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naraburns  nihil supernum  1yr ago (text post)   16082 thread views

Culture War Roundup for the week of December 19, 2022

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Requiring that people hold valid licenses for their entire training sets isn't even enforceable enough to do anything

Why do we think this is unenforceable? Unappetizing because it hits AI hard, sure, but surely not unenforceable.

NAI, who suffered a high-profile hack & went on to watch their model be used as the basis for a thousand merges and derivatives, recently posted an infographic about how you can use their (unique, supposedly) style tokens to identify if a model is derived from theirs, and even the rough degree to which it was mixed in.

Tokens (even unused tokens!) are identifiable components of the model file structure, and (probably?) have to be. Combinations of tokens (which almost all of the NAI style tokens are) would be harder if you didn't know them, but they're still testable in seconds on consumer GPU or minutes on CPU. But very few people are interested in controlling tokens, and while NAI isn't the only group, there's not a ton of artists there.

Artists want to enforce on the media-level output, which is... more complicated, at best.

Well how would you enforce it?

Any model without an associated public data set is presumed guilty.

ban proprietary ML

I mean I guess that works, and I don't even have objections to that. But I don't think presumed guilt is legally tractable.

Models don't have rights.

The people who make them do. The civil forfeiture argument was never convincing to anybody. I don't see how this is any different.

My hypothetical model is speech which is free by default and you need to prove it's illegal in court before you can censor me or you're denying me due process.

Otherwise, enjoy the crypto wars again, I'm sure we can find a way to make weights fit on a t shirt.

A completed model doesn't really have stored information about the datasets used to generate it in any accessible manner (not least of all because it could easily outsize the model by several orders of magnitude). Someone could easily say a model was generated on dataset X and instead use dataset X + dataset Y, and proving otherwise would be very hard at current understanding of how models work.

And there's a variety of complications downstream from that -- if the original model X was trained on purely legal data, and someone brings a tuned model that they say was only trained on a subselection from rights-compliant source, for example.

(And then there's the downstream economic forces: if half of the image hosts require you to give up whatever AI/ML rights for submission, then this goes wonky places even if most hardcore artists don't use them.)

Right the only way to make this work would be nothing up your sleeve training-wise. You'd provide your training set and if your model can't replicate, bam, you're busted.

You'd need to disclose not only your training set, and model, but also the training environment and initial configuration. And then someone would need to spend hundreds to hundreds of thousands to do the actual training.

That's an interestingly roundabout way of mass-banning, but it runs into the same problem as just trying to ban the tech, in that a lot of people are just going to smuggle AI-gen outputs as 'naturally'-generated.

You'd need to disclose not only your training set, and model, but also the training environment and initial configuration

Done and done.

That's an interestingly roundabout way of mass-banning

I'm ok with this.

a lot of people are just going to smuggle AI-gen outputs as 'naturally'-generated.

Which is going to happen anyway, in fact it already is happening.

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