Description: Coffee County, Georgia, prosecutors allege former sheriff's deputy Chris Ashley Rozar used the department's Flock Safety license-plate reader system and other law-enforcement databases for personal purposes, including tracking and surveilling a woman without her consent in April–May 2024. A 2026 grand-jury indictment charged him with stalking, computer invasion of privacy, misuse of captured license-plate data, and violation of oath.
Editor Notes: The incident ID date is 04/10/2024, the earliest date in the indictment's reported 04/10/2024–05/01/2024 alleged-conduct window; available reporting does not establish that this was specifically the first Flock search. In 2024, then-Sheriff Doyle Wooten requested a GBI investigation, and Rozar was terminated after the investigation began. On 05/05/2026, Rozar was arrested following an eight-count indictment and released on bond. On 05/08/2026, the alleged victim spoke publicly while remaining anonymous. The incident ID was created on 09/30/2026.
Entities
View all entitiesAlleged: Surveillance technology developers , Flock Safety and Automated license plate reader (ALPR) developers developed an AI system deployed by Stalkers , Law enforcement , Coffee County Sheriff's Office (Georgia) and Chris Ashley Rozar, which harmed Women and girls , Women , Victims of stalking , Unnamed woman allegedly tracked by Chris Ashley Rozar , Privacy , Individuals whose license plate data were accessed for non-law-enforcement purposes and Individuals subjected to unauthorized surveillance.
Incident Stats
Incident ID
1716
Report Count
1
Incident Date
2024-04-10
Editors
Daniel Atherton
Incident Reports
Reports Timeline
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DOUGLAS, Ga. (WALB) — The woman at the center of the stalking allegations against former Coffee County Sheriff’s deputy Chris Ashley Rozar is now speaking out, saying she hopes sharing her story encourages other women to come forward.
Rozar…
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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