Mara Hvistendahl wrote for Science Magazine about whether 'predictive policing' can prevent crime before it happens:
Riding high in their squad car, officers Jamie Pascucci and Joe Kania are cruising the neighborhood of Homewood, scanning the streets for trouble. Pittsburgh, Pennsylvania, has one of the highest murder rates among large U.S. cities, and violent crime is particularly severe in Homewood, a 98% black pocket of aging, pock-marked Victorians on the east side. Young, white officers from outside the neighborhood, Pascucci and Kania patrol using a mixture of police radio, calls to their department's communications center, and instinct. They get occasional help from ShotSpotter, a network of sensors that detects gunshots and relays the information to a laptop mounted between the front seats.
But starting next month, Pascucci and Kania may get a new type of guidance. Homewood is set to become the initial pilot zone for Pittsburgh's "predictive policing" program. Police car laptops will display maps showing locations where crime is likely to occur, based on data-crunching algorithms developed by scientists at Carnegie Mellon University here. In theory, the maps could help cops do a better job of preventing crime.
Many other cities have already adopted similar systems, which incorporate everything from minor crime reports to criminals' Facebook profiles. They're catching on outside the United States as well. Drawing on approaches from fields as diverse as seismology and epidemiology, the algorithms can help bring down crime rates while also reducing bias in policing, their creators say. They replace more basic trendspotting and gut feelings about where crimes will happen and who will commit them with ostensibly objective analysis.