Bollinger argues that even a statistically sound generalization doesn't automatically allow you to cross some threshold for treating something as being true. Let's take reasonable suspicion, he says: If an officer has enough grounds to search and frisk all ten to find the one shoplifter, then ten percent certainty is enough for reasonable suspicion. Bollinger’s view is that this isn't right, even if the statistical analysis is correct. The costs of failing to treat it as true even if it is, are not that high, or the cost of the false positives,. treating the person as though this is true to them when it isn't, are actually quite high.
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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