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.

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.
  
  A company using a photo to choose a candidate is really concerning regardless if they use AI to do it.
  
  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.
- It still perfectly and visibly demonstrates the big point of criticism in AI: The tendencies the the training material inhibits.
- 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.
- This is like a demonstration of lack of self awareness
- Yup
- 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.
- 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.
  
  They aren't justifying anything, they literally said it was about the training data.

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.
- Yeah there are a lot of cases of claims being made of AI “bias” which is in fact just a reflection of the real world (from which it was trained). Forcing AI to fake equal representation is not fixing a damn thing in the real world.
- I recall the being a study of the typical CEO. 6+ feet tall, white males.
  But yeah, the output she was getting really depends heavily on the data that whatever model she used was trained on. For someone who is a computer science major, I'm surprised she simply cried "racial bias" rather than investigating the why, and how to get the desired results. Like cranking down the denoising strength.
  To me it just seems like she tried messing around with those easy to use, baity websites without really understanding the technology.
- 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.
- 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.

They should just call AIs “confirmation bias amplifiers”.
- AI learns what is in the data.
  
  The AI we have isn't "learning". They are pre-trained.
- Stereotype machines
  
  Humans will identify sterotypes in AI generated materials that match the dataset.
  Assume the dataset will grow and eventually mimic reality.
  How will the law handle discrimination based on data supported sterotypes?
  
  That's just stupid and shows a lack of understanding of how this all works.

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.
- I've taken a look at the website for the one she used and it looks like a cheap crap toy. It's free, which is the first clue that it's not going to be great.
  Not a million miles from the old "photo improvement" things that just run a bunch of simple filters and make over-processed HDR crap.

Garbage in = Garbage out
ML training data sets are only as good as their data, and almost all data is inherently flawed. Biases are just more pronounced in these models because they scale the bias with the size of the model, becoming more and more noticeable.

Can we talk about how a lot of these AI-generated faces have goat pupils? That's some major bias that is often swept under the rug. An AI that thinks only goats can be professionals could cause huge disadvantages for human applicants.

These biases have always existed in the training data used for ML models (society and all that influencing the data we collect and the inherent biases that are latent within), but it’s definitely interesting that generative models now make these biases much much more visible (figuratively and literally with image models) to the lay person
- But they know the AI's have these biases, at least now, shouldn't they be able to code them out or lessen them? Or would that just create more problems?
  Sorry, I'm no programer so I have no idea if thats even possible or not. Just sounds possible in my head.
  
  You don't really program them, they learn from the data provided. If say you want a model that generates faces, and you provide it with say, 500 faces, 470 of which are of black women, when you ask it to generate a face, it'll most likely generate a face of a black woman.
  The models are essentially maps of probability, you give it a prompt, and ask it what the most likely output is given said prompt.
  If she had used a model trained to generate pornography, it would've likely given her something more pornographic, if not outright explicit.
  You've also kind of touched on a point of problem with large language models; they're not programmed, but rather prompted.
  When it comes to Bing Chat, Chat GPT and others, they have additional AI agents sitting alongside them to help filter/mark out problematic content both provided by the user, as well as possible problematic content the LLM itself generates. Like this prompt, the model marked my content as problematic and the bot gives me a canned response, "Hi, I'm bing. Sorry, can't help you with this. Have a nice day. :)"
  These filters are very crude, but are necessary because of problems inherent in the source data the model was trained on. See, if you crawl the internet for data to train it on, you're bound to bump into all sorts of good information; Wikipedia articles, Q&A forums, recipe blogs, personal blogs, fanfiction sites, etc. Enough of this data will give you a well rounded model capable of generating believable content across a wide range of topics. However, you can't feasibly filter the entire internet, among all of this you'll find hate speech, you'll find blogs run by neo nazis and conspiracy theorists, you'll find blogs where people talk about their depression, suicide notes, misogyny, racism, and all sorts of depressing, disgusting, evil, and dark aspects of humanity.
  Thus there's no code you can change to fix racism.
  
