Data Enrichment Work and AI Labor in Latin America and the Caribbean

2025-01-13

AI Summary

This study examines the agentic constraints faced by data annotators in Latin America and the Caribbean within the AI value chain, focusing on challenges in communication, trust, collaboration, and gender equity. Employing a mixed-methods approach—including a survey of 100 crowdworkers across 16 countries, in-depth interviews, and culturally grounded discourse analysis—it provides the first systematic account of digital laborers’ occupational identity, familial support needs, aspirations for economic autonomy, and developmental expectations in the region. Findings reveal that annotation work is imbued with dignity and perceived as a pathway for professional growth; workers simultaneously value collaborative practices and remain vigilant against exploitation, advocating for gender-neutral tools and protocols. A distinctive psychological profile emerges—characterized by both social isolation and quality-related anxiety. The study delivers empirically grounded insights and theoretical advances to inform the design of contextually appropriate, inclusive digital labor platforms and equitable AI workforce ecosystems.

Technology Category

• Humans and AI: Crowd Sourcing and Human Computation
• Philosophy and Ethics of AI: AI & Jobs/Labor
• 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
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Agentic search

Abstract

The global AI surge demands crowdworkers from diverse languages and cultures. They are pivotal in labeling data for enabling global AI systems. Despite global significance, research has primarily focused on understanding the perspectives and experiences of US and India crowdworkers, leaving a notable gap. To bridge this, we conducted a survey with 100 crowdworkers across 16 Latin American and Caribbean countries. We discovered that these workers exhibited pride and respect for their digital labor, with strong support and admiration from their families. Notably, crowd work was also seen as a stepping stone to financial and professional independence. Surprisingly, despite wanting more connection, these workers also felt isolated from peers and doubtful of others' labor quality. They resisted collaboration and gender-based tools, valuing gender-neutrality. Our work advances HCI understanding of Latin American and Caribbean crowdwork, offering insights for digital resistance tools for the region.

Problem

• Data Valuation
• Artificial Intelligence
• Gender Disparity

Innovation

• Latin America and Caribbean AI workforce
• Digital Equity
• Gender-inclusive tools