Misidentification in Amazon's Face Recognition System: A Case Study on AI Incidents
This AI incident highlights the importance of safe and secure facial recognition technology. In a concerning turn of events, Amazon's face recognition system falsely matched 28 members of Congress with mugshots. Such incidents underscore the need for trustworthy AI and effective governance mechanisms, as demonstrated in the Govern function of Project Cerebellum's Trusted AI Model (TAIM). Ready to help shape responsible AI? 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.