In the latest version of our Power and Consequences podcast, we (Gary Gensler and Simon Johnson) talk about Artificial Intelligence, with a particular focus on what is and should be policy for AI in the United States.
Although sometimes debates about AI are presented in technical terms with a lot of jargon, we think the underlying questions are actually quite straightforward – although not easy to answer with a high degree of certainty. A new technology is arriving with potentially profound implications. Surely it will reshape some parts of how we organize the economy and our lives. But how quickly will we see these effects? Who wins and who loses, in terms of jobs? If productivity does increase, will the benefits be widely shared?
And if we can get a handle on any of these issues, what are the implications for policy?
Some readings for your consideration are below. Some of these we refer directly in our podcast, while others are items that you will find interesting if you would like to dig deeper. That’s a primary goal of this podcast – to encourage everyone to read more for themselves, to assess competing views, and then to update those views as new facts become available.
The recent AI Policy announcement from the White House: President Donald J. Trump Unveils National AI Legislative Framework, March 20, 2026. And here’s the Framework. As expressed in our opening, Gary is more skeptical of this proposal; Simon thinks it might actually have some value.
Gary has written extensively on AI-related issues. Here are two recent items.
Trump, Trade, and AI Growth, CEPR Vox Podcast, Gary interviewed by Tim Phillips) January 2026.
Artificial Intelligence Development and Policy Landscape, a paper by Gary as included in our co-edited ‘The Economic Consequences of the Second Trump Administration’ is availably on SSRN, December 2025.
And here is some material from Gary’s time at the U.S. Securities and Exchange Commission.
Office Hours with Gary Gensler – Short (3 -4 minutes each) videos: AI, Investors, Issuers, & the Markets; Systemic Risk in Artificial Intelligence; Fraud and Deception in Artificial Intelligence; Conflicts of Interest in Artificial Intelligence; AI Washing, February – October 2024
AI, Finance, Movies, and the Law, Yale Law School Remarks, February 13, 2024.
Isaac Newton to AI, Gensler, National Press Club Remarks, July 17, 2023.
And here is what has become a widely cited paper by Gary, anticipating (in 2020!) how the development of AI could affect financial stability.
Deep Learning and Financial Stability, Gary Gensler and Lily Bailey, November 2020.
As mentioned on the podcast, Simon is co-director of the MIT Stone Center on Inequality and Shaping the Future of Work, with Daron Acemoglu and David Autor. Here are a few recent work products of relevance.
Building Pro-Worker AI, by Daron, David, and Simon, February 2026. Can we change the path of technology development and deployment, to create more good jobs?
Expertise, by David and Neil Thompson, June 2025. How should we think about what happens to the tasks that we all do within our jobs, as AI arrives?
Learning from Ricardo and Thompson: Machinery and Labor in the Early Industrial Revolution and in the Age of AI, by Daron and Simon, August 2024. See this paper for more detail on what happened in the British cotton industry during the early decades of industrialization.
Simon and Daron’s 2023 book, Power and Progress; puts the age of AI – promise and peril – in the context of historical innovations, including many of the examples that we talk about in the podcast.
As promised in the podcast, here is a link to the fascinating work of Erik Brynjolfsson, Director of the Stanford Digital Economy Lab.
And here is a link to the very important work of Rumman Chowdhury.
