For example, let’s assume you are building an AI system recommending people for a specific job. You utilize all relevant data available to train your model and find an existing bias towards a particular race who already populate most of the filled jobs. The model could develop a race bias, making the resumes of this cohort more likely to be selected for the job. In this case, it is clear that including racial and geographical features as a part of a training engine is problematic.
Conversely, if you are building a system to recommend clothing types and skin-care products, then geographic and ethnic parameters might help positively in doing so. There could be a specific fashion trend emerging from a particular geography/ethnicity which people may like to follow.