Woman Pulled From Car at Gunpoint By Police After Mistaken Flock Alert - Twice

On Thursday, police surrounded the woman’s car, drew their weapons, and instructed her to exit with her hands up, believing she was connected to a recent murder. The response was triggered by an alert from a Flock license plate reader that had incorrectly associated her plate with a suspect. The woman described the experience as frightening, fearing that any sudden movement could be fatal.

A similar stop occurred on Monday, when officers again pulled her over with guns drawn, towed her car, and released her without explanation. She said the repeated incidents left her traumatized and scared to drive, with her daughter sharing that fear. She reported sleeplessness and intrusive images of guns whenever she tried to rest.

Police attributed the problem to a data entry error made by another department that failed to remove the outdated alert from the Flock system. They emphasized that the Flock cameras themselves were not at fault, but that the incorrect data persisted in the network. The woman demanded an apology, saying the failure was systemic and personal.

For engineers, the case underscores that the reliability of automated license plate readers depends entirely on the accuracy of the data fed into them. Adopting such systems requires rigorous processes for data entry, timely updates, and cross-departmental coordination to prevent stale or wrong records. When data integrity breaks down, the technology can produce false positives that escalate to armed confrontations.

The incident also shows where the technology stops working: if a record is not purged or corrected, the system will continue to match innocent vehicles to outdated alerts, regardless of camera quality. Mitigation strategies include automated expiration of alerts, human review before escalation, and clear accountability for data management. Without those safeguards, the risk of harm to the public remains high.