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Ai, Task Changes in Jobs, and Worker Reallocation
Abstract
How does Artificial Intelligence (AI) affect the task content of work, and how do workers adjust to the diffusion of AI in the economy? To answer these important questions, we combine novel patent-based measures of AI and robot exposure with individual survey data on tasks performed on the job and administrative data on worker careers. Like prior studies, we find that robots have reduced routine tasks. In sharp contrast, AI has reduced non-routine abstract tasks like information gathering and increased the demand for 'high-level' routine tasks like monitoring processes. These task shifts mainly occur within detailed occupations and become stronger over time. While displacement effects are small, workers have responded by switching jobs, often to less exposed industries. We also document that low-skilled workers suffer some wage losses, while high-skilled incumbent workers experience wage gains.
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Uncertainty over the impact of genAI on the economy in part reflects a lack of systematic evidence on the frequency and intensity of genAI adoption.
“Uncertainty over the impact of genAI on the economy in part reflects a lack of systematic evidence on the frequency and intensity of genAI adoption, and most studies pre-date the release of widely accessible genAI tools (Acemoglu, Autor, Hazell, and Restrepo, 2022; Albanesi et al., 2024; Gathmann, Grimm, and Winkler, 2024).”
From The Rapid Adoption of Generative AI (2024) · cites this paper as Gathmann, Grimm, and Winkler, 2024
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Experimental evidence on the productivity effects of generative artificial intelligence
Noy, S., & Zhang, W. (2023) · Science · doi:10.1126/science.adh2586 · Cited by 2,150
Artificial Intelligence and Jobs: Evidence from Online Vacancies
Acemoglu, D., Autor, D., Hazell, J., & Restrepo, P. (2022) · Journal of Labor Economics · doi:10.1086/718327 · Cited by 1,193
The Impact of AI on Developer Productivity: Evidence from GitHub Copilot
Peng, S., Kalliamvakou, E., Cihon, P., & Demirer, M. (2023) · arXiv · doi:10.48550/arxiv.2302.06590 · Cited by 287
Artificial Intelligence Index Report 2024
Maslej, N., Fattorini, L., Perrault, R., Parli, V., Reuel, A., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., Manyika, J., et al. (2024) · arXiv · doi:10.48550/arxiv.2405.19522 · Cited by 159
Artificial Intelligence, Scientific Discovery, and Product Innovation
Toner-Rodgers, A. (2024) · arXiv · doi:10.48550/arxiv.2412.17866 · Cited by 17
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Cited by
Sorted by citations
The Rapid Adoption of Generative AI
Bick, A., Blandin, A., & Deming, D. (2024) · NBER Working Paper · doi:10.3386/w32966 · Cited by 200
The Rapid Adoption of Generative AI
Bick, A., Blandin, A., & Deming, D. J. (2026) · Management Science · doi:10.1287/mnsc.2025.02523 · Cited by 48
Metadata
- Authors
- Gathmann, C., Grimm, F., & Winkler, E.
- ORCID
- Gathmann, Christina
- Publisher
- Elsevier BV
- Published
- 2024
- Cited by
- 10
- References
- 5
- Type
- Preprint
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