Government Risk Profiling: A Recipe for Discrimination

Margriet Vermeer · 2026-05-07

Government risk profiling sounds like a smart tool on paper. Use data to spot threats, prevent crime, and keep citizens safe. But what happens when that tool starts drawing lines based on race, zip code, or economic status? A recent study from the Universiteit van Amsterdam warns that without principled measures, the risk of discrimination and harm remains too great. ### The Hidden Danger of Profiling Risk profiling isn't new. Law enforcement and government agencies have used it for years to predict who might commit a crime or pose a security threat. The problem is, these systems often reflect the biases of the people who build them. If the data used to train an algorithm comes from a history of over-policing certain neighborhoods, the tool will flag those same communities again and again. It becomes a cycle that's hard to break. Think about it this way: if you're a Black or Hispanic person living in a low-income area, you're more likely to be stopped, searched, or questioned. That's not because you're more dangerous. It's because the system is built on assumptions that haven't been checked. The study says it plainly: "Without principled measures, the risk of discrimination and harm remains too great." That's not just academic talk. It's a real warning for every American city.  ### Why Principled Measures Matter So what are "principled measures"? They're rules that force transparency and fairness into the system. Things like: - Regular audits of profiling algorithms for bias - Clear guidelines on what data can be used and why - Independent oversight boards with community representation - Public reporting on how profiling affects different groups Without these, the government risks turning a tool meant for safety into a machine that deepens inequality. And once that happens, trust in institutions erodes. People stop cooperating with law enforcement. They stop reporting crimes. The whole system breaks down. ### The Real Cost of Getting It Wrong Let's be real: the cost isn't just social. It's financial too. When profiling leads to wrongful arrests or harassment, cities pay out millions in settlements. Taxpayers foot the bill. And the damage to communities? That can't be measured in dollars. Families are torn apart. Kids grow up afraid of the police. The American dream becomes a nightmare for people who did nothing wrong. ### What Needs to Change The answer isn't to throw out all data-driven tools. That would be like throwing the baby out with the bathwater. But we need to slow down and think. Every algorithm should be tested for bias before it's deployed. Every model should be reviewed by people who aren't just tech experts but also community advocates and civil rights lawyers. We also need to stop pretending that technology is neutral. It's not. It's built by humans with all their flaws. That doesn't mean we can't use it. It means we have to be honest about its limits. ### A Path Forward If you're a policymaker, advocate, or just someone who cares about justice, here's what you can do: push for laws that require transparency in government algorithms. Support independent audits. And most importantly, listen to the people who are most affected by these systems. They know the problem better than any data scientist. This isn't about being anti-government. It's about being pro-fairness. The Universiteit van Amsterdam study is a wake-up call. Let's not hit snooze.