[Summary: Say you use a fair test to predict a quality for which other non-tested factors matter, and then you make a decision based on this prediction. Then people who do worse on the test measure (but not necessarily the other factors) are subject to different error rates, even if you estimate their qualities just as well. If that’s already obvious, great; I additionally try to present the notion of fairness that lets one stop at “the test is fair; all is as it should be” as a somewhat arbitrary line to draw with respect to a broader class of notions of statistical fairness.] [Not sure if this text will appear anywhere in LW 2.0, so this is a test.]

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