This doesn't really address the core issue. There's a difference between determining loan rate based on race of the applicant, and using features that correlate

This doesn't really address the core issue. There's a difference between determining loan rate based on race of the applicant, and using features that correlate with failed loan repayment that happen to overrepresented among black people. While it is illegal to use race as an input to your algorithm, biases in outcomes will still be present given the bias in the relevant non-protected properties. Are ML algorithms required to normalize for race in the face of bias in the relevant variables?