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I think you have a really good point here. The problem is that we have this current bias in society and people wish to change it. I think there is a fear, that if we reflect this bias, in the way we talk, we re-enforce the bias.

It seems an effective tool, if you want to change thinking then police the way words can be used around the topic. It is however worrying that machines could start playing a role in this. It could become a powerful tool in steering public opinion. This doesn't seem too bad, but that could be used to favour an incumbent political party, or more than likely to sell products we otherwise don't really want.

But you are right machines need accuracy and removing that bias could be detrimental to the task they're solving.




My point isn't that accuracy and bias are orthogonal, but that bias is contained in the accuracy metric.


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?




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