Master the economics of the most consequential technology ever built!

If you have spent any time at the intersection of economics and AI, you have probably noticed a strange gap: the popular discourse moves at the speed of press releases, and the serious academic literature — the growth theory, the automation models, the mechanism design — tends to remain siloed inside PhD programs and NBER working papers. Neither end of that spectrum is particularly useful if what you actually want to do is think rigorously about what transformative AI (TAI) means for the economy.

That gap is what this school/seminar is designed to close. Not by dumbing the economics down, and not by retreating into pure formalism — but by working through the latest frontier research agenda at the level it deserves. We will take general-purpose technology theory seriously. We will stress-test task-based automation models. We will engage honestly with what we cannot yet measure and why that matters. And we will treat AI safety and governance not as an ethics seminar but as an applied problem in public and institutional economics and mechanism design — which is what it actually is.

I built this curriculum because I believe the most important questions in economics right now are not being taught systematically outside of a handful of elite PhD programs — and even there, TAI economics tends to be scattered across fields rather than integrated. Growth economists, labor economists, innovation scholars, and governance researchers are all working on adjacent pieces of the same puzzle. This school assembles those pieces into a coherent research agenda you can orient yourself within, contribute to, and argue with.

You will not leave this school with a tidy set of settled answers. The honest truth is that transformative AI is generating open questions faster than the discipline can close them, and calibrated uncertainty is more valuable here than false confidence. What you will leave with is the theory cum praxis vocabulary, the methodological tools, and the critical habits to engage with this literature at the latest frontier — whether that means writing a dissertation chapter, designing a policy proposal, or simply refusing to accept a shallow analysis of the definitely most consequential economic transformation of your lifetime.

The work is demanding. The models are real. And frankly, that is rather the point. If you are ready to take the economics of transformative AI seriously, I am glad you are here.