That means we so far have: * Palantir sued for not hiring enough Asians [0] * Google sued for not turning over compensation data [1] * Oracle sued for hiring too many Asians While it's possible that discriminatory processes have happened at all these places, it seems these lawsuits can be targeted at whoever one wishes. It's always going to be possible to find data that indicates discrimination, unless companies hire…
Not saying that I agree with quotas as a solution to problems like discriminatory biases in hiring, but how is a quota system "discriminatory"? What race, sex or age group is discriminated against by a requirement that appropriate proportions of those demographics make up the companies employees? (Heck in most cases quotas are simply a low bar, they are not even proportional to the population demographics.) I can und…
Basically a fair hiring process as defined by the above would be:
P(hire | features) = P(hire | race=1, features) = P(hire | race=2, features)
This may sound a bit silly or unnecessary, but unless this formula is specifically enforced, if a race were correlated with expected profit of a hire, a hiring algorithm might accidentally infer race from the other features. You can see the paper for an extended discussion.
With that background out of the way, let's consider hiring based on quotas. Since hiring takes place continuously across time, in order to maintain a quota across time we would need to change P(hire | race=1) based on the current composition of the company. Therefore P(hire | race=1) != P(hire | race=2) at least some of the time. Therefore it's discriminatory according to the above definition.
Of course, you may not like the definition. I would be very interested to hear an alternate formalization of non-discrimination!