Documents Jacobs, Julian 1 results

"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."