  if (bot.response == racist) { dont(); }
  But rather simple measures that read the user/agent interaction, filtering it for possible bad words, or likely using another AI model to gauge the probability of an interaction being negative,
  
  if (interaction.weightedResult < negative) { return "I'm sorry, but I can't help you with this at the moment. I'm still learning though. Try asking me something else instead! 😊"; }
  As an aside, if she'd prompted "professional Asian woman" it likely would've done a better job. Depending on how much "creative license" she gives the model though, it still won't give her her own face back. I get the idea of what she's trying to do, and there's certainly ways of acheiving it, but she likely wasn't using a product/model weighted to do specifically the thing she was asking to do.
  Edit
  Just as a test, because I myself got curious; I had Stable Diffusion generate 20 images given the prompt
  professional person dressed in business attire, smiling
  20 sampling steps, using DPM++ 2M SDE Karras, and the v1-5-pruned-emaonly Stable Diffusion model.
  Here's the result
  I changed the prompt to
  professional person dressed in business attire, smiling, [diverse, diversity]
  And here is the result
  The models can generate non-white men, but it is in a way just a reflection of our society. White men are the default. Likewise if you prompt it for "loving couple" there'll be so many images of straight couples. But don't just take my word for it, here's an example.
  
  That's not how it works. You don't just "program out the biases" you have to retain the model with more inclusive training data.
  
  If you can code it, it isn't really AI.
  AI is able to make the connections when given the data by itself. The problem is that the data required is usually enormous, so the quantity of data is more valued than the quality.
  
  Shouldn't they be able to code them out?
  You can't "code them out" because AI isn't using a simple script like traditional software. They are giant nested statistical models that learn from data. It learns to read the data it was trained on. It learns to understand images that it was trained on, and how they relate to text. You can't tell it "in this situation, don't consider race" because the situation itself is not coded anywhere. It's just learned behaviors from the training data.
  Shouldn't they be able to lessen them?
  For this one the answer is YES. And they DO lessen them as much as they can. But they're training on data scraped from many sources. You can try to curate the data to remove racism/sexism, but there's no easy way to remove bias from data that is so open ended. There is no way to do this in an automated way besides using an AI model, and for that, you need to already have a model that understands race/gender/etc bias, which doesn't really exist. You can have humans go through the data to try to remove bias, but that introduces a ton of problems as well. Many humans would disagree on what is biased. And human labelers also have a shockingly high error rate. People are flat out bad at repetitive tasks.
  And even that only covers data that actively contains bigotry. In most of these generative AI cases, the real issue is just a lack of data or imbalanced data from the internet. For this specific article, the user asked to make a photo look professional. Training data where photos were clearly a professional setting probably came from sites like LinkedIn, which had a disproportionate number of white users. These models also have a better understanding of English than other languages because there is so much more training data available in English. So asian professional sites may exist in the training data, but the model didn't understand the language as well, so it's not as confident about professional images of Asians.
  So you can address this by curating the training data. But this is just ONE of THOUSANDS and THOUSANDS of biases, and it's not possible to control all of them in the data. Often if you try to correct one bias, it accidentally causes the model to perform even worse on other biases.
  They do their best. But ultimately these are statistical models that reflect the existing data on the internet. As long as the internet contains bias, so will AI
  
  It’s possible sure. In order to train these image AIs you essentially feed them a massive amount of pictures as “training data.” These biases happen because more often than not the training data used is mostly pictures of white people. This might be due to racial bias of the creators, or a more CRT explanation where they only had the rights to pictures of mostly white people. Either way, the fix is to train the AI on more diverse faces.
  
  There are LoRAs available (hundreds, maybe thousands) to tweak the base model so you can generate exactly what you want. So, problem solved for quite a while now.

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.

User error, be more specific

She asked the AI to make her photo more like what society stereotypes as professional, and it made her photo more like what society stereotypes as professional.

Hm. Probably trained on more white people than Asians shrug

Why is anyone surprised at this? People are using AI for things it was never designed and optimized for.
- This was kind of my thought, this is a rather complex task that I'm not clear what even a "good" outcome would look like especially given the first photo was a pretty good photo. Should it just color correct and sharpen it? Should it change the background? Should it position your head?
  I'm curious what it would do if you just fed it already good professional photos of white people, would it just spit back the same image?
  Like there has to be a cap on how much it will change so it still looks like you, in which case I assume you'd need to feed it multiple images to get a good result.
- because most people don't understand ai

Garbage post

White = professional?!
Blonde hair = Super Saiyan
- Hotel = Trivago

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"

This is why you get a human to take professional shots for you.

