Sam Lavigne offers an overview of White Collar Crime Risk Zones, a predictive policing application that uses industry-standard predictive policing methodologies to predict financial crime at the city-block level with an accuracy of 90.12%. Unlike typical predictive policing apps, which criminalize poverty, White Collar Crime Risk Zones criminalizes wealth.
Sam Lavigne is an editor at the New Inquiry and an instructor at NYU and the New School. An artist, programmer, and teacher, Sam has exhibited his work—which deals with data, cops, surveillance, natural language processing, and automation—at Rhizome, Flux Factory, Lincoln Center, SFMOMA, Pioneer Works, DIS, and the Smithsonian, among others.
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