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Notes -
I think there are a couple uses of the word "discriminatory".
First, yeah, defining a training subset is a decision to favor one group over another. Making the historically-accurate-armor AI is going to disappoint the fantasy-art users. An AI that makes everyone [insert feature here] is going to disappoint the people wanting it to be realistic. And of course there's nothing stopping the dataset curator from excluding all members of a race, or all Christians, or all women with realistic proportions; doing so would be obviously discriminatory.
On the other hand, a sentencing or profiling AI is categorically different. When a predictive machine discriminates, it is causing a disparate impact on actual people rather than on the collective. I'm struggling to find the right words...it is the difference between perpetuating an injustice vs. causing it, a sort of active vs. passive harm.
(I think there's also an argument to be made that the ill-trained AI is more obvious that an AI trained well on an evil world, and thus more compatible with exit-rights liberalism, but I'm not so confident in that...)
The OP argued that predictive AI was a zero-sum game where only reverse racism could compensate for the inbuilt discrimination. I think...there's some degree to which that is correct? It's extending that conclusion to generative AI that strikes me as wrong. I believe generative discrimination is an easier problem than predictive because it's a lesser problem. Maybe you can't make a "world that could be" generative AI without excluding anyone, but I'm reasonably sure you can make one without actively harming any individuals.
Anyway, thanks for pressing me on this. It's an interesting philosophical topic.
OK, so it sounds like based on this post that when you wrote:
about a theoretical generative AI model based around a world that could be (instead of the world as is), you were making a general statement about how no generative AI model could possibly discriminate against someone. Which seems like a strange thing to say about 1 specific type of generative AI model (i.e. based on a world that could be) when discussing 2 different theoretical types of models that are both generative (i.e. the other one being based on the world as it is), but technically true, I suppose.
More or less, though I wouldn't frame it as an absolute, if only because that's inviting extreme counterexamples.
The original article was writing about unimpressive debiasing in corporate generative models. When sulla responded with the assertion that this is unavoidable in a bleeding-edge AI, I thought it appropriate to point out that his examples were all predictive rather than generative. I think that really undermines his equation of discrimination with the "true but verboten." A generative AI could be wildly discriminatory, in the loose sense, without ever discriminating in the narrow, personal sense, and it is the latter which is a one-way ticket to a media circus.
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