Editor's note

Police departments are collecting lots of data about crime – to predict where crimes will happen in the future and even to identify potential criminals. But existing racial, income and gender biases in police work may mean these data-driven computer analyses reinforce, rather than reimagine, existing police practices. William Isaac of Michigan State and Andi Dixon of Columbia explain what that means for police, the public, and, especially, people of color.

Earlier this year, “Moonlight” became the first film with no white actors to score the best picture Academy Award. It also tackles one of the most contentious issues in education today: school discipline. Derek Black, professor of law at the University of South Carolina, examines Moonlight through the lens of his research on school discipline reform.

And, following a recent case in which comedian Stephen Fry was accused of blasphemy under Irish law, Case Western Reserve’s Steven Pinkerton explains how this is a reminder that “anti-blasphemy laws are hardly unique to the Muslim world.”

Jeff Inglis

Editor, Science + Technology

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How does bad data affect predictive policing algorithms? Photosani/shutterstock.com

Why big-data analysis of police activity is inherently biased

William Isaac, Michigan State University; Andi Dixon, Columbia University

Crime data reflect only what crimes are identified by the police – not all the crimes that occur. So decisions based on crime data are necessarily biased and incompletely informed.


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