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By STEVE LOHR, The New York Times, May 20, 2007

Programs add new streams of data -- about neighborhood demographics and payday schedules, for example -- to try to predict where crimes might occur.

RODNEY MONROE, the police chief in Richmond, Va., describes himself as a lifelong cop whose expertise is in fighting street crime, not in software. His own Web browsing, he says, mostly involves checking golf scores.

But shortly after he became chief in 2005, a crime analyst who had retired from the force convinced him to try some clever software. The programs cull through information that the department already collects, like “911” and police reports, but add new streams of data — about neighborhood demographics and payday schedules, for example, or about weather, traffic patterns and sports events — to try to predict where crimes might occur.

...

The results, says Jon M. Kleinberg, a computer scientist at Cornell University, are a “revolution in measurement” and the “introduction of computing and algorithmic processes into the social sciences in a big way.” The phenomenon is strikingly evident in economics, business and crime prevention.

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There are plenty who do. Big retailers like Wal-Mart Stores and Kohl’s use today’s advanced computing and math to more accurately predict what sizes of clothes should go to what stores. Harrah’s and other casinos decipher slot-machine results to optimize customer traffic and profits, and they use face-recognition software to identify people with criminal records. And Stockholm and other cities use traffic data and patterns to determine “congestion pricing.”

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