DARR
Home / Navigator / MR-044
MR-044 Third party & supply chain Organization scope

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

Source standard
MIT AI Risk Repository v4
MIT source entries
8 entries across 7 papers
  • Abercrombie2024A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms58.07.09
  • Hagendorff2024Mapping the Ethics of Generative AI: A Comprehensive Scoping Review05.12.00
  • Leech2024Ten Hard Problems in Artificial Intelligence We Must Get Right54.01.01
  • Li2025A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents66.04.07
  • Shelby2023Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction11.05.04
  • Uuk2025A Taxonomy of Systemic Risks from General-Purpose AI61.01.04 61.02.25
  • Weidinger2023Sociotechnical Safety Evaluation of Generative AI Systems18.06.05

Ev IDs of the entries consolidated into this risk in the MIT AI Risk Repository (V4); the source sheet row appears on hover.

ISO/IEC references
23894 src 4, 10 | 42001 ctrl A.10.3

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.

Sourcesframeworks that contributed to the register
1
  • A.10.3 ISO/IEC 42001 Annex A A.10.3
Cross-checksframeworks mapped in to test coverage
1
  • ibm-human-exploitation Human exploitation

More in Third party & supply chain

MR-018MR-047MR-064MR-065
See all Third party & supply chain risks →

Part of the Deployer AI Risk Register, an open-source resource powered 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.