AIBlindspot
← All case studies
HUMHUM-005 — Workforce Displacement Anxiety

AI Industry Conceals Dependence on Exploited Global South Data Workers

3/5Sector: TechnologyGeography: GlobalStage: DevelopIngested: —

Executive Summary

Machine learning systems rely on a $13.7 billion annotation industry staffed largely by low-paid Global South workers whose rights are routinely disregarded. Boards risk reputational, supply-chain ethics, and regulatory exposure by treating data labour as an invisible input rather than a governed dependency.

Domain

Human Factors

Blindspots in change management, skills, human-AI collaboration, trust, workforce, and culture.

Source

MIT AI Risk Repository — Ten Hard Problems in Artificial Intelligence We Must Get Right (Leech2024) ↗

https://airisk.mit.edu/

Could this happen in your organisation?

A Velinor AI Audit maps your active AI portfolio against the 50+ blindspots and benchmarks against documented sector failures like this one. A board-ready foresight document in 5 weeks.