Can Artificial Intelligence Improve Gender Equality? Evidence from a Natural Experiment
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.
This paper was accepted by Elena Katok, Special Issue on the Human-Algorithm Connection.
Funding: D. Huang gratefully acknowledges financial support from the National Natural Science Foundation of China [Grants 72503232, 71988101, and T2293771]. C. Lin gratefully acknowledges financial support from the National Natural Science Foundation of China [Grant 72192841] and the Research Grants Council of the Hong Kong Special Administration Region, China [Project No. T35/710/20R].
Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02787.

