was a very impressive guy. This conceit in the movie that he has this little trinket he drops on the moon, that was completely made up and it's not true to life. But I'll tell you what they tell me was true to life that surprised me was how violently they were shaken up during the launch phase. And I said, “Is that the way it was, routinely?” And they said, yeah, it was a very rough ride that those guys had. And the movie does an excellent job of conveying something that somebody who'd spent a lot of time studying the Apollo program didn't know.

I don't know if you've seen the Apple series For All Mankind by Ronald D. Moore, which is based on the premise I raised earlier that Apollo didn’t end, we just kept up the Space Race and we kept advancing off to building moon colonies and off to Mars. Have you seen that? And what do you think about it if you have? I don't know that you have.

I did not watch it. I have a problem with a lot of these things because I have my own image of the Apollo Program, and it drives me nuts if somebody does something that is egregiously wrong. I went to see Apollo 13 and I'm glad I did it because it was so accurate, but I probably should look at For All Mankind.

Very reverential. A very pro-space show, to be sure. Have you seen the Apollo 11 documentary that's come out in the past five years? It was on the big screen, it was at theaters, it was a lot of footage they had people had not seen before, they found some old canisters somewhere of film. I don’t know if you've seen this. I think it's just called Apollo 11.

No, I haven't seen that. That sounds like something that I ought to look at.

Perspectives on space flight (24:50)

My listeners love when I read . . . Because you mentioned the idea of: Why do we go to space? If it's merely about exploration, I suppose we could just send robots and maybe eventually the robots will get better. So I want to just briefly read two different views of why we go to space.

Why should human beings explore space? Because space offers transcendence from which only human beings can benefit. The James Webb Space Telescope cannot articulate awe. A robot cannot go into the deep and come back with soulful renewal. To fully appreciate space, we need people to go there and embrace it for what it fully is. Space is not merely for humans, nor is space merely for space. Space is for divine communion.

That’s one view.

The second one is from Ayn Rand, who attended the Apollo 11 moon launch. This is what Ayn Rand wrote in 1969:

The next four days were torn out of the world’s usual context, like a breathing spell with a sweep of clean air piercing mankind’s lethargic suffocation. For thirty years or longer, the newspapers had featured nothing but disasters, catastrophes, betrayals, the shrinking stature of man, the sordid mess of a collapsing civilization; their voice had become a long, sustained whine, the megaphone a failure, like the sound of the Oriental bazaar where leprous beggars, of spirit or matter, compete for attention by displaying their sores. Now, for once, the newspapers were announcing a human achievement, were reporting on a human triumph, were reminding us that man still exists and functions as a man. Those four days conveyed the sense that we were watching a magnificent work of art—a play dramatizing a single theme: the efficacy of man’s mind.

Is the answer for why we go to space, can it be found in either of those readings?

They're going to be found in both. I am a sucker for heroism, whether it's in war or in any other arena, and space offers a kind of celebration of the human spirit that is only found in endeavors that involve both great effort and also great risk. And the other aspect of transcendence, I'm also a sucker for saying the world is not only more complicated than we know, but more complicated than we can imagine. The universe is more complicated than we can imagine. And I resonate to the sentiment in the first quote.

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As I often remind subscribers to Faster, Please!, predictions are hard, especially about the future. The economic boom of the 1990s came as a surprise to most economists. Equally surprising was that it ended so soon. Neither of these events caught Ed Yardeni off-guard. Some forecasters, Yardeni included, anticipated a new Roaring ’20s for this century… only to be interrupted by the pandemic. But is it too late for this prediction to become a reality? According to Yardeni, not at all.

Ed Yardeni is president of Yardeni Research, and he previously served as chief investment strategist at a number of investment companies, including Deutche Bank.  He has additionally held positions at the Federal Reserve Bank of New York, Federal Reserve Board of Governors, and US Treasury Department. For more economic insights and investment guidance, visit yardeni.com.

