A great example is how very resentful many young white men of college age are that universities are requiring them to take sensitivity courses designed to reduce the instance of campus rape, but strictly speaking men of that age are the overwhelming majority of bad actors in that environment. Statistically and logistically speaking, it's smarter and cheaper to just require all men of college age to take courses reminding them that rape is not okay rather than dealing with the moral, legal and healthcare costs of the alternative.
In some cases, our relatively primitive algorithms pick up on correlations that should not be acted on because we're actively working to correct them. For example, it would be inappropriate to pre-reject job applications based on skin color if in a certain culture, it's less likely for that person to have a college degree.
Even if that insight is correct, it's usually part of something that society hopes to correct or that applicants should be given the benefit of the doubt about, otherwise very serious negative responses will emerge.
Acting on existing categories may reinforce. It may not. For now, it's a case-by-case basis we'll have to act on. Maybe one day, modeling techniques and data sources will become sophisticated and robust enough to make every decision for us. That day is not today.