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Data and Racism in Machine Learning?

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We often hear stories these days about racism in machine learning algorithms. The subtlety in these stories is often missing. I've been reading about this recently and found this quote very telling:
A wave of scholarship, triggered by the ProPublica report, illuminated the statistical challenge at the heart of the argument: Given that the underlying “base rate” of rearrest is higher for blacks than for whites, it is mathematically inevitable that the burden of false positives will fall more heavily on black defendants than on white ones. In other words, given that more black defendants than white defendants actually do have a high risk of reoffending, a “high risk” label that is correct 70% of the time for both white and black defendants will still mis-label more black than white defendants as high risk. A study titled “Inherent Tradeoffs in the Fair Determination of Risk Scores” proved mathematically that when rearrest rates are not equal between races, a well-calibrated tool like…