Misidentification in Facial Recognition Systems: The Case of an Asian Man

An alarming incident occurred recently where a facial recognition system incorrectly identified an Asian man as having his eyes closed. This underscores the need for responsible AI, ensuring that these systems are safe and secure. Improper training data can lead to such mistakes, highlighting the importance of trustworthy AI governance and harm prevention measures.

Matched TAIM controls

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

MEASURE 2.2 — similarity 0.462, rank 1. TAIM detail and related incidents →
MAP 1.6 — similarity 0.442, rank 2. TAIM detail and related incidents →
MAP 3.5 — similarity 0.442, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/48

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.