Woodbridge Police Department wrongfully arrests man via facial recognition
The Woodbridge Police Department arrested Nijeer Parks for shoplifting after facial recognition software incorrectly identified him as a suspect. Parks was jailed for ten days despite being 30 miles away during the crime.
Records by entity: Woodbridge Police Department
Nijeer Parks was wrongfully jailed for ten days after the Woodbridge Police Department relied on a false facial recognition match.
Facial recognition software produced a false match that police relied upon to arrest an innocent man.
Key facts
- What
- The Woodbridge Police Department arrested Nijeer Parks for shoplifting after facial recognition software incorrectly identified him as a suspect.
- Incident date
- Feb 1, 2019
- Who
- Woodbridge Police Department
- Failure mode
- Hallucination
- AI surface
- Computer Vision
- Severity
- High
What happened
The Woodbridge Police Department arrested Nijeer Parks following a misidentification by facial recognition software. He was accused of shoplifting and attempting to hit a police officer with a car. Parks was held in jail for ten days before the error was recognized.
What broke inside the model
The facial recognition system generated a false positive match between a suspect's image and Parks's license photo. Police relied on this AI lead as primary evidence without verifying Parks's actual location at the time of the crime.
What it cost
Sources
Cite this entry
https://failureindex.ai/failures/woodbridge-police-department-wrongfully-arrests-manAI Failure Index. "Woodbridge Police Department wrongfully arrests man via facial recognition" (FI-0444). Realm Labs. https://failureindex.ai/failures/woodbridge-police-department-wrongfully-arrests-man (indexed Jun 10, 2026).Data fields CC-BY 4.0, prose citation permitted. Incident ID FI-0444. Full dataset at /data.
Note from Realm Labs, the Index steward
How Realm fits
- Prism
- OmniGuard
- AI Detection & Response (AIDR)
This entry sits in the index's predictive wing: a system that scores, ranks, perceives, or steers rather than generates. Realm's runtime layer is built for the generative and agentic systems now moving into these same decision seats, where it watches a model's internal state and holds an unsupported claim or an unchecked action before it commits. The control gap on this record, an automated decision that reached people with no runtime check in front of it, is the same gap. The index keeps predictive failures on the record because the pattern carries straight into the systems shipping today.