Manish Raghavan


Manish Raghavan

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Affiliated MIT Sloan Group

MIT Department

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.


"The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization."

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.

"Model Multiplicity: Opportunities, Concerns, and Solutions."

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.

"Stochastic Model for Sunk Cost Bias."

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.

"Algorithmic Monoculture and Social Welfare."

Kleinberg, Jon, and Manish Raghavan. Proceedings of the National Academy of Sciences Vol. 118, No. 22 (2021): e201834011. Download Paper.

"Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness."

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.

"How do Classifiers Induce Agents to Invest Effort Strategically?"

Kleinberg, Jon, and Manish Raghavan. ACM Transactions on Economics and Computation Vol. 8, No. 4 (2020): 1-23. arXiv Preprint.

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Ideas Made to Matter

Accelerated research about generative AI

Emerging insights suggest road maps, policy recommendations, and calls for action regarding generative artificial intelligence.

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Making Good Business Decisions About AI

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.

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