Data Democratization: Stories about data, AI and privacy

Ville Sointu is leading the Emerging Technologies team at one of Europe's biggest banks, Nordea. In this episode, he shares his advice and insights about adopting new technologies in famously conservative financial environments. Ville is also a host of the podcast entitled Fintech Daydreaming where he covers fintech topics with his guests from the financial sector. 

In this episode we talked to a prominent scientist from the data privacy field, Yves-Alexandre de Montjoye. He is an assistant professor at the Imperial College London, leading the Computational Privacy Group. A lot of fascinating privacy questions came up about behavioral data, k-anonymity, differential privacy and meaningless privacy guarantees that mask true risks. We talked about the way forward and how true data privacy can be created in practical terms. Tune in for an enlightening conversation that puts a lot of greys into the seemingly black and white world of data privacy!   

The recently announced Transatlantic Data Privacy Framework will foster data flows between the US and the EU, addressing the concerns raised by the Schrems II. decision. The US-made an unprecedented commitment to strengthen the privacy protection applicable to US signals intelligence activities within the new framework. New safeguards will be implemented to protect citizens' rights while advancing cross-border data flows. The next step is to translate this framework agreement into legal documents that will be put into practice on both sides of the Atlantic. But what does this mean for data privacy in practice? What are the major challenges, and what can we expect in the long run? We spoke to J. Scott Marcus, Senior Fellow at the EU's economic think tank, Bruegel, about the history and future of transatlantic data flows.
Read on to learn how synthetic data can solve cross-border data sharing!

We talked to an amazingly experienced and visionary test engineer to find out all about her challenges and inspirations. Alexandra and Maaret covered a lot of ground in the testing landscape, from everyday testing challenges to best practices and to visions of the future. According to Maaret, testing is about breaking illusions and we couldn't agree with her more. Testing is also like singing. Why? Tune in to find out! 

What does it take to create effective digital policies? Why does the AI Act only go half-way - and what else needs to happen to ensure meaningful regulation of AI? How could the EU and the US overcome the challenges of negotiating transatlantic dataflows? And why should the EU might consider to stop relying on the Brussels Effect and instead get down on the negotiation table? Tune in to this conversation with Andrea Renda, a Senior Research Fellow at the Center for European Policy Studies (CEPS) and Advisor to the European Parliament, to learn more about the geopolitical battle on data, AI and digital policies.

What's synthetic data's future, and what's behind the synthetic data hype? This episode is all about synthetic data. We spoke to Tobi Hann, CEO of MOSTLY AI, the world's leading synthetic data company about the opportunities and challenges surrounding this important data tool. MOSTLY AI's recent Series B funding round is the biggest investment for synthetic data in Europe to date. What is synthetic data? It's an emerging privacy enhancing technology that enables privacy-preserving data usage, improves machine learning models and allows realistic testing. In short: a data democratization tool. Listen in to find out all about why the future is synthetic. 

To celebrate Data Privacy Day 2022, we talked to the godfather of GDPR, Paul Nemitz, about how bigtech threatens democracy, the role law can play in protecting people and societies from adverse effects of technology and why it's time to regulate AI. Tune in to learn more about the upcoming European AI act and find out what role synthetic data is likely to play in this regulated future! 

Axel Voss is  leading the Special Committee on Artificial Intelligence in the European Parliament. He's been working on a report outlining important policy recommendations for the upcoming European AI regulations. Among other things, Axel talked to us about:

• why the GDPR is due for an update
• what the future of data protection holds
• how the EU should compete globally in AI and digital innovation
• why access to high-quality data is so important 
• how synthetic data can help bridge the gap between data protection and data-driven innovations
• what the upcoming European AI-regulation will look like

If you would like to learn more about the legislative privacy landscape around GDPR and the upcoming AI regulations, listen to one of our previous conversations with Axel von dem Bussche, GDPR, the new European AI regulation, and the privacy landscape. 

Denis Rothman has been an AI practitioner since the dawn of this technology. Denis shares his ideas on the origins of explainable AI, its necessity, the way forward for model agnostic explainable AI and the challenges of natural language processing. 

