How data science can win the debate on police reform

The recent deaths of Walter Wallace Jr., George Floyd, Breonna Taylor, Philando Castile and a number of other Black citizens who have lost their lives during an interaction with law enforcement officers have put the topic of police reform at the top of the national agenda. The phrase “defund the police” became a rallying cry across many American cities over the summer as protesters marched for social justice. But police reform isn’t as simple as a catchphrase.

Magnifying glass on a thumbprint that is comprised of zeros and ones on a graphic background.

Two scholars who have been studying the issue for years say solving the problem starts with better data. Dean Knox is a Wharton professor of operations, information, and decisions, and Jonathan Mummolo is a professor of politics and public affairs at Princeton. They’ve published several papers on racial bias in policing and, with the help of Analytics at Wharton, co-founded Research on Policing Reform and Accountability, an organization dedicated to bringing academic rigor and science to what is often a very emotional debate.

“These cases grab our attention because the facts are just so outrageous. That’s important because it brings attention to this important issue. But for those of us who are seeking to reform policing, we need to keep in mind that these are instances of what is unfortunately a very common problem,” says Knox.

“The problem is we know far less than we need to about these questions. What we do notice is that we’re massively underestimating the problem because of data limitations and the poor quality of existing statistical analyses.”

Better data can help with police reform, but data analysis comes after the fact. What about the upfront work in hiring and training that would help root out bias in police departments? According to Knox, retrospective data analysis can help inform future practices.

Read more at Knowledge@Wharton.