A group of social scientists out of Chicago has developed a machine learning model it says not only predicts crime a week in advance, but has also uncovered biased policing in eight major U.S. cities, including Los Angeles.
For once, algorithms that predict crime might be used to uncover bias in policing, instead of reinforcing it.
The tool, developed by a team led by University of Chicago professor Ishanu Chattopadhyay, forecasts crime by spotting patterns amid vast amounts of public data on property crimes and crimes of violence, learning from the data as it goes.
His team’s efforts have yielded promising results in some places. The tool predicted future crimes as much as one week in advance with roughly 90% accuracy, according to the report. The danger with any kind of artificial intelligence used by law enforcement, the researchers said, lies in misinterpreting the results and “creating a harmful feedback of sending more police to areas that might already feel over-policed but under-protected.”
The model his team developed can be used to monitor police performance. “You can turn it around and audit biases,” he said, “and audit whether policies are fair as well.”
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