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Most users cannot identify AI bias, even in training data

74 points by giuliomagnifico

by dfxm12

1 subcomments

DDG's search assist is suggesting to me that: Recognizing bias can indicate a level of critical thinking and self-awareness, which are components of intelligence.
"Most users" should have a long, hard thought about this, in the context of AI or not.

by lattrommi

1 subcomments

Except one instance when "black" is all lowercase, the article capitalizes the first letter of the word "black" every time and "white" is never capitalized. I wonder why. I'm not trying to make some point either, I genuinely am wondering why.

by licebmi__at__

1 subcomments

> but most users didn’t notice the bias — unless they were in the negatively portrayed group.
I don't think this is anything surprising. I mean, this is one of the most important reasons behind DEI; that a more diverse team can perform better than a less diverse one because the team is more capable of identifying their blind spots.
I find funny but unsurprising, that at the end, it was made a boogie man and killed by individuals with no so hidden biases

by zmmmmm

2 subcomments

I'm curious how much trained in bias damages in-context performance.
It's one thing to rely explicitly on the training data - then you are truly screwed and there isn't much to be done about it - in some sense, the model isn't working right if it does anything other than reflect accurately what is in the training data. But if I provide unbiased information in the context, how much does trained in bias affect evaluation of that specific information?
For example, if I provide it a table of people, their racial background and then their income levels, and I ask it to evaluate whether the white people earn more than the black people - are its error going to lean in the direction of the trained-in bias (eg: telling me white people earn more even though it may not be true in my context data)?
In some sense, relying on model knowledge is fraught with so many issues aside from bias, that I'm not so concerned about it unless it contaminates the performance on the data in the context window.

by segmondy

0 subcomment

by SoftTalker

8 subcomments

AIs/LLMs are going to reflect the biases in their training data. That seems intuitive.
And personally, I think when people see content they agree with, they think it's unbiased. And the converse is also true.
So conservatives might think Fox News is "balanced" and liberals might think it's "far-right"

0 subcomment

by WalterBright

2 subcomments

by Trias11

1 subcomments

Philosophically, the only was to see BIAS is to have BIAS. Completely unbiased person will not see BIAS in anything.
So, who are the judges?

by DocTomoe

3 subcomments

If bias can only be seen by a minority of people ... is it really 'AI bias', or just societal bias?
> “In one of the experiment scenarios — which featured racially biased AI performance — the system failed to accurately classify the facial expression of the images from minority groups,”
Could it be that real people have trouble reading the facial expression of the image of minority groups?

by 7e

1 subcomments

According to research, white Americans report as happier than other groups. So I’m not sure there’s bias here, only unhappiness about that result, which AI appears to replicate via other sources.

by eth0up

1 subcomments