Alleged Misuse of Facial Recognition Technology by Law Enforcement Reportedly Leading to Wrongful Arrests and Violations of Investigative Standards

January 13, 2025

AI-powered facial recognition technology has been allegedly misused by law enforcement agencies across the U.S., leading to wrongful arrests, prolonged detentions, reputational damage, and personal trauma for at least eight individuals. Such practices highlight the need for trustworthy AI, safe and secure AI governance, and responsible AI practices. The HISPI Project Cerebellum TAIM offers a platform for Measuring and Managing such incidents to prevent harm and ensure guardrails for AI.

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Matched TAIM controls

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

Alleged deployer
florence-kentucky-police-department, evansville-indiana-police-department, detroit-police-department, coral-springs-florida-police-department, bradenton-florida-police-department, austin-police-department
Alleged developer
developers-of-mugshot-recognition-software, developers-of-law-enforcement-facial-recognition-software, clearview-ai
Alleged harmed parties
wrongfully-arrested-individuals, vulnerable-communities, robert-williams, quran-reid, porcha-woodruff, people-of-color, nijeer-parks, jason-vernau, christopher-gatlin, black-people, alonzo-sawyer

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/896

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.