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

Gianna Williams, Maya De Los Santos, Alexandra To, Saiph Savage
1/13/2025
cs.CYcs.AIcs.HC

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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.

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@article{williams2025data,
  title  = {Data Enrichment Work and AI Labor in Latin America and the Caribbean},
  author = {Gianna Williams and Maya De Los Santos and Alexandra To and Saiph Savage},
  year   = {2025},
  eprint = {2501.06981},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2501.06981v1}
}

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