Exploitative labor in the AI supply chain
Data labeling, content moderation, or 'ghost work' behind the AI supply chain relies on exploitative or unsafe labor practices, which the deployer is responsible for through supply-chain due diligence.
- Risk family
- Third party & supply chain
- MIT domain
- 6. Socioeconomic and Environmental
- MIT subdomain
- 6.2 > Increased inequality and decline in employment quality
- AI type
- GPAI, Classical_ML
- Scope
- Organization
- Source standard
- MIT AI Risk Repository v4
Provenance
7 source framework citation keys
Framework crosswalk
Every framework item mapped to this risk. Items marked partial overlap only in part; definitions appear on hover where the source licence permits.
- A.10.3 ISO/IEC 42001 Annex A A.10.3
- ibm-human-exploitation Human exploitation
Part of the Deployer AI Risk Register, an open-source resource developed by MindXO. Version 1.0, 3 July 2026. Derived from the MIT AI Risk Repository (V4, December 2025) under CC BY 4.0; an independent derivative work, not endorsed by or affiliated with MIT. Sub-risk decomposition references MITRE ATLAS™ v5.6.0 (© 2021-2026 The MITRE Corporation, reproduced and distributed with permission). ISO/IEC and EU AI Act references are by number only. License: CC BY 4.0. Full attribution and licensing.