NYU Study Shows ‘Predictive Policing Systems’ Promote Bad Data, Bad Policing
by Dale Chappell
A New York University study shows that “predictive policing” does nothing to prevent crime but actually increases bad policing in cities already struggling with corrupt police forces.
This means that in at least 13 cities, predictive policing is helping to propagate more bad police work where cops already have a problem being honest. The problem, the study says, is that predictive policing sends cops to where the most crime happens, based on the information fed into an algorithm. So, if most of the crime is happening in a black neighborhood, for example, predictive policing says more cops are needed there.
But the flaw there is that if cops continue to look for crime in only certain areas, that’s where they will find it. If cops keep targeting people in a black neighborhood, such as frisking for and finding weapons, predictive policing says it is a high-crime area that requires more policing. This results in an insidious, self-fulfilling prophecy.
In cities where corrupt policing is rampant, this causes predictive policing to target select areas based on racial bias or other illegal police activities.
The study pointed to Chicago, New Orleans, and Maricopa County, which are under some form of investigation or court monitoring, to show how predictive policing is flawed. When these departments kept feeding data on where they found crime into the predictive policing model, the study found a link to bad policing.
“Deploying predictive policing systems in jurisdictions with extensive histories of unlawful police practices presents elevated risks that dirty data will lead to flawed, biased, and unlawful predictions which in turn risk perpetuating additional harm,” the study concludes.
The use of predictive policing “must be treated with skepticism,” the authors of the study say, and that “mechanisms for the public to examine and reject such systems are imperative.”
Fairness, equity, and justice are at stake.
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