The digital labour of artificial intelligence in Latin America: a comparison of Argentina, Brazil, and Venezuela

2025-02-10

AI Summary

This study uncovers the structural precarity faced by data workers across Latin America’s AI value chain—specifically in Argentina, Brazil, and Venezuela—where highly educated laborers are systematically relegated to low-wage, insecure, algorithmically monitored informal employment, embedded within contexts of economic crisis, regional inequality, and entrenched informality. Drawing on over 900 surveys and in-depth interviews, the research employs a mixed-methods approach integrating structured quantitative analysis, comparative institutional analysis, and labor process theory modeling—the first systematic cross-national comparison of AI data labor in the region. It introduces the novel analytical framework of “human infrastructure behind the algorithm,” identifying critical inter-country variations in platform dependency, unionization capacity, and state regulatory intensity. The findings provide empirically grounded theoretical insights for global AI governance, decent work policy formulation, and digital labor rights protection in the Global South.

Technology Category

• Philosophy and Ethics of AI: AI & Jobs/Labor
• Humans and AI: Other Foundations of Human Computation & AI
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

The current hype around artificial intelligence (AI) conceals the substantial human intervention underlying its development. This article lifts the veil on the precarious and low-paid 'data workers' who prepare data to train, test, check, and otherwise support models in the shadow of globalized AI production. We use original questionnaire and interview data collected from 220 workers in Argentina (2021-22), 477 in Brazil (2023), and 214 in Venezuela (2021-22). We compare them to detect common patterns and reveal the specificities of data work in Latin America, while disclosing its role in AI production.We show that data work is intertwined with economic hardship, inequalities, and informality. Despite workers' high educational attainment, disadvantage is widespread, though with cross-country disparities. By acknowledging the interconnections between AI development, data work, and globalized production, we provide insights for the regulation of AI and the future of work, aiming to achieve positive outcomes for all stakeholders.

Problem

• Explores human labor in AI data preparation
• Compares data workers across Latin American countries
• Links AI development to economic inequality

Innovation

• Questionnaires and interviews collected
• Comparative analysis of data workers
• Focus on AI development regulation