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Unfortunately this doesn't work, one of the basic things to know about ML fairness is that you generally can't get the outcomes you want by hiding things from y
by mgraczyk 3y ago
Unfortunately this doesn't work, one of the basic things to know about ML fairness is that you generally can't get the outcomes you want by hiding things from your model.
For example you can infer the race of a candidate from other facts about them. The model could still illegally discriminate by first inferring race, then discriminating on the basis of inferred race.
- jncfhnb 3y agoThen those things shouldn’t be on the whitelist. That’s the point of a whitelist. The problem you describe affects blacklists that try to remove only the things you obviously don’t want to use.
- mgraczyk 3y agoYou will end up adding things to your whitelist that you think are innocuous, but if that's all you do you will very likely end up discriminating and not even knowing it.