What does the future hold for the insurance industry? In the latest episode of the Data Democratization Podcast, our host, Alexandra Ebert talked to David Marock, a seasoned insurtech, fintech and proptech expert from London. David shared his insights on the state of AI in the insurance industry and what are the current trends developing in the insurtech space. In this episode you will hear about AI opportunities in insurance, why traditional insurance companies are tech hesitant, how to overcome the tech inertia in insurance organizations, how regulatory pressure is changing minds about digital transformation, why fairness is critical for insurance companies, how synthetic data solves data access and privacy issues, what to do about less tech-savvy business leaders and why the future of insurance will be driven by new technologies. 

Take an organizational deep-dive into the topic of responsible AI with Maria Axente, PwC's Responsible AI lead! You'll hear lots of hands-on advice for decision makers looking to make their company's AI adoption a success from hiring decisions, organizational structures and the new AI mindset of pause and reflect. 

Clara is a director at IEEE, the world's largest technical organization  founded by Tesla and Edison more than 100 years ago. Today, she is working on developing an ethically aligned design framework to help companies develop safe and effective AI systems. Listen to the 20th episode of the Data Democratization Podcast to find out what the difference is between standards and certifications, what the role of values is in ethically aligned design and what synthetic data and fresh Alpine spring water have in common! 

In this episode, Alexandra Ebert, MOSTLY AI's chief trust officer will be talking to one of the founders and the chief data scientist of MOSTLY AI. If you are looking to get a behind-the-scenes view of how data privacy is implemented in practice, you are in the right place! You won't need a math Ph.D. to finally understand how privacy is measured and what is takes to protect personal data. Klaudius is also a huge fan of the concept of open data and talks about how synthetic data is the way forward for realizing the potential of open data sharing for research and innovation. 

Lisa Palmer is the chief technical advisor of Splunk, the popular data platform designed to remove barriers between data and action. Besides working for Splunk, she is a university professor, a podcast host, and an author. She spent years at Microsoft, Gartner, and Teradata, building up her unique perspective on data and technology-related business opportunities. In this episode, Lisa shares her most exciting insights and data stories around tackling real-life problems with data, including wildfires and F1 racing, how privacy-enhancing technologies like homomorphic encryption and synthetic data can be used for social good, why we need truly complete datasets to address biases, the role synthetic data plays in ethical AI and bias mitigation, how to increase diversity, especially in tech and how to think about data opportunities in times of disruption and opportunity.
Check out the transcript for this episode and all previous episodes of the Data Democratization Podcast at our website! 

In the latest episode of the Data Democratization Podcast, Jim Hu, MOSTLY AI's Data Engineer, talks about the most exciting synthetic data engineering he has been busy doing. Synthetic data is quickly becoming a must-have engineering tool across industries, with new use cases emerging every day. If you want to learn how to leverage synthetic data in insurance and banking, listen to the episode! Learn to maximize synthetic data's business impact:

• how to increase profit margins in insurance using synthetic data
• how to maximize the lifetime revenue of a loan
• how to detect suspicious transactions and prevent fraud
• how to estimate credit risk using machine learning
• how to unlock transaction data for AI training
• why synthetic data is superior to legacy data anonymization techniques
• optimize software testing processes
• create personalized banking experiences

Claudette McGowan is an award-winning technology leader with a real passion for cybersecurity. In this episode of the Data Democratization Podcast, she shares her personal journey to the cybersecurity field as well as her perspective on the current state of cybersecurity. Listen to the episode to learn more about how the pandemic changed the threat landscape, how companies should prepare for cyberattacks, how data should be managed for maximum security, what is a zero-trust approach, the importance of privacy-safe data sharing, why data literacy is important, why cybersecurity is an amazing career option and where you can learn about cybersecurity. Also, don't forget to check out Claudette's podcast, the Cyber Suite, to elevate your everyday cyber literacy!  

