Police Use Predictive Maps ala 'Minority Report' Routinely

Still stuck in a world of "post-crime? Try the world of predictive policing, instead.

Today's crime-prediction tech doesn't identify suspects, like in Hollywood's fictional pre-crime units. Instead, traditional digital policing uses maps that are historical, then layers it with on-the-ground knowledge to provide custom insights about how to change the behavior of police on their beats.

One example of popular mapping software is ESRI's ArcMap, which takes crime data historical crime reports, call-ins, officer interactions, whatever else can be given a time and place and makes a historical map. In Dallas, where precincts are so large that they're like cities unto themselves, crime analysts layer digital crime maps with locations of community stakeholders, census data, demographics, known gang activity and any other kind of data they can.

"We engage the community, collect surveys, work with neighborhood associations and churches to set up crime watch groups, and encourage them to call if there's suspicious activity," Sgt. Steve Armon, head of operational technology for the Dallas Police Department, told Mic. "We're not sending an officer there and tell them, 'Stay and don't leave.'"

But then there are the maps produced by companies like PredPol, one of the leading predictive mapping companies, which claim to predict crime ahead of time like it's an oncoming storm. These systems show colored "hotspots" that say where crime is likely to occur and when. Then police are dispatched for extra time to those locations. There's no additional recommendations for police behavior but to reduce the likelihood of crime simply by giving those areas extra patrol

Fans of literary science fiction as well as movies are familiar with the idea of precrime (as well as post-crime) thanks to Philip K. Dick's 1956 short story Minority Report as well as Steven Spielberg's 2002 Minority Report movie.

Be sure to read this very detailed and well-written article at Tech.Mic.

Scroll down for more stories in the same category. (Story submitted 11/6/2015)

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