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Stanford Engineers' 'law, Order & Algorithms' Data Project Aims to Identify Bias in the Criminal Justice System

By Stanford Report

February 12, 2016

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Stanford University researchers have launched the Project on Law, Order, & Algorithms, an open database of 100 million traffic stops from cities and towns across the U.S.

The researchers say they already have collected data on about 50 million stops from 11 states, recording basic facts about the stop plus any available demographic data that does not reveal an individual's identity.

The goal of the project is to produce a statistical method to assess whether police discriminate against people on the basis of race, ethnicity, age, or gender and, if so, how frequently and under what circumstances. The project also aims to help law enforcement agencies design practices that are more equitable and effective at reducing crime.

The researchers plan to use the database to create a software toolkit that others could use to acquire data from municipal or county governments and perform similar analyses.

"Technically, much of this is already public data, but it's often not easily accessible, and even when the data are available, there hasn't been much analysis," says Stanford professor Sharad Goel.

For example, the researchers examined 760,000 instances of New York City's "stop-and-frisk" policy in which people were stopped on suspicion of holding an illegal weapon, and found African Americans who had been stopped were significantly less likely to have a weapon than whites who had been stopped.

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