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. Across decision-making, pricing, and production tasks, we show that social outcomes improve as information diversity increases. We discuss implications for the development, deployment, and use of AI.

Bio: 

Manish Raghavan is the Drew Houston (2005) Career Development Professor at the MIT Sloan School of Management and Department of Electrical Engineering and Computer Science. Before that, he was a postdoctoral fellow at the Harvard Center for Research on Computation and Society (CRCS). His research centers on the societal impacts of algorithms and AI.