Case Studies

Predictive police in Chicago

Chicago’s Chief Data Officer Brett Goldstein is attempting to prevent violent crimes in the city before they happen. Goldstein’s predictive analytics unit runs spatial algorithms on 911 call data to identify where and when violent crimes or robberies are most likely to happen. As Goldstein puts it, “Different parts of the city behave in predictable ways — beyond a city of neighborhoods, Chicago is a city of blocks, and these blocks are part of an ecosystem. We can create mathematical models with this ecosystem that are statistically significant, and give us leading indicators for when an expected level of a given behavior is likely to happen.”

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