To satisfy the condition of equalized odds in algorithmic bias auditing, what must be true about the relationship between the model's predictions, the actual labels, and the protected demographic groups?

Equalized odds is a fairness criterion requiring that a model performs with the same level of accuracy across different protected demographic groups. To satisfy this condition, the model's predictions must be statistically independent of the protected group attribute, conditional on the actual label. This means the model mu....