Big data is used to sentence criminals, can algorithms predict future risk?

Criminal history is consistently one of the strongest predictors of future crime

In 2013, a man named Eric L. Loomis was sentenced for eluding police and driving a car without the owner’s consent.

When the judge weighed Loomis’ sentence, he considered an array of evidence, including the results of an automated risk assessment tool called COMPAS. Loomis’ COMPAS score indicated he was at a “high risk” of committing new crimes. Considering this prediction, the judge sentenced him to seven years.

Loomis challenged his sentence, arguing it was unfair to use the data-driven score against him. The U.S. Supreme Court now must consider whether to hear