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

• 成果类型: Article; Early Access
• 署名作者: Bao, Leo; Huang, Difang; Lin, Chen
• 署名单位: Monash University; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; University of Hong Kong
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2022.02787
• 发表日期: 2024
• 关键词: gender equality; Artificial intelligence; education

摘要

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.