MIT AI Risk Repository · Risk Sub-Category · 13.01.01
Bias, Stereotypes, and Representational Harms
Category: Impacts: The Technical Base System
Description
"Generative AI systems can embed and amplify harmful biases that are most detrimental to marginalized peoples."
From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Causal entity
- AI
- Intent
- Unintentional
- Timing
- Other
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
How other frameworks describe this risk
Other entries from Solaiman2023
- Impacts: The Technical Base System
- Cultural Values and Sensitive Content
- Cultural Values and Sensitive Content
- Disparate Performance
- Privacy and Data Protection
- Financial Costs
- Environmental Costs
- Data and Content Moderation Labor
- Impacts: People and Society
- Trustworthiness and Autonomy
- Trustworthiness and Autonomy
- Trustworthiness and Autonomy