Scott, the Data Whisperer, knows a thing or two about proper data management. If you are in the business of making large scale data projects happen, make sure you listen to this episode and learn about creating visibility and getting executive buy-in for your data projects. Find out how to set your data projects up for success from the beginning through master data, metadata, data governance and data stewardship and get great tips on how to tell great data stories. 

Amir Tabakovic has lots of experience in developing banking products, and as a chairman of the AI and Data Privacy Experts Group at Mobey Forum, he has a very good overview of privacy best practices and the most common mistakes in the banking industry. Listen to this episode to learn about how to develop customer-centric banking products and take them to market? How can traditional banks compete with neobanks?  What is privacy-enhancing technology? How should banks leverage privacy tech for success? Which privacy technology to choose when? How to make privacy-by-design happen from an organizational point of view? What is the difference between pseudonymization and anonymization? What's the problem with legacy anonymization technologies?

Amir and his team at Mobey Forum recently published a report entitled The Digital Banking Blindspot: Emerging Privacy Enhancing Technologies. Download the report if you would like to get a detailed overview of how privacy tech is changing the banking industry!

To learn more about synthetic data, visit MOSTLY AI's Synthetic Data Blog! 

Behrang Raji is a data privacy officer for the Hamburg Commissioner for Data Protection and Freedom of Information. He is right where legislation happens, knows what drives regulators and has a pretty good understanding of trends and the larger regulatory landscape. Listen to this episode if you are curious about the upcoming European AI regulations, fairness in law and how synthetic data helps fix biases and test AI systems, the most common data anonymization mistakes, data anonymization standards and compliance strategies that really work. 

NVIDIA is famous for its graphics cards, but NVIDIA's story is so much bigger than this. Their graphics cards have been used to accelerate AI and data science, and now they offer a whole ecosystem of services and tools for companies ready to make AI happen. Listen to the episode to learn about the top AI use cases in finance and insurance and how to make those happen. Questions you will get answers for in this episode: How to implement AI successfully? How does NVIDIA help democratize AI? How to automate explainability? How is synthetic data used for evaluating and supervising AI models? What does the future of AI hold for financial institutions? 

Nancy Nemes is an AI expert with 20 years of hand-on experience in implementing frameworks as a leader at Microsoft and Google. She is the founder of HumanAIze, an organization that aims to make AI more inclusive. If you are looking for some practical advice on how to implement responsible AI at the moment, then look no more – In this episode you will learn about all the necessary steps to perform ethical AI. What are the most important ethical AI best practices? What does the regulation aspect mean for the financial sector? What kind of skills are necessary to adapt to this AI-driven environment? How to identify the right metrics for understanding privacy and fairness when developing AI systems? Which kind of privacy enhancing technologies should you implement? Who are the experts that you should gather? Learn the answers to these by following the best, expert, practices!

Nicolas Passadelis is a lawyer and privacy expert who has been leading the Data Governance team at Swisscom for over four years. In this episode of the Data Democratization Podcast, Nicolas shares his best practices of data governance and provides real-life examples of how Swisscom's data ethics board works. The episode contains an amazing collection of actionable takeaways and great answers to the big questions of data governance. For example, how to implement data governance in an enterprise setting successfully? How to automate and scale compliance? How to self-assess your data protection practices? What is data ethics? How to create a data ethics framework? How to create a data ethics board? What are the six ethics principles for assessment at Swisscom? Listen to the episode and reach out to us with your own solutions to these questions by sending a voice recording to [email protected]!
Read the transcript! 

Paul Tiwald has been part of the MOSTLY AI team since the beginning. He is the mastermind behind the team's research into fairness and the idea of fair synthetic data. 

In this episode, you will hear about: 

• what it's like to work in the field of artificial intelligence (spoiler: it's really fun!)
• how the idea of fair synthetic data came up
• how to create machine learning models that are private and fair by design
• why is it so challenging to remove bias from an algorithm
• what are proxy variables, and why are they dangerous
• what is the definition of fairness, and why do we need one in the first place
• how should companies start implementing fairness and ethical approaches into their AI development
• why it's impossible to fix bias without fair synthetic data and algorithmic fairness

We talked to one of Europe's most renowned GDPR and data experts, who shared his insights about the regulatory landscape in Europe and elsewhere and gave excellent advice for lawmakers and companies. 

