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.
A recent MIT FutureTech report on AI risk drew responses from 272 specialists, including professor Jackson Lu, research scientist Peter Slattery, and principal research scientist Neil Thompson. "These findings are a call to arms for those building and governing AI to make sure the worst outcomes do not occur," said Thompson.
Artificial intelligence could transform the economy faster than any previous technology, and policymakers must move equally quickly to figure out how to respond, a group of economists and researchers are warning. The statement, titled "We Must Act Now,"was signed by nearly 200 people, including 15 Nobel laureates. MIT Sloan signatories are Institute Professor Daron Acemoglu, professor Sinan Aral, assistant professor Michiel Bakker, research scientist Christian Catalini, Professor Emeritus Bengt Holmström, professor Simon Johnson, professor Thomas W. Malone, professor Scott Stern, and principal research scientist Neil Thompson.
Joseph Briggs, who leads the global economics team at Goldman Sachs Research, said on a recent episode of the bank's "Exchanges" podcast that he expects about 9% of the US workforce to be displaced as AI is adopted across the economy. Speaking on the same podcast, principal research scientist Neil Thompson said most jobs can be partly automated by AI rather than eliminated, and the outcome depends on which tasks machines take over. AI, in his framing, is a "rising tide" workers can see coming and adapt to, not a "crashing wave" that sweeps them away.
Institute Professor Daron Acemoglu said: "AI is more likely to replace than augment jobs in the near term. But the scale of job losses won't be anywhere close to the very large layoffs some are predicting." Principal research scientist Neil Thompson said AI's technical capability alone does not guarantee widespread job losses. "The impact AI ultimately has on the labour market may not be nearly as large as its impressive capabilities suggest," Thompson said.
