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Race, Ethnicity, and the Future of Work

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  • Moradi, Pegah

Abstract

Leading up to and following the 2016 American presidential election, “White working class” employment and political agency has become particularly salient. A simultaneous discussion on the role of automation in unemployment complicates the political narrative; by one estimate, 47% of American jobs are at risk of computerization (Frey and Osborne, 2013). This study analyzes how occupational automation corresponds with racial and ethnic demographics within occupational groups from both a historical and contemporary perspective. I find that throughout American industrialization, non-White and immigrant workers shifted to low-wage, unskilled work because of the political and social limitations imposed upon these groups. In the context of today’s AI-driven automation, I find that White workers are more heavily affected by automatability than other racial groups. Conversely, however, I found that the proportion of White workers in an occupation is negatively correlated with an occupation’s automatability. I conclude with suggestions for a susceptibility-based approach to predicting employment outcomes from AI-driven automation.

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  • Moradi, Pegah, 2019. "Race, Ethnicity, and the Future of Work," SocArXiv e37cu, Center for Open Science.
    • Handle: RePEc:osf:socarx:e37cu
    DOI: 10.31219/osf.io/e37cu
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    1. Borowczyk-Martins, Daniel & Bradley, Jake & Tarasonis, Linas, 2018. "Racial discrimination in the U.S. labor market: Employment and wage differentials by skill," Labour Economics, Elsevier, vol. 50(C), pages 45-66.
    2. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    3. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    4. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    5. David Card & John E. DiNardo, 2002. "Skill-Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles," Journal of Labor Economics, University of Chicago Press, vol. 20(4), pages 733-783, October.
    6. Carl Benedikt Frey & Thor Berger & Chinchih Chen, 2018. "Political machinery: did robots swing the 2016 US presidential election?," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(3), pages 418-442.
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