Author archives

Surya Mattu, Senior Data Engineer and Investigative Data Journalist. An engineer by training, Surya built tools and gathered data to tell stories about how algorithmic systems perpetuate systemic biases and inequalities in society. He left The Markup in August 2022. Before The Markup, Surya was the data reporter at Gizmodo’s Special Projects Desk and a contributing researcher at ProPublica. He has also worked as a researcher at Bell Labs, Data & Society, and the MIT Media Lab. At ProPublica, he was part of the team that was named a finalist for the Pulitzer Prize in Explanatory Reporting for the series “Machine Bias.” At Gizmodo, “The House that Spied on Me” won the National Press Foundation’s Technology in Journalism award and was also made into a TED talk. Surya’s OpenPGP key fingerprint is 1710 BE3C B4AF 40A8 FA9F 20CE 9B98 0BE8 CCA5 ED64.

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.

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