Economics of automation,

humans v robots

2021-09-20 — 2025-04-15

economics
faster pussycat
innovation
language
machine learning
mind
neural nets
technology
UI

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What does innovation in automation mean for the economy as it pertains to people?

Figure 1

Soundtrack: Machines work, by B(iftek) (video clip).

Daron Acemoglu has written much on the economics of modern automation recently(, , ).

Many others have been thinking about this for a long time. It is tricky. What even is the role of manufacturing in the economy? How much does automation affect dematerialised economies? How about at the singularity?

As usual, Scott Alexander’s opinion might not be definitive but it does point to some interesting stuff: Technological Unemployment: Much More Than You Wanted To Know.

Various questions about the economics of social changes wrought by ready access to LLMs, the latest generation of automation. This is a short-to-medium-term frame question, whatever “short” and “medium” mean. The big question here is whether [AI Automation is different](.

For that, see Economics of AI automation.

Longer-term, some folks might also be interested in whether AI will replace us with grey goo or turn us into raw feedstock for building computronium etc.

1 References

Acemoglu, and Johnson. 2023. Power and Progress: Our Thousand-Year Struggle over Technology and Prosperity.
Acemoglu, and Restrepo. 2018. “Artificial Intelligence, Automation and Work.” In The Economics of Artificial Intelligence: An Agenda. Working Paper Series.
———. 2020. “The Wrong Kind of AI? Artificial Intelligence and the Future of Labour Demand.” Cambridge Journal of Regions, Economy and Society.
Andrus, Dean, Gilbert, et al. 2021. “AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks.”
Babina, Fedyk, He, et al. 2021. “Artificial Intelligence, Firm Growth, and Industry Concentration.” SSRN Scholarly Paper ID 3651052.
Danaher. 2018. “Toward an Ethics of AI Assistants: An Initial Framework.” Philosophy & Technology.
Eloundou, Manning, Mishkin, et al. 2023. “GPTs Are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models.”
Felten, Raj, and Seamans. 2019. “The Occupational Impact of Artificial Intelligence: Labor, Skills, and Polarization.” SSRN Scholarly Paper ID 3368605.
Kalyani, Bloom, Carvalho, et al. 2025. “The Diffusion of New Technologies.” The Quarterly Journal of Economics.
Lane, and Saint-Martin. 2021. “The Impact of Artificial Intelligence on the Labour Market: What Do We Know so Far?”
Lee. 2025. “The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers.”
Shumailov, Shumaylov, Zhao, et al. 2023. “The Curse of Recursion: Training on Generated Data Makes Models Forget.”
Smith. 2022. The Internet Is Not What You Think It Is: A History, a Philosophy, a Warning.
Thirunavukarasu, Ting, Elangovan, et al. 2023. “Large Language Models in Medicine.” Nature Medicine.
Xexéo, Braida, Parreiras, et al. 2024. “The Economic Implications of Large Language Model Selection on Earnings and Return on Investment: A Decision Theoretic Model.”