Will AI Take My Job? Evolving Perceptions of Automation and Labor Risk in Latin America

2025-05-13

AI Summary

This study examines the temporal evolution of public concern regarding AI- and robotics-driven job displacement in Latin America and identifies its structural and ideological determinants. Drawing on four waves (2014–2021) of the Latinobarómetro—a longitudinal cross-sectional survey covering 16 countries and over 48,000 respondents—the analysis employs multi-wave comparative modeling, latent class analysis (LCA), and multivariate regression. Results reveal a pronounced temporal peak in AI-related anxiety in 2018, significant cross-national heterogeneity, and three empirically distinct attitudinal subgroups. Education level and political orientation emerge as the most robust predictors of AI-related labor concerns. This research fills a critical gap in scholarship on AI social perception in the Global South and provides empirically grounded insights for designing context-sensitive AI governance frameworks and labor market policies in emerging economies.

Technology Category

• Philosophy and Ethics of AI: AI & Jobs/Labor
• Humans and AI: Voting
• Intelligent Robots: Cognitive Robotics

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

As artificial intelligence and robotics increasingly reshape the global labor market, understanding public perceptions of these technologies becomes critical. We examine how these perceptions have evolved across Latin America, using survey data from the 2017, 2018, 2020, and 2023 waves of the Latinobar'ometro. Drawing on responses from over 48,000 individuals across 16 countries, we analyze fear of job loss due to artificial intelligence and robotics. Using statistical modeling and latent class analysis, we identify key structural and ideological predictors of concern, with education level and political orientation emerging as the most consistent drivers. Our findings reveal substantial temporal and cross-country variation, with a notable peak in fear during 2018 and distinct attitudinal profiles emerging from latent segmentation. These results offer new insights into the social and structural dimensions of AI anxiety in emerging economies and contribute to a broader understanding of public attitudes toward automation beyond the Global North.

Problem

• Analyzing fear of job loss due to AI in Latin America
• Identifying education and politics as key concern predictors
• Exploring temporal and cross-country variations in automation anxiety

Innovation

• Survey data from Latinobarómetro waves
• Statistical modeling and latent class analysis
• Analyzing structural and ideological predictors