In This Episode

* The ’90s Internet boom (1:25)

* The Digital Revolution (5:01)

* The new Roaring ’20s (9:00)

* A cautious Federal Reserve (14:24)

* Speedbumps to progress (18:18)

Below is a lightly edited transcript of our conversation

The ’90s Internet boom (1:25)

Pethokoukis: Statistically speaking, the PC Internet boom that you first started writing about back in the early ’90s ended in 2004, 2005. How surprising was that to economists, investors, policy makers? I, to this day, have a report, a 2000 report, from Lehman Brothers that predicted, as far as the eye could see, we would have rapid growth, rapid productivity growth for at least another decade. Now, of course, Lehman didn't make it another decade. Was that a surprise to people that we didn't have an endless productivity boom coming out of the ’90s?

Yardeni: I think it definitely was a surprise. I mean, it was surprising both ways. Not too many people expected to see a productivity boom in the second half of the 1990s, which is what we had. I did, as an economist on Wall Street. More importantly, Alan Greenspan was a big promoter of the idea that the technology revolution would in fact lead to better productivity growth and that that might mean better economic growth and lower inflation. And it didn't look that way for a while; then suddenly the Bureau of Economic Analysis went back and revised the data for the late 1990s and, lo and behold, it turned out that there was a productivity boom. And then it all kind of fizzled out, and it raises the question, why did that happen? Why was it such a short lived productivity boom? And the answer is—well, let me give you a personal anecdote.

I worked at Deutsche Bank in New York in the late 1990s, and I had to be very careful walking down the corridors of Deutsche Bank in midtown Manhattan not to trip over Dell boxes. Everybody was getting a Dell box, everybody was getting the Dell boxes loaded up with the Windows Office. And when you think back on what that was able to do in terms of productivity, if you had a lot of secretaries on Selectric typewriters, Word could obviously increase productivity. If you had a lot of bookkeepers doing spreadsheets, Excel could obviously increase productivity. But other than that, there wasn't really that much productivity to be had from the technology at the time. So again, where did that productivity boom come from? It couldn't have been just secretaries and bookkeepers. Now the answer is that the boxes themselves were measured as output, and so output per man hour increased dramatically. It doesn't take that many workers to produce Dell boxes and Windows Office and Windows software. So as a result of that, we had this big boom in the technology output that created its own productivity boom, but it didn't really have the widespread application to all sorts of business model the way today's evolution of the technology boom is, in fact, capable of doing.

What you've just described, I think, is the explanation by, for instance, Robert Gordon, Northwestern University, that we saw a revolution, but it was a narrow revolution.

It was the beginning! It was the beginning of a revolution. It was the Technology Revolution. It started in the 1990s and it's evolved, it's not over, it's ongoing. I think a big development in that revolution was the cloud. What the cloud allowed you to do was really increase productivity in technology itself, because you didn't need to have several hundred people in the IT department. Now, with the cloud, one person can upgrade the software on hundreds of computers, and now we're renting software so that it automatically upgrades, so that's been a big contribution to productivity.

The Digital Revolution (5:01)

So perhaps I spoke too soon. I talked about that boom—that ’90s boom—ending. Perhaps I should have said it was more of a pause, because it seems what we're seeing now, as you've described it, is a new phase of the Digital Revolution—perhaps a broader phase—and, to be clear, if I understand what you've been speaking about and writing about, this isn't an AI story, this predates what we're seeing in the data now, it predates ChatGPT, when do you date this new phase beginning—and you mentioned one catalyst perhaps being the cloud, so—when did it begin and, again, what are the data markers that you've been looking at?

I don't remember the exact date, but I think it was 2011 where my little investment advisory got ourselves on the Amazon cloud, and that's been a tremendous source of productivity for us, it saves us a lot of money. We used to have a couple of servers on a server farm in the old days, and every now and then it would go down and we'd have to reach somebody on the server farm and say, “Would you mind turning it on and off?” Remember the word “reboot?” I don't remember the word “reboot” being used in quite some time. Amazon's never gone down, as far as I can recall. I think they've always had their systems in Virginia, and they had a backup somewhere overseas, but it's always worked quite well for us.

