Bias in Automated Adult Content Detection Tools: Impact on Women's Visibility
February 25, 2006
Automated content moderation tools, designed to filter sexual explicitness or 'raciness', have reportedly demonstrated gender bias, leading to suppression of women's content reach despite adherence to platform policies. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). JOIN US: Help us ensure safe and secure AI by reporting incidents like this.
- Alleged deployer
- meta, linkedin, instagram, facebook
- Alleged developer
- microsoft, google, amazon
- Alleged harmed parties
- linkedin-users, instagram-users, facebook-users
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/469
Data source
Incident data is from the AI Incident Database (AIID).
When citing the database as a whole, please use:
McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.
Pre-print on arXiv · Database snapshots & citation guide
We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.