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You are viewing ARCHIVED CONTENT released online between 1 April 2010 and 24 August 2018 or content that has been selectively archived and is no longer active. Content in this archive is NOT UPDATED, and links may not function.Extract from article by Doug Austin
Most of us love the idea of big data analytics and how it can ultimately benefit us, not just in the litigation process, but in business and life overall. But, there may be one group of people who may not be as big a fan of big data analytics as the rest of us: criminals who are being sentenced at least partly on the basis of predictive data analysis regarding the likelihood that they will be a repeat offender.
This article in the ABA Journal (Legality of using predictive data to determine sentences challenged in Wisconsin Supreme Court case, written by Sony Kassam), discusses the case of 34-year-old Eric Loomis, who was arrested in Wisconsin in February 2013 for driving a car that had been used in a shooting. He ultimately pled guilty to eluding an officer and no contest to operating a vehicle without the owner’s consent. Loomis, a registered sex offender, was then sentenced to six years in prison because a score on a test noted he was a “high risk” to the community.
During his appeal in April, Loomis challenged the use of the test’s score, saying it violated his right to due process of law because he was unable to review the algorithm and raise questions about it.
As described in The New York Times, the algorithm used is known as COMPAS (CorrectionalOffender Management Profiling for Alternative Sanctions).
























