Fairness seen as global sensitivity analysis

Ensuring that a predictor is not biased against sensitive feature the goal of fair learning. Meanwhile, Global Sensitivity Analysis (GSA) used in numerous contexts to monitor influence any on an output variable. We merge these two domains, and Fairness, by showing how fairness can be defined using special framework based various usual indicators are common between fields. also present new indices, as well rates convergence, useful proxies.