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In NYC, companies will have to prove their AI hiring software isn't sexist or racist (www.nbcnews.com)
submitted 3 years ago by to c/technology@lemmy.world
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AI-infused hiring programs have drawn scrutiny, most notably over whether they end up exhibiting biases based on the data they’re trained on.

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[–] [S] 7 points 3 years ago (2 children)

I figure you’d audit it by examining the results, and if bias isn’t detectable in the results then I’d argue that’s at the very least still better than the human-based systems we’ve been relying on up til now.

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  • [–] 5 points 3 years ago (1 child)

    Unequal outcomes isn’t evidence of bias.

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  • [–] 6 points 3 years ago (1 child)

    Not inherently, but things can be tested.

    If you have a bunch of otherwise identical résumés, with the only difference being the racial connotation of the name, and the AI gives significantly different results, there's an identifiable problem.

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  • [–] 4 points 3 years ago (1 child)

    What would unbiased results look like?

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  • [–] [S] 3 points 3 years ago (1 child)

    When the demographics of the output are roughly equivalent to the demographics of the input. If ten men and fifty women apply, and eight men and two women are hired, that is worth investigating.

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  • [–] 1 point 3 years ago (1 child)

    That would be a pretty extreme bias to have, so yeah that would make sense. If it’s not so drastic it might be harder to spot by just looking at the results.

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  • [–] [S] 2 points 3 years ago (1 child)

    It’s a flag, not the entire investigation. If something seems suspicious, that’s the queue to investigate, not just immediately slap cuffs on someone.

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  • [–] 1 point 3 years ago (1 child)

    Right, that’s why I was trying to ask you for your opinion on what the threshold for “investigation worthy” results

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  • [–] [S] 1 point 3 years ago (1 child)

    I’m not a policy expert, author of the bill, or in charge of the department that will lead these investigations. Even if I were an expert on the subject, what I’d do and what this department will do aren’t likely to be the same.

    I just support civilian oversight and audits of these algorithms and LLMs as they take up a more prominent position in hiring and firing.

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  • [–] 2 points 3 years ago*

    I figure you’d audit it by examining the results, and if bias isn’t detectable in the results

    I was just asking for more info on how you’d examine the results for bias since it would need to be pretty extreme like the example you gave to be identifiable as something worth investigating.

    All good if you don’t have a more specific answer, I was just curious what your personal thoughts were here.

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