Manish Raghavan, Drew Houston (2005) Career Development Porfessor at the MIT Sloan School of Managaement and Department of Electrical Engineering and Computer Science
Friday, May 16, 2025 1:30 - 3:00pm
Abstract
AI systems often consist of multiple actors or agents with different goals, incentives and critically, information. In this talk, we explore the role that heterogeneous information plays in AI systems. We examine (1) how differences in information between humans and AI impact clinical decision-making, and (2) how homogeneous information impacts competition between users of similar AI systems.
Biography
Manish Raghavan is the Drew Houston (2005) Career Development Porfessor at the MIT Sloan School of Managaement and Department of Electrical Engineering and Computer Science. Before that, he was a postdoctoral fellow at the Harvard Center for Reseach on Computation and Society (CRCS). His research centers on the societal impacts of algorithmic decision making.