Anton Korinek

Developing a free online course to prepare students for cutting-edge research on the economics of transformative AI.

Update December 2021: This course is now live [here.](https://www.coursera.org/learn/economics-of-ai)

Anton applied to improve and professionalize a free Coursera course on the economics of transformative AI in time for an initial public run this fall. Anton is an associate professor of economics and had previously created a beta version of the course for his own graduate students at the University of Virginia. He applied for funding to pay for his own time working on the course, the time of a graduate student assistant, professional video editing, guest lecturers, copyright fees, and support from the University of Virginia.

I have spoken to Anton before and read large parts of his and Philip Trammel’s paper, [Economic growth under transformative AI](https://globalprioritiesinstitute.org/wp-content/uploads/Philip-Trammell-and-Anton-Korinek_economic-growth-under-transformative-ai.pdf), which I thought was a good summary of existing economics work on the subject. My sense is that Anton is a competent economist and well-suited to creating an academic course.

I also skimmed the course materials for the beta course and watched parts of the associated video lectures. I would summarize the course as starting in more conventional AI economics covering the automation of labor and economic growth, and ending in more longtermist AI economics covering economic singularities, the macroeconomics of AI agents, and the control problem. The course is fairly technical and aimed towards advanced economics students. I am somewhat familiar with the economics work Anton is drawing from; while I didn’t investigate the course materials in depth, I didn’t see anything obviously inaccurate. The presentation of the beta version of the course seemed rough on certain dimensions (in particular, video quality); I can imagine it benefitting substantially from additional work and editing.

I was interested in funding this course because I think it could introduce smart economists to longtermist work, though much of the course isn’t explicitly focused on the long-term impacts of transformative AI. I think the work of many economists, including Philip Trammell and Robin Hanson, has been really influential in longtermist thinking, and a lot of the AI forecasting work I’m most excited about now is based in economics. It doesn’t seem implausible to me that a course like this could find the “low-hanging fruit” of economics students who turn out to be really interested in longtermist work when exposed to it. (As a secondary path to impact, this course is the best collection of materials around the economics of transformative AI that I know of, and I can imagine using it as a resource in the future.)

One risk of funding work that isn’t strictly longtermist is that it misrepresents longtermist ideas in an attempt to have broader appeal, discouraging people who would be on board with longtermism and attracting people who don’t really understand it. Anton strikes me as someone who is careful in his presentation of concepts, so I think this is unlikely to happen here.

I think there’s a significant chance the course doesn’t have much of an impact, at least in its first run. Anton’s goal is to have 50 students complete the course in the fall; even if that goal is met, it seems likely to me that that’s too small a number to find anyone who ends up being really excited about the material. However, given that the course is likely to have multiple runs and iterations in the future, I think the upside from this grant is worth it.