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The bulk of the trained data is from western technology, images, books, television, movies, photography, media. That's where the very real and recognized biases come from. They're the result of a gap in data nothing more.

Look at how DALL-E 2 produces little bears rather than bear sized bears. Because its data doesn't have a lot of context for how large bears are. So you wind up having to say "very large bear" to DALL-E 2.

Are DALL-E 2 bears just a "natural consequence of natural differences"? Or is the model not reflective of reality?



That's true for some things, but the "gender bias for some professions" is likely to just be reflecting reality.


Don't really know that, either. They said they didn't do an empirical analysis on it. For example, it may show a few male nurses for hundreds of prompts or it may show none for thousands. They don't give examples. Hopefully they release a paper showing the biases because that would be an interesting discussion.




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