Researchers analyzed nearly 93 million traffic stop reports from 21 U.S. state patrol agencies and 29 police departments from 2001 to 2017. The team of professionals from the Stanford Computational Policy Lab factored in demographics, gender, reasons for traffic stops, and time of day in order to create the most balanced, standardized set of data possible.
“Relative to their share of the residential population, we find that black drivers are, on average, stopped more often than whites," said the report which was organized by the Stanford Open Policing Project.
According to researchers, data showed a level of leniency with Black police officers when dealing with white drivers and “a marked drop in the proportion of drivers stopped after dusk who are black, suggestive of discrimination in stop decisions."
David Lowery, the founder of the Chicago-based advocacy group, Living & Driving While Black Foundation, said, "There's no longer the idea of Officer Friendly, who might help you understand why they pulled you over. Now, it's about using racial profiling to control people and place fear in them.
"Then, you've got money tied up into this," he added. "Who can write the most tickets? Who can put the most people in jail and into the court system? It’s no longer about a simple traffic stop for safety."
Stanford data scientist Amy Shoemaker told CNN, “Our work doesn't necessarily reveal anything new; activists and individuals of color have long presented anecdotal evidence of this kind of bias.”
Shoemaker said the report was meant to provide journalists, analysts, and policy makers with “clean, public data” in order to make a change in policy or allocate resources to better assist citizens and minorities in particular.
"A lot of policy makers feel the need to have data-driven decisions, and so this is a data-driven approach to racial profiling," she said.
In their report, researchers said, "We hope that police departments start regularly analyzing their data and report the results of their findings.”