The future of policing, it seems, will look a lot like the present of policing, just faster and with more math. Instead of using inherent bias and simplistic statistics to racially profile individuals on a street, cops of the future will be able to use complicated statistics to racially profile people in their homes. In the summer of 2013, for instance, the Chicago Police Department implemented a pilot program intended to reduce violent crime. It used an algorithm developed by an engineer at the Illinois Institute of Technology to generate a “heat list” of roughly 400 people who were most likely to become perpetrators or victims of violence. Cops tracked down some of these individuals, showed up at their homes, and warned them they were being watched. Similar programs using technology have been tested in recent years, all under the rubric of what’s been called “predictive policing.”
This approach has understandably caused concern and outrage among civil-liberties advocates—the very name “predictive policing” sounds like something out of Minority Report, just without psychics hanging out in a pool. As Jay Stanley, senior policy analyst at the ACLU, commented about the Chicago program: “Unfortunately, there are all too many reasons to worry that this program will veer towards the worst nightmares of those who have been closely watching the growth of the data-based society.”
These are real concerns. It’s easy to imagine how biased data could render the criminal-justice system even more of a black box for due process, replacing racist cops with racist algorithms. That said, the cases in which police attempt to predict individual behavior based on data analysis are still relatively rare among the many approaches that have been shoehorned under the heading of predictive policing. Thus far, in fact, predictive policing has been less Minority Report than Groundhog Day—that is, yet another iteration of the same data-driven policing strategies that have proliferated since the 1990s. As it’s currently implemented, predictive policing is more a management strategy than a crime-fighting tactic. Whether it works is perhaps not as useful a question as who it works for—its chief beneficiaries aren’t patrol cops or citizens, but those patrol cops’ bosses and the companies selling police departments a technical solution to human problems.
* * *
Part of predictive policing’s image problem is that it doesn’t actually have a very clear image to begin with. When a police department declares that it’s using predictive policing, it could be doing a whole range of things that vary greatly in their technical sophistication, effectiveness, and ethical concerns. The term itself came into fashion thanks to a 2009 symposium organized by William Bratton, who at the time was the police chief of Los Angeles, and the National Institute of Justice. Following the symposium, the NIJ distributed a series of grants that funded predictive-policing research by universities and pilot programs with several police departments, including in Los Angeles.
The NIJ funding led to a partnership between the LAPD and Jeffrey Brantingham, an anthropologist at the University of California, Los Angeles, who was studying the use of predictive modeling techniques for forecasting civilian deaths and counterinsurgency activities in Iraq. Brantingham’s research, which began in 2006, had been funded partly by grants from the Army Research Office. By 2009, when he began working with the LAPD, he’d apparently determined that data-driven urban warfare wasn’t all that different from data-driven policing. In 2012, Brantingham turned his research into PredPol, the software and company perhaps most associated with the public’s understanding of predictive policing.