ValentinLAFARGUE/EIF-Manipulated-distributions

Exposing the Illusion of Fairness (EIF) Manipulations Results We consider use cases where the auditee has developed a model which has fairness issues. It tries to hide the problem by picking a subsample while optimizing the fairness metric that will be computed by the auditor. Yet, from the supervisory authority, submitting a non-representative sample constitute a deceptive attempt by the auditee to obstruct or distort the assessment. We present here the original empirical… See the full description on the dataset page: https://huggingface.co/datasets/ValentinLAFARGUE/EIF-Manipulated-distributions.