How the New York Police Department is Using Artificial Intelligence ? Answers (latest)

Use of AI in NYPD ( AI news)

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AI has been changing things in many industries and departments recently, here is how it has had an impact on the New York Police Department. If you wanna know more about AI and be updated an AI trends you can follow me on-
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When a syringe wielding drill their tried sticking up a home spot near Yankee Stadium,police figured out quickly that it wasn't a one-off. A man had also used syringe a few weeks earlier while stealing a drill at another home depot 11 km south in Manhattan. 

The match,though,wasn't made by an officer looking through files. It was done by pattern-recognition computer software developed by the New York Police Deparment.

The software ,dubbed Paternizr, allow crime analysts stationed in each of the department's 77 precincts t compare robberies, larcenies and thefts t hundreds of thousands of crimes logged in the NYPD's database, transforming their hunt for crime patterns with the click of a button.

It's much faster than the old method, which involved analysts sifting through reports,racking their brains for key details about various crimes and decideing whether they fit into a pattern. It's more comprehensive, too, with analysts able to spot patterns across the city instead of just their precinct . 

"Because   Patternizsr picked up those key details in the algorithm, it brought back complaints from other precincts that wouldn't have known," said Bronx crime analyst Rebecca Shutt.

Evan Levine, the NYPD's assistant commissioner of data analytics, and Alex Cholas-wood, the department 's former director of analysts pics, spent two years developing the software before rolling it out in December 2016.

The department disclosed its use of the technology only this month , with Levine and Cholas-Wood detailing their work in the 'INFORMS JOURNEL on Appiled  Analytics .'

Speaking about it with the news media for the first time, they said theirs is the first police department in the country to use a pattern-recognition tool like this.

Levine and Cholas-wood were inspired by the work of New York University team that studied a similar approach to pattern recognition but never produced a workable version. 

Like human crime analysts, software compares factors such as method of entry, type of goods taken and the distance between crimes. "The real advantage of the is that we minimize  the amount of leg work and busy work that analysts or detectives have to do and allow them to leverage their expertise and experience in going through a much smaller list of results," said Cholas-Wood. 

In the past, analysts worked only with crimes in their precinct, making it difficult or even impossible for them to spot patterns in other parts of the city. "Truthfully, it was inefficient ," Levine said. "It wasn't a modern way to do these things ."

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