But now we're finding with some of the other software that's available now, we can actually cut back on our Amazon costs and use some of these other technologies. There's lots of technologies that are very user-friendly, very powerful, and they apply themselves to all sorts of different businesses, and, as you said, it's not just AI. I think the cloud—let's put it around 2011 or so—was a huge development because it did allow companies to do information processing in a much more efficient way, and the software gets automatically updated, and with what it used to take hundreds of people in an IT department to do, now you can do it with just one, which is what we, in fact, have, just one person doing it all for us. But I would say that's as good a point as any. But along the way here, what's really changed is the power of the software that's available, and how cheap it is, and how you can rent it now instead of having to own it.

That's a fantastic example, and, of course, we want to see these sort of examples at some point reflected in the data. And going through some of your writings, one period that you were very focused on was, we may have seen a bottom, maybe at the end of 2015, before the pandemic, where we saw the slowest, I think 20-quarter average… annual average growth rate of productivity.

0.5 annual rate.

But by 2019, leading into the pandemic, it tripled. Is the story of that tripling, is it the cloud? And that certainly has to be one reason why you, among other people, thought that we might see a new Roaring ’20s, right into the teeth of the pandemic, unfortunately.

Well, it's not so unfortunate, I mean, clearly nobody saw the pandemic coming, but we weathered the storm very, very well, and I don't think we can come to any conclusion about productivity during the pandemic, it was all over the place. At first, when we were on lockdown, it actually soared because we were still producing a lot with fewer workers, and then it took a dive, but we're now back up to two percent. We had a really, really good year last year in productivity. The final three quarters of last year, we saw above-trend growth in productivity. And so we're already now back up to two percent, which, again, compared to 0.5, is certainly moving in the right direction, and I don't see any particular reason why that number couldn't go to three-and-a-half, four-and-a-half percent per year kind of growth—which sounds delusional unless you look back at the chart of productivity and see that that's actually what productivity booms do: They get up to something like three-and-a-half to four-and-a-half percent growth, not just on a one-quarter basis, but on a 20-quarter trailing basis at an annual rate.

The new Roaring ’20s (9:00)

This forecast predates the word “generative AI,” predates ChatGPT, and, in fact, if I understand your view, it's even broader than information technology. So tell me a bit about your broader Roaring ’20s thesis and the technological underpinnings of that.

One of the developments we've seen here, which has been somewhat disconcerting, is the challenge to globalization. I'm a big believer in free trade, and the free trade creates more economic growth, but, on the other hand, we have to be realistic and realize that China hasn't been playing by the rules of the game. And so now, as a result, we're seeing a lot of production moving out of China to other countries, and we're seeing a lot of on-shoring in the United States, so we're building state-of-the-art manufacturing facilities that are full of robots and automation that I think are going to bring manufacturing productivity back quite significantly.

Everybody seems to be of the opinion that the reason productivity is weak is because of services. It's actually manufacturing. What happened is, when China joined the World Trade Organization back at the end of 2001—December 11th, 2001, to be exact—manufacturers said hasta la vista to the United States, and we've had absolutely no increase in industrial production capacity since that time, since 2001. And so companies basically gave up on trying to do anything, either expand capacity or improve productivity of manufacturing here, when they could do it so much more cheaply over in China.

I think what's really the most important thing that's changed here is, demographically, we've run out of workers. Certainly even in China, we don't have a growth in the working-age population. We don't have a growth in the working-age population here. And when it comes to skilled labor, that's even more the case, so there's tremendous incentive and pressure on companies to figure out, well, how do we deal with an environment where our business is pretty good, but we can't find the workers to meet all the demand? And the answer has to be productivity. Technology is part of the solution. Managing for productivity is another part of the solution. Giving workers more skills to be more productive is a very good use of money, and it makes workers sticky, it makes them want to stay with you because you're going to have to pay them more because they’re more knowledgeable, and you want to pay them more because you want to keep them.

