AI, Skill, and Productivity: The Case of Taxi Drivers

• 成果类型: Article
• 署名作者: Kanazawa, Kyogo; Kawaguchi, Daiji; Shigeoka, Hitoshi; Watanabe, Yasutora
• 署名单位: University of Tokyo; Yokohama National University; IZA Institute Labor Economics; Simon Fraser University; National Bureau of Economic Research
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2023.01631
• 发表日期: 2026
• 关键词: Artificial intelligence; skill; PRODUCTIVITY; taxi drivers; prediction; demand forecasting; Machine Learning

摘要

We examine the impact of artificial intelligence (AI) on productivity in the context of taxi drivers. The AI we study assists drivers with finding customers by suggesting routes along which the demand is predicted to be high. We find that AI improves drivers' productivity by shortening the cruising time, and this gain is accrued only to low-skilled drivers, narrowing the productivity gap between high- and low-skilled drivers by 13.4%. This case study provides evidence that AI and skill are indeed substitutes, offering direct support for the underlying assumption of recent projection exercises regarding job displacement by AI.