on Toshareproject.it - curated by Bruce Sterling
https://www.programmablemutter.com/p/the-political-economy-of-ai-a-syllabus
HENRY FARRELL
JUL 12, 2025
As I’ve noted occasionally before, one of the most potentially useful things that academics do is preparing syllabi, and hence organizing information about the world. I’m not aware of any course syllabi on the political economy of AI: here’s one, in draft form, to be taught to international policy MA students in the fall. Comments, suggestions or corrections warmly welcomed. As with other such courses, the idea of the course is not to promote my own ideas but to give students a (doubtlessly partial and imperfect) sense of some of the ideas and debates there are out there.
Section I – AI Transition
Week 1 – Different Stories about the AI Transition
Daniel Kokotajlo, Scott Alexander, Thomas Larsen, Eli Lifland, Romeo Dean (2025), AI 2027.
Arvind Narayanan & Sayash Kapoor (2025), AI as Normal Technology (Knight Foundation).
Henry Farrell, Alison Gopnik, Cosma Shalizi and James Evans (2025), “Large AI Models are Cultural and Social Technologies,” Science.
Helen Toner (2025), Unresolved Debates about the Future of AI, Rising Tide.
Week 2 – The Empirics of the AI Transition
Arjun Ramani and Zhendong Wang, “Why Transformative Artificial Intelligence is Really, Really Hard to Achieve,” The Gradient, June 26, 2023.
Andrew McAfee (2024), Generally Faster: The Economic Impact of Generative AI.
Kristina McElheran, J. Frank Li, Erik Brynjolfsson, Zachary Kroff, Emin Dinlersoz, Lucia S. Foster and Nikolas Zolas (2023), “AI Adoption in America: Who, What, and Where,” National Bureau of Economic Research, Working Paper 31788.
Weixin Liang, Yaohui Zhang, Mihai Codreanu, Jiayu Wang , Hancheng Cao , and James Zou (2025), The Widespread Adoption of Large Language Model-Assisted Writing Across Society.
Week 3 – The Business Models of the AI Transition
Rich Sutton (2019), The Bitter Lesson.
Karen Hao (2020), “The Messy, Secretive Reality Behind OpenAI’s Bid to Save the World,” MIT Technology Review, February 17, 2020.
Andrew J. Lohn (2023), Scaling AI: Cost and Performance of AI at the Leading Edge, CSET.
Brian Merchant (2024), AI Generated Business: The Rise Of AGI and the Rush to Find a Working Revenue Model (AI Now Institute).
Section 2 – Inputs
Week 4 – Capital
Catherine Bracy (2025), “Chapter One: The Methodology. How Venture Capitalists Think,” World Eaters: How Venture Capital is Cannibalizing the Economy (Dutton).
Gregory C. Allen, Georgia Adamson, Lennart Heim, and Sam Winter-Levy (2025), The United Arab Emirates’ AI Ambitions, CSIS.
[READING TBD on how the AI labs raise money]
Week 5 – Chips
Chris Miller (2022), “Chapter 41: How Intel Forgot Innovation,” Chip War: The Fight for the World’s Most Critical Technology (Simon & Schuster).
Saif M. Khan (2020), AI Chips: What They Are and Why They Matter (CSET).
Jake Sullivan, Remarks by National Security Advisor Jake Sullivan at the Special Competitive Studies Project Global Emerging Technologies Summit, September 16, 2022.
Matt Sheehan and Sam Winter-Levy (2025), Chips, China, and a Lot of Money: The Factors Driving the DeepSeek AI Turmoil (Carnegie Endowment).
Week 6 – Energy and Material Resources…