Learning conditional mean vs conditional median for superresolution might be differently affected by a large chunk of outgroup. That was what I remember folks talking about during this twitter feud. Or, like with word embeddings, where people have added some balance penalties to the loss function to make it unbiased in the presence of biased data. Dataset bias caused this, but dataset bias can sometimes be well mitigated.