Predictive Patrols: Flawed Data Over-Polices Poor Areas

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Predictive policing software utilizes historical arrest data to forecast where future crimes are likely to occur, creating a dangerous feedback loop. Tech investigations demonstrate that feeding historically biased policing records into automated algorithms results in continuous over-policing and harassment of impoverished, working-class neighborhoods.

The Bharat Media Association highlights algorithmic accountability as a crucial civil rights defense. By demystifying how predictive models encode historical discrimination into automated patrol maps, journalists force law enforcement agencies and municipal authorities to reconsider deploying unproven algorithmic policing experiments that disproportionately criminalize vulnerable communities.

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