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Is data-driven policing just tech-based stereotyping?

With constant calls for police to stop racial profiling, law enforcement agencies want concrete, race-neutral information to help them target people based on their behavior alone. Many officers believe that a small number of people are responsible for the majority of non-drug street crime. Identifying those people could be crucial to keeping crime down.

Police might once have hauled in "all the usual suspects," but arresting people without probable cause is unconstitutional. Plus, "the usual suspects" were often simply people of color with whom the police had already had contact.

Today, some departments are experimenting with data-driven policing. The name sounds good, but does it just lend a scientific veneer to something that isn't really new?

Data-driven policing commonly involves plotting crimes on a map and cross-referencing them with variables such as traffic offenses and the locations of known offenders. It can also involve collecting publicly available personal data and using algorithms to predict crime.

There are a number of privacy, ethical and constitutional questions to be answered, but does data-driven policing work?

That's unclear. Consider Los Angeles's experience. In those LAPD divisions involved in "Operation LASER," officers receive daily "mission sheets" focused on a specific area they are to target. Real-time crime mapping is used, along with an algorithm meant to predict the locations of potential property crimes.

"These are the hot spots," one officer explained to NPR. "These are where the crimes tend to happen, this day, this time, based on the crime mapping that we do."

The mission sheets also contain names and mug shots from the "Chronic Offenders Bulletin," which lists people in certain neighborhoods that police think are likely to commit crimes. This is based on a point system that considers gang membership and previous criminal justice contacts.

The LAPD's deputy chief believes Operation LASER works. Crime is far lower than a generation ago, although that's a long-term trend. What convinces him is that arrest numbers are also down.

"We're arresting the right people. We're not out there saturating, we're not out there picking up people for everything."

Community members aren't so sure.

For one thing, the chronic offender score is based partly on contacts with police. That's simply more likely to happen in neighborhoods that are heavily patrolled, so the system could just be reinforcing existing stereotypes.

Moreover, if data-driven policing has made noticeable changes to police behavior, it's not obvious. The same people and the same neighborhoods are being targeted.

"If you put in bad data, you're going to get bad data," acknowledged the LAPD's deputy chief.

Do you think data-driven policing is a positive change or does it just lend credibility to the often-biased information police were already relying on?

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