Ravi Shroff, NYU
Click here to register. This seminar will be cohosted with the Office of Diversity, Inclusion, and Belonging.
ABSTRACT: To assess racial disparities in police interactions with the public, we compiled and analyzed a dataset detailing nearly 100 million municipal and state patrol traffic stops conducted in dozens of jurisdictions across the country---the largest such effort to date. We analyzed these records in three steps. First, we measured potential bias in stop decisions by examining whether Black drivers are less likely to be stopped after sunset, when a "veil of darkness" masks one's race. Second, we investigated potential bias in decisions to search stopped drivers. Finally, we examined the effects of legalizing recreational marijuana on policing in Colorado and Washington state. We find evidence of bias against minority drivers in both stop and search decisions, and also that the bar for searching minority drivers remains lower than for white drivers after marijuana legalization.
Ravi Shroff is an Assistant Professor of Applied Statistics in NYU's Steinhardt School of Culture, Education, and Human Development. His research interests are broadly related to computational social science, and in particular, the application of statistical and machine learning methods to a variety of urban issues. Previously, Ravi was a Senior Research Scientist at NYU's Center for Urban Science and Progress, and before that, he was a postdoc in the Mathematical Sciences Institute at the Australian National University.
Institute for Applied Computational Science (IACS) and Office for Diversity, Inclusion, and Belonging