That's fine if you are measuring the bias component too. If you're not, you risk perpetuating it. It's natural if I read a sentence about hands to conclude that the test refers to people and not fish, but if I read about 'the hands of a surgeon' and assume that those hands are male based on the current demographics of the surgical profession, I'm making an unwarranted assumption on insufficient information. It's wise to grant utility to uncertainty by maintaining a 'Don't know' option rather than being in a rush to make a determination before it is necessary, not least because of the computational cost of unwinding incorrect assumptions.
Totally agree with you. I'm not at all trying to say accuracy and bias can be orthogonal.
I'm trying to say some people think they have a good enough reason to throw away accuracy if that means they can change a societal bias. But that can only be a good thing if you agree with the change being made.
Isn't it preferable to accurately measure and account for Bias? The same metrics can be used to combat bias that reinforce it. Without accurate metrics, how do you form your argument against bias? Feelings?