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In a study with potentially far-reaching implications for criminal justice in the United States, a team of California researchers has found that algorithms are significantly more accurate than humans ...

Recidivism is the likelihood of a person convicted of a crime to offend again. Currently, this rate is determined by predictive algorithms. The outcome can affect everything from sentencing decisions ...

The Louisiana state government in the United States uses the TIGER criminal recidivism prevention algorithm to score the recidivism risk of inmates in prison. TIGER was originally designed as a tool ...

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, ...

Algorithms are just as biased as the people who make them. An investigation by ProPublica found that Northpointe, creators of an algorithm that attempts to predict an incarcerated person’s likelihood ...

When the Sentencing Reform and Corrections Act of 2015 was introduced in the United States Congress last year, Republican and Democratic senators backed the ambitious bill. Experts complimented its ...

"'[I]nformation, guidance, ideas, and recommendations' are not 'product[s]' under the Third Restatement, both as a definitional matter and because extending strict liability to the distribution of ...

Algorithms used by authorities to predict the likelihood of criminal conduct are facing a major legal test in Wisconsin. The state’s highest court is set to rule on whether such algorithms, known as ...

Richard Berk likes to think he knows what criminals will do—even before they know. The statistics professor, who teaches at the University of Pennsylvania, was recently willing to show off his skills.