Earlier quoted context omitted.
So I'd consider that part of the system. You could also train your model to debias by using a cost function that incorporates race and minimizes the KL divergence between different ethnicities. (Obviously it would be best to use interpretable models and/or causal ones) A Mahalanobis distance might also be good here. But when training your model you might want to PCA it and if race isn't an included factor then you ca…
I don't assume this is easy or even possible to solve. If the model is trying to determine something like the applicant's level of adversity based on whatever info college admissions has, of course the result will have a divergence between races, and historical racism will have shaped some of your input variables (like high school) to some degree that we'll never fully understand. Using some statistical difference be…
So how do you expect the expert to de-bias the system without some cost function?