Imagine going about your day, only to find yourself boxed in by four police cars — all because of a partial license plate alert triggered by a private company’s surveillance system. This exact scenario recently befell two journalists testing Land Rover press vehicles, highlighting a troubling disconnect between institutional safeguards and the real-world consequences of data errors.
Flock’s License Plate Matching: A Cautionary Tale
Flock, a company providing license plate recognition technology to law enforcement, flagged two different Land Rover test vehicles for "stolen plates" — based on what turned out to be partial or inaccurate data. Joel Feder of The Drive found himself cornered in a Kohl’s parking lot by Plymouth police, who had been monitoring him for days using Flock’s cameras. Shortly after, Tim Esterdahl from Pickup Truck + SUV Talk was detained for 90 minutes during a similar vehicle check.
- The plates causing the alerts were manufacturer plates from New Jersey, labeled as "34 10 DTM" and "34 08 DTM," with the middle numbers distinguishing individual cars.
- The original entry into the National Crime Information Center (NCIC) system was a partial plate, "34DTM," classed as stolen — but it turns out the plate had been lost, not stolen, during a Land Rover photoshoot.
Policies Ignored, Systems Overwhelmed
According to the NCIC operating manual, which governs entries into this law enforcement database, several clear rules were violated:
- Theft reports are mandatory: Only license plates with official theft reports can be entered as stolen. No such report existed here.
- Partial plates are prohibited: The manual explicitly forbids entries of partial license plates to prevent false matches.
- Plate types must be specified: Manufacturer plates are classified distinctly, which wasn’t properly recorded.
- Verification is essential: Before an officer acts on a hit, they must confirm the plate matches exactly with the entry. Here, stops were based on partial matches without confirmation.
- DMV checks can correct errors: State vehicle registries can flag and cancel erroneous entries but apparently were not engaged in this case.
In short, every safeguard designed to keep innocent people from being wrongly stopped was either ignored or ineffective.
Private Data, Public Consequences
Flock’s system, according to its Chief Communications Officer Joshua Thomas, intentionally alerts on any partial matches, reflecting what law enforcement prefers. But this approach clashes directly with NCIC policies and risks turning citizens’ private vehicle data into a source of mistaken identity. Notably, the alerts appeared on officers’ smartphones without the critical warnings mandated by NCIC for partial matches — warnings that could prevent wrongful stops.
This case is a stark reminder that private companies controlling sensitive data have outsized influence on people’s everyday lives. When data quality falters, ordinary individuals face serious consequences, like prolonged detentions or confrontations with police. As Feder observed, such mistakes could have led to someone getting hurt or worse.
A Call for Accountability
The crux of the problem isn’t just "messy data" or imperfect software — it’s how institutions abdicate responsibility and let flawed processes persist. The existing guardrails are not missing; they’ve been disregarded. Rather than calling for more complex rules, there’s a pressing need to reevaluate who holds the keys to sensitive data, how that data is validated, and how its misuse is curtailed.
In the meantime, consumers and citizens should remain aware that private companies like Flock, wielding real-time surveillance data, can inadvertently ensnare innocent people. Transparency, oversight, and respect for established protocols must become priorities—not optional extras.
For a deeper dive into the original reporting and detailed analysis, see The Drive’s article.