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Survey on Causal-based Machine Learning Fairness Notions
[article]
2022
arXiv
pre-print
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
arXiv:2010.09553v7
fatcat:wblrqiv7wzdvvlsbup2d7eblfi