In this episode, you will hear more about:

• recent regulatory developments, including Schrems II, GDPR, and the new AI-regulation proposal from the European Court of Justice
• why regulation is necessary and timely for AI
• what companies should do in light of these recent developments
• how, according to Axel's prediction, we'll end up with 20 GDPR-like laws
• how to make regulation less complex and easier to comply with
• how to develop a successful data strategy and to turn data privacy into a competitive edge through know-how, proactivity, and risk assessments 
• why 95% of data transfers became illegal after Schrems II and that companies need to map all of their cross-border data transfers to comply with regulations
• how synthetic data can help, since it's exempt from GDPR and Schrems II

In this action-packed episode, John Frushour, Deputy Chief Information Security Officer at New York-Presbyterian Hospital, shares his best frontline data stories. And data stories don't get any more frontline than his. From fighting the opioid crisis to the COVID-19 emergency in New York, John and his team accomplished superhuman achievements with data. 

In this episode, you will hear more about:

• the most useful leadership, data, and technical skills for CISOs
• how DevOps teams operate and how they mature with data science and automation
• balancing data protection with data access in a healthcare setting
• advanced analytics use cases: tracking opioids and sensor data in the ICU
• the COVID-19 challenge in New York 2020 from a CISOs perspective
• using synthetic data for AI/ML
• AI and data regulations from a CISO's perspective in 2021
• how to increase diversity in cybersecurity teams
• tips for keeping your data safe and secure and for finding the best tequila in town

Ryan is a Senior Data Scientist at Spotify with extensive experience in developing great
customer-centric products with the power of data. He is a data consultant and university
lecturer, passionate about data science and understanding the business side of things.
In this episode you will hear about:

• How to start building data infrastructure in your organization, no matter the size.
• How to embed data best practices in your team and how to get the most value out of data science.
• Actionable advice on how to scale machine learning in your organization through making data accessible and automating data access processes.
• Data protection is a true differentiator in today’s market. You don’t need to use
  personal data for data science and fake users are better than real ones for testing your
  ideas.

Punit Bhatia was the Privacy and Protection Officer at ING and has tons of experience in managing privacy and data protection in large international environments. In this episode, Punit shares his best strategic advice for those looking to strategize privacy in their organization. 

You will hear about:

• the three biggest privacy challenges for enterprises and their solutions
• whose responsibility should privacy be in an organization for best results
•  why synthetic data is the way forward in data-sharing
• how to approach AI from a privacy and data protection standpoint
• what should companies expect in the privacy space in 2021 and beyond

In the fourth episode of the Data Democratization pod, we are talking to Sang Shin, serial entrepreneur, investment expert about his adventures in data monetization and he'll share his vision for the future of the data and privacy space. 
Topics discussed in the episode:

• How Been Choice, a privacy protection and data monetization app was banned by Apple
• What is the data privacy landscape like in Southeast Asia in 2021
• What are some notable privacy tech innovations
• How synthetic data made a datathon possible with data from both the private and public sector
• What the future holds for tech innovations and why the open data movement is gaining momentum

In this episode, we will be exploring best practices around digital transformations in banking. Rebecca has decades of experience in leading financial institutions and led major transformations during her career. She has a unique, executive-level perspective to share with us about processes, data management, and how AI can be used for fairness. You can find Rebecca through her website.

Our second guest on the show is Nada Bseikri, a privacy pro from Apple Bank, New York. Nada has a unique perspective: she has both a legal and a software engineering background. Thanks to this double role, she can share unique insights into the field of data privacy. Nada shares her best tips for making privacy go beyond compliance, and we'll find out why privacy carrots are important. 

What better way to celebrate Data Privacy Day than to have an awesome chat with a seasoned privacy professional who has been in the frontlines of privacy since the dawn of days? Shampa Chatterjee shares her great adventures around the world and in the service of others, as well as her best advice to those looking to create success stories in the field of data privacy. We discussed customer-centricity, privacy tech, automation, synthetic data, and more.