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The gen AI gender gap

Author

Listed:
  • Iñaki Aldasoro
  • Olivier Armantier
  • Sebastian Doerr
  • Leonardo Gambacorta
  • Tommaso Oliviero

Abstract

Generative artificial intelligence (gen AI) is expected to increase productivity. But if unequally adopted across demographic groups, its proliferation risks exacerbating disparities in pay and job opportunities, leading to greater inequality. To investigate the use of gen AI and its drivers we draw on a representative survey of U.S. household heads from the Survey of Consumer Expectations. We find a significant "gen AI gender gap": while 50% of men already use gen AI, only 37% of women do. Demographic characteristics explain only a small share of this gap, while respondents' self-assessed knowledge about gen AI emerges as the most important factor, explaining three-quarters of the gap. Gender differences in privacy concerns and trust when using gen AI tools, as well as perceived economic risks and benefits, account for the remainder. We conclude by discussing implications for policy to foster equitable gen AI adoption.

Suggested Citation

  • Iñaki Aldasoro & Olivier Armantier & Sebastian Doerr & Leonardo Gambacorta & Tommaso Oliviero, 2024. "The gen AI gender gap," BIS Working Papers 1197, Bank for International Settlements.
    • Handle: RePEc:bis:biswps:1197
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    References listed on IDEAS

    as
    1. Jonah B. Gelbach, 2016. "When Do Covariates Matter? And Which Ones, and How Much?," Journal of Labor Economics, University of Chicago Press, vol. 34(2), pages 509-543.
    2. Jeffrey T. Prince & Scott Wallsten, 2022. "How much is privacy worth around the world and across platforms?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(4), pages 841-861, November.
    3. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2023. "Generative AI at Work," Papers 2304.11771, arXiv.org.
    4. Mauro Cazzaniga & Ms. Florence Jaumotte & Longji Li & Mr. Giovanni Melina & Augustus J Panton & Carlo Pizzinelli & Emma J Rockall & Ms. Marina Mendes Tavares, 2024. "Gen-AI: Artificial Intelligence and the Future of Work," IMF Staff Discussion Notes 2024/001, International Monetary Fund.
    5. Iñaki Aldasoro & Sebastian Doerr & Leonardo Gambacorta & Daniel Rees, 2024. "The impact of artificial intelligence on output and inflation," BIS Working Papers 1179, Bank for International Settlements.
    6. Chen, S. & Doerr, S. & Frost, J. & Gambacorta, L. & Shin, H.S., 2023. "The fintech gender gap," Journal of Financial Intermediation, Elsevier, vol. 54(C).
    7. Sebastian Doerr & Leonardo Gambacorta & Luigi Guiso & Marina Sanchez del Villar, 2023. "Privacy regulation and fintech lending," BIS Working Papers 1103, Bank for International Settlements.
    8. Lythreatis, Sophie & Singh, Sanjay Kumar & El-Kassar, Abdul-Nasser, 2022. "The digital divide: A review and future research agenda," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    9. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
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    More about this item

    Keywords

    artificial intelligence; privacy; gender; gen AI;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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