Stanford engineers’ ‘Law, Order & Algorithms’ data project aims to identify bias in the criminal justice system

“A team of engineers uses computational analysis tools to scrape information from police-related incidents to reveal discrimination and reduce crime….The project is led by computational social scientist Sharad Goel, an assistant professor of management science and engineering. He also teaches a course at Stanford Engineering that explores the intersection of data science and public policy issues revolving around policing. Among other activities, Goel’s team is building a vast open database of 100 million traffic stops from cities and towns around the nation. The researchers have already gathered data on about 50 million stops from 11 states, recording basic facts about the stop – time, date and location – plus any available demographic data that do not reveal an individual’s identity. These demographics might include race, sex and age of the person…”