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.
Raghavan, Manish, MIT Sloan Working Paper 7186-24. Cambridge, MA: MIT Sloan School of Management, December 2024.
Alur, Rohan, Loren Laine, Darrick K. Li, Dennis Shung, Manish Raghavan, and Devavrat Shah, Working Paper. October 2024.
Suriyakumar, Vinith M., Rohan Alur, Ayush Sekhari, Manish Raghavan, and Ashia C. Wilson, Working Paper. October 2024.
Kleinberg, Jon, Sendhil Mullainathan, and Manish Raghavan. Management Science Vol. 70, No. 9 (2024): 6336-6355. Cornell Chronicle.
Cynthia Dwork, Chris Hays, Jon Kleinberg, and Manish Raghavan. June 2024. arXiv.
Alur, Rohan, Manish Raghavan, and Devavrat Shah, Working Paper. May 2024.
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.”
An exciting collaboration between MIT's Sloan School of Management and Schwarzman College of Computing, this immersive, two-week program on campus dives deep into both the technical and business aspects of artificial intelligence, providing a comprehensive understanding of AI's impact across industries. The program will bridge the gap between AI technology and business leadership through practical, hands-on learning experiences, ensuring participants can apply AI strategies effectively in their organizations.