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Over the course of his career, U.S. Chief Data Scientist DJ Patil has used data to improve everything from weather forecasting to LinkedIn recommendations to personalized medicine.
And a few months after he came to the White House, in 2015, he helped launch the Police Data Initiative, a project aimed at rebuilding trust between the police and the public. This was less than a year after the unrest that followed the killing of an unarmed black man, Michael Brown, by a white police officer in Ferguson, Missouri.
On the latest episode of Recode Decode, hosted by Kara Swisher, Patil said local police departments around the country were willing to collect data about their work, but they weren’t collecting or using it consistently, or sharing it among departments. As a result, their conclusions about the use of excessive force were often based on anecdote.
“Anecdotal is almost always wrong,” Patil said.
He credited a team from the University of Chicago, working on the Police Data Initative, with discovering a surprising “signal” about why police may overreact.
“The first set of signals were all the usual suspects: ‘You’re a bad actor, you shouldn’t be here,’” he said. “Suddenly, in the middle, two interesting signals show up. One is that you responded recently to a suicide. Another one is you responded to domestic violence where a child was present.”
In other words, officers coming from those difficult circumstances were quickly being re-dispatched to their normal beats, because no one was taking into account where they had just come from.
“You’re back out there on beat patrol, and someone’s flippant with you — where did the system fail?” Patil asked. “The dispatch system doesn’t take this data into account! Let’s give this officer time to decompress. Let’s treat them as a human, not a robot.”
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This article originally appeared on Recode.net.
