Full Citation

Title: The Impact of Artificial Intelligence on the Labor Market

Citation Type: Miscellaneous

Publication Year: 2019

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Abstract: I develop a new method to predict the impacts of any technology on occupations. I use the overlap between the text of job task descriptions and the text of patents to construct a measure of the exposure of tasks to automation. I first apply the method to historical cases such as software and industrial robots. I establish that occupations I measure as highly exposed to previous automation technologies saw declines in employment and wages over the relevant periods. I use the fitted parameters from the case studies to predict the impacts of artificial intelligence. I find that, in contrast to software and robots, AI is directed at high-skilled tasks. Under the assumption that historical patterns of long-run substitution will continue, I estimate that AI will reduce 90:10 wage inequality, but will not affect the top 1%.

Url: https://web.stanford.edu/~mww/webb_jmp.pdf

User Submitted?: No

Authors: Webb, Michael

Publisher: Stanford University

Data Collections: IPUMS USA

Topics: Labor Force and Occupational Structure, Other

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