I think these attempts are still valuable as machine learning makes hidden biases more obvious. A human may discriminate against women, but if asked he will rationalize, claiming other reasons to not hire those women. A computer analyzing all the applications he has taken part of won’t try to hide the patterns it finds. Having it out in plain view it is then easier to train the staff to avoid basing decisions on statements that ought to be irrelevant. (Assuming the staff is honest and trying to find the best applications and the bias is unintentional).
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