Lirong XiaLink opens in a new windowLink opens in a new window (Rensselaer Polytechnic Institute)

Title: AI-Powered Group Decision Making

Abstract: Making fair, efficient, and trustworthy collective decisions for groups of agents has been a significant concern among the public across a wide range of scenarios, such as elections, public policy making, recommender systems, crowdsourcing, and blockchain governance. Unfortunately, in many cases, the architectures and mechanisms are suboptimal and fall far below people’s expectations.

In this talk, I will present our work on the theory and practice of building AI-powered group decision making systems to improve fairness, efficiency, and trustworthiness in the processes of modeling, learning, and aggregation of preferences. Our approach is highly multi-disciplinary and based on leveraging principles, ideas, and methodologies from disciplines including behavioral sciences, economics, political science, statistics, and computer science. Specifically, in addition to presenting the overall AI-powered framework, I will talk about leveraging ideas in statistics to improve trustworthiness of the interpretation of preference models, leveraging ideas in economics to improve statistical efficiency and computational efficiency of preference learning, leveraging ideas in computer science to circumvent impossibility theorems in economics and political sciences, and bridging theory and practice via the open-source Online Preference Reporting and Aggregation (OPRA) system.

Bio: Lirong Xia is an associate professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI). Prior to joining RPI in 2013, he was a CRCS fellow and NSF CI Fellow at the Center for Research on Computation and Society at Harvard University. He received his Ph.D. in Computer Science and M.A. in Economics from Duke University. His research focuses on the intersection of computer science and microeconomics. He is the recipient of an NSF CAREER award, a Rensselaer James M. Tien'66 Early Career Award, and was named as one of "AI's 10 to watch" by IEEE Intelligent Systems.