Twitter's Photo Crop Algorithm Bias Towards White Faces and Women: An Examination of Responsible AI

A recent study revealed that Twitter's photo crop algorithm appears to favor white faces and women, raising concerns about safe and secure AI and its impact on AI governance. The findings suggest a need for more robust trustworthy AI models and harm prevention strategies.

Matched TAIM controls

Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

GOVERN 3.1 — similarity 0.510, rank 1. TAIM detail and related incidents →
MEASURE 2.11 — similarity 0.509, rank 2. TAIM detail and related incidents →
MAP 1.6 — similarity 0.502, rank 3. TAIM detail and related incidents →

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.