MIT AI Risk Repository · Risk Sub-Category · 52.01.01
Discrimination and Stereotype Reproduction
Category: Risks from Unreliability
Description
"General purpose AI models interpret and respond to inputs based on their training data, potentially causing Discrimination and Stereotype Reproduction. Since they are “black-box” models, the exact mechanism behind decisions remains opaque and attempts to mitigate harmful outputs are not fully reliable yet. These models have the capacity to influence a multitude of downstream applications, decisions, and processes, thereby affecting many individuals simultaneously. The extent of this impact could outstrip the range of any single human or group of humans, amplifying the potential consequences o
From Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks (Maham2023 ), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Causal entity
- AI
- Intent
- Unintentional
- Timing
- Post-deployment
Subdomain definition: Unequal treatment of individuals or groups by AI, often based on race, gender, or other sensitive characteristics, resulting in unfair outcomes and representation of those groups.
Real-world incidents in this subdomain
- DOGE Reportedly Relied on Unvetted ChatGPT Outputs in Canceling National Endowment for the Humanities Grants
- Sora Video Generator Has Reportedly Been Creating Biased Human Representations Across Race, Gender, and Disability
- Meta AI Characters Allegedly Exhibited Racism, Fabricated Identities, and Exploited User Trust
- Alleged AI-Generated Photo Alteration Leads to Inappropriate Modifications in Speaker's Conference Picture
- Algorithmic Bias in French Welfare System Allegedly Discriminates Against Marginalized Groups
- Department for Work and Pensions (DWP) AI Systems Allegedly Discriminate Against Single Mothers