[urish]

My only disagreement is with: >Human processes just add additional bias

Bias with respect to what? As you say, there is already bias baked into the data collection and the algorithmic choices.

The bias that human editors introduce is different, but not necessarily larger, however you even measure it. There are also myriad human choices behind the choice and deployment details of the algorithm.

An important plus for human editors is greater interpretability and greater transparency regarding the biases the system ends up showing.

[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?