Predictive policing technology is spreading across the country, and Los Angeles is the epicenter. A small group of LA activists are in a lopsided campaign against billions of dollars in city, federal, and Silicon Valley money using algorithms to predict where and when the next crime is going to occur, and even who the perpetrators are going to be. Barry embeds with the Stop LAPD Spying coalition for a week in Skid Row and investigates how state-of-the-art predictive policing programs work. He then talks to sociologists and philosophers about how big data is changing the relationship between police and the communities they serve. We then turn to the justice of using statistical predictions for the purposes of profiling and police intervention. This is part 1 of 2 on the use of statistical algorithms in criminal justice. Guest voices include the LAPD police commissioners, Hamid Khan, Jamie Garcia, Sarah Brayne, Flora Salim, and Renee Bolinger.
(Full transcript of episode here PreCrimeUnit (Full Transcript))
To get an ad-free feed for this and all other Slate podcasts, and to get bonus content for this season, sign up for Slate Plus. Just go to slate.com/hiphiplus
This episode is brought to you by Care/Of. For 50% off your first month of personalized Care/of vitamins, go to TakeCareOf.com and enter promo code HIPHI50 at check out.
Reading List and Links
Sarah Brayne’s “Big Data Surveillance: The Case of Policing”
Frederick Schauer’s Profiles, Probabilities, and Stereotypes (Amazon link).