I think a big part of the productivity story really has to do with the demographic story. China, of course, accelerated all that with the One Child Policy that, as a result, I kind of view China as the world's largest nursing home. They just don't have the workforce that they used to have. Japan doesn't have the workforce. Korea, Taiwan, all these countries… If you want to find cheap, young labor, it's still in Africa and in India, but there are all sorts of issues with how you do business in these countries. It's not that easy. It's not as simple as just saying, “Well, let's just go there.” And so I think we are seeing a tremendous push to increase productivity to deal with the worldwide labor shortage.

We have three really good quarters of productivity growth and, as you mentioned, economists are always very cautious about those productivity numbers because of revisions, they're volatile. But if this is something real and sustainable, it should also reflect in other parts of the economy. We should see good capital investment numbers for here on out if this is a real thing.

I think not only capital investment, but also real wages. Productivity is fairy dust. I mean it's a win-win-win situation. With better-than-expected productivity, you get better-than-expected, real GDP, you get lower-than-expected unit labor costs, which, by the way, unit labor costs, which reflect hourly wages offset by productivity, they're under two percent—or they're around two percent, I should say more accurately—and that's highly correlated with the CPI, so the underlying inflation rate has already come down to where the Fed wants it to be. This is not a forecast, this is where we are right now with unit labor costs. So there's a very strong correlation between productivity growth and the growth of inflation-adjusted compensation. So you can take average hourly earnings, you can take hourly compensation…

There are a bunch of measures of wages, and divide them by the consumption deflator, and you'll see on a year-over-year basis that the correlation is extremely high. And, theoretically—it's the only thing I learned when I went to college in economics that ever made any sense to me, and that is—people in a competitive marketplace—it doesn't have to be perfectly competitive, but in a relatively competitive marketplace—people get paid their real wage. The productivity the workers have, they get paid in their real wages, and we've seen, for all the talk about how “standards of living have stagnated for decades,” if you look at average hourly earnings divided by the consumption deflator, it's been going up 1.4 percent since 1995. That's a doubling of the standard of living every 40 years. That's pretty good progress. And if productivity grows faster than that, you'll get even a better increase in real wages.

If we don't have workers, if there's a shortage of workers—though, obviously, immigration puts a whole different spin on these things—but for what we know now in terms of the workers that are available that are allowed to work, they are getting paid higher real wages. I know that prices have gone up, but people sometimes forget that wages have also gone up quite a bit. But again, it's fairy dust: You get better real growth, you get lower inflation, you get real wages going up, and you get better profit margins. Everybody wins.

A cautious Federal Reserve (14:24)

In the ’90s, we had a Fed chairman who was super cautious about assuming a productivity boom, but eventually saw the reality of it and acted accordingly. It seems to me that we have a very similar such situation where we have a Federal Reserve chairman who is certainly aware of these numbers, but seems to me, at this point, certainly reluctant to make decisions based on those numbers, but you would expect that to change.

Yeah, well, I mean if you just look at the summary of economic projections that the Federal Open Market Committee… that comes out on a quarterly basis reflecting the consensus of Fed Chair Powell's committee that determines monetary policy, they're looking for real GDP growth of less than two percent per year for the next couple of years, and they're obviously not anticipating any improvement in productivity. So I think you're right, I think Fed Chair Powell is very much aware that productivity can change everything; and, in fact, he's talked about productivity, he knows the equation. He says, “Look, it's okay to have wages growing three percent if inflation's two percent.” Then he implied, therefore, that productivity is growing one percent. So he's basically in the one percent camp, recognizing that, if productivity is more than that, then four percent wage growth is perfectly fine and acceptable and non-inflationary. But at this point he's, in terms of his pronouncements, he's sticking to the kind of standard line of economists, which is, maybe we'll get one percent, and if we get one percent and the Fed gets inflation down, let's say to only two-and-a-half percent, then wages can grow three-and-a-half percent, and right now wages are growing at a little bit above. I think we're growing more like four percent, so the wage numbers aren't there yet, but they could be the right numbers if, in fact, productivity is making a comeback.

