Opening Keynote

AI systems are increasingly deployed with promises of improved productivity and decision-making, yet are often implemented onto people rather than designed with them. Emerging evidence shows that 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, priorities, and lived practices. I develop participatory methods that combine (1) co-design approaches, enabling designers, developers, and affected stakeholders to collaboratively reimagine what AI should do, and (2) computational tools that translate stakeholders’ values and priorities into legible, actionable metrics and visualizations. These tools allow non-specialists to shape system behavior—such as fairness and well-being objectives—within their specific organizational contexts. In this talk, I will present applications of these methods across domains, including gig work, knowledge work, and public assistance. Our findings reveal that participatory methods not only uncover novel AI applications that users find legitimate and useful, but also foster critical reflection on workplace practices and priorities. I conclude by outlining open challenges and a future research agenda for participatory AI systems and governance.