• Heresy_generator@kbin.social
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    1 year ago

    ANNs like this will always just present our own biases and stereotypes back to us unless the data is scrubbed and curated in a way that no one is going to spend the resources to. Things like this are a good demonstration of why they need to be kept far, far away from decision making processes.

    • 4dpuzzle@beehaw.org
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      1 year ago

      Of course they will be used for decision making processes. And when you complain, they will neglect you saying that the ‘computer’ said so. The notion that the computer is infallible existed even before LLMs became mainstream.

    • megopie@beehaw.org
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      1 year ago

      And even if moderated, it will display new unique biases, as otherwise unassuming things will get moderated out of the pool by people who take exception to it.

      Not to mention the absurd and inhuman mental toll this work will take on the exploited workers forced to sort it.

      Like, this is all such a waist of time, effort, and human sanity, for tools of marginal use that are mostly just a gimmick to prop up the numbers for tech bros who have borrowed more money than they can pay back.

    • Pigeon@beehaw.org
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      1 year ago

      Also, it’s the type of thing that makes me very worried about the fact that most of the algorithms used in things like police facial recognition software, recidivism calculation software, and suchlike are proprietary black boxes.

      There are - guaranteed - biases in those tools, whether in their processors or in the unknown datasets they’re trained on, and neither police nor journalists can actually see the inner workings of the software to know what those biases are, to counterbalance them or to recognize if the software is so biased as to be useless.

    • Greg Clarke@lemmy.ca
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      1 year ago

      This isn’t an Large Language Model, it’s an Image Generative Model. And given that these models just present human’s biases and stereotypes, then doesn’t it follow that humans should also be kept far away from decision making processes?

      The problem isn’t the tool, it’s the lack of auditable accountability. We should have auditable accountability in all of our important decision making systems, no matter if it’s a biased machine or biased human making the decision.

      This was a shitty implementation of a tool.

    • magnetosphere @beehaw.org
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      1 year ago

      Something as simple and obvious as this makes me wonder what other hidden biases are just waiting to be discovered.

      • hh93@lemm.ee
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        1 year ago

        I think the best example about how AI will only further a bias that’s already there is the one when Amazon used AI to weed out applications by training an ai with which applications resulted in hired people and which failed - eventually they found that they almost only had interviews with men and upon closer inspection identified that they already were subconsciously discriminating against women earlier but at least HR sent them an equal amount of men and women to the interviews which now wasn’t the case anymore since the AI didn’t see the value in sending the women to interviews if most of them wouldn’t be hired anyway.

    • jarfil@beehaw.org
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      1 year ago

      Things like this are a good demonstration of why they need to be kept far, far away from decision making processes.

      Somewhat ironic to say, on a platform that’s already using ANNs as a first line of defense against users spamming CSAM.

      I have no delusions regarding decision makers using them, my only doubt is for how long they’ve been using them to decide the next step in wars around the world.

    • EthicalAI@beehaw.org
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      1 year ago

      I mean, maybe we can make an Ai that uses reason to uncover these biases in the future from this starting point. We are only at the beginning.

  • fosforus@sopuli.xyz
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    1 year ago

    Plenty of actual photographs exist with Palestinian children wielding rifles and Hamas headbands. Perhaps the AI is just trained with those images as well?

    • taanegl@beehaw.org
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      1 year ago

      By that logic I demand stickers of obesity, respiratory issues and heart issues being portrayed when I search “American”. Preferably where each character has a fat hamburger shoved in their face.

      • Kalash@feddit.ch
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        1 year ago

        “American” can be interpreted as the adjective as well, not just the people. So you mostly find flags, eagles and the statue of liberty.

        You have to search for “average American” to get what you’re looking for.

      • fosforus@sopuli.xyz
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        1 year ago

        Why would you demand a negative thing for another group to counter a negative thing for one group? That makes no sense.

        But also, “American children” has plenty of cultural material to build an image from. Probably some of it is obese and filled with junk food, but a good portion is most probably something else. In contrast, the only public photo material of palestinian children is either from adults carrying them away from some atrocity or adults giving them assault rifles and parading them for the cameras. In short, they seem to only exist as propaganda material.

        • acastcandream@beehaw.org
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          1 year ago

          They’re not actually asking for it, they’re making a point about the problem. The person they’re responding to is basically going “those images exist tough shit.”

    • GunnarRunnar@beehaw.org
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      1 year ago

      Why does it matter what the excuse is?

      You shouldn’t get a stereotype (or in this case I suppose propaganda?) when you give a neutral prompt.

      • jarfil@beehaw.org
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        1 year ago

        You shouldn’t get a stereotype […] when you give a neutral prompt.

        Actually… you kind of should. A neutral prompt should provide the most commonly appearing match from the training set… which is basically what stereotypes are; an abstraction from the most commonly appearing match from a person’s experience.

      • sqgl@beehaw.org
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        1 year ago

        Should, would, could. AI is trained on what it scrapes off the internet. It is only feeding the Augmented Idiocy which is already a problem.

      • magnetosphere @beehaw.org
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        1 year ago

        To me, it should only “matter” for technical reasons - to help find the root of the problem and fix it at the source. If your roof is leaking, then fix the roof. Don’t become an expert on where to place the buckets.

        You’re right, though. It doesn’t matter in terms of excusing or justifying anything. It shouldn’t have been allowed to happen in the first place.

        • GunnarRunnar@beehaw.org
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          1 year ago

          I do agree that technical mistakes are interesting but with AI the answer seems to always be creator bias. Whether it’s incomplete training sets or (one-sidedly) moderated results, it doesn’t really matter. It pushes the narrative to certain direction, and people trust AIs to be impartial because they presume it’s just a machine that interprets reality when it never is.

          • jarfil@beehaw.org
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            1 year ago

            it’s just a machine that interprets reality

            …as seen by the machine.

            It’s amazing how easily people seem to forget that last part; they wouldn’t trust a person to be perfectly impartial, but somehow they expect an AI to be.

            • GunnarRunnar@beehaw.org
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              1 year ago

              It’s amazing how easily people seem to forget that machines uses tools its creator provides. You can’t trust AI to be impartial because it never is as it is a collection of multiple choices made by people.

              This is such a bore, having this same conversation over and over. Same thing happened with NFTs and whatever is currently at the height of its tech hype cycle. Don’t buy into the hype and realize both AIs potential and shortcomings.