AI-enabled systems that are responsible and human-centered, will be powerful partners to humans in the very near future. UX research (UXR) is necessary to create systems that people are willing to be responsible for. This talk describes the UXR skills and methods that are needed for proper data identification and preparation, bias identification, prevention of harm, human-machine interaction design and prototyping, and the critical oversight activities needed for dynamic AI systems to continue to be effective.
These UXR skills and methods support creation of AI-enabled systems that responsibly augment human abilities. AI-enabled systems that provide appropriate evidence of system capabilities and integrity will support calibrated trust (an individual’s balanced view of the risks and rewards of collaboration), and UXR informs what is appropriate in each context, how the AI system will augment the experience, and how the dynamic nature of the experience will be managed. This session will introduce each of these complex topics and provide references for further exploration of these exciting issues.