Author archives

Aaron Sankin, Investigative Reporter. Sankin reports on the intersection of technology and inequality. While at The Markup, he has focused on issues ranging from the digital divide and social media platform governance to law enforcement technology and car insurance regulation. Before The Markup, he covered online extremism for the Center for Investigative Reporting, where he launched the Hate Report newsletter and co-created the Hate Sleuths citizen journalism initiative. Before that, he was a senior staff writer at the Daily Dot and a founding editor of the Huffington Post’s San Francisco vertical. Aaron’s reporting has won various journalism awards, such as the Edward R. Murrow Award, the National Association of Black Journalists Salute to Excellence Award, the Sigma Award, and the SABEW Association for Business Journalists Award. His work has appeared in The New York Times, The Washington Post, The Motley Fool, and Gizmodo.

Predictive Policing Software Terrible At Predicting Crimes

Crime predictions generated for the police department in Plainfield, New Jersey, rarely lined up with reported crimes, an analysis by The Markup has found, adding new context to the debate over the efficacy of crime prediction software. Geolitica, known as PredPol until a 2021 rebrand, produces software that ingests data from crime incident reports and produces daily predictions on where and when crimes are most likely to occur. Aaron Sankin, Investigative Reporter and Surya Mattu, Senior Data Engineer and Investigative Data Journalist examined 23,631 predictions generated by Geolitica between Feb. 25 to Dec. 18, 2018 for the Plainfield Police Department (PD). Each prediction they analyzed from the company’s algorithm indicated that one type of crime was likely to occur in a location not patrolled by Plainfield PD. In the end, the success rate was less than half a percent. Fewer than 100 of the predictions lined up with a crime in the predicted category, that was also later reported to police.

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Subjects: Big Data, Civil Liberties, Criminal Law, Data Mining, Privacy, Spyware, Technology Trends
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