In the ongoing effort to reform our criminal justice system, are algorithms the answer…and are these self-proclaimed “validated” assessments racist?
Undark.org dug deeper into the issue with an article published in March of 2018 that explores that very question…
( excerpt published by Undark.org – March 20 2018)
In 2016, ProPublica, the New York-based nonprofit journalism organization, published an investigation of a computer-based prediction tool called COMPAS. The software, which uses a proprietary cocktail of variables to predict future re-arrests, and is used by judges to determine whether that person should be released or held in jail until their court hearings, was biased against black defendants, and thus unfair, the investigation argued.
The company behind the software, originally called Northpointe but renamed Equivant last year, vigorously defended their algorithm in a follow-up report, and many independent researchers have since pointed out that the concept of “fairness,” in all of its legal and ethical complexity, may not be so easy to define. Arvind Narayanan, a computer scientist at Princeton, details 21 different kinds of fairness, for example. Richard Berk and colleagues at the University of Pennsylvania have described six kinds.
But I would add one further conundrum to the COMPAS debate — one that many commentators have thus far neglected to mention: Achieving ProPublica’s concept of fairness would actually require treating people differently by race, a reality that raises its own set of ethical and even constitutional questions.
The debate over COMPAS is pretty straightforward. The ProPublica reporting team looked at people who had been deemed by COMPAS as a “high risk” to be re-arrested, and yet who were not re-arrested over two years. Among black defendants, that percentage was about twice the rate of white defendants (45 percent compared to 24 percent). On the flip side, the percentage of defendants who had previously been judged “low risk” and yet were later re-arrested was much higher for whites than for blacks (48 percent compared to 28 percent), suggesting that COMPAS was getting things wrong in part on the basis of race.