Incident Analysis: Amazon's Facial Recognition System Mistakes 28 Congress Members with Mugshots - Highlighting the Need for Responsible AI
This AI incident involving Amazon's facial recognition system underscores the importance of trustworthy and safe AI. The system falsely matched 28 members of Congress with mugshots, highlighting the potential risks of unregulated AI use. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).JOIN US To help prevent such incidents and promote harm prevention through responsible AI governance, join us.
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/114
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.