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.
Hm. Probably trained on more white people than Asians shrug
Racial bias propagating, click-baity article.
Did anyone bother to fact check this? I ran her exact photo and prompt through Playground AI and it pumped out a bad photo of an Indian woman. Are we supposed to play the raical bias card against Indian women now?
This entire article can be summarized as “Playground AI isn’t very good, but that’s boring news so let’s dress it up as something else”
Also depends on what model was used, prompt, strength of prompt etc.
No news here, just someone who doesn’t know how to use AI generation.
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.
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”.
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.
Especially ones that are still heavily in development
A company using a photo to choose a candidate is really concerning regardless if they use AI to do it.
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.)
Again, that’s not really the case.
I have Asian friends that have used these tools and generated headshots that were fine. Just because this one Asian used a model that wasn’t trained for her demographic doesn’t make it a reflection of anything other than the fact that she doesn’t understand how MML models work.
The worst thing that happened when my friends used it were results with too many fingers or multiple sets of teeth 🤣
No company would use ML to classify who’s the most professional looking candidate.
- 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?
- The amount of bad press and ridicule this would attract isn’t worth it to any company.
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?
You said yourself you hate inherent bias yet attempt to justify the result by saying if used again it’s just going to produce another white face.
that’s the problem
It’s a racial bias baked into these AIs based on their training models.
I doubt it is concious racial bias, it’s most likely that the training data is made up of mostly white people and labeled poorly.
I also wouldn’t say it was conscious bias either. I don’t think it’s intentionally developed in that way.
The fact still remains though whether conscious or unconscious, it’s potentially harmful to people of other races. Sure it’s an issue with just graphic generation now. What about when it’s used to identify criminals? When it’s used to filter between potential job candidates?
The possibilities are virtually endless, but if we don’t start pointing out and addressing any type of bias, it’s only going to get worse.
I feel like you’re overestimating the capabilities of current ai image generation. And also presenting problems that don’t exist.
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.
Garbage post
This is not surprising if you follow the tech, but I think the signal boost from articles like this is important because there are constantly new people just learning about how AI works, and it’s very very important to understand the bias embedded into them.
It’s also worth actually learning how to use them, too. People expect them to be magic, it seems. They are not magic.
If you’re going to try something like this, you should describe yourself as clearly as possible. Describe your eye color, hair color/length/style, age, expression, angle, and obviously race. Basically, describe any feature you want it to retain.
I have not used the specific program mentioned in the article, but the ones I have used simply do not work the way she’s trying to use them. The phrase she used, “the girl from the original photo”, would have no meaning in Stable Diffusion, for example (which I’d bet Playground AI is based on, though they don’t specify). The img2img function makes a new image, with the original as a starting point. It does NOT analyze the content of the original or attempt to retain any features not included in the prompt. There’s no connection between the prompt and the input image, so “the girl from the original photo” is garbage input. Garbage in, garbage out.
There are special-purpose programs designed for exactly the task of making photos look professional, which presumably go to the trouble to analyze the original, guess these things, and pass those through to the generator to retain the features. (I haven’t tried them, personally, so perhaps I’m giving them too much credit…)
If it’s stable diffusion img2img, then totally, this is a misunderstanding of how that works. It usually only looks at things like the borders or depth. The text based prompt that the user provides is otherwise everything.
That said, these kinds of AI are absolutely still biased. If you tell the AI to generate a photo of a professor, it will likely generate an old white dude 90% of the time. The models are very biased by their training data, which often reflects society’s biases (though really more a subset of society that created whatever training data the model used).
Some AI actually does try to counter bias a bit by injecting details to your prompt if you don’t mention them. Eg, if you just say “photo of a professor”, it might randomly change your prompt to “photo of a female professor” or “photo of a black professor”, which I think is a great way to tackle this bias. I’m not sure how widespread this approach is or how effective this prompt manipulation is.
Disappointing but not surprising. The world is full of racial bias, and people don’t do a good job at all addressing this in their training data. If bias is what you’re showing the model, that’s exactly what it’ll learn, too.
