Inequality Inertia Projected: How Americans Envision a Stratified AI Future

• In Event: Inequality, Poverty, and Mobility Section Roundtables
  In Refereed Roundtable (60 minute): 10. AI and Technology

Abstract

This study investigates the social construction of AI as a systemic inequality enhancer, asking which groups are perceived as most vulnerable to job displacement and how these perceptions vary across respondents. We fielded a vignette experiment in the United States (N = 8,141). Net of occupation, respondents attribute significantly greater replacement risk to targets with lower education—a pattern of inequality inertia. This gradient steepens among respondents who perceive high societal inequality and those with low AI exposure, consistent with societal projection under uncertainty. High-SES respondents perceive the sharpest gradients, reflecting crystallized schemas of how advantage operates. The study makes two contributions. Methodologically, our design isolates status effects from job content. Substantively, we capture how existing cognitive frameworks shape forecasts of technological change, revealing that the public expects AI to reproduce, not disrupt, existing status hierarchies.

Authors

• Zihui Lei, The University of Hong Kong

• Lemeng Liang, Princeton University

• Yu Xie, Princeton University