Anand Shah is a fourth-year PhD candidate at MIT Sloan focused on studying the economics of AI, advised by Parag Pathak, John Horton, and David Parkes.
His research asks how AI is reshaping core institutions and how those institutions should be redesigned in a world of ubiquitous AI use. * In the legal system, he authored the first large-scale evidence of generative-AI use by self-represented litigants in U.S. federal courts, covered in the media by the New York Times, the Washington Post, NPR, and the Economist, among others. * In education, he is currently investigating the optimal design of education under AI as a graduate researcher at Blueprint Labs. * In the acceleration of social sciences, he has authored two works investigating the uses and limits of LLMs in producing synthetic data. * And in governance, he has worked on designing personalization infrastructure — how people can control the personal context their AI agents will use via interoperable, user-centered systems.
Before MIT, Anand was a research professional at Chicago Booth working with Eric Budish and Jacob Leshno. He graduated from the University of Chicago with a B.S. in Mathematics and a B.A. in Economics (with Honors), where he was awarded the Economics Department's David S. Hu Undergraduate Thesis Award for market design work in de-escalating political fundraising. As service, Anand has also served two terms on the board of the Young Jains of America, a nonprofit serving more than 10,000 young Jains across the United States. In his free time, he likes to box, listen to podcasts dangerously fast, and go on Chipotle runs with the nearest willing friend. Please feel free to reach out at avshah@mit.edu.