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The gen AI gender gap

Author

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

Abstract

Data from the Survey of Consumer Expectations shows that 50% of men use generative AI tools, compared to 37% of women. Privacy concerns and perceived opportunities and risks explain a quarter of the gender gap. Respondents’ self-assessed knowledge emerges as the most important factor.

Suggested Citation

  • Aldasoro, Iñaki & Armantier, Olivier & Doerr, Sebastian & Gambacorta, Leonardo & Oliviero, Tommaso, 2024. "The gen AI gender gap," Economics Letters, Elsevier, vol. 241(C).
    • Handle: RePEc:eee:ecolet:v:241:y:2024:i:c:s0165176524002982
    DOI: 10.1016/j.econlet.2024.111814
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    References listed on IDEAS

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    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. 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).
    3. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    4. 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.
    5. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2023. "Generative AI at Work," Papers 2304.11771, arXiv.org.
    6. 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.
    7. 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.
    8. Doerr, Sebastian & Gambacorta, Leonardo & Guiso, Luigi & Sanchez del Villar, Marina, 2023. "Privacy regulation and fintech lending," CEPR Discussion Papers 18216, C.E.P.R. Discussion Papers.
    9. Chen, S. & Doerr, S. & Frost, J. & Gambacorta, L. & Shin, H.S., 2023. "The fintech gender gap," Journal of Financial Intermediation, Elsevier, vol. 54(C).
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    More about this item

    Keywords

    Generative artificial intelligence; Privacy; Gender;
    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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