MIT AI Risk Repository · Risk Category · 56.01.00
Discrimination
Description
"More broadly, bad decisions or errors by AI tools could lead to discrimination or deeper inequality"
From Future Risks of Frontier AI (GOS2023), 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
How other frameworks describe this risk
Other entries from GOS2023
- Inequality
- Environmental impacts
- Amplification of biases
- Harmful responses
- Lack of transparency and interpretability
- Intellectual property rights
- Providing new capabilities to a malicious actor
- Misapplication by a non-malicious actor
- Poor performance of a model used for its intended purpose, for example leading to biased decisions
- Unintended outcomes from interactions with other AI systems
- Impacts resulting from interactions with external societal, political, and economic systems
- Loss of human control and oversight, with an autonomous model then taking harmful actions