The wrong kind of AI? Artificial intelligence and the future of labour demand
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Artificial intelligence (AI) is set to influence every aspect of our lives, not least the way production is organised. AI, as a technology platform, can automate tasks previously performed by labour or create new tasks and activities in which humans can be productively employed. Recent technological change has been biased towards automation, with insufficient focus on creating new tasks where labour can be productively employed. The consequences of this choice have been stagnating labour demand, declining labour share in national income, rising inequality and lowering productivity growth. The current tendency is to develop AI in the direction of further automation, but this might mean missing out on the promise of the ‘right’ kind of AI, with better economic and social outcomes.
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Acemoglu, Autor, Hazell, and Restrepo (2020) conclude no significant effect yet in the last decade at the occupation or industry level in the US.
“A study by Acemoglu, Autor, Hazell, and Restrepo (2020) concludes no significant effect yet in the last decade at the occupation or industry level in the US.”
From Artificial intelligence and work: a critical review of recent research from the social sciences (2024) · cites this paper as Acemoglu et al. 2020
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Sanders, C. E., Mayfield-Smith, K., & Lamm, A. J. (2021) · Sustainability · doi:10.3390/su132112033 · Cited by 34 · see citing works
How to compete with robots by assessing job automation risks and resilient alternatives
Paolillo, A., Colella, F., Nosengo, N., Schiano, F., Stewart, W., Zambrano, D., Chappuis, I., Lalive, R., & Floreano, D. (2022) · Science Robotics · doi:10.1126/scirobotics.abg5561 · Cited by 35 · see citing works
Infosphere, Datafication, and Decision-Making Processes in the AI Era
Lavazza, A., & Farina, M. (2023) · Topoi · doi:10.1007/s11245-023-09919-0 · Cited by 33 · see citing works
Flanagan, F., & Walker, M. (2020) · New Technology Work and Employment · doi:10.1111/ntwe.12178 · Cited by 32 · see citing works
Manufacturing-led development in the digital age: how power trumps technology
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Labour-Saving Automation and Occupational Exposure: A Text-Similarity Measure
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Wang, L., Cao, Z., & Dong, Z. (2023) · Structural Change and Economic Dynamics · doi:10.1016/j.strueco.2023.05.010 · Cited by 32 · see citing works
JOSHI, D. J. M. D. A. (2023) · European Economic Letters (EEL) · doi:10.52783/eel.v13i4.589 · Cited by 29 · see citing works
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Furendal, M., & Jebari, K. (2023) · Philosophy & Technology · doi:10.1007/s13347-023-00631-w · Cited by 31 · see citing works
New technologies and jobs in Europe
Stefania Albanesi, Y., da Silva, A. D., Jimeno, J. F., Lamo, A., & Wabitsch, A. (2023) · Documentos de trabajo/Documento de trabajo - Banco de España, Servicio de Estudios · doi:10.53479/33414 · Cited by 37 · see citing works
Investigating the politics and content of US State artificial intelligence legislation
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Loewenstein, G., & Wojtowicz, Z. (2025) · Journal of Economic Literature · doi:10.1257/jel.20241665 · Cited by 24 · see citing works
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Yang, G., & Deng, F. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e14607 · Cited by 28 · see citing works
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Jia, K., & Zhang, N. (2021) · Electronic Markets · doi:10.1007/s12525-021-00480-5 · Cited by 23 · see citing works
- Authors
- Acemoglu, D., & Restrepo, P.
- Affiliations
- MIT, Cambridge, MA, USA
- Boston University (US)
- Venue
- Cambridge Journal of Regions, Economy and Society
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-12-18
- Volume
- 13
- Issue
- 1
- Pages
- 25-35
- ISSN
- 1752-1378 (ISSN-L)
- 1752-1386
- OpenAlex
- W4230775373
- Cited by
- 634
- References
- 39
- Citations by year
- 2026: 143 · 2025: 137 · 2024: 111 · 2023: 103 · 2022: 76 · 2021: 47 · 2020: 16
- FWCI
- 43.38
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Cambridge Journal of Regions Economy and Society (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Funders
- National Science Foundation
- Alfred P. Sloan Foundation
- Smith Richardson Foundation
- Sid W. Richardson Foundation
- Accenture
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic Growth and Productivity
- Keywords
- artificial intelligence, labor demand, automation, technological change, labor share, income inequality, productivity growth, employment, task creation, future of work
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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