The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine
Learning
The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine
Learning
Fairness metrics are a core tool in the fair machine learning literature (FairML), used to determine that ML models are, in some sense, "fair". Real-world data, however, are typically plagued by various measurement biases and other violated assumptions, which can render fairness assessments meaningless. We adapt tools from causal sensitivity …