An Asian MIT student asked AI to turn an image of her into a professional headshot. It made her white with lighter skin and blue eyes.::Rona Wang, a 24-year-old MIT student, was experimenting with the AI image creator Playground AI to create a professional LinkedIn photo.

  • ExclamatoryProdundity@lemmy.world
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    1 year ago

    Look, I hate racism and inherent bias toward white people but this is just ignorance of the tech. Willfully or otherwise it’s still misleading clickbait. Upload a picture of an anonymous white chick and ask the same thing. It’s going go to make a similar image of another white chick. To get it to reliably recreate your facial features it needs to be trained on your face. It works for celebrities for this reason not a random “Asian MIT student” This kind of shit sets us back and makes us look reactionary.

    • AbouBenAdhem@lemmy.world
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      1 year ago

      It’s less a reflection on the tech, and more a reflection on the culture that generated the content that trained the tech.

      Wang told The Globe that she was worried about the consequences in a more serious situation, like if a company used AI to select the most “professional” candidate for the job and it picked white-looking people.

      This is a real potential issue, not just “clickbait”.

      • HumbertTetere@feddit.de
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        1 year ago

        If companies go pick the most professional applicant by their photo that is a reason for concern, but it has little to do with the image training data of AI.

        • AbouBenAdhem@lemmy.world
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          1 year ago

          Some people (especially in business) seem to think that adding AI to a workflow will make obviously bad ideas somehow magically work. Dispelling that notion is why articles like this are important.

          (Actually, I suspect they know they’re still bad ideas, but delegating the decisions to an AI lets the humans involved avoid personal blame.)

          • Square Singer@feddit.de
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            1 year ago

            It’s a massive issue that many people (especially in business) have this “the AI has spoken”-bias.

            Similar to how they implement whatever the consultant says, no matter if it actually makes sense, they just blindly follow what the AI says .

          • Water1053@lemmy.world
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            1 year ago

            Businesses will continue to use bandages rather than fix their root issue. This will always be the case.

            I work in factory automation and almost every camera/vision system we’ve installed has been a bandage of some sort because they think it will magically fix their production issues.

            We’ve had a sales rep ask if our cameras use AI, too. 😵‍💫

      • drz@lemmy.ca
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        1 year ago

        No company would use ML to classify who’s the most professional looking candidate.

        1. Anyone with any ML experience at all knows how ridiculous this concept is. Who’s going to go out there and create a dataset matching “proffesional looking scores” to headshots?
        2. The amount of bad press and ridicule this would attract isn’t worth it to any company.
        • kbotc@lemmy.world
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          1 year ago

          Companies already use resume scanners that have been found to bias against black sounding names. They’re designed to feedback loop successful candidates, and guess what shit the ML learned real quick?

    • hardypart@feddit.de
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      1 year ago

      It still perfectly and visibly demonstrates the big point of criticism in AI: The tendencies the the training material inhibits.

    • Buddahriffic@lemmy.world
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      1 year ago

      The AI might associate lighter skin with white person facial structure. That kind of correlation would need to be specifically accounted for I’d think, because even with some examples of lighter skinned Asians, the majority of photos of people with light skin will have white person facial structure.

      Plus it’s becoming more and more apparent that AIs just aren’t that good at what they do in general at this point. Yes, they can produce some pretty interesting things, but they seem to be the exception rather than the norm, and in hindsight, a lot of my being impressed with results I’ve seen so far is that it’s some kind of algorithm that is producing that in the first place when the algorithm itself isn’t directly related to the output but is a few steps back from that.

      I bet for the instances where it does produce good results, it’s still actually doing something simpler than what it looks like it’s doing.

    • Thorny_Thicket@sopuli.xyz
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      1 year ago

      Almost like we’re looking for things to get mad about.

      Also what are these 50 people downvoting you for? Too much nuance I suppose.