It really depends on the specifics of the optimization problem in question. If ML is trained on biased data where an optimality exists only at an unbiased solu

It really depends on the specifics of the optimization problem in question. If ML is trained on biased data where an optimality exists only at an unbiased solution (think a shaped reward function in RL to disincentivize class bias or something similar), then no, the ML is most certainly not supposed to echo the bias they've been fed. On the other hand, if an optimal solution to the ML optimization problem exists at a biased solution, ex. a naive prediction of if a nurse is a man or a woman, then yeah, we would say that it was supposed to echo the bias. All too often I feel people forget that ML is just an optimization problem. What you're trying to optimize really matters - generalizing about all ML without talking about the optimization problem in question is pointless.