The problem is that people still tend to complain about the outcome if it's not an egalitarian distribution, regardless of the accuracy of the inputs. Let's sa

The problem is that people still tend to complain about the outcome if it's not an egalitarian distribution, regardless of the accuracy of the inputs. Let's say I want to identify violent criminals based on things like type of jewelry or clothes they wear, or tattoos (symbol, location). Reasonable model: it tries to identify gang membership by visible gang membership symbols (i.e. it exploits something gangsters themselves signal). It's not perfect (false positives: hip hop artists who are not necessarily actual gangsters) but it's probably a decent model. I would not be surprised if the outcome did not match the racial distribution of the US population, precisely for the reason you mentioned. Would that model be racially biased?