> And one of the things that I learned (in [1]) is that, even if you're carfull with the features you use, you might still have a negative effect. One needs to

> And one of the things that I learned (in [1]) is that, even if you're carfull with the features you use, you might still have a negative effect. One needs to understand how these features interplay with each other. For example, you may not directly use a protected class feature (race) to make your prediction but you might end up using a secondary or tertiary variable (like location) to end up learning a protected class feature due to statistical correlations.