A cynic might think that the value of a complicated algorithm is you can, as Pinboard said in a similar context, money launder your bias.
Hell, I do ml on a daily basis, and for anything but a regression or a decision tree, it's complex and/or impossible to even explain why an algorithm picked what it did for a specific example. Let alone to evaluate what an algorithm is picking up on in general.
And that doesn't even get into the mess that is highly correlated variables (eg ethnicity, SES, income, peer income, parental income, education, arrest rate, housing location) most of which are largely synonyms for each other. And the bias in the data themselves -- being poor or minority increases the detection rate of criminality.
I like this phrase. I'm stealing it :-)
source: https://twitter.com/Pinboard/status/744595961217835008
Whether it's a "sophisticated" algorithm or a sheet where a parole officer writes down numbers and adds them up, there's this constant idea that it can be used to determine how likely an individual is to re-offend.
Rejecting the use of such a system would call into question the methodology used in deciding whether or not to revoke someone's parole/probation - this is incredibly significant, because, to take the example of Wisconsin, over half of the state prison inmates are in on revocation.
I'm just saying this by way of presenting an alternative idea of why the court might have rejected the appeal. It's also important to note that in Wisconsin we have a very conservative supreme court.
I find that the more I learn about the criminal justice system, the more shocked I am that we allow it to continue. It's not a law and order vs. wishy-washy liberalism thing - our criminal justice system demonstrably increases recidivism.