'Minority Report'? Data helps group target the next crime

MINNEAPOLIS -- Ryan Hughes, a young, spiky-haired computer analyst for the Minneapolis Police Department, pulls up a map of the Twin Cities on his screen.

"Here, here, here," he begins, pointing to six red dots. Each marks a robbery probably committed by the same man.

"And here," Hughes continues, pointing to a dot just northeast of Minneapolis, "is where I predicted he would go next."

Simple as a crime map, seemingly as far-fetched as ESP, such scenes are becoming more common. Police departments from Minneapolis to Los Angeles are turning to the emerging science of using recent crime data to predict where criminals will strike next.

The potentially revolutionary step could fundamentally alter the nature of police work.

The idea is that everyone, even criminals, are creatures of habit. With enough information about past crimes, it's possible to forecast their future target.

"We usually look at the last week and say, 'This is what happened in the last week,' " said Minneapolis Chief Tim Dolan. "Well we've added to that, saying, 'This is what we think's going to happen next week.' "

That kind of thinking has just begun in Minneapolis, but Dolan says it's already paid off in north and southwest Minneapolis, areas that led the city last year in reducing overall crime rates.

The strategy looks slightly different everywhere it's used, but predictive policing relies mainly on a police department's ability to accumulate deep databases of crime information that detail time, location, methods and numerous other bits of revealing data. Crunched by a computer analyst, the numbers reveal patterns.

That's the task facing a crew of five such crime analysts who work out of a second floor office in City Hall. Every day, they pore over recent crime data, slicing it different ways and sometimes using software to crunch it further. If a pattern emerges, they mark it down for consideration on an internal crime map that gets passed along to the chief for his weekly meeting with top inspectors and lieutenants.

A handful of police departments around the country have spent tens of thousands of dollars on more advanced software, or are working with university researchers and technology companies on algorithms to help them spot crime trends. It's akin to predicting where an earthquake's aftershocks will be felt, says a Santa Clara University mathematician developing formulas for such police work.

As for Hughes' prediction of where the Minneapolis robber would strike next? It was made using free software distributed by the National Institute of Justice. The software examines the location and timing of each crime to draw its conclusions. The estimate of the robber's next target turned out to be a mile off. But in the world of crime prediction, that's still counted as a success -- the kind of information that could put a patrol car close to the action.

Hughes, who hopes the Minneapolis department will eventually use more high-powered software for predictive policing, said that his maps have accurately predicted the locations of 45 percent of the city's violent crime.

"I have a better batting average than Joe Mauer," Hughes said.

To better understand predictive policing, consider the Pop-Tarts story.

Businesses such as Wal-Mart have long anticipated customers' needs based on weather and time of year. Coastal stores knew that as hurricanes approached, customers stocked up on bottled water and duct tape. Those things made sense, but looking more closely at customer data and comparing it to weather patterns, analysts at Wal-Mart noticed that customers anticipating a hurricane also bought more strawberry Pop-Tarts.

It's the sort of anecdote that the emerging industry of predictive policing embraces because it shows how analyzing data can turn up surprises, things that can be used to predict future behavior.

The promise of doing the same thing with crime has prompted some large police departments such as Los Angeles to invest in partnerships with university researchers to devise predictive algorithms or formulas. As exotic as it sounds, it's just the next step in the changing world of police work, said William Bratton, the celebrated former chief of police in Los Angeles and New York City.

"It's really the continuation of the evolution of policing," Bratton said.

Starting in the 1990s, when police began using crime reports to identify hot spots, the focus has been on putting police officers near high-crime areas. Putting laptops in squad cars and publishing crime maps helped shorten response time. Now, police departments can quickly analyze a lot of crime data to spot crime trends as they're occurring.

"So after two or three incidents we can put a stop to it instead of waiting for 20 or 30," said Bratton, who now works as an independent security consultant.

"This is potentially labor-saving," he said. "That's very important because as we're going into very tough times with public financing, it's going to become more and more critical."

The hope is that predictive policing will help supplant random patrolling, which studies have shown doesn't work well.

"It's not enough to send people out and expect that they will have an impact on crime," said Chuck Wexler, executive director of the Police Executive Research Forum in Washington.

(c) 2011, Star Tribune (Minneapolis)

Visit the Star Tribune Web edition on the World Wide Web at http://www.startribune.com

Distributed by McClatchy-Tribune Information Services.

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