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.
  
  So who is going to go cry that this image is racist??

Media: "I don't understand technology" even though writing about the technology multiple times.
AIs are completely based on the training data that they'll use. If they only loaded professional headshots of Asian people, a white person would turn Asian if added.
Besides which you run it multiple times, and choose the one you want, I'm sure if you did that, it'd change her eye color multiple times.
Really blame the AI, not AI in general. Or blame the media for making clickbait articles in the first place.

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

Interestingly, many stable diffusion models are trained on pictures of Asian people and thus often generate people that look more or less Asian if there's no specific input or tuning otherwise. It's all in the training data and tuning.
See for example here for reference.
- not just asian people, mostly just pictures of kpop/cpop supermodels (who often have had cosmetic surgery)
- many stable diffusion models are trained on pictures of Asian people
  Yeah, but what if we want want the people wearing clothes in the final results. /s

AI turned her into a White Walker
- I read this as a "White Wanker"
  
  I read Walter White, i'm going to sleep now.

This is just dumb rage-bait. At worst this shows a bias in training data, probably because the AI was developed in a majority white country that used images of majority white people to train it.
And likely its not even that. The AI has no concept of race, so doesnt know to make white people white and asian people asian, so would also be likely to do the reverse.
- This is a real issue for non-white people. Sure in this instance it’s trivial and doesn’t have any major impact - yet.
  It again highlights the necessity to diversify your training data but time and time again we have this white bias issue.
  If you don’t think that paints a picture of a bleaker future when AI tools are more advanced and widespread yet STILL operating on biases, you’re being naive.
  
  LoRAs already exist to fix this issue

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…
  
  Which model did they use, and what was it specialized for? Was professional headshots what it was designed for? Those are the issues to be mad at. Not something as ambiguous as "AI".

It reminds me of Google back in the day (probably early 2010s). If you searched for White Women, it returned professional and respectable images. But if you searched for Black Women, it returned explicit images.
Machine learning algorithms are like sponges and learn from existing social biases.

So? There are white people in the world. Ten bucks says she tuned it to make her look white for the clicks. I've seen this in person several times at my local college. People die for attention, and shit like this is an easy-in.

AI Kanye

That's funny!

I wouldn't say "closer to Caucasian". She straight turned white
- These are the results you get when your training data consists of nothing but a loop of this song in reverse.

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.

Like what some has already said here: it's a commentary of what Anglo-centric societies view as "professional" at the time the model is trained. Why Anglo-centric? By virtue that the US is the center of internet activity.

Sigh...
It's not racial bias, it works from a limited dataset and what it understands a "professional headshot" even is.
Seems like some ragebait to me.
- It isn't intended to be racial bias, it just happens to be racial bias.
- While I agree with the dataset point I will say that I don’t believe this to be rage bait. It’s just pointing out and saying exactly what something did. That said AI isn’t meant for taking a picture and asking it to do something more with it for now. As well though to AI when it has tags like “professional headshot” in America and as an English input it will most likely pull from data that’s built around Hollywood types which will be a completely lopsided amount of blondes with blue eyes. It’s really important to me though that people read stuff like this article, and understand how we end up with some “news” outlets saying things like “someone said computers are racist” without understanding the context such as this. Outputs are only as good as the inputs.

Garbage in, garbage out! This AI is woefully badly trained.

10 Ways AI is RACIST! Click here to see more RACIST AIs DISRESPECTING RACE!!1!!1

How can bias amplification be controlled in these models? Surely it’s built in?

Who is AI?

Awpresshawn and shit

- sorry to rant at you, but imo this whole "children aren't born racist" stuff is bs. racism is genetically baked into us and it makes perfect sense evolution wise. If we pretend that humans are nice and lovely by nature, and that racism is some evil force from outer space, we will never overcome racism.

A.I. - Aryan Intelligence.

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."

I asked a taxi driver in Bollywood to take me to the home of someone famous. He took me to an Indian person's house. Does he think all famous people are Indian?

Edit