Ok now how do we make it more fair? Kit Rodolfa at #FAT2020: recidivism algorithms.
Too true: anything you optimize for will have a down side. In this case, let’s look at recall optimization. In other words, equal rates of finding those who will actually re-offend, regardless of race (I think? Might have that backwards...)
Surprise! One size fits all doesn’t work. Perhaps different thresholds will improve equity to cater to different groups who have different needs?
Sadly, resources here constrain the equity. Can’t allocate interventions if they don’t exist.
Solution: choose the best possible version of the algorithm. Except maybe not? One alternative might be just to not let algorithms dictate who gets help in staying out of jail. Allocate more resources, or work to stop our culture of incarceration...
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