Faculty
Neil Thompson is an Innovation Scholar at MIT’s Computer Science and Artificial Intelligence Lab and the Initiative on the Digital Economy. He is also an Associate Member of the Broad Institute.
Previously, he was an Assistant Professor of Innovation and Strategy at the MIT Sloan School of Management, where he codirected the Experimental Innovation Lab (X-Lab), and a Visiting Professor at the Laboratory for Innovation Science at Harvard University. He has advised businesses and government on the future of Moore’s Law and Machine Learning, and has been on National Academies panels on transformational technologies and scientific reliability.
He did his PhD in business and public policy at UC Berkeley, where he also did Master's degrees in computer science and statistics. He has a Master's in economics from the London School of Economics, and undergraduate degrees in physics and international development. Prior to academia, he worked at organizations including Lawrence Livermore National Laboratories, Bain and Company, The United Nations, the World Bank, and the Canadian Parliament.
Kuhn, Jeffrey M., and Neil Thompson. International Journal of the Economics of Business. Forthcoming.
Lashkari, Danial, Wensu Li, Christina Qiu, and Neil Thompson, MIT Sloan Working Paper 7381-26. Cambridge, MA: MIT Sloan School of Management, July 2026.
Thompson, Neil C., and Douglas Hanley, MIT Sloan Working Paper 5238-17. Cambridge, MA: MIT Sloan School of Management, September 2017.
Thompson, Neil. 2012.
Thompson, Neil. 2012.
Thompson, Neil. 2012.
AI performance is improving across many workplace tasks broadly, not in sudden shocks, new MIT research finds. That cadence gives companies and workers time to prepare for task-level displacements.
Which AI risks could cause the most harm in the next five years? New MIT research shows that businesses should be aware of threats like competitive pressure and dangerous AI capabilities.
"All of them know that they're playing a bad game," said principal research scientist Neil Thompson. "This is a game where they know that if everybody continues to race as fast as they can, we're going to continue to accumulate these dangerous capabilities in a way that is a problem. But they also know that unilaterally they can't change that game."
A report out this week from principal research scientist Neil Thompson and co-authors set out to measure how AI is changing the economics of science in a variety of fields and, in the process, pointed to places where it still stalls. About 44 percent of scientists surveyed said that, over the past two years, their main research bottleneck had shifted downstream, toward later stages such as physical experimentation and data collection. Forty-one percent said their backlog of untested hypotheses had grown.
Principal research scientist Neil Thompson joined Yahoo Finance's "Market Domination" to discuss the real threats AI could pose, following public claims by Jacob Coxon, a former Anthropic researcher, who said AI could lead to the extinction of all humans by 2030.
Turning a company into an agentic enterprise isn't just a tech upgrade — it's a massive economic bet in compute, talent, and time. Should businesses go all in from day one, or build it out in stages? On this podcast episode, principal research scientist Neil Thompson discussed the smartest way to place that bet.
This in-person course, led by MIT Professor Andrew W. Lo, provides a practical, executive-level exploration of how AI and machine learning are reshaping the financial industry. Participants will gain a foundational understanding of AI’s evolution—from early machine learning to the current LLM era—before diving into real-world applications across the buy side, sell side, banking, insurance, and risk management sectors. Through interactive sessions, case studies, and guest lectures from leading practitioners and researchers, executives will examine the capabilities and limitations of today’s AI tools and consider how emerging innovations will forge the next generation of FinTech.
