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Policing · Netherlands · 2026 · A police profiling algorithm run on number plate camera data without monitoring of what its hits led to, without a data protection impact assessment and, the minister later told parliament, without ever being checked for discriminatory bias

Dutch Auditors Found Police Did Not Track What Their Number Plate Algorithm Led To

By Ellie Harris · Filed Algorithm in use by the police, including the Flexible Intervention Team on main transport routes, at the time of the audit of 2025

Alleged: Dutch National Police (Politie) developed or deployed the AI system implicated in this incident. Details are drawn from public reports; parties are presumed innocent of any wrongdoing not established by an official finding.

Dutch Auditors Found Police Did Not Track What Their Number Plate Algorithm Led To

What happened

The Netherlands Court of Audit (Algemene Rekenkamer) reported on 20 May 2026 on the police’s use of iTrechter, an algorithm that analyses data from sensors, including cameras that recognise number plates. According to the report, iTrechter runs profiles based on different kinds of criminal behaviour. When it picks up a possible match, it produces a “hit” that the police can act on.

The audit examined how the Flexible Intervention Team uses iTrechter on main transport routes such as motorways. The report describes the process: cameras scan passing vehicles, the algorithm identifies possibly suspicious cars, and officers decide whether to stop them.

The Court of Audit tested 48 risks. It found that the police managed many of them well or partly, but identified gaps in monitoring, privacy, software maintenance and IT security.

What an auditable version would have shown

According to the report, officers use their own judgement to decide which hits to follow up, and a hit alone is not enough to use police powers.

The Court of Audit found that the police did not monitor what happened after a hit. It could not establish how many were followed up, or how many led to a positive result.

The report said profiles can lead to people being wrongly stopped, or to some groups being checked more often without reason, and that the police try to refine a profile when they notice this. It does not record a case where that happened.

A record of each hit, the officer’s decision and the result would have shown how many hits were followed up and what they led to.

Where the gap was

The Court of Audit found that the police had not carried out a data protection impact assessment for iTrechter. It said the law required one because the processing was large scale and potentially high risk. The minister disputes that the requirement applied, saying iTrechter was already in use when the relevant rules took effect.

For some profiles, the report found that the police had not adequately explained why the data were needed. Their working method did not address whether the data could be used for that purpose, or the risk of indirect discrimination.

The report described iTrechter’s availability as fragile and its software as outdated. The police had intended to replace it for five years. They could not show the auditors that every system involved was fully secured.

A ConductRecord keeps each hit, the officer’s decision and the outcome.

A MetricRecord is designed to hold aggregate figures, such as hits, stops and results by profile, bound to the underlying records so they can be checked.

ConductRecord and MetricRecord are Headlights designs.

What governance should have looked like

According to the report, several police departments assess each profile before it is used. A public prosecutor considers its ethical aspects and must approve it. Profiles may run for no longer than one year.

In response, the minister said the findings on privacy, lifecycle management and IT security were partly recognised, and that the police were working on a replacement.

Answering questions from the House of Representatives on 9 June 2026, the minister said that iTrechter had not previously been checked for possible discriminatory bias, that its functionality is being moved to the Generieke Sensingplatform, that an impact assessment will be carried out for that platform, and that measures against the risks the auditors rated medium or high will be built into it.

Where police use an algorithm to select vehicles for stops, best practice would be to record what each hit leads to and report stops and results by profile. The working method should address indirect discrimination, and an impact assessment should cover the system while it remains in use.

Failure Pattern: police ran a profiling algorithm on number plate camera data without tracking what its hits led to, leaving them unable to establish how many hits were followed up or led to a result, and without a data protection impact assessment, which the auditors said the law required and the minister said it did not.

Governance Principle: a police force using a profiling algorithm should be able to show what each hit led to, who was stopped as a result, and that a completed impact assessment covered the processing.

The reference implementation of ConductRecord and MetricRecord is open source. It lives at github.com/saffronandindia/headlights-oss, Apache 2.0 licensed and free to install. The repository is public now.

Sources

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The record

An auditable system would have produced a signed, tamper-evident record the moment this happened: what the system did, the version that did it, the basis it acted on, and the action taken, and Dutch National Police (Politie) could have produced it on demand.

This is the record the system as deployed did not produce in a signed, auditable form.

What this teaches
Capture what happened when it happens
What the system did, the version that did it, the basis it acted on, and the action taken, recorded at the moment, not reconstructed after.
Sign it, so no one has to trust the record-keeper
A tamper-evident entry. Edit it later and the signature breaks. The record does not ask for the benefit of the doubt.
Make it verifiable by anyone
A court, a regulator, a customer's lawyer can check the record themselves, without taking the company, or us, at our word.

Headlights summarises publicly reported AI incidents. All summaries are independently written, attributed to their original sources, and intended for research and educational purposes. Allegations are identified as such until established through official findings.

Last reviewed September 2026. This report is based on the sources listed above and reflects information available at the time of review; later developments may not be captured. Where a person is described as charged with or alleged to have done something, that allegation is unproven unless a conviction or a court or regulatory finding is stated. Headlights publishes journalism and commentary, not legal advice.

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