Cities are modern society’s hubs for economic productivity and innovation, and now accommodate over half of the world’s population. As job migration is the leading factor in urbanization, policymakers are increasingly concerned about the likely impact of artificial intelligence and automation on city employment. While researchers have investigated automation in national economies and individual employment, it remains unclear a priori how cities will respond to this threat. Answering this question has implications for everything from urban migration to investment, and from social welfare policy to educational initiatives.
Here, we undertake a comparative examination of cities using data from the US Bureau of Labor Statistics giving the employment distribution of about 700 different occupations across each of 380 US metropolitan statistical areas and combined statistical areas in 2014. From the data we estimate the “risk of computerization” as an educated guess about which occupations will experience greater adjustment due to machine substitution of a large portion of their content, and correlate these occupations with city size. Our analysis indicates that small cities will experience greater adjustments in the face of automation, including worker displacement and job content substitutions. We demonstrate that large cities exhibit increased occupational and skill specialization due to increased abundance of managerial and technical professions. These occupations are not easily automatable, and, thus, reduce the potential impact of automation in large cities.
Frank MR, Sun L, Cebrian M, Youn H, Rahwan I. 2018 Small cities face greater impact from automation. J. R. Soc. Interface 15: 20170946. http://dx.doi.org/10.1098/rsif.2017.0946
Available online at http://rsif.royalsocietypublishing.org/content/15/139/20170946