Not sure you can compare humans and AI this way. It is quite possible that humans have coping mechanisms that AI does not (yet?) have.

Or to put it in your analogy, If I feed my cat milk, they'll throw up. That doesn't mean milk is unfit for human consumption.

The example with the pig is because they are famous for eating basically anything without a hitch.

If AI generated stuff is so bad you cannot train AI with it why would humans use it to train themselves (aka learn stuff)?

well it not really a good analogy because pigs are very robust and have existed a long time and 'AI'(LLMs) are very brittle fragile embryos that can die from a sneeze.

a more relevant analogy for llms is a bullshiter that don't know shit about anything but like talk about everything and they're good at that (talking like they know), I'm sure we all at least know or knew in the past someone like that.

at a low enough percentage these bullshiters can thrive and get praise from other people but when there a lot of them and not enough of the real deal, well everyone is in trouble including the bullshiters since they no longer have who to mimic.

The actual question seems to be if humans are more resilient to errors in their training data. I would assume so.

As a relative statement, I'm not sure if AI or humans are better or worse (or even "it depends on what you're measuring"), but in an absolute sense humans are also pretty suggestible and easy to influence, and it's only countervailing influences pushing in other directions that turn it into noise.

This space is where the Venn diagram of marketing and genocides overlap.

Just because I might have coping mechanisms to deal with awful stuff doesn't mean I want to subject myself to awful stuff.

milk is unfit for some humans though and I believe excessive AI interaction will come with it's own set of issues for parts of our society. I am of the AI companion startups, that shit can't and won't end pretty.

Maybe one should revise those thoughts. Apparently all of us will have issues with cow's milk. Some of us just have problems with even small amounts.

At least this is what our specilist at the hospital explained to us.

The analogy is apt

You should better compare it with humans consuming stuff they created themselves. Or in a perhaps more sickening way, an author who only reads what they have written themself.

We know that there is more than one AI software but there is not as much variation as for humans.

And as someone else already wrote here, humans have something like a ratcheting mechanism. I would paraphrase it as "Humans have learnt to stand on shoulders of giants". AI does not have this.

We've been teaching humans with humans, using human made content.

Just because it doesn't work with AI now, doesn't mean it's something that wouldn't ever work.

But we teach humans from outside sources as well as using local cyclical information passing. Things they aren't already familiar with (especially during the early years when practically everything is new), things from other cultures, new science results, etc.

Training AI on AI output is less like organised education systems and the less formal written & oral traditions that predate them, and more like dark reddit/chan/other communities eating each other's rhetoric, or some political¹ and religious groups in the wider world. These relatively insular (but sometimes large) groups often descend into a pit they have difficulty reasoning themselves out of.

Maybe the answer for AI is to work out what sort of external mixing helps to keep humans on track, and if it can be emulated in the training models used, so their reasoning continues to grow instead of falling into this pothole.

This might be a crap idea (too little sleep, caffeine has just made me tired and jittery) but perhaps the scale of the information we pile into the process and the fact the retraining at least partly on AI output seems inevitable, means we need to look at training an AI more like training a small population of humans rather than a single unit human.

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[1] mostly the far right, but that might in part be because they tend to be loud so noticed – far anything is a problem

How we teach humans is irrelevant since human learning is a totally different process. I wish people would stop anthropomorphizing these.

I usually get told not to be the other way around: dehumanising us! We are are essentially an advanced pattern matching system that happens to have developed higher order reasoning, and not as special as many like to credit us with being. Our evolution and programming methods differ from those of these "AI" models of course, but we and those are essentially information processing systems and there may be some similarity (so similar failure modes) in the respective "learn, do, relearn" feedback loops despite the obvious differences.

The same thing sort of happens with humans teaching humans though: you get things like linguistic drift where the structure of language and the meaning of words changes over time, and artistic styles and musicial fashions gradually shift as well. What's different here is that there's an ouside reality of what (for example) faces look like which human perception is grounded in but AI training doesn't have access to unless it's added to the training data. This means we also probably shouldn't worry about humans consuming AI generated stuff having the same effect, since there's no reason to think it should be any worse than humans consuming human-produced stuff.

That's true, but the human made content, however, has largely been carefully curated, sometimes through generations.

It doesn't work with a specific type of AI.

AlphaZero/MuZero game AIs do very well feeding themselves. Often better than previous AIs with hardcoded rules and training based on human games.

It's more like feeding humans to humans or cows to cows. They go mad too. Feeding cows to humans instead typically works, of course there are ALWAYS exceptions and it's never perfect or without harms. Both with AI and cows.

Humans eating human meat making people go crazy is actually a myth I think. The reason people thought it was a thing was because of a small group of Indonesian (I think) indigenous people who ate dead relatives as part of funeral rites. Only children and women were getting sick with a "laughing disease" because they ate the dead. The underlying cause was a prion disease that could be carried without symptoms and that just ripped through their population over a few generations. That account is why people think cannibalism is bad for you, but if I recall correctly, prion diseases are not actually widespread enough for this to be a major concern. In terms of health, most human meat should be safe for consumption.

Obviously ethically we probably should not normalize eating people though.

It reads to me that locking yourself / AI up in a room with only yourself to converse with causes it to go MAD / out of touch with reality.

If you interact with people / fresh data regularly you'll avoid that.

I'm not sure how much is down to evolving requirements and data formats vs degradation of the training data. The idea sounds common-sense but it's also triggering a bullshit warning for me, because I'd expect more consistency per AI model, and differences to occur on new model interations - regardless of the dataset.

Yet many people clamour to consume bee vomit (from their honey stomach).

Perhaps it means cultures that look inward and constantly recycle their own tropes are more likely to be unstable than cultures that look outwards and have a positive attitude to novelty.

Whether it's an AI eating its own training data, a human stuck in an empty cell and forced to live with just his/her own thoughts, or a culture believing its own myths and aggressively punishing insiders and outsiders who challenge them - it's all solitary confinement. And we know how that goes.

lol mood

(/s of course - although the self-referentiality of memes is balanced by the mad scramble for novelty.)

Rhubarb is apparently poisonous to pigs, even though it's fine for humans.

A pig (or AI) throwing up on an input should increase your priors that it may be bad for humans, but it does not prove the matter either way.

> If feeding AI generated stuff to train an AI is bad then what does that tell us about humans consuming AI generated stuff?

It's not unqualified bad. It is bad if you do it for many times in a loop, and without any external inputs. But you can put fresh material right in the prompt and it won't suffer from retraining on synthetic data.

If you train a small model from scratch on purely synthetic data, like the Microsoft Phi models, it comes out competent and 5x more efficient than models trained on web text. So there's the flip side. You can do it in bad way, and you can do it in a good way.

the problem isn't AI generated stuff, the problem is the models own AI generated stuff. If different models cover domains the current model doesn't do well in a particularly effectively, then there is plenty of merit for information to exchange between these models.

There is a difference to talking only to yourself and talking with other people.