'White Collar' crime tracker mocks police profiling bias

Artists are using predictive policing tech to highlight financial crime.

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As Police forces edge ever closer to realizing the plot of Minority Report, a new art-slash-research project aims to point out inequality in our society. With White Collar Crime Risk Zones, three artists come researchers are reworking predictive policing tech to highlight police bias. Instead of utilizing heat maps to predict where street crime could occur, this software flags potential financial crime hotspots. Using an algorithm based on historical white collar offences committed since 1964, it assesses the risk of financial crime in any given area, even predicting the most likely offense.

Cleverly, the project simultaneously points out that predictive algorithms are a worrying policing trend while also highlighting that financial crime often goes unpunished. Taking a further jab at the questionable algorithms US police use to make arrests, White Collar Crime Risk Zones takes 7,000 LinkedIn photos of financial industry executives to generate mugshots of 'offenders'. Unsurprisingly, when tested in New York, The Financial District, Trump Tower and Midtown Manhattan were all flagged as likely financial crime hotspots.

While the tech is currently only accessible via browser, the trio are eventually planning to integrate the software into an iOS app. With predictive policing tech reportedly showing in-built racial bias, this project brilliantly turns the worrying police algorithms on their head. Still, with most bankers responsible for almost collapsing the world economy still walking free, it's nice to see artists also drawing attention to such gross inequality.

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