| If you read deeper than a one line description you'll see: 1. Even after accounting for criminal history, recidivism, age and gender, black defendants were still scored as much more likely to re-offend. 2. It incorrectly predicted that black defendants would re-offend much more frequently than white defendants. 3. It incorrectly predicted that white defendants would not re-offend much more frequently than black defendants. Considering those three things and that they have refused to give any details about how the algorithm works, I see zero reason to give them the benefit of the doubt. Fire them until they can demonstrate that the algorithm is not in fact biased like it appears to be. The score also takes into account answers to questions like whether the defendant's parents were separated or whether their parents were ever arrested. Those things are completely out of the defendant's control and are highly correlated with race. Even including those things in their score is damning. |
* Out of 100 white people, 5 were labeled high risk.
* Out of 100 black people, 20 were labeled high risk.
* Out of the 5 white people labeled high risk, 4 re-offended.
* Out of 20 black people labeled high risk, 16 re-offended.
In either case, someone labeled high risk had the same likelihood to re-offend: 80%.
"It incorrectly predicted that black defendants would re-offend more frequently than white defendants." This is technically correct, but not because the algorithm was bad a predicting rates if re-offending. It's because there was higher rates of re-offending. The likelihood of re-offending among someone labeled high risk is the same.
This kind of objection seems like a blanket rejection of any system that produces an inequitable outcome. But the reality is that rates of re-offending is not equal. Even a perfectly accurate prediction of re-offense is going to predict higher rates of re-offending among men. Because men re-offend at higher rates. This isn't sexism.
That doesn't mean we shouldn't recognize the disparate impact of incarceration on underprivileged people. But simply concluding bias due to inequitable outcomes is simplistic.