  We provide the asymptotic distribution of the major indexes used in the
statistical literature to quantify disparate treatment in machine learning. We
aim at promoting the use of confidence intervals when testing the so-called
group disparate impact. We illustrate on some examples the importance of using
confidence intervals and not a single value.
