How the Dutch Police Clung to Predictive Policing for a Decade Without Evidence - AlgorithmWatch

How the Dutch Police Clung to Predictive Policing for a Decade Without Evidence

by Lotte Debrauwer The Crime Anticipation System was discontinued in early 2026 after a devastating internal report concluded that its 'predictive' capabilities were extremely limited. The police were never able to demonstrate that the algorithm had any measurable impact on reducing crime.

Story<br>August 18, 2026<br>Auf Deutsch lesen<br>#fellowshipstory #netherlands #predictivepolicing

Image credit: Mingo Hagen | Flickr (CC BY 2.0)

While Dick Willems is coding on a computer in a small office at the headquarters of the Dutch police in Amsterdam, a sense of chaos and excitement lingers in the air. It is 2013 and the Dutch police is going through a major transformation: 25 regional units are merged into a single National Police. Key to the process is a new approach to ‘intelligence-led policing’, a strategy which aims to use data and knowledge to deploy police resources more effectively and plan incident-driven approaches proactively instead of just reacting to crime.

Dick Willems is a seasoned data scientist. He was hired to develop a ‘predictive’ policing algorithm for so-called “high-impact crimes” such as burglary. The system is inspired by an existing model which he developed earlier in his corporate career: Originally, this algorithm was meant to predict which customers were most likely to switch away from certain brands.

In 2015, Willem’s work at the police resulted in the birth of CAS, short for Crime Anticipation System. The goal of CAS, much like similar statistical tools tested in different cities and regions across Europe, was to classify crime-prone areas across the country and allocate police resources accordingly. CAS was initially created to operate in Amsterdam only, but the system would become the norm for ‘predictive’ policing in the entire Netherlands for years to come.

The Dutch police regarded themselves as the pioneers of ‘predictive’ policing in Europe, since they used CAS in the whole country and not just a few cities. Until late 2025, when the once-so-beloved system was abruptly decomissioned. The reason: its “added value” was “unclear”, as a devastating internal police report that was carried out a decade after the system’s deployment exposed. The report has now seen light of day due to freedom of information requests.

As stated in this ‘Kraai’ report (Quality and Risk Management System for Algorithms and AI) from September 2025, only one out of 50 incidents in the city of Amsterdam was correctly predicted by the algorithm. This represents 11,5% less than what police researchers claimed in the early stages of the system’s deployment eight years prior.

Confronted with this number, the police admits that they stopped using CAS “because it was impossible to prove that burglaries decreased due to the use of the system”, a police spokesperson admitted via email. The story of how they ended in this tight spot is even more convoluted.

Hot times and hotspots

The Crime Anticipation System divided cities into a grid of areas each measuring 125 square meters. Subsequently, it collected as much information as possible about each area. For instance, how many crimes occurred in the past or whether known suspects lived nearby. The system combined police information with data from the Central Bureau for Statistics. This allowed the police to add socioeconomic data to the formula, such as the average income of a neighborhood or whether large families lived there.

The system assessed burglaries, car or bicycle thefts and nuisance. The output were the so-called ‘hot times’ and ‘hotspots’. Reading the system’s recommendations was pretty straightforward: specific areas on a map of the city were automatically colored if CAS recommended deploying police patrols during time intervals consisting of four hours each. CAS is a closed system, which meant that police officers could not see what data the model was using to make a specific prediction.

Screenshot of the Crime Anticipation System. Source: Lauren Waardenburg, Anastasia Sergeeva, Marleen Huysman. Hotspots and Blind Spots. Working Conference on Information Systems and Organizations (IS&O), Dec 2018, San Francisco, CA, United States. pp.96-109

“Practically speaking, the algorithm is actually very simple,” says researcher Lauren Waardenburg during a conversation via Zoom. Waardenburg followed the CAS data team and police officers for several years as part of her work at the Free University of Amsterdam and ESSEC Business School. “Officers are assigned to a small area. They then drive through that neighborhood once, maybe a second time an hour later. And that’s it. If they are there for five minutes, that’s already a lot.”

Living close to a burglar

CAS considered certain areas more dangerous than others based on the data it was trained on, including the number of criminal...