Crime Predicting Software, CivicScape, Excludes Data on Marijuana Possession

Crime predicting software is in use at many police departments throughout the country in an effort to help prevent crime, but it is still far from a perfect calculator. Companies are able to be selective about the data that is running through the algorithm. CivicScape has elected to leave out data on certain topics like marijuana possession because it created too many racial disparities. Creating this transparency is important because the model is a neural network in an attempt to make it artificially intelligent.

There’s a story Brett Goldstein likes to tell. It starts on a Friday night in 2010 with him sitting in a darkened Crown Victoria on a Chicago street, poring over maps. Goldstein was a commander at the Chicago Police Department, in charge of a small unit using data analysis to predict where certain types of crimes were likely to occur at any time. Earlier that day, his computer models forecast a heightened probability of violence on a particular South Side block. Now that he and his partner were there, Goldstein was doubting himself.

“It didn’t look like it should be a target for a shooting,” he recalled. “The houses looked great. Everything was well manicured. You expect, if you’re in this neighborhood, you’re looking for abandoned buildings, you’re looking for people selling dope. I saw none of that.”

Several hours later, Goldstein woke up to the sound of his BlackBerry buzzing. There had been a shooting—on the block where he’d been camped out. “This sticks with me because we thought we shouldn’t be there, but the computer thought we should be there,” said Goldstein. He took the near-miss as vindication of his vision for the future of law enforcement. “I do believe in a policeman’s gut. But I also believe in augmenting his or her gut,” he said.

Seven years after his evening on the South Side, Goldstein threw on a gray suit and some aerodynamic sunglasses and headed out from his hotel in Midtown Manhattan into New Jersey. This spring, he founded CivicScape, a technology company that sells crime-predicting software to police departments. Nine cities are either using the software or in the process of implementing it, including four of the country’s 35 largest cities by population. Departments pay between $30,000 a year to use the software in cities with less than 100,000 people to $155,000 a year in cities with populations that exceed 1 million. Goldstein wanted to check in on the two clients who were furthest along—the police departments in the New Jersey towns of Camden and Linden.

Neural networks are favored by computer scientists working with huge data sets, but one of their shortcomings is their opaqueness. Unlike an algorithm in which a human has consciously told the system what to think about each factor, neural networks find their own paths and can’t effectively explain to humans what they’ve done. This has the potential to make CivicScape even less transparent than other predictive policing software, which use different types of algorithms.

Scott Thompson, Camden’s police chief, said he hasn’t heard any criticism about transparency. For its part, CivicScape said its openness comes from inviting discussion about the types of data its models use. The company decided against using arrests for marijuana possession at all, for instance, given widespread research showing racial disparities in these arrests.

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Source: MJFeed

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