Meanwhile every trained model on Civit.ai produces 12/10 Asian women…
Joking aside, what you feed the model is what you get. Model is trained. You train it on white people, it’s going to create white people, you train it on big titty anime girls it’s not going to produce WWII images either.
Then there’s a study cited that claims Dall-e has a bias when producing images of CEO or director as cis-white males. Think of CEOs that you know. Better yet, google them. It’s shit but it’s the world we live in. I think the focus should be on not having so many white privileged people in the real world, not telling AI to discard the data.
Cool let’s just focus on skin color. If you’re white you shouldn’t be in power cause my racism is better than your racism. How about we judge people by their quality of work instead of skin color. I thought that was the whole point.
Also sure, let’s judge male white CEOs on merit. Let’s start with Elon Musk…
Also I can’t understand why there are people here assuming that the only way to “focus on having less white male CEOs” == eliminating them. This shit is done organically. Eliminating wage gap, providing equal opportunities in education etc.
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How did you get from what I wrote to “tearing down” anyone is a bit puzzling. It’s simply about striving to change the status quo and not the AI model representing it. I’m not advocating guillotining Bezos or Musk, hope that’s clear.
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They should just call AIs “confirmation bias amplifiers”.
Stereotype machines
That’s just stupid and shows a lack of understanding of how this all works.
Honestly news stories about dumb ideas not working out don’t really bother me much. Congrats, the plagiarism machine tried to make you look like you fit in to a world that, to the surprise of nobody but idealists, still has a shitload of racial preferences.
Honestly it’s just not being used correctly. I actually believe this is just user error.
These AI image creators rely on the base models they were trained with and more than likely were fed wayyyyy more images of Caucasians than anyone else. You can add weights to what you would rather see in your prompts, so while I’m not experienced with the exact program she used, the basics should be the same.
You usually have 2 sections, the main prompt (positive additions) and a secondary prompt for negatives, things you don’t want to see. An example prompt could be “perfect headshot for linked in using supplied image, ((Asian:1.2))” Negative: ((Caucasian)), blue eyes, blonde, bad eyes, bad face, etc…
If she didn’t have a secondary prompt for negatives I could see this being a bit more difficult, but still there are way better systems to use then. If she didn’t like the results from the one she used instead of jumping to “AI racism!” she could have looked up what other systems exist. Hell, with the model I use with Automatic1111 I have to put Asian in my negatives because it defaults to that often.
Edit: figures I wrote all this then scrolled down and noticed all the comments saying the same thing lol at least we’re on the same page
Why is anyone surprised at this? People are using AI for things it was never designed and optimized for.
Ask AI to generate an image of a basketball player and see what happens.
This isn’t some OMG ThE CoMpUtER Is tHe rAcIsT… this is using historical data and using that data to alter or generation a new image. But our news media will of course try to turn it into some clickbait BS.
Just for fun, I did.
Prompt: basketball player, gym, standing in gym, basketball hoop, sports uniform, facing camera, smiling
Model: base stable diffusion 1.5
That image highlights an important point, these AI produce an infinite number of images for any given prompt. It’s easy to pick one and make conclusions based on just one, like this this article did, but you’re literally ignoring infinity other images produced for the same prompt.
This was the first one I generated. I could keep generating and get different results.
I could add a LoRA and get another infinity worth of different results.
Actually though… is it infinity? Or just a very high number based on the seed?
My intuition says that it’s just a very high number, because there’s a finite variation of initial noise and a finite seed number.
AI turned her into a White Walker
I read this as a “White Wanker”
I read Walter White, i’m going to sleep now.
Or… and Im just spit balling here. Dont ask it to do something you knew probably wouldnt give you something youre happy with and you wont be insulted…
and you wont be insulted…
I’m guessing you didn’t read the article? This was just someone playing with AI generation and sharing a result they found funny.
“My initial reaction upon seeing the result was amusement,” Wang told Insider. “However, I’m glad to see that this has catalyzed a larger conversation around AI bias and who is or isn’t included in this new wave of technology.”
Rage bait to push the ethics in AI narrative
Do you not see an issue?
Nope… because I just tried it as a white male and got back a pure Asian man using the same prompts… and I’ll be damned if I’m not jealous/sad because the man it spit back out was way better looking than me…
