Abstract
Predictive policing that aims to work out when and where a crime will take place promises a future of data-driven law enforcement. But a flaw found in the design of the software used suggests that instead of fixing biases in policing, predictive algorithms are to blame for a whole new set of problems. Pre-crime tech is catching on in the US. PredPol--a market-leading system--is already used by police departments in places such as California, Florida and Maryland. Their hope is that such systems will bring down crime rates while simultaneously reducing human bias in policing. What this means, says Matt Kusner at the Alan Turing Institute in London, is that the PredPol system seems to be learning from arrest rates--which are higher in areas where there are more police--rather than from underlying crime rates
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