Survey on Causal-based Machine Learning Fairness Notions. (arXiv:2010.09553v4 [cs.LG] UPDATED)

Addressing the problem of fairness is crucial to safely use machine learning
algorithms to support decisions with a critical impact on people's lives such
as job hiring, child maltreatment, disease diagnosis, loan granting, etc.
Several notions of fairness have been defined and examined in the past decade,
such as, statistical parity and equalized odds. The most recent fairness
notions, however, are causal-based and reflect the now widely accepted idea
that using causality is necessary to appropriately address the problem of …

arxiv fairness learning machine machine learning survey