The Political Economy of AI: A Syllabus

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

Kate Crawford (2021), “Chapter 1: Earth,” Atlas of AI, Yale University Press.

Tamara Kneese and Meg Young (2024), “Carbon Emissions in the Tailpipe of Generative AI,” Harvard Data Science Review.

International Energy Agency, 2025, Energy and AI (IEA).

Eric Schmidt (2025), “Converting Energy into Intelligence: The Future of AI Technology, Human Discovery, and American Global Competitiveness,” Testimony to House Energy and Commerce Committee.

Week 7 – Human Knowledge

Melissa Heikkilä and Stephanie Arnett, “This Is Where the Data to Build AI Comes From,” MIT Technology Review, December 18, 2024.

C. Thi Nguyen (2024), “The Limits of Data,” Issues in Science and Technology 40, 2.

Saffron Huang and Divya Siddarth (2023), Generative AI and the Digital Commons.

Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Nicolas Papernot, Ross Anderson & Yarin Gal (2024), “AI Models Collapse When Trained on Recursively Generated Data,” Nature 631:755–759.

Jason Burton et al. (2024), “How Large Language Models Can Reshape Collective Intelligence,” Nature Human Behavior.

Section 3 - Outputs

Week 8 – Market

Marion Fourcade and Kieran Healy (2024), “Chapter Two: The Data Imperative, Section Three (Thou Shalt Learn)” and “Chapter Four: The Great Unbundling, Section Two (Market Modulations), The Ordinal Society (Harvard University Press).

U.S. Department of Justice (2024), United States vs. RealPage: Complaint.

Ludwig Siegele (2019), “Can Technology Plan Economies and Destroy Democracy?,” The Economist.

Henry Farrell and Cosma Shalizi (2023), “Artificial Intelligence is a Familiar-Looking Monster,” The Economist.

Week 9 - State

Daniel Berliner (2024), “What AI Can’t Do for Democracy,” Boston Review.

Leif Weatherby (2025), “Our Spreadsheet Overlords,” The Ideas Letter.

Henry Farrell and Marion Fourcade (2023), “The Moral Economy of High-Tech Modernism,” Daedalus 152(1):225-235.

Mariano-Florentino Cuéllar and Aziz Z. Huq (2022), “Artificially Intelligent Regulation,” Daedalus, 151,2:335-347.

Don Moynihan (2025), “Robodebt: When Automation Fails,” Can We Still Govern?

Week 10 – Culture

Ted Chiang (2023), “ChatGPT Is a Blurry JPEG of the Web,” New Yorker.

Ted Underwood (2025), “A More Interesting Upside of AI,” tedunderwood.com.

Kevin Munger (2025), “In The Belly of the MrBeast,” Never Met a Science.

Baptiste Caramiaux, Kate Crawford, Q. Vera Liao, Gonzalo Ramos and Jenny Williams (2025), Generative AI and Creative Work: Narratives, Values, and Impacts.

Section 4 - Conflicts

Week 11 – AGI

Jasmine Sun, “AGI (Disambiguation),” jasmi.news.

Dario Amodei (2024), Machines of Loving Grace.

Marc Andreessen (2023), The Techno-Optimist Manifesto (Andreessen-Horowitz).

Yoshua Bengio et al (2024), “Managing Extreme AI Risks Amid Rapid Progress,” Science 384 (6698): 842–845.

AI Now Institute (2025), “Chapter 1: AI’s False Gods,” Artificial Power Report (AI Now).

Week 12 – Geopolitics

Ben Buchanan and Ezra Klein (2025), “The Government Knows AGI Is Coming,” New York Times.

Remco Zwetsloot, Helen Toner, Jeffrey Ding (2018), “Beyond the AI Arms Race: America, China, and the Dangers of Zero-Sum Thinking,” Foreign Affairs.

Dan Hendrycks, Eric Schmidt and Alexandr Wang, Super-Intelligence Strategy: Expert Version.

Dan Wang, “Chapter Two: Tech Power,” Breakneck: China’s Quest to Engineer the Future.

Week 13 - Work

Jim VandeHei and Mike Allen (2025), “A White-Collar Bloodbath,” Axios.

Daron Acemoglu and Simon Johnson (2024), “Learning From Ricardo and Thompson: Machinery and Labor in the Early Industrial Revolution and in the Age of Artificial Intelligence,” Annual Review of Economics, 16:597-621.

Aiha Nguyen and Alexandra Mateescu (2024), Generative AI and Labor: Power, Hype and Value at Work (Data & Society).

Jeff Schuhrke, “Lights, Camera, Collective Action: Assessing the 2023 SAG-AFTRA Strike,” New Labor Forum, 33,2, 2024.

Week 14 – Conclusions

TBD.