[yummyfajitas]

It's been reproduced across many experiments that humans will add bias that harms accuracy when making decisions. I.e., if x[6] represents race, humans will systematically wrongly weight x[6].

Machines simply don't do this.

As you say, there is already bias baked into the data collection and the algorithmic choices.

That's not what I said.

What I said is that you can't have collective equality (e.g. same rate of false positives, lack of disparate impact) and also accuracy (getting the right answer) except in trivial/unrealistic cases.

Human editors are fundamentally less interpretable and transparent than machines. You can easily interrogate machines and test for bias; how do you do that to humans?

Or, to take a historical example, why did colleges switch from algorithms to humans when the supreme court said that transparent racial bias is forbidden?