The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
AI and the Economy
Abstract
We review the evidence that artificial intelligence (AI) is having a large effect on the economy. Across a variety of statistics—including robotics shipments, AI start-ups, and patent counts—there is evidence of a large increase in AI-related activity. We also review recent research in this area that suggests that AI and robotics have the potential to increase productivity growth but may have mixed effects on labor, particularly in the short run. In particular, some occupations and industries may do well while others experience labor market upheaval. We then consider current and potential policies around AI that may help to boost productivity growth while also mitigating any labor market downsides, including evaluating the pros and cons of an AI specific regulator, expanded antitrust enforcement, and alternative strategies for dealing with the labor market impacts of AI, including universal basic income and guaranteed employment.
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Cites
Endogenous Technological Change
Romer, P. M. (1990) · Journal of Political Economy · doi:10.1086/261725 · Cited by 17,711
The future of employment: How susceptible are jobs to computerisation?
Frey, C. B., & Osborne, M. A. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.08.019 · Cited by 8,727
The Skill Content of Recent Technological Change: An Empirical Exploration
Autor, D. H., Levy, F., & Murnane, R. J. (2003) · The Quarterly Journal of Economics · doi:10.1162/003355303322552801 · Cited by 6,205
Platform Competition in Two-Sided Markets
Rochet, J.-C., & Tirole, J. (2003) · Journal of the European Economic Association · doi:10.1162/154247603322493212 · Cited by 5,642
Why Are There Still So Many Jobs? The History and Future of Workplace Automation
Autor, D. H. (2015) · Journal of Economic Perspectives · doi:10.1257/jep.29.3.3 · Cited by 3,917
The polarization of the U.S. labor market
Autor, D. H., Katz, L. F., & Kearney, M. S. (2006) · American Economic Review · doi:10.1257/000282806777212620 · Cited by 1,594
Americans Do IT Better: US Multinationals and the Productivity Miracle
Bloom, N., Sadun, R., & Reenen, J. V. (2012) · American Economic Review · doi:10.1257/aer.102.1.167 · Cited by 1,028
Are Ideas Getting Harder to Find?
Bloom, N., Jones, C. I., Van Reenen, J., & Webb, M. (2020) · American Economic Review · doi:10.1257/aer.20180338 · Cited by 1,002 · cited 1×
“Moreover, Bloom, Jones, et al. (2017) document the many domains in which ideas are getting harder to find—that is, larger research inputs are needed to produce additional productivity outputs.”
Deep Learning: A Critical Appraisal
Marcus, G. (2018) · arXiv · doi:10.48550/arxiv.1801.00631 · Cited by 853
Cited by
Artificial intelligence, firm growth, and product innovation
Babina, T., Fedyk, A., He, A., & Hodson, J. (2024) · Journal of Financial Economics · doi:10.1016/j.jfineco.2023.103745 · Cited by 1,460
Dell'Acqua, F., McFowland III, E., Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4573321 · Cited by 794
Is artificial intelligence improving the audit process?
Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022) · Review of Accounting Studies · doi:10.1007/s11142-022-09697-x · Cited by 461
The impact of artificial intelligence on labor productivity
Damioli, G., Van Roy, V., & Vertesy, D. (2021) · Eurasian Business Review · doi:10.1007/s40821-020-00172-8 · Cited by 345
Yigitcanlar, T., & Cugurullo, F. (2020) · Sustainability · doi:10.3390/su12208548 · Cited by 337
Metadata
- Authors
- Furman, J., & Seamans, R.
- Venue
- Innovation Policy and the Economy
- Publisher
- University of Chicago Press
- Published
- 2019-01
- Volume
- 19
- Pages
- 161-191
- ISSN
- 1531-3468 (ISSN-L)
- 1537-2618
- OpenAlex
- W2806375370
- Cited by
- 483
- References
- 9
- FWCI
- 25.20
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
