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Incident 1476: Maryland Police Allegedly Relied on Facial Recognition Lead in Wrongful Arrest and Detention of Kimberlee Williams

Description: Kimberlee Williams was reportedly arrested in Oklahoma on Maryland warrants after police allegedly relied on a facial recognition lead that incorrectly identified her as a suspect in bank fraud cases. The ACLU said Williams had never been to Maryland, police failed to investigate alibi evidence placing her in Oklahoma, and she spent about six months in jail before the charges were dropped.
Editor Notes: Timeline notes: The incident date of 06/23/2021 marks the reported date of Kimberlee Williams's arrest, which was based on warrants from December 2019 and January 2020. The incident ID is based off of reporting from the ACLU's article of 04/14/2026. The incident ID was created 05/03/2026.

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Alleged: Unknown facial recognition technology developers developed an AI system deployed by Montgomery County Police Department , Anne Arundel County Police Department and Prince George's County Police Department, which harmed Kimberlee Williams , Wrongfully arrested individuals and Epistemic integrity.
Alleged implicated AI systems: Facial recognition technology and Crimedex

Incident Stats

Incident ID
1476
Report Count
1
Incident Date
2021-06-23
Editors
Daniel Atherton

Incident Reports

Reports Timeline

Incident OccurrenceMore than a Dozen Wrongful Arrests Due to Police Reliance on Facial Recognition Technology
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More than a Dozen Wrongful Arrests Due to Police Reliance on Facial Recognition Technology

More than a Dozen Wrongful Arrests Due to Police Reliance on Facial Recognition Technology

aclu.org

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More than a Dozen Wrongful Arrests Due to Police Reliance on Facial Recognition Technology
aclu.org · 2026

One ACLU client spent six months in jail, because police relied on facial recognition technology to incorrectly identify her as a suspect. She's the fourteenth person known to be wrongfully arrested due to the technology's failures.

When po…

Variants

A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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