It's really the paperclip maximizer argument again. "Superintelligent AI" will supposedly change the world, but will lack enough common sense to understand a simple instruction with ethical constraint. Same here, the crappy AI content will somehow take over the world, despite the fact that most humans can actually mostly recognize original content from a generated one.
The art that humans created doesn't replace nature, just like tons of kitsch don't pose a problem for new artists. In the same way, crappy AI content is not gonna replace good content, just augment it, and any decent AI (which has good enough common sense to be called "intelligent") will be able to tell the difference. Nobody's gonna care about crappy content in a few years, we are all gonna just throw it away, and this process happens continuously.
In theory. In reality what you get is the Climate Change "debate".
(1) accuracy or fit for purpose, not natural, is the issue.
(2) evaluation, not having a discussion, is the issue.
(3) LLMs can definitely do evaluation, and probably can also have discussions and decide to, if given a proper prompt and access to ground truth in the first case, and if also used in a properly constructed agent framework, for the second.
(4) if you did all that, and used LLM decisions and not human decisions to guide retraining, I suspect with current LLMs you’d actually have made the problem worse not better, because you’d reduce the influence of higher-capacity and more diverse humans on the training cycle and increase the influence of less diverse, lower capacity LLMs.
They do, but the problem is poorly stated. The problen isn't “If your models are influencing the generation of data that they are later retrained on”, its “If output produced by your models with inadequate filtering for quality/accuracy is dominating the data that they are later retrained on.”
Humans definitely experience the same problem: we see it when societies become closed, inward-looking, and locked into models of information filtering that don't involve accuracy or fitness for purpose other than confirming an in-groups priors. There are some examoles in stagnation of large societies, but probably the clearest examples are cults that socially isolate their membership and degrade into increasingly bizarre behaviors terminating in mass suicide, murder/suicides, etc.
LLM’s experience self-reinforcing degradation more acutely because they are individually less capable than humans and they are less diverse.