Data scientist says local journalists should take 'deep dive' into racial bias and policing

Stanford University data scientist Amy Shoemaker encouraged local journalists to delve into data on racial biases at police departments in an interview that aired Wednesday on Hill.TV's "Rising."

"There are certain locations that are recording data better than others, and that's definitely something that we want to surface to have departments be able to sort of see what kind of departments are collecting really great data," Shoemaker, who works at the Stanford Computational Policy Lab, told hosts Krystal Ball and Buck Sexton last month. 

"In terms of how much racial profiling or racial bias is happening within these jurisdictions, we're leaving that to local journalists to do a deep dive into each place," she continued. "It's really important to look at local context and policies, whether it's a centralized or decentralized police department. Those types of questions." 

The Stanford Open Policing Project collected and analyzed 200 million records of traffic stops across the nation, revealing that police officers tend to stop black drivers at higher rates than white drivers. 

The study also found that officers ticket, search, and arrest black and Hispanic drivers at a higher rate than white drivers. 

Black drivers are 20 percent more likely to get a ticket from police officers than white drivers, while Hispanic drivers are 30 percent more likely to get a ticket than white drivers. 

"Our findings just take a state of the way that the country is nationwide, painting with a broad brushstroke," Shoemaker said. 

— Julia Manchester