Detroit Police Wrongfully Arrested Black Man Due To Faulty FRT

January 30, 2020

A recent incident in Detroit underscores the importance of trustworthy and safe AI practices. A Black man was wrongfully detained by law enforcement due to a faulty facial recognition result, emphasizing the need for robust governance and guardrails in AI deployment.

This unfortunate event serves as a stark reminder of the potential harm that can arise from the misuse or misapplication of AI technologies. The HISPI Project Cerebellum TAIM (Govern) seeks to prevent such incidents by providing insights into AI incident mapping and measurement, aiming for the implementation of safe and secure AI practices.

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Matched TAIM controls

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

MEASURE 2.6 — similarity 0.738, rank 1. TAIM detail and related incidents →
MAP 4.1 — similarity 0.702, rank 2. TAIM detail and related incidents →
MAP 1.6 — similarity 0.698, rank 3. TAIM detail and related incidents →

Alleged deployer: detroit-police-department
Alleged developer: dataworks-plus
Alleged harmed parties: robert-julian-borchak-williams, black-people-in-detroit

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/74

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.