  This paper critically examines arguments against independence, a measure of
group fairness also known as statistical parity and as demographic parity. In
recent discussions of fairness in computer science, some have maintained that
independence is not a suitable measure of group fairness. This position is at
least partially based on two influential papers (Dwork et al., 2012, Hardt et
al., 2016) that provide arguments against independence. We revisit these
arguments, and we find that the case against independence is rather weak. We
also give arguments in favor of independence, showing that it plays a
distinctive role in considerations of fairness. Finally, we discuss how to
balance different fairness considerations.
