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Increasing overall accuracy won't help if it's applied to all ethnicities. It has to be an increase only for the affected type of people. But if you're going to
by lopmotr 7y ago
Increasing overall accuracy won't help if it's applied to all ethnicities. It has to be an increase only for the affected type of people. But if you're going to do that, you could also just artificially cripple the accuracy for the too-accurate groups. That sounds like the easiest solution, if it's actually a problem to be solved in the first place.
- SamReidHughes 7y agoNo, it would help a lot. Let's say you shrink mistakes from 10% and 20% to 1% and 2%. That means the gap in misidentification likelihood has shrunk from 10% to 1%.
- lopmotr 7y agoHuh? Isn't that just clever accounting? 2% is still twice as much as 1%. If a black person and a white person each travel the same number of times, the black can still expect twice as many additional checks as the white, the same as before the improvement.
- SamReidHughes 7y agoNo, it’s the appropriate measure of ”unfairness.” If you designed a system where 5 black guys got misidentified but 1 white guy, out of the U.S. population, that would be far less unfair compared to 2%/1% despite the ratio being higher. And why did you pick that ratio to compare instead of 90%/80% vs. 99%/98%? The right means of comparison — for fairness — is the absolute difference in proportion. I don’t mean to imply that’s the right metric at all, of course, because it specially privileges minorities. The proper measure should equally weight the algorithm’s performance on all people in the population, or at least weight them irrespective of race. That’s just not a measure of fairness between races.
- deleted 7y ago[deleted]