The UC Davis Center for Poverty & Inequality Research is pleased to announce our upcoming conference,  Artificial Intelligence and Social Inequality, which will take place on Tuesday, March 17, 2026 from 9:00am to 4:00pm at the UC Student and Policy Center, (1115 11th Street), just steps away from the State Capitol.

As AI systems become increasingly integrated across employment, education, public services, and healthcare, a critical question emerges: How will AI affect existing socioeconomic, health, and opportunity gaps? This conference will convene an international slate of academic researchers, members of the policy community, and industry representatives for a day of research presentations, keynote talks, and meaningful dialogue. California sits at the intersection of technological innovation and progressive policy leadership, making Sacramento an ideal location for this critical conversation. Our conference provides a unique forum where researchers studying AI’s impacts can directly engage with those shaping its regulation and deployment.

Lunch, coffee/tea, and light refreshments will be provided. Please complete the online registration form to reserve your seat at this timely and exciting event.

Keynote Speakers
 Dr. Genevieve Smith is the Founding Director of the Responsible AI Initiative at the UC Berkeley Artificial Intelligence Research Lab (BAIR), a member of the Professional Faculty at Berkeley Haas, and a postdoctoral research fellow at Stanford University. She received her PhD from the University of Oxford where her research examined societal impacts of fintech AI tools. She is also a research affiliate at the Minderoo Centre for Technology & Democracy at Cambridge University and a research affiliate at the Technology & Management Centre for Development at University of Oxford. She recently served as the Interim Co-Director of the UC Berkeley AI Policy Hub and was the Responsible AI Fellow at USAID. Her research and work has been published in journals such as Big Data & Society and California Management Review, as well as shared in Wall Street Journal, Forbes, Social Stanford Innovation Review, the Economist and more. Her research has been presented and published in proceedings of leading conferences including the International Conference on Machine Learning (ICML), the ACM Conference on Fairness, Accountability & Transparency (FAccT), and the Academy of Management