AI, Skill, and Productivity: The Case of Taxi Drivers - Kyogo Kanazawa; Daiji Kawaguchi; Hitoshi Shigeoka; Yasutora Watanabe (Institute of Labor Economics (IZA), 2022)
We examine the impact of Articial 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 such gain is accrued only to low-skilled drivers, narrowing the productivity gap between high- and low-skilled drivers by 14%. The result indicates that AI's impact on human labor is more nuanced and complex than a job displacement story, which was the primary focus of existing studies.
Keywords: J22; J24; L92; R41; 330; artificial intelligence; skill; productivity; taxi-drivers; prediction; demand forecasting; machine learning