Flock makes undisclosed algorithm mandatory to flag police misuse of license plate readers

Flock’s Audit Assistance tool is now a non-negotiable component for every customer. The company states the tool detects abnormal activity, such as repetitive searches on the same license plate or inconsistent case codes, and locks out flagged users until an administrator intervenes. However, Flock has not provided a detailed explanation of the algorithm’s logic, the data it uses, or the thresholds that trigger flags. This lack of transparency makes it difficult for engineers to evaluate whether the tool reliably identifies misuse or merely creates a superficial compliance layer.

The tool’s effectiveness remains unverified. Flock claims Audit Assistance has already helped customers spot abuse, yet it has not shared statistics on detection rates, false positives, or false negatives. Without independent audits or published benchmarks, agencies adopting the tool cannot assess its accuracy or reliability. Privacy advocates argue that without these metrics, the tool may serve as a public relations measure rather than a functional safeguard. Engineers integrating such systems need concrete data to determine whether the tool meets operational or legal requirements.

Flock’s decision to mandate the tool by year-end raises operational concerns. Customers must now rely on an undisclosed algorithm to monitor user behavior, which could lead to unintended disruptions if the tool flags legitimate searches as suspicious. The company’s assertion that the tool is not AI-driven does not address whether it can adapt to evolving misuse tactics. Without clear documentation, agencies may struggle to justify the tool’s use in court or to oversight bodies, increasing legal and reputational risks.

The broader implications extend beyond Flock’s platform. If the tool proves ineffective, it could set a precedent for other surveillance vendors to implement opaque compliance mechanisms. Engineers working on similar systems should note the importance of transparency in detection logic, as well as the need for third-party validation to ensure tools meet their stated goals. The absence of these elements in Flock’s rollout highlights the risks of adopting unproven safeguards in high-stakes environments.