Algorithmic Decision Making and Society

The Algorithmic Decision Making and Society group designs and analyses algorithms that make decisions for groups of individuals with competing interests. As algorithms increasingly shape our lives, we study and formalize what characterizes good and fair decision making. Our research spans multiple disciplines, including the aggregation of preferences into collective decisions (studied in social choice), individual and group fairness in AI selection systems, and the (sequential) allocation of scarce resources in areas like public health. Our interdisciplinary approach integrates AI, combinatorial optimization, economics, game theory, and reinforcement learning to create theoretically grounded systems with a positive societal impact.