The artificial intelligence shock and socio-political polarization

Julian Jacobs

Technological Forecasting and Social Change, 2024, vol. 199, issue C

Abstract: Are artificial intelligence's complimenting and displacing labor market effects corresponding with similar polarization in socio-political beliefs? This study answers this question by analyzing survey data of 26,311 Americans, collected from the American National Election Survey. Data is deployed alongside 22-category Manyika et al. (2017) ‘automation potential’ estimates (proxying for ‘displacement due to AI’) and Michael Webb (2019) ‘AI-exposure’ estimates (proxying for labor complimented by AI). The study summarizes the demographic characteristics and socio-political views of the highly AI-exposed and automation-susceptible groups. It deploys a year and region fixed effects OLS model, with standard error clustered at the occupation level. This study then finds that automation-susceptible ‘losers’ of AI are more likely to be culturally conservative and economically left-leaning. Those complimented by AI are more likely to hold socially liberal and fiscally conservative views. The results suggest AI's labor market polarization may accompany radicalization and socio-political divergence, with implications for vote capture and representation of working-class interests in government.

Keywords: Artificial intelligence; Digitalization; Economic shocks; Inequality; Polarization; Political psychology (search for similar items in EconPapers)
JEL-codes: D63 D72 D83 D91 H23 J68 O33 O38 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:199:y:2024:i:c:s0040162523006911

DOI: 10.1016/j.techfore.2023.123006

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