Ethics in Machine Learning: Interview with Dr. Hanie Sedghi, Google Brain
From the article: &quot;What this means is that, we calibrate classifiers parameters such that it has the same acceptance ratio for all subgroups of sensitive features, e.g. race, sex, etc.&quot;<p>But statistics such as crime rates and default rates are NOT the same across race and sex. Is she saying that models should be fiddled with to make the same average prediction by race, sex, and other demographic variables?