Assessing Classifier Fairness with Collider Bias. (arXiv:2010.03933v2 [cs.LG] UPDATED)

Web: http://arxiv.org/abs/2010.03933

The increasing application of machine learning techniques in everyday
decision-making processes has brought concerns about the fairness of
algorithmic decision-making. This paper concerns the problem of collider bias
which produces spurious associations in fairness assessment and develops
theorems to guide fairness assessment avoiding the collider bias. We consider a
real-world application of auditing a trained classifier by an audit agency. We
propose an unbiased assessment algorithm by utilising the developed theorems to
reduce collider biases in the assessment. Experiments and …

arxiv bias fairness