Participatory AI: Designing and Governing AI with Stakeholders

Abstract: AI systems are increasingly deployed with promises of improved productivity and decision-making, yet are often implemented onto people rather than designed with them. This approach can lead to unrealized benefits, harmful biases, and distrust. In my research, I propose Participatory AI, a set of methods and tools that bring affected stakeholders directly into the design and governance of AI systems to better align AI with human values and lived practices. I develop participatory methods that combine co-design, through which stakeholders collaboratively reimagine what AI should do, with computational tools that translate their values and priorities into actionable system objectives. Together, these approaches enable non-specialists to shape AI behavior within their organizational contexts. Speaker Bio: Min Kyung Lee is an Associate Professor in the School of Information at the University of Texas at Austin and director of the Human-AI Interaction Lab. Her research develops human-centered and participatory approaches to AI, with a particular focus on algorithmic management, AI governance, and the social implications of AI in workplaces and communities. She has conducted some of the earliest empirical studies of algorithms’ emerging roles in management and developed methods that enable stakeholders to participate directly in the design and governance of AI systems. Her work has received the Allen Newell Award for Research Excellence, multiple best paper awards and honorable mentions, and support from the National Science Foundation and other organizations. She received her PhD and MS in Human-Computer Interaction and MDes in Interaction Design from Carnegie Mellon University.