The Gender Gap in Attitudes toward Workplace Technological Change

• In Event: Economic Insecurity, Policy Preferences, and Voting Behavior

Abstract

Advanced economies are experiencing a series of labour market disruptions, including those deriving from changes in market demand, free trade, and automation and artificial intelligence (AAI). Many economists think that these shocks produce on average larger gains than losses, but they also entail distributional consequences, leaving some groups better off, and other groups worse off. As a result, public opinion toward these economic shocks is often highly divided, including along gender lines. Yet while a significant body of research has examined the gender gap in attitudes toward other economic disruptions like trade, very little research has examined the possibility of a similar gender gap in attitudes toward AAI. This is a significant oversight in the literature; given both the potentially large benefits and distributional costs of AAI, and the possibility that the rapid pace of technological change may incent politicians to increasingly politicize the issue, it is important to understand which groups oppose AAI and why.

To address this gap, this paper provides one of the first systematic analyses of gender’s effect on attitudes toward AAI. Using data from a survey of ten advanced economies, and comparing the gender gap in attitudes toward automation with the gender gap in attitudes toward offshoring and market changes, we provide evidence of a significant gender gap in attitudes toward the adoption of technology in the workplace. Drawing in part on insights from the literature on gender differences in attitudes toward other economic shocks, we examine four sets of potential explanations for this gap: differences in material position, technological knowledge gaps, different levels of sociotropic concern, and differences in social status perceptions. Our findings suggest that accounting for these various explanations does not substantially reduce the gender gap in automation preferences. We conclude with a discussion of alternative explanations for this gap.

Authors

• Sophie Borwein, University of British Columbia

• Beatrice Magistro, California Institute of Technology

• Peter Loewen, University of Toronto

• Bart Bonikowski, New York University

• Blake Lee-Whiting, University of Toronto