2026-09-20T23:22:28.549Z
- publishedAt:
Not provided→ 2023-07-03T00:00:00.000Z
SOURCE-LINKED INTELLIGENCE
Harmful Stereotyping of Non-Cisgendered People via Text-to-Image Systems
Text-to-image systems such as DALL-E are allegedly generating biased and often insulting representations of non-cisgender identities. The systems tend to generate stereotypical and sexualized images when prompted with gender identity terms like "trans," "nonbinary," or "queer," highlighting systemic issues of bias.
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- recordType
- incident-report
- evidenceStatus
- reported
- region
- Global
Reported occurrence date: 2023-07-03T00:00:00.000Z
Evidence & attribution
- AI Incident Database
- AI Incident Database · 2023-07-03T00:00:00.000Z
AI Incident Database, Responsible AI Collaborative; McGregor (2021), Preventing Repeated Real World AI Failures by Cataloging Incidents. Incident-specific contributor credits are available at each citation link. Metadata adapted; article text excluded.
License: CC BY-SA 4.0
First collected: 2026-09-19T22:50:59.123Z. This is not the publication date.
Observed changes
AIIC observation times, not verified publisher revision times. Up to eight recent revisions.