I'm not seeing any evidence that the ML approach doesn't have the same or similar biases. I'm sure the results are different but we can't say they're better jus

I'm not seeing any evidence that the ML approach doesn't have the same or similar biases. I'm sure the results are different but we can't say they're better just because a computer generates them. In fact, we've seen many times that ML may often tend to give implicit biases even more emphasis, because in an attempt to create "objective" measures against which to judge a dataset, ML creators inject their own biases, or rely on data which is itself biased in its collection or categorization. (So, for example, if zip code is a major indicator in the ultimate ML algorithm, it may be completely "objective", while still reinforcing biases against minority applicants, simply because of how wildly self-segregated many US cities are, or because of self-reinforcing effects of systemic bias in other, human-controlled parts of the economy.)