Scientists at Cornell University and the University of California, Berkeley obtained indications of how police in New York City may be deployed in local neighborhoods by tapping a deep learning computer model and a dataset of dashboard camera (dashcam) images from rideshare drivers.
The researchers trained their model on thousands of annotated images from dashcam provider Nexar to identify marked police vehicles.
They counted more than 233,000 images including such vehicles recorded throughout all five boroughs of New York City at all times of day, then checked them against various factors, including local census data.
Patterns revealed by this analysis included a greater police presence in affluent commercial areas and in low-income neighborhoods with more numbers of Blacks and Latinos.
From Cornell Chronicle
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