Exploitative Labour to “Train” Datasets

Datasets are “trained” by exploitative, racialized labour practices, hiring workers in the global south to view traumatic images and flagged content for racist, sexist, and offensive content, for example.

Training AI datasets also has internal processes that perpetuate gendered harms. In their Excavating AI project, Kate Crawford and Trevor Paglen revealed, “We find an implicit assumption here: only ‘male’ and ‘female’ bodies are ‘natural’.”

Read more: 

• Excavating AI: The Politics of Images in Machine Learning Training Sets
• OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic
• At the Tensions of South and North: Critical Roles of Global South Stakeholders in AI Governance
• The False Comfort of Human Oversight as an Antidote to A.I. Harm