> For example, the model under discussion, which can tell the difference between men and women and believes in differences between them, probably doesn't know t

> For example, the model under discussion, which can tell the difference between men and women and believes in differences between them, probably doesn't know that intersex people exist. Considering that the frequency of intersex people in a population lies somewhere between 0.05% and 0.07%, not accounting for a secondary trait such as whether a biological M or F happens to be intersex is an irrelevant classification error that has a negligible (if any) impact on a model's predictive ability. And by the way, any model can be regenerated if any attribute left out is found to be significant.