Tuesday, April 11, 2017

Pre-Trial Algorithms Deserve a Fresh Look, Study Suggests
"What if a predictive tool used at the moment of arraignment could simultaneously reduce the number of people sent to jail before trial, reduce crime, and also reduce racial disparities in incarceration? Such a tool could be a game changer in criminal justice reform. There’s good reason to be skeptical, however: Several high-profile analyses of COMPAS — a popular, commercially available “risk assessment” tool — have claimed that the tool unfairly labels black defendants as higher risk, and it does so more often than it overestimates the risk posed by white defendants.

But a new large scale study — Human Decisions and Machine Predictions—  demonstrates that it’s possible to build a predictive tool that simultaneously accomplishes three desirable goals: reducing pre-trial detention rates, reducing re-arrest rates of those released pending trial, and reducing racial disparities in which defendants are jailed. Policymakers across the ideological spectrum should be interested in this result and encourage further study."

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