New assessment tool for incarceration

The more that I studied music, the more faith I had in its timeless beauty and infinite variation and admiration for its greatest practitioners. The more I studied law, the more I realized that most of it was built on entirely unfounded assumptions. And there is an odd, awkward, and often misguided interaction between the social science findings and the legal reactions to them. This sort of blind leading the blind feature of the law is troubling, to say the least, which is why I love the empirical movement in law (and continuing expansion in social science).

That's why I was so interested to read that the Kentucky in the United States has established a new risk assessment tool to determine when a potential parolee is likely to be a reoffender based on (wait for it) -- actual verifiable and replicable data! If this surprises you that this was not the status quo or if you don't quite believe me, these quotes from the article:

"We have had a risk-assessment tool since 1976, the Vera scale. Over time, modifications were being made to factors used to determine risk that were reactionary. The indicators for determining risk were not research-based," says Klute.
***
"Good, reliable data drive good bond decisions," says Kentucky Circuit Court Judge David Tapp. "It's definitely changed the way I decide. When I was a young judge, I relied on intuition and community expectations. Now I know with verified information what is statistically likely" if the defendant is released. 
***
"It enables us to make better arguments for our clients," says Scott West, general counsel of the Kentucky Department of Public Advocacy. "It allows a factual argument to rebut gut instinct." 

Not everyone is a fan, including U.S. Attorney General Eric Holder:

On the PBS NewsHour with Gwen Ifill on July 31, 2014, Holder questioned the use of big data on the front end to determine detention. States are already "using that as a predictor, though, of how likely this person is going to be a recidivist. Using group data to make an individualized determination, I think, can result in fundamental unfairness."

No doubt big data can often lead to stereotypes and covert racism, but statisticians have gotten increasingly more sophisticated about trying to filter out those tendencies (I believe), and if there is no evidence that this is what actually is happening (again from real, reliable data), then I'm not sure how non research-based risk assessment tools are any more fundamentally fair than research-based ones?

For anyone who has been worried that being tagged a sociopath would lead to their permanent incarceration should they ever be caught up in the system...