If the human using the ML system is more biased than the average training sample, then the ML system's predictions could reduce their bias.

There's also a phenomenon called bias reversal, where the ML system will be biased in the opposite direction of the humans generating the dataset. This occurs when the datasets is built through a non-random biased sampling methodology, e.g. racist police officers checking for illegal items. I'm not going to go into the full details, but here's a paper on it https://arxiv.org/abs/1909.08518