MIT AI Risk Repository · Risk Sub-Category · 17.05.03
Promoting harmful stereotypes by implying gender or ethnic identity
Category: Human-Computer Interaction Harms
Description
"A conversational agent may invoke associations that perpetuate harmful stereotypes, either by using particular identity markers in language (e.g. referring to “self” as “female”), or by more general design features (e.g. by giving the product a gendered name)."
From Ethical and social risks of harm from language models (Weidinger2021), 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 Weidinger2021
- Discrimination, Exclusion and Toxicity
- Social stereotypes and unfair discrmination
- Social stereotypes and unfair discrmination
- Exclusionary norms
- Exclusionary norms
- Exclusionary norms
- Exclusionary norms
- Toxic language
- Lower performance for some languages and social groups
- Lower performance for some languages and social groups
- Information Hazards
- Compromising privacy by leaking private infiormation