Bias in Twitter's Photo Crop Algorithm: Impact on White Faces and Women - Highlighting the Need for Responsible AI Governance
This AI incident sheds light on a concerning bias within Twitter's photo crop algorithm, disproportionately favoring white faces and women. It underscores the importance of safe and secure AI governance in promoting trustworthy AI practices. Join us in advancing harm prevention efforts by adhering to guardrails for AI with Project Cerebellum, an initiative dedicated to building an AI incident database. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/103
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.