Santa Cruz's Minority Report-like experiment: Stopping tomorrow's crime?

One big problem for law enforcement officers is that they're often chasing yesterday's criminals. That could change if an experiment in Santa Cruz, Calif., proves successful. Like the police in the film Minority Report, cops in Santa Cruz are using a computer program that predicts crime before it happens, giving police officers a leg up on burglaries, car theft, and other illegal activities. Here, a brief guide to this innovation:

How does this computer program predict crime?

It uses an algorithm that was originally developed to "predict aftershocks following a large earthquake," says Joel N. Shurkin at Talking Points Memo. The program assumes that future criminals will commit crimes in the same place as a previous crime, and at roughly the same time of day. A successful burglary on a particular block at 3:00 p.m., for example, might foreshadow another mid-afternoon burglary a few days later in the same neighborhood — something police can plan for.

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Does the program work?

It seems to. "The algorithm has a 40 percent success rate" in predicting crime, says Graeme McMillan at TIME, although its use is currently limited to property crimes. There are no predictions of murder, rape, assault, or other violent crimes. Since the program's inception in July, burglaries are down 27 percent. It's still not clear, though, if that's a coincidence or the result of increased police presence in areas where the computer forecasts trouble.

Does this anti-crime program have a future?

It appears so. Other police agencies are carefully watching the program's success rate, especially in hard economic times when they have to do more work with less funding. The program's inventor, George Mohler of Santa Clara University, is already at work with the Los Angeles Police Department to track gang warfare, since "retaliations commonly occur within days of, and at nearly the same location, as the initial attack," says Peter Murray at SingularityHub.com.

Sources: Boston Globe, SingularityHub.com, Talking Points Memo, TIME