A Data-Centric Analysis of “Stop and Frisk” in New York City

Recent incidents in the United States involving police action against people of color has created a lot of controversy and public turmoil. There have been many calls for reform in police practices and the way they are funded, and debates have reached legislative bodies across the country. However, to make any substantive changes in laws and rules regarding practices, data needs to be collected in a systematic fashion and analyzed critically to form the basis for change. In this paper, we look at one police practice: “Stop and Frisk'' in New York City, which has received a lot of coverage in the media regarding its partiality towards people of color. We examined publicly available data for 2003–2019. The data analysis clearly shows that the practice was biased until 2012 but has since improved, possibly due to subsequent legal action.