this post was submitted on 04 Nov 2023
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Some image generators produce more problematic stereotypes than others, but all fail at diversity (algorithmwatch.org)
submitted 1 year ago by JRepin@lemmy.ml to c/technology@lemmy.ml
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Automated image generators are often accused of spreading harmful stereotypes, but studies usually only look at MidJourney. Other tools make serious efforts to increase diversity in their output, but effective remedies remain elusive.

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[–] Terces@lemmy.world 2 points 1 year ago

I may have oversimplified my statement. Of course an objective description of reality is impossible. A curse on all social sciences and statistics.

My post was more a showerthought...even if the data is incomplete, whatever THAT data implies will also be the stereotype the AI will learn. Misrepresentation of minorities in sample data is absolutely nothing new. But even if the data WAS complete, it would probably still be very biased. I think we often don't notice structural discrimination and AI would simply reproduce those and confront us with it. In that sense I think it is a very interesting way to get a sort of 'outside look' at our own society and that is something that's very useful.