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Can Artificial Intelligence Improve Gender Equality? Evidence from a Natural Experiment

Author

Listed:
  • Leo Bao

    (Department of Banking and Finance, Monash Business School, Monash University, Caulfield East, Victoria 3145, Australia)

  • Difang Huang

    (Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China)

  • Chen Lin

    (Faculty of Business and Economics, University of Hong Kong, Hong Kong)

Abstract

Gender discrimination in education hinders women’s representation in various fields. How can we create a gender-neutral learning environment when teachers’ gender composition and mindset are slow to change? Recent development in artificial intelligence (AI) provides a way to achieve this goal as engineers can make AI trainers gender neutral and not take gender-related information as input. We use data from a natural experiment in which such AI trainers replace some human teachers for a male-dominated strategic board game to test the effectiveness of AI training. The introduction of AI improves teaching outcomes for boys and girls and reduces the preexisting gender gap. Survey responses indicate that AI’s information advantage, friendly appearance, and interactive features helped students to learn faster, and class recordings suggest that AI trainers’ nondiscriminatory emotional status can explain the improvement in gender equality. We demonstrate AI’s potential in improving learning outcomes and promoting diversity, equity, and inclusion in analogous settings.

Suggested Citation

  • Leo Bao & Difang Huang & Chen Lin, 2026. "Can Artificial Intelligence Improve Gender Equality? Evidence from a Natural Experiment," Management Science, INFORMS, vol. 72(1), pages 474-494, January.
    • Handle: RePEc:inm:ormnsc:v:72:y:2026:i:1:p:474-494
    DOI: 10.1287/mnsc.2022.02787
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    1. Bernd Irlenbusch, 2026. "Human Trust in AI: Evidence from Experimental Economics," ECONtribute Discussion Papers Series 417, University of Bonn and University of Cologne, Germany.

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