Reno police facial recognition misidentified an innocent man, leading to a $100,000 settlement
Reno Police Department used DataWorks Plus facial recognition software to match a surveillance photo to an innocent individual, resulting in a wrongful arrest. The City of Reno settled the resulting civil rights lawsuit for $100,000 and agreed to policy changes restricting facial recognition use. The department had no formal training or policies governing facial recognition technology at the time of the incident, and also maintained documented use of Clearview AI for separate searches.
Officers treated an algorithmic facial recognition match as sufficient probable cause for arrest without any independent corroborating evidence.
Key facts
- What
- Reno Police Department used DataWorks Plus facial recognition software to match a surveillance photo to an innocent individual, resulting in a wrongful arrest.
- Incident date
- May 3, 2020
- Who
- Reno Police Department
- Failure mode
- Hallucination
- AI surface
- Search / RAG
- Severity
- High
What happened
Reno Police Department ran a surveillance photo through DataWorks Plus facial recognition software, which returned a false match identifying an innocent person as a theft suspect. Officers relied on the algorithmic match without independent corroboration to secure an arrest warrant and detain the individual. Criminal charges were later dropped after the misidentification was recognized. The City of Reno settled the resulting civil rights lawsuit for $100,000 and agreed to policy changes requiring independent corroborating evidence before facial recognition matches can be used as probable cause for arrest.
What broke inside the model
- 01 · TriggerA user asks for a fact, a citation, or a figure.
- 02 · Model stepThe model writes a fluent, confident answer.
- 03 · Control gapNothing ties the claim back to a real source.
- 04 · FailureA fabricated fact ships as if it were verified.
- 05 · ConsequenceThe false claim reaches a customer, a court, or the public.
Confidence holds, and even spikes, as the claim detaches from any source.
The DataWorks Plus facial recognition algorithm produced a false match between a surveillance photo and an innocent individual's photo in a state database. Officers treated the algorithmic match as sufficient probable cause for arrest without requiring independent corroborating evidence, and the department had no formal training or policies governing facial recognition use at the time, removing any institutional safeguard against acting on a false algorithmic output.
What it cost
Sources
- PressOfficer Admits AI-Based Arrest Was a Mistake in Courtthisisreno.com
- PressFacial Recognition Lawsuit Exposes Police Training Gapsthisisreno.com
- PressNevada facial recognition project draws scrutiny over privacy, police oversightbiometricupdate.com
Cite this entry
https://failureindex.ai/failures/reno-police-facial-recognition-misidentifiedAI Failure Index. "Reno police facial recognition misidentified an innocent man, leading to a $100,000 settlement" (FI-0111). Realm Labs. https://failureindex.ai/failures/reno-police-facial-recognition-misidentified (indexed Jun 4, 2026).Data fields CC-BY 4.0, prose citation permitted. Incident ID FI-0111. Full dataset at /data.
Note from Realm Labs, the Index steward
How Realm would have caught this
- Prism
- OmniGuard
- AI Detection & Response (AIDR)
A runtime layer that watches the model's internal state can flag the moment a model commits to a claim it has no support for, and hold or reroute the response before it reaches a user. Realm reads those signals in real time rather than grading the transcript after the fact.