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The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market

Author

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  • Xiang Hui
  • Oren Reshef
  • Luofeng Zhou

Abstract

Generative Artificial Intelligence (AI) holds the potential to either complement knowledge workers by increasing their productivity or substitute them entirely. We examine the short-term effects of the recent release of the large language model (LLM), ChatGPT, on the employment outcomes of freelancers on a large online platform. We find that freelancers in highly affected occupations suffer from the introduction of generative AI, experiencing reductions in both employment and earnings. We find similar effects studying the release of other image-based, generative AI models. Exploring the heterogeneity by freelancers’ employment history, we do not find evidence that high-quality service, measured by their past performance and employment, moderates the adverse effects on employment. In fact, we find suggestive evidence that top freelancers are disproportionately affected by AI. These results suggest that in the short term generative AI reduces overall demand for knowledge workers of all types, and may have the potential to narrow gaps among workers.

Suggested Citation

  • Xiang Hui & Oren Reshef & Luofeng Zhou, 2023. "The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market," CESifo Working Paper Series 10601, CESifo.
    • Handle: RePEc:ces:ceswps:_10601
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    1. Edward W. Felten & Manav Raj & Robert Seamans, 2018. "A Method to Link Advances in Artificial Intelligence to Occupational Abilities," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 54-57, May.
    2. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    3. Erik Brynjolfsson & Xiang Hui & Meng Liu, 2019. "Does Machine Translation Affect International Trade? Evidence from a Large Digital Platform," Management Science, INFORMS, vol. 65(12), pages 5449-5460, December.
    4. Moshe A. Barach & John J. Horton, 2021. "How Do Employers Use Compensation History? Evidence from a Field Experiment," Journal of Labor Economics, University of Chicago Press, vol. 39(1), pages 193-218.
    5. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    6. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    7. Bo Cowgill & Fabrizio Dell'Acqua & Samuel Deng & Daniel Hsu & Nakul Verma & Augustin Chaintreau, 2020. "Biased Programmers? Or Biased Data? A Field Experiment in Operationalizing AI Ethics," Papers 2012.02394, arXiv.org.
    8. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    9. Helpman, Elhanan & Trajtenberg, Manuel, 1994. "A Time to Sow and a Time to Reap: Growth Based on General Purpose Technologies," CEPR Discussion Papers 1080, C.E.P.R. Discussion Papers.
    10. Xueming Luo & Siliang Tong & Zheng Fang & Zhe Qu, 2019. "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases," Marketing Science, INFORMS, vol. 38(6), pages 937-947, November.
    11. Chad Syverson, 2004. "Market Structure and Productivity: A Concrete Example," Journal of Political Economy, University of Chicago Press, vol. 112(6), pages 1181-1222, December.
    12. David Card & John E. DiNardo, 2002. "Skill-Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles," Journal of Labor Economics, University of Chicago Press, vol. 20(4), pages 733-783, October.
    13. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    14. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    15. Emma van Inwegen & Zanele Munyikwa & John J. Horton, 2023. "Algorithmic Writing Assistance on Jobseekers' Resumes Increases Hires," Papers 2301.08083, arXiv.org.
    16. Emma Wiles & Zanele T. Munyikwa & John J. Horton, 2023. "Algorithmic Writing Assistance on Jobseekers’ Resumes Increases Hires," NBER Working Papers 30886, National Bureau of Economic Research, Inc.
    17. Eric Overby & Sandra A. Slaughter & Benn Konsynski, 2010. "Research Commentary ---The Design, Use, and Consequences of Virtual Processes," Information Systems Research, INFORMS, vol. 21(4), pages 700-710, December.
    18. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    19. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    20. Ginger Zhe Jin, 2018. "Artificial Intelligence and Consumer Privacy," NBER Working Papers 24253, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Daniel Goller & Christian Gschwendt & Stefan C. Wolter, 2023. ""This time it's different" Generative Artificial Intelligence and Occupational Choice," Economics of Education Working Paper Series 0209, University of Zurich, Department of Business Administration (IBW).
    2. Cattaneo, Maria Alejandra & Gschwendt, Christian & Wolter, Stefan C., 2024. "How Scary Is the Risk of Automation? Evidence from a Large Scale Survey Experiment," IZA Discussion Papers 17097, Institute of Labor Economics (IZA).
    3. Maria A. Cattaneo & Christian Gschwendt & Stefan C. Wolter, 2024. "How Scary is the Risk of Automation? Evidence from a Large Survey Experiment," Economics of Education Working Paper Series 0213, University of Zurich, Department of Business Administration (IBW).
    4. Lijia Ma & Xingchen Xu & Yong Tan, 2024. "Crafting Knowledge: Exploring the Creative Mechanisms of Chat-Based Search Engines," Papers 2402.19421, arXiv.org.
    5. Mourelatos, Evangelos & Zervas, Panagiotis & Lagios, Dimitris & Tzimas, Giannis, 2024. "Can AI Bridge the Gender Gap in Competitiveness?," GLO Discussion Paper Series 1404, Global Labor Organization (GLO).

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    Keywords

    generative AI; large language model (LLM); online labor market;
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