But our 'fitness functions' for social problems are normally pretty good or above reproach of the model. These tend to be easy to measure like 'did the person s

But our 'fitness functions' for social problems are normally pretty good or above reproach of the model. These tend to be easy to measure like 'did the person skip bail?' If a model of 'likelihood to show up to court after making bail' can make better predictions with information about protected characteristics (e.g if the model used sex to predict likelihood to show up in court), that feature would reduce the bias of the model. I think the issue progressives have with 'bias' is that some of society's prejudices ('bias') have an evidentiary basis. We already make decisions that progressives would tell us are prejudiced but we probably want to use those prejudices if they're useful. Consider a group of young men standing outside of a Church. If they're all clean shaven, smiling, and 'appropriate' for the Church it's nothing concerning. If they're white guys with shaved heads / neo nazi haircuts, and they don't look nice, and they're standing outside of a black Church, the prejudiced among us might correctly decide to alert the authorities to it. My personal opinion is that we should allow models to consider protected traits but we should ensure that models that make important decisions aren't prejudiced along those protected traits. The way to measure this is simply to ensure that the accuracy and precision of the classification decisions are comparable among protected traits.