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

Author

Listed:
  • 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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    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10601.pdf
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    References listed on IDEAS

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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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    More about this item

    Keywords

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