Law
Due Process Implications of Predictive Policing Algorithms
Quick fact
A 2018 study of the Chicago Police Department's Strategic Subject List found that only about 6% of those on the list were later arrested for a shooting—yet the algorithm's opaque reasoning still influenced police attention, raising due process concerns.
Why this is interesting
What if a computer predicted a crime you haven't committed—and you never get to see the reasons? That is the unsettling reality many face when predictive policing algorithms shape police actions.
Read the full explanation
Understanding Due Process Implications of Predictive Policing Algorithms
Predictive policing uses algorithms to forecast where and when crimes are likely to occur, often based on historical crime data. These systems can imagine people as future offenders or places as future hotspots. But when these predictions influence police stops, arrests, or sentencing, they trigger due process protections under the Constitution—those that ensure fair treatment in the legal system. Due process requires that individuals know the accusations against them, have a chance to respond, and receive a fair hearing. However, predictive algorithms are often 'black boxes': they do not explain why a person or location was flagged. This lack of transparency challenges the core of due process: how can a person defend themselves against a prediction they cannot inspect or understand? Moreover, the data used to train these systems can embed historical biases, meaning arrests, stops, and surveillance may be based on discriminatory patterns, compounding the problem.
A deeper explanation
Understanding the due process implications of predictive policing involves seeing the conflict between algorithmic logic and legal procedure. The Fifth and Fourteenth Amendments guarantee that no person shall be deprived of life, liberty, or property without due process of law. In the context of policing, due process includes the right to be informed of the charge, the right to counsel, and the right to present evidence. Predictive algorithms introduce two major tensions. First, the output of an algorithm is often used to justify police stops or targeted surveillance, which may constitute a 'seizure' under the Fourth Amendment. Yet, the algorithm's reasoning is proprietary or secret, so the individual cannot challenge the basis of the stop—undermining the adversarial process. Second, if an algorithm generates evidence that could exonerate a defendant (exculpatory evidence), the government may be required to disclose it under the Brady rule, but doing so may require understanding how the algorithm works, which is often not feasible. The mechanism at issue is the delegation of decision-making to a system that lacks transparency and accountability, which conflicts with due process's demand for notice and an opportunity to be heard. As courts begin to grapple with these issues, they are setting precedents that will shape whether algorithmic predictions are compatible with constitutional protections.