Verifying Individual Fairness in Machine Learning Models

21 Jun 2020Philips George JohnDeepak VijaykeerthyDiptikalyan Saha

We consider the problem of whether a given decision model, working with structured data, has individual fairness. Following the work of Dwork, a model is individually biased (or unfair) if there is a pair of valid inputs which are close to each other (according to an appropriate metric) but are treated differently by the model (different class label, or large difference in output), and it is unbiased (or fair) if no such pair exists... (read more)

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