Seminars topic: 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.

Scholars Background: HUANG Liangfang is an Associate Researcher at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences. His main research areas cover financial technology and artificial intelligence. His research results have been published in leading journals in natural science and financial management, such as PNAS, PNAS Nexus, Nature Human Behaviour, Management Science, Journal of Accounting Research, and Journal of Financial and Quantitative Analysis.

Time and Location: September 19, 2025, 10:00–11:30, Room A723, School of Management

Language: EN & CN