If we hit productivity gains of the sort you've talked about—three percent, four percent by the end of the decade—that is a radically different-looking economy than what the Fed, or the CBO, or even a lot of Wall Street firms are talking about. So it's not just this statistic will be different; we're looking at really something very different. I would assume a much higher stock market; I'm not sure what interest rates look like, but what does that world look like in 2030?

These are all good questions, they’re the ones I'm grappling with. I mean, should interest rates be lower or should they be higher? It’s the so-called real interest rates, so if the economy can live with a Fed funds rate of, let's say five and a half percent—five and a quarter, five and a half percent, which is what it is now—and the bond yield at four and a half percent and the economy is doing perfectly fine and inflation's coming down, and it's all because productivity is making comeback, then those rates are fine. They're doing their job, they're allocating capital in a reasonable fashion, and capital is going to get allocated to where capital should go. You mentioned before that, in order to increase productivity, we are going to need more capital investments.

Here the Fed has raised interest rates dramatically, and most of the economists said, “Oh, that's going to lead to a big drop in capital,” because capital spending is dependent on interest rates, and that hasn't happened at all, really, because the technology capital spending—which now, in current dollars, technology capital spending accounts for about 50 percent of capital spending in nominal terms. You can't do it in real terms because there's an indexing problem. But in nominal terms, half of capital spending is technology. And by the way, that's an understatement because that's information technology, hardware, it's software and R&D. It doesn't even include industrial machinery, which is mostly technology, hardware and software these days. And even the trucking industry, the truck is sort of the device, and then there's a software that runs the device logistics. There's so many areas of the economy that have become very high-tech that people still think of as a low-tech industry.

Speedbumps to progress (18:18)

If this doesn't happen. Well, I suppose one thing we could say may have happened is that we've really overestimated these technologies and they're not as transformative. But let me give you two other things that people might point to as being—and you've written a bit about these—that could be speed bumps or barriers. One: debt, possible debt crisis. And two: this energy revolution, climate change transition, which we really have a lot of government involvement and a lot of government making decisions about allocating resources. So what is the risk that those two things could be a slow things down, speed bump, or what have you?

There's three issues that you're raising. One is sort of the private sector issue of whether a lot of this artificial intelligence and technology stuff is hype, and it's not going to have the impact on productivity. The other one, as you mentioned, is the two government issues, government’s meddling in the climate change policies, and then the government having this irresponsible fiscal excesses.

With regards to artificial intelligence, even though I should be a cheerleader on this, because I should say, “See, I told you so…” I have been telling people I told you so because I said, I'll tell you when the stock market started to discount the Roaring ’20s was November 30th, 2022 when Open AI introduced ChatGPT, and that's when these AI stocks went crazy. A week later I signed up for the $20 a month version of ChatGPT, figuring, “This is great! I'm not going to have to work anymore. This is going to do all my writing for me. I'll just ask it the question and say, ‘What do you think we should be writing about this? Go ahead and write about it.’” Well, it took me more time to correct all the errors for what it produced than it would've taken me just to write the damn thing.

So I kind of cooled off to chat GPT, and I come to the conclusion that, from what I see right now in terms of what is available to the public and what's tied to the internet, it's really autofill on speed and the steroids. You know when you type Word and sometimes it guesses what you're going to say next? That's what this thing does at the speed of light. But, you know, “haste makes waste,” as Benjamin Franklin used to say, and it makes a lot of mistakes. And, by the way, garbage in, garbage out. It could create even more garbage on the internet because I've seen situations where it starts quoting its own sources that would never have existed in the first place. So there's some really funky stuff when you have it in the public domain.

But I think that when you have it sort of segmented off and it only has the data that you need for your specific industry, and it's not polluted by other the open source ability to take any data, I think it may very well work very well. But it's basically just a really fast, lightning-speed calculations. So I think it has lots of potential in that regard, but I think there is a certain amount of hype. But look, so much money is being spent in this area. I can't believe it's all going to go for naught. I mean, we saw a lot of money spent in the late 1990s on internet and dotcoms and all that. The internet's still here, but the dotcoms are gone.

