Government Risk Profiling: Discrimination Risks Remain High

Margriet Vermeer · 2026-05-07

Government agencies use risk profiling to flag potential threats, but a new study from the University of Amsterdam warns that without principled safeguards, these systems can cause serious harm. ### The Core Problem Risk profiling sounds like a smart way to catch bad actors before they act. But here's the thing: when algorithms and data sets are built on biased foundations, they don't just reflect existing inequalities—they amplify them. The researchers argue that current methods often lack the transparency and accountability needed to prevent discrimination. Think about it this way: if a system is trained on historical data that already over-polices certain communities, it will keep targeting those same groups. That's not just unfair—it's dangerous. It erodes trust in institutions and can lead to real harm for innocent people.  ### Why Principled Measures Matter - **Transparency**: Citizens deserve to know how decisions about them are made. Without clear rules, profiling becomes a black box. - **Accountability**: Who is responsible when a profiling system flags the wrong person? Without oversight, no one is. - **Fairness**: Algorithms can't replace human judgment. They need constant checks to ensure they don't reinforce stereotypes. > "Without principled measures, the risk of discrimination and harm remains too great." That quote from the study sums it up. It's not about abandoning risk profiling entirely—it's about building guardrails that protect everyone equally.  ### Real-World Impact Let's be honest: this isn't an abstract academic debate. In the United States, we've seen how flawed risk assessments can affect everything from policing to hiring. A system that works for one community might completely fail another. The stakes are high, and the margin for error is razor-thin. The researchers suggest that governments need to slow down and think carefully before rolling out these tools. That means involving communities in the design process, testing for bias, and creating independent oversight bodies. ### What This Means for You If you work in policy, social justice, or tech, this study is a wake-up call. It's easy to get excited about the potential of data-driven decision-making, but we can't ignore the downsides. The goal should be to create systems that are both effective and equitable—not one or the other. So, what can you do? Push for transparency in your own organization. Ask hard questions about where data comes from and how algorithms are tested. And remember: technology is a tool, not a solution. It's only as good as the principles we build around it. ### Moving Forward The University of Amsterdam's findings are a reminder that we need to be proactive, not reactive. Waiting for a crisis to fix flawed systems is too late. By then, the damage is already done. Let's make sure we get this right. Because when it comes to risk profiling, the cost of failure isn't just a bad algorithm—it's people's lives.