Time
Friday, 10/30/20 at 12:00 PM - 1:00 PM (Central)
Title
Fair and Participatory AI
Abstract
As artificial intelligence (AI) is transforming work and society, it is ever more important to ensure AI systems are fair and responsible and can gain societal trust. In this talk, I argue that building procedurally-fair and participatory AI is critical to achieving this vision. I will first present empirical findings on people’s experiences with and fairness perceptions of resource allocation algorithms, and considerations for enabling procedural fairness in AI. Then, I will present WeBuildAI, a participatory framework that enables people to build algorithmic policy for their communities. In our case study with a nonprofit, 412 Food Rescue, we applied the framework to a matching algorithm that operates an on-demand food donation transportation service in order to adjudicate equity and efficiency trade-offs.
Bio
Min Kyung Lee is an assistant professor in the School of Information, the University of Texas at Austin. Dr. Lee has conducted some of the first studies that empirically examine the social implications of algorithms’ emerging roles in management and governance in society. She has extensive expertise in developing theories, methods and tools for human-centered AI and deploying them in practice through collaboration with real-world stakeholders and organizations. She developed a participatory framework that empowers community members to design matching algorithms that govern their own communities. Her current research is inspired by and complements her previous work on social robots for long-term interaction, seamless human-robot handovers, and telepresence robots. Dr. Lee is a Siebel Scholar and has received the Allen Newell Award for Research Excellence along with research grants from NSF and Uptake. She received a PhD and a MS in Human-Computer Interaction and an MDes in Interaction Design from Carnegie Mellon University and a BS from the Korea Advanced Institute for Science and Technology (KAIST).