Additionally, this extends to the usage of latent or inferred variables that behave as a proxy to a protected class - so neural networks and other discriminative approaches outside of a distinctly diagnosable decision tree, could be in a rather grey area legally if used for credit scores, etc.
It's possible that the upshot of a legal challenge could be a crippling cap on the accuracy of models as they explicitly avoid any information derived from any protected factors.
It's possible that the upshot of a legal challenge could be a crippling cap on the accuracy of models as they explicitly avoid any information derived from any protected factors.