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Learn More About Neil Thompson
Neil Thompson is the Director of the FutureTech research project at MIT’s Computer Science and Artificial Intelligence Lab and a Principal Investigator at MIT’s Initiative on the Digital Economy.
Previously, he was an Assistant Professor of Innovation and Strategy at the MIT Sloan School of Management, where he co-directed the Experimental Innovation Lab (X-Lab), and a visiting professor at the Laboratory for Innovation Science at Harvard. Thompson has advised businesses and government on the future of Moore’s Law, has been on National Academies panels on transformational technologies and scientific reliability, and is part of the Council on Competitiveness’ National Commission on Innovation & Competitiveness Frontiers.
Thompson has a PhD in Business and Public Policy from Berkeley, where he also completed master’s degrees in computer science and statistics. In addition, he holds a master’s in economics from the London School of Economics as well as undergraduate degrees in physics and international development. Prior to academia, Thompson worked at organizations such as Lawrence Livermore National Laboratory, Bain and Company, the United Nations, the World Bank, and the Canadian Parliament.
Neil Thompson is available to advise your organization via virtual and in-person consulting meetings, interactive workshops and customized keynotes through the exclusive representation of Stern Speakers & Advisors, a division of Stern Strategy Group®.
The Economic Realities of Artificial Intelligence
As powerful artificial intelligence systems continue to improve and spread, is it possible to analyze the economics of AI the same way researchers can foresee the coming technological advancements? According to Neil Thompson, Ph.D., principal investigator at MIT’s Initiative on the Digital Economy, understanding the deep trends that are driving AI progress can demystify how AI’s economic impacts will play out. In this revealing presentation, Thompson explores the intersection of tech and money with timely topics ranging from the future of work – is it actually economically feasible to replace humans with AI in some instances? – to sustainability and the cost of the strain that massive computing power puts on the environment. With advanced degrees in both computer science and economics, Thompson applies his unrivaled cross-discipline expertise to provide audiences with practical strategies for employing tech trend insights to glean useful economic wisdom, allowing companies to forge a cost-effective, AI-enabled path ahead.
AI Now and in the Future – How Will Work and Business Change?
We’re already seeing the start of artificial intelligence’s impact across the economy. But as AI advances and diffuses, what impact will it have on business, jobs and society? From the practicality of building multimillion-dollar AI systems to what those systems will actually be able to do as the technology advances, Neil Thompson, Ph.D., Director of the FutureTech research project at MIT’s Computer Science and Artificial Intelligence Lab, offers insight into where AI is, where it’s going and why leaders should care. Through his research as a computer scientist and economist, Thompson provides a level-headed look at the business and economics of AI and how we should be thinking about it as leaders and individuals. Audiences will gain an understanding of how jobs will – and won’t – change and how businesses can leverage AI for strategic, practical and economically sound purposes.
Technology’s Powerful Future: A Look Ahead at What Leaders Need to Know
The powerful technology advancements of the near future will touch virtually all aspects of life – work, business, economies and society at large. What are the key technologies leaders should familiarize themselves with as they prepare their organizations for the high-tech future? In this fascinating talk, Neil Thompson, Ph.D., director of the FutureTech research project at MIT’s Computer Science and Artificial Intelligence Lab, looks at practical applications for rapidly developing and emerging technologies – including even greater advancements in AI and nascent quantum computing and how they may (or may not) provide new avenues of prosperity and growth. In addition, he lifts the curtain on potential implications on jobs, the business world and even geopolitics. Helping audiences understand how technologies evolve and what they mean for society, Thompson’s unique multidisciplinary analysis provides a lens into how business, government and non-profit leaders can prepare now to familiarize themselves with and leverage the powerful tech of tomorrow.
Insights Into How AI Will Change The Ways Public Policy is Created
Technological advancements over the past decade have made tasks that were traditionally only possible for human workers possible to do with artificial intelligence (AI). Such automation promises major changes in the economy, both good (productivity increases, new scientific discoveries) and bad (worker displacement, more powerful bad actors). In this talk, Neil Thompson, Ph.D., Director of MIT FutureTech, will discuss the policy implications of AI task automation. Using an interdisciplinary lens, he will discuss both what is technically possible and also — using a methodology developed in his MIT group — discuss which tasks are economically attractive to automate. Together these will paint a picture of opportunities and challenges facing policy as AI task automation occurs. Audiences will leave with a new understanding of how to boost strategic planning for optimally using AI to fine-tune policy.
Silicon Valley Is Pricing Academics Out of AI Research
March 10, 2024
Automation May Be Possible — But When Will Businesses Want To Do It?
February 20, 2024
We May Not Lose Our Jobs to Robots So Quickly, MIT Study Finds
January 22, 2024
Will AI Take Our Jobs? Maybe Not Just Yet.
January 22, 2024
Quantum Computing: What Leaders Need to Know Now
January 11, 2024
AI's Impact on the Future of Work with Neil Thompson (Audio)
January 1, 2024
Will Quantum Computing Be Better For Your Business?
November 17, 2023
5 Questions for MIT’s Neil Thompson
June 2, 2023
Study: Industry Now Dominates AI Research
May 18, 2023
Study Finds Wikipedia Influences Judicial Behavior
July 27, 2022
Deep Learning's Diminishing Returns
September 24, 2021
Why Innovation’s Future Isn’t (Just) Open
May 11, 2020
We're Not Prepared for the End of Moore's Law
February 24, 2020
Beyond AI Exposure: Which Tasks are Cost-Effective to Automate with Computer Vision?
(MIT FutureTech, January 2024)
Should Firms Hold More Patents? A Randomized Control Trial on the Commercial Value of Patents
(Academy of Management, July 2023)
Democratising Case Law While Teaching Students
(European Journal of Legal Education, June 2023)
Economic Impacts of AI-Augmented R&D
(arXiv, January 2023)
How Fast Do Algorithms Improve? [Point of View]
(Proceedings of the IEEE, October 2021)
The Decline of Computers as a General Purpose Technology
(Communications of the ACM, March 2021)
Moore's Law: What Comes Next?
(Communications of the ACM, February 2021)
Building the Algorithm Commons: Who Discovered the Algorithms That Underpin Computing in the Modern Enterprise?
(Global Strategy Journal, February 2021)
Sourcing Innovation in the Digital Age
(SSRN, October 2020)
Does Winning a Patent Race Lead to More Follow-On Innovation?
(Journal of Legal Analysis, June 2020)