Software 'No More Accurate Than Untrained Humans' At Predicting Recidivism
Software 'No More Accurate Than Untrained Humans' At Predicting Recidivism
Published on January 18, 2018 at 12:00PM
An anonymous reader quotes a report from The Guardian: The credibility of a computer program used for bail and sentencing decisions has been called into question after it was found to be no more accurate at predicting the risk of reoffending than people with no criminal justice experience provided with only the defendant's age, sex and criminal history. The algorithm, called Compas (Correctional Offender Management Profiling for Alternative Sanctions), is used throughout the U.S. to weigh up whether defendants awaiting trial or sentencing are at too much risk of reoffending to be released on bail. Since being developed in 1998, the tool is reported to have been used to assess more than one million defendants. But a new paper has cast doubt on whether the software's predictions are sufficiently accurate to justify its use in potentially life-changing decisions. The academics used a database of more than 7,000 pretrial defendants from Broward County, Florida, which included individual demographic information, age, sex, criminal history and arrest record in the two year period following the Compas scoring. The online workers were given short descriptions that included a defendant's sex, age, and previous criminal history and asked whether they thought they would reoffend. Using far less information than Compas (seven variables versus 137), when the results were pooled the humans were accurate in 67% of cases, compared to the 65% accuracy of Compas. In a second analysis, the paper found that Compas's accuracy at predicting recidivism could also be matched using a simple calculation involving only an offender's age and the number of prior convictions.
Published on January 18, 2018 at 12:00PM
An anonymous reader quotes a report from The Guardian: The credibility of a computer program used for bail and sentencing decisions has been called into question after it was found to be no more accurate at predicting the risk of reoffending than people with no criminal justice experience provided with only the defendant's age, sex and criminal history. The algorithm, called Compas (Correctional Offender Management Profiling for Alternative Sanctions), is used throughout the U.S. to weigh up whether defendants awaiting trial or sentencing are at too much risk of reoffending to be released on bail. Since being developed in 1998, the tool is reported to have been used to assess more than one million defendants. But a new paper has cast doubt on whether the software's predictions are sufficiently accurate to justify its use in potentially life-changing decisions. The academics used a database of more than 7,000 pretrial defendants from Broward County, Florida, which included individual demographic information, age, sex, criminal history and arrest record in the two year period following the Compas scoring. The online workers were given short descriptions that included a defendant's sex, age, and previous criminal history and asked whether they thought they would reoffend. Using far less information than Compas (seven variables versus 137), when the results were pooled the humans were accurate in 67% of cases, compared to the 65% accuracy of Compas. In a second analysis, the paper found that Compas's accuracy at predicting recidivism could also be matched using a simple calculation involving only an offender's age and the number of prior convictions.
Read more of this story at Slashdot.
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