Imagine you’re a police officer in Chicago, driving around your district. But instead of just reacting to calls on your radio, imagine there’s a computer in your car that’s able to predict where and when a particular type of crime might occur. It shows a map of the city with little red boxes on it that indicate areas in which there’s a high probability of crime.
This isn’t just something you’d see in a movie like Minority Report. In fact, this kind of technology already exists and it’s being used in cities around the country. It’s part of a new law enforcement strategy known as “predictive policing” that uses advanced data analytics and algorithms to predict where and when certain crimes are most likely to occur based on a variety of information — historical crime reports, arrest data, calls from the community, and other sources. According to the National Institute of Justice, the goal of this technology is to “move law enforcement from reacting to crimes into the realm of predicting what and where something is likely to happen and deploying resources accordingly.”
In some ways, predictive policing is a natural extension of existing policing techniques in a world where new sources of citizen information, and the ability to analyze those sources, are readily available and have the potential to lower crime rates. At the same time, though, the technology raises a variety of infrastructural and political concerns that may prevent it from achieving widespread adoption.
This website is designed to give you a better understanding of the socio-technical issues surrounding predictive policing by using a variety of sociological frameworks. Use the navigation menu in the upper-right to jump around to specific pages, or click here to go to the next page, where we talk about some of the relevant social groups for whom the technology has meaning.