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

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. This paper was accepted by Joshua Gans, business strategy. Funding: This work was supported by the JSPS KAKENHI [Grants 23K25495, 23H00828, 22H00847, 22H05009, and 22H00057], JST RISTEX [Grant JPMJRX18H3], and JST ERATO [Grant JPMJER2301]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01631 .