RMIT researchers got their hands on check-in data from the mobile app Four Square in Brisbane and New York City. Data is anonymized, but you do have information about an individual's check-in history. You can see how many check-ins are at a location and how that changes over time. Another thing you can look at is the ratio of newbies to regulars at a place. These things change over time as people are moving around the city.
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.
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