Flock’s Abuse Detection Tool Faces Skepticism Over Missing Details

Flock, the surveillance technology company that operates automated license plate reader systems for law enforcement, announced a series of new accountability measures on Thursday. Central to the announcement is a tool called Audit Assistance, which the company says will help police departments detect and prevent misuse of its cameras. Yet despite claims that the feature is critical to curbing abuse, Flock has declined to fully explain how the system actually works.

The New Framework

Flock’s announcement introduced several policy changes designed to tighten controls on its systems. The company now recommends that police departments retain data for seven days instead of the previous 30-day standard. For situations requiring longer retention, a new feature called Evidence Mode allows customers to keep records in “exceptional cases” — but only when tied to a specific case number, adding a layer of documentation.

Departments using Flock can now also restrict how they share data with other customers based on the type of offense under investigation. These changes reflect an attempt to reduce the window during which plate reader data remains accessible and to limit its circulation among law enforcement agencies.

Audit Assistance: What Flock Says It Does

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The centerpiece of Flock’s accountability strategy is Audit Assistance, which the company launched in April. According to Flock’s announcement, more than one-third of its current customers have already enabled the tool — a sign of adoption that Flock now intends to make mandatory, requiring all customers to turn it on by the end of the year.

The Stated Capabilities

Flock describes Audit Assistance as a system that “detects abnormal activity and flags it for Administrator review.” When flagged, the tool can automatically lock out users until an administrator intervenes. Company executives have pointed to specific examples of what the tool catches. Ashley Haber, Flock’s head of trust and compliance, cited in a video the tool’s ability to flag “what may look like an odd search history from a specific user.” Co-founder Paige Todd described the feature as one that “flags unusual patterns early,” offering a concrete example: “a user searching the same plate repetitively for more than 30 days.”

How It Actually Works — and Doesn’t

Flock told TechCrunch that Audit Assistance is not based on machine learning or artificial intelligence. Instead, the company characterizes it as “a data tool that flags atypical search patterns for further review.” When pressed for specifics, Flock offered one example: a flag would trigger if a user searched for the same license plate using multiple different case codes, which “could potentially indicate abuse.”

The company emphasized that a flag does not constitute proof of misconduct — it merely signals that activity warrants investigation. Beyond this limited explanation, Flock has resisted providing deeper technical details. Questions about the tool’s underlying algorithm, the data used to train it, the specific categories of patterns it identifies as abnormal, and what precisely constitutes “abnormal activity” remain unanswered.

A Case Study in Law Enforcement Response

Major Patrick Krieg of the Dunwoody, Georgia Police Department, a Flock customer, described Audit Assistance in a press release as “an algorithm that has notified us of any type of bias.” Earlier this week, three former Georgia sheriff’s deputies were arrested and accused of using Flock cameras to stalk individuals with whom they had personal relationships. In that case, Bibb County Sheriff David Davis specifically credited Flock’s new tool with uncovering the misuse, lending credibility to claims that the system can detect real abuses.

The Privacy Advocacy Pushback

Privacy organizations and security researchers have greeted Flock’s announcement with caution and skepticism, pointing to fundamental gaps in accountability and proof of effectiveness.

ACLU’s Verification Challenge

Chad Marlow, senior policy counsel at the American Civil Liberties Union, responded to Flock’s announcement by questioning whether the company has provided any real evidence of the tool’s success. He noted that while dozens of officers have been arrested, fired, or disciplined for misusing Flock systems, this alone does not demonstrate the tool’s efficacy. “Unless we know the number of officers misusing the system, we cannot conclude if Flock and its auditing tools are catching 95% of violators or 5%,” Marlow wrote. He called for independent evaluation of Audit Assistance to determine its actual effectiveness, arguing that without such verification, it remains unclear whether the tool is a legitimate security measure or merely a public relations exercise.

EFF’s Systemic Concerns

Cooper Quintin, a security researcher and senior public interest technologist at the Electronic Frontier Foundation, raised a different but equally troubling concern. Even if Audit Assistance works as intended, law enforcement could develop workarounds to evade detection. More fundamentally, Quintin argued that detection alone is insufficient without enforcement: “If there are no consequences for abuse and whoever [the tool] reports to is the same police agency that is doing the abuse, it’s just a fig leaf for Flock.” He suggested that the most effective accountability mechanism would be legislation constraining the technology’s use and requiring warrants for deployment.

Brennan Center’s Cautious Support

Rachel Levinson-Waldman, director of the Brennan Center’s Liberty and National Security Program, offered a more measured perspective. She acknowledged that making Audit Assistance mandatory represents progress and that the tool is “a great idea” in theory. However, she emphasized that the tool itself requires independent auditing before conclusions about its real-world effectiveness can be drawn.

The Missing Data

Flock has not disclosed several critical metrics that would help evaluate Audit Assistance’s true impact. No statistics show how many flagged incidents have been investigated, confirmed, or led to disciplinary action. The tool’s false positive rate — how often it flags legitimate searches — and its false negative rate — how many abuses it misses — remain unknown. Third-party audit results, if any have been conducted, have not been made public.

Escalating Real-World Incidents

The announcement comes against a backdrop of documented abuse involving Flock’s technology. The arrest of three former sheriff’s deputies in Bibb County, Georgia earlier this week represents just the latest in what privacy advocates describe as a pattern. These deputies allegedly used Flock cameras to stalk individuals with whom they had personal relationships — a form of abuse that law enforcement agencies themselves have acknowledged as a risk.

The Accountability Gap

Flock’s policy changes address data retention and sharing, while Audit Assistance targets detection of unusual search behavior. Yet skeptics argue these measures do not address the fundamental accountability problem: the absence of independent oversight. When the tool flags potential abuse, the investigation typically falls to the same department or agency whose employees may be under suspicion. Without external auditing of the tool itself and independent investigation of flagged incidents, critics contend that Flock’s new framework amounts to internal policing of internal misconduct — an inherent conflict of interest.