Sworn Declaration from Ex-Security Officer Exposes Flaws in Peppermill Reno Facial Recognition Technology
Former Peppermill Reno officer Aaron Gamino alleges the facial recognition system produced up to 12 false matches per shift with minimal staff training. His sworn statement supports Jason Killinger’s 2023 wrongful arrest lawsuit, now backed by the ACLU and Innocence Project. It contradicts defense claims that the system made no errors.
SCCG Take — This testimony exposes liability risks for operators using unverified facial recognition without training or database corrections. Casinos must add human verification layers to limit false arrests and civil rights claims.
A former security officer at Peppermill Reno has alleged that the casino resort’s facial recognition system regularly produces false matches. The claims by Aaron Gamino appear in a sworn declaration connected to civil rights litigation filed after a patron’s mistaken arrest.
Jason Killinger visited the property in 2023 and was arrested after the system incorrectly identified him as a previously banned customer. Killinger presented legal documents verifying his identity yet was still detained. He filed suits against Peppermill Reno, the arresting casino worker, and the City of Reno. The resort settled with Killinger while the remaining cases continue. Those actions have now secured support from the American Civil Liberties Union (ACLU) and the Innocence Project.
Gamino worked at the resort from 2024 to 2026, after the Killinger incident. His account directly contradicts earlier statements by the defendants that the system did not generate incorrect identifications.
Management Practices and Reported Errors
Gamino said that the facial recognition system regularly misidentified patrons. He reported as many as 12 false matches within a single shift. Security personnel received almost no training on the technology. Management instructed officers to detain suspected trespassers even when valid documents proved their identity. Gamino added that his supervisor was harsh toward colleagues who questioned the approach. The casino also allegedly failed to correct its database after errors were discovered.
Civil liberties advocates maintain that automated facial recognition alone is not a cause for arrest, as reported by GamblingNews.
Liability Exposure in Automated Security Systems
The conflicting accounts and pending litigation highlight concrete risks when casinos deploy identification technology without verification steps or staff preparation. Operators face potential civil rights claims and amplified scrutiny from advocacy groups whenever system errors lead to wrongful arrests. Future deployments will require documented accuracy checks and training records to reduce exposure on similar facts.
Reporting: GamblingNews
Generated by SCCG’s automated editorial system from published source reporting. SCCG Management holds editorial responsibility.
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