Seminar: AI Alignment in the Provision of Social Services: Opportunities and Challenges
Sanmay Das
Professor of Computer Science
VT Institute for Advanced Computing
Friday, September 5, 2025
2:30 - 3:45 p.m.
Academic Building One, Room 3130
Abstract
Artificial intelligence and machine learning are increasingly used to aid decision-making about the allocation of scarce societal resources, for example housing for homeless people, organs for transplantation, and educational supports for K-12 students. What does it mean for these systems to be "aligned" with human preferences? In practice, this involves attempts to achieve some combination of fairness, efficiency, and incentive compatibility, depending on the preferences of some set of stakeholders. In this talk I will give an overview of my group's research in this space, informed by the theories of local justice and of street level bureaucracy. I will discuss our work on characterizing and analyzing the efficiency, the fairness, and the distributive justice implications of human, machine, and human+machine decision-making in public service provision, with a particular focus on resources that serve those experiencing, or at high risk of, homelessness. I will give a peak into theoretical, empirical, and experimental results, and discuss where I think AI can be most helpful, as well as significant human and technical challenges.
Biography
Sanmay Das is a professor of computer science in the College of Engineering and the associate director of artificial intelligence (AI) for social impact at the Sanghani Center for Artificial Intelligence and Data Analytics at the Virginia Tech Institute for Advanced Computing. He is chair of the ACM Special Interest Group on Artificial Intelligence, a member of the DARPA ISAT Study Group, and an emeritus member of the board of directors of the International Foundation for Autonomous Agents and Multiagent Systems. He serves as an associate editor for the ACM Transactions on Economics and Computation, the Journal of Artificial Intelligence Research, and Autonomous Agents and Multiagent Systems, and also as an arXiv moderator. He has served as program co-chair of AAMAS and of the AAAI/ACM Conference on AI, Ethics, and Society, and as Associate Program Chair for IJCAI. He has been recognized with awards for research, teaching, and service, including a National Science Foundation CAREER Award, the Department Chair Award for Outstanding Teaching at Washington University, and the Outstanding Service Award from the Computer Science Department at George Mason University. He was selected as an ACM Distinguished Member in 2023 for contributions to AI and economics, AI for social good, and for service to the profession. He has also worked with the US Treasury department on machine learning approaches to credit risk analysis and occasionally consults in the areas of technology and finance.