Artificial Intelligence and Jobs: Evidence from US Commuting Zones

Arbeitspapier

We study the effect of Artificial Intelligence (AI) on employment across US commuting zones over the period 2000-2020. A simple model shows that AI can automate jobs or complement workers, and illustrates how to estimate its effect by exploiting variation in a novel measure of local exposure to AI: job growth in AI-related professions built from detailed occupational data. Using a shift-share instrument that combines industry-level AI adoption with local industry employment, we estimate robust negative effects of AI exposure on employment across commuting zones and time. We find that AI's impact is different from other capital and technologies, and that it works through services more than manufacturing. Moreover, the employment effect is especially negative for low-skill and production workers, while it turns positive for workers at the top of the wage distribution. These results are consistent with the view that AI has contributed to the automation of jobs and to widen inequality.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CESifo Working Paper ; No. 10685

Classification and Topics

• Classification: Wirtschaft ; Labor Demand ; Human Capital; Skills; Occupational Choice; Labor Productivity ; Technological Change: Choices and Consequences; Diffusion Processes
• Subject: artificial intelligence ; automation ; displacement ; labor

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Bonfiglioli, Alessandra ; Crinò, Rosario ; Gancia, Gino ; Papadakis, Ioannis
• Event: Veröffentlichung
• (who): Center for Economic Studies and ifo Institute (CESifo)
• (where): Munich
• (when): 2023

Further information

• Handle: http://hdl.handle.net/10419/282373
• Last update: 10.03.2025, 11:43 AM CET