Stopping Future Crimes

Stopping Future Crimes

Stopping Future Crimes

Future Tense
The Citizen's Guide to the Future
Aug. 16 2011 11:17 AM

Stopping Future Crimes

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Photo by Justin Sullivan/Getty Images

If you want to commit a crime in Santa Cruz, Calif., try to be unpredictable. The New York Times reports that the city’s police department is using new data analysis software to determine which locales are most likely to see crime on a given day:

Torie Bosch Torie Bosch

Torie Bosch is the editor of Future Tense, a project of Slate, New America, and Arizona State that looks at the implications of new technologies. 

Based on models for predicting aftershocks from earthquakes, it generates projections about which areas and windows of time are at highest risk for future crimes by analyzing and detecting patterns in years of past crime data. The projections are recalibrated daily, as new crimes occur and updated data is fed into the program.
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When the Times reporter was watching, the software helped police decide to watch a parking garage that, it was predicted, would see car thefts that day. While there, the cops picked up two women “peering into cars”—one for drugs, the other for outstanding warrants. Crime databases aren’t new, but the older software programs are “calibrated less frequently, rely more on humans to recognize patterns, and allocate resources based on past crimes rather than predicted future offenses,” says the Times.

If the system works—Santa Cruz is in the midst of a six-month study period—blame (or credit) Big Retail:  “Predicting crime with computer programs is in some ways a natural outgrowth of the technology that companies like Wal-Mart now use routinely to predict the buying habits of customers.”

Read more on the New York Times.

 

Future Tense is a partnership of SlateNew America, and Arizona State University.