From a fairness angle, our technique shares similarities with adversarial training (Zhang et al., 2018a;Madras et al., 2018) in asking the model to optimize for an additional objective that transitively unbiases the classifier.
those approaches work to remove protected attributes from the representation layer, which is unstable.