With regards to the government policies, I have this very simplistic view that it's amazing how well this country has done despite Washington. Washington just keeps meddling and meddling, it just keeps picking our pockets, keeps interfering, comes up with industrial policies that, to a large extent, don't work. And yet, the economy continues to do well because working stiffs like you and me and people listening in, that's what we do for a living: we work. We don't have time for politics. So the politicians have plenty of time to figure out how to pick our pockets. Well, we have to just figure out, “Okay, given their meddling, how do we make our businesses better, notwithstanding these challenges.” Maybe it's really more my hope that we somehow in the private sector figure out how to keep doing what we're doing so well, including increasing productivity, in the face of the challenges that the government poses with its policies.

But then, if we are successful in the private sector at creating good productivity growth that gives you better real GDP growth, that real growth is one way to reduce the debt burden. It doesn't make it go away and it would be a lot better if we didn't have it, but some of these projections of how this debt is going to eat us all up may be too pessimistic about their assumptions for economic growth. But look… I guess I had a happy childhood, so I tend to be an optimist, but I can't say anything good at all about this deficit problem. And we did get a little glimpse in August, September, October, of what happens when the bond market starts to worry about something like supply. It worried about it for three months, and then lower inflation and less supply of long-term bonds helped to rally the bond market. But here we are back at four and a half percent, and if we do have some more fears about inflation coming back, then we could very well have a debt crisis more imminently. People like Ray Dalio has been saying that we're under verge of getting it. I think it's an issue, but I don't think it's an issue that's going to be calamitous at this time.

The problems people talk about, you have the skepticism about free enterprise, or the skepticism about trade, and immigration. I would like to see what this country looks like in 2030 with the economic scenario you've just outlined: Strong real wage growth. Maybe it's too simplistic, but I think people being able to see in their everyday lives, big gains year after year, I think the national mood would be considerably different.

Well, I think, even now, if you look at real consumption per household, it's $128,000, it's at an all-time record high. And yeah, I guess the rich might be gluttons and might eat more than the rest of us, and maybe they have bigger and more houses and cars, but there just aren't enough of them to really explain how it could possibly be that real consumption per household is at an all-time record high. And I know that's materialistic, but I can't think of a better way to measure the standard of living than looking at real consumption per household: All-time record high.

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Micro Reads

▶ Business/ Economics

Meta, in Its Biggest A.I. Push, Places Smart Assistants Across its Apps - NYT

Google streamlines structure to speed up AI efforts - FT

Tesla’s Layoffs Won’t Solve Its Growing Pains - Wired

▶ Policy

Put Growth Back on the Political Agenda - WSJ

Regulate AI? How US, EU and China Are Going About It - Bberg

Three ways the US could help universities compete with tech companies on AI innovation - MIT

▶ AI/Digital

The AI race is generating a dual reality - FT

Searching for the Next Big AI Breakthrough at the TED Conference - Bberg

These photos show AI used to reinterpret centuries-old graffiti - NS

Environmental Damage Could Cost You a Fifth of Your Income Over the Next 25 Years - Wired

AI now surpasses humans in almost all performance benchmarks - New Atlas

▶ Biotech/Health

A new understanding of tinnitus and deafness could help reverse both - New Scientist

Beyond Neuralink: Meet the other companies developing brain-computer interfaces - MIT

▶ Robotics

Hello, Electric Atlas: Boston Dynamics introduces a fully electric humanoid robot that “exceeds human performance” - IEEE Spectrum

▶ Space/Transportation

NASA may alter Artemis III to have Starship and Orion dock in low-Earth orbit - Ars

▶ Up Wing/Down Wing

Technological risks are not the end of the world - Science

▶ Substacks/Newsletters

Five things to be optimistic about in America today - Noahpinion

Who Governs the Internet? - Hyperdimensional

Meta is Surprisingly Relevant in Generative AI - AI Supremacy

Larry Summers isn’t worried about secular stagnation anymore - Slow Boring

Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.