And overall in I’d say… 7 out of 10 images this is a white woman in a Google search. So the probability is high that the training data also has a bias towards that.
Someone in the original lemmy.nz post said they did the exact same thing, same image, same prompt, and it turned her Indian. So if you have very wide training data the result would be rather “random”. Or you have very narrow training data and the result will always be looking similar.
Grab an app focused on an Asian audience with beauty filters for example and it will turn a white person into an Asian one. But no one complains there that the app is racist.
That’s because the denoising was set low. You can tell that it did actually modify her sweatshirt and the background. The model is just not able to turn her sweatshirt into a blazer, and keep her face relatively similar.
To do this kind of editing, you add noise to the image and get the model to remove the noise, painting in new details. To fully change clothes, you would have to add so much noise that you would lose the original image entirely and end up getting a completely different person, background, pose, everything.
We shouldn’t be surprised that race changed. The model didn’t know what race she was in the first place. It was just told to ‘change the image according to these prompts’ with about this |_| much wiggle room.
It doesn’t really matter that it was her in this image. When you put “professional” into it then you can expect something along these results:
https://www.google.com/search?q=professional+woman
And overall in I’d say… 7 out of 10 images this is a white woman in a Google search. So the probability is high that the training data also has a bias towards that.
Someone in the original lemmy.nz post said they did the exact same thing, same image, same prompt, and it turned her Indian. So if you have very wide training data the result would be rather “random”. Or you have very narrow training data and the result will always be looking similar.
Grab an app focused on an Asian audience with beauty filters for example and it will turn a white person into an Asian one. But no one complains there that the app is racist.
Notice how not a single woman there is wearing a university sweatshirt.
My point still stands. It didn’t touch her clothing to make it more “professional.” Just her race. It screwed up on multiple levels here.
That’s because the denoising was set low. You can tell that it did actually modify her sweatshirt and the background. The model is just not able to turn her sweatshirt into a blazer, and keep her face relatively similar.
To do this kind of editing, you add noise to the image and get the model to remove the noise, painting in new details. To fully change clothes, you would have to add so much noise that you would lose the original image entirely and end up getting a completely different person, background, pose, everything.
We shouldn’t be surprised that race changed. The model didn’t know what race she was in the first place. It was just told to ‘change the image according to these prompts’ with about this |_| much wiggle room.