Accelerated research about generative AI
Emerging insights suggest road maps, policy recommendations, and calls for action regarding generative artificial intelligence.
Faculty
Manish Raghavan is the Drew Houston (2005) Career Development Professor and an Assistant Professor of Information Technology at the MIT Sloan School of Management.
Manish was most recently a postdoctoral fellow at the Harvard Center for Research on Computation and Society (CRCS), working with Cynthia Dwork.
He completed his PhD at the computer science department at Cornell University, advised by Jon Kleinberg. His research studies the impacts of computational tools on society with a focus on decision-making, behavioral economics, and hiring algorithms.
Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan. In Proceedings of the 2022 ACM Conference on Economics and Computation, New York, NY: July 2022. Download Paper.
Emily Black, Manish Raghavan, and Solon Barocas. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, New York, NY: June 2022. Download Paper.
Jon Kleinberg, Sigal Oren, Manish Raghavan, Nadav Sklar. In Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, edited by Cassio de Campos, Erik Quaeghebeur, and Marloes H. Maathuis. Portland, Oregon: July 2021. Supplementary PDF. Download Paper.
Kleinberg, Jon, and Manish Raghavan. Proceedings of the National Academy of Sciences Vol. 118, No. 22 (2021): e201834011. Download Paper.
Jessie Finocchiaro, Roland Maio, Faidra Monachou, Gourab K Patro, Manish Raghavan, Ana-Andreea Stoica, and Stratis Tsirtsis. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, New York, NY: January 2021. Download Paper.
Kleinberg, Jon, and Manish Raghavan. ACM Transactions on Economics and Computation Vol. 8, No. 4 (2020): 1-23. arXiv Preprint.
Emerging insights suggest road maps, policy recommendations, and calls for action regarding generative artificial intelligence.
Assistant Professor Manish Raghavan wants to teach his students how to make good business decisions about deploying (or not deploying) AI-based products and services.
“There’s a finite number of jobs that you know about. There are more you don’t.”