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ZorbaTHut  1yr ago (text post)   35194 thread views

Culture War Roundup for the week of September 19, 2022

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If my model generates pictures of people from an even ethnic spectrum, I do not believe I am discriminating against anyone. It's not the Harvard auditions, and this isn't actual people I'm failing to generate or generating excessively.

By this logic, then no model is discriminating against anyone. If a model only ever returns white women for "good person" and black men for "bad person," then that's not discriminating against anyone since it's not the Harvard auditions, and this isn't actual people you're failing to generate or generating excessively. Great, looks like we can associate any race with any quality we want in our model and not worry about discriminating against anyone!

If I'm a designer using a generative AI to fill a world of my making, I do not care for "accurate" demographic representation being baked in the model.

Indeed, and notably no one seems to have any problem with such models existing. There's room for multiple types of generative AI models in this world, including ones that have uniform distributions, desired distributions, best-attempt-at-accurate distributions, or really any other arbitrary distributions of demographics.

If a model only ever returns white women for "good person" and black men for "bad person," then that's not discriminating against anyone since it's not the Harvard auditions, and this isn't actual people you're failing to generate or generating excessively.

Do you really think your example is as egregious as generating perfectly uniform selections for both "good person" and "bad person" (or "criminal" and "Harvard student", for that matter)?

Do you really think your example is as egregious as generating perfectly uniform selections for both "good person" and "bad person" (or "criminal" and "Harvard student", for that matter)?

What does being egregious have to do with this in any way? As you wrote, either way, "it's not the Harvard auditions, and this isn't actual people I'm failing to generate or generating excessively." Given that the reason that perfectly uniform selections isn't discrimination has literally nothing to do with the type of distribution and everything to do with the fact that these are generated images rather than actual people, we can change the distribution to anything we want (including my example of encoding "good person" with "white woman" and "bad person" with "black man") and still land at the same result of "no discrimination is taking place."

What does being egregious have to do with this in any way?

Pretty clear to me that the analogy you deployed was deliberately absurd.

But anyway, provided that you clearly label your Pro-White-Women, Anti-Black-Men model as such, go ahead.

Pretty clear to me that the analogy you deployed was deliberately absurd.

Yes, that was the point of the analogy. Your own reasoning requires that the absurd model I described as "not discriminating against anyone." If you want to describe your theoretical uniform distribution model as "not discriminating against anyone" but my absurd one as "discriminating against someone," you can't have to rely on something other than "this isn't actual people I'm failing to generate or generating excessively" to justify your theoretical uniform distribution model.

But anyway, provided that you clearly label your Pro-White-Women, Anti-Black-Men model as such, go ahead.

Well, I don't need your permission to deploy such a model, and I wasn't looking for it from you or anyone else. I was merely demonstrating one necessary conclusion from your line of reasoning, by describing a theoretical and intentionally absurd model.

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