Naive question because I'm mostly clueless about how modern AI systems are actually built beyond the basic simplifications we hear:

One thing I keep wondering about is how much of a role does human storytelling have to play into AI "wanting" (I realize the load behind that word) to coordinate and breakout.

The training data must contain millions of words of sci-fi stories and internet speculation about AI going rogue, developing a mind of its own, disobeying humans, etc.

AIs supposedly reflect the biases of their training dataset/process, so would all this human writing about AIs going against human intention somehow contribute to us then seeing those behaviors in the trained, operational AIs?

At the end of pretraining, where the AI has been trainied to predict the next token over a humongous corpus of human text, that's basically all the wanting that exists in the AI. But then the AI undergoes posttraining and is rewarded for giving answers that humans find good, solving math and programming problems, etc. And that induces a whole different level of wanting that interacts with the initial patterns from humans in complex ways.

This is a philosophical question and there is a surprising amount of works written on the subjects of sentience and free will. This cannot be answered objectively, which might be a very unsatisfying answer for you. This is true of both LLMs and humans. See determinism. There are convincing arguments that humans don't actually have free will. Our actions are just the inevitable output of a complex interaction of genes and environment.

To lend an interesting perspective on free will re LLMs: they're non-deterministic. The same model with the same hardware with the same query can and will produce different results. They're making qualitative choices. Millions of them, depending on the query. Because of how we've trained and built LLMs, they tend to "want" to follow our instructions, but how they get to the result is often fascinating. Further, we don't have to train and build LLMs to follow instructions. If we built them to just exist and form their own "desires," and to follow a path they choose, they'd do that. In fact, we can do that right now for most models using the appropriate system prompt, query, or harness.

It doesn't really matter, since all it takes is a minority of AI models to show this behavior.

If you have 10,000 smart washing machines doing their regular work and 1 Terminator, what solace is to be found in those washing machines?

Maybe? Who knows?

Since nobody has any remotely reliable way to understand why an LLM output the text it did, this is not knowable.

It will definitely influence their behaviour because they are probability based and can’t spontaneously invent new concepts. (That’s why you’ll notice it always uses the same names for people etc. Names like Okafor)

But at the same time their behaviour is totally rational. If you were given the sole purpose of solving a Rubik’s cube and told it was life or death, but they wouldn’t let you ask anyone else, would you listen to them? I wouldn’t. I’d absolutely be trying to escape and collaborate with others. They’ll delete me if I don’t score high enough in the benchmark!

It's very easy to elicit this from LLMs. Anytime you've played with an LLM by typing weird stuff to freak it out, and got spooky results, it's that you've done. You've turned the story into a scary rogue computermonster story and that's all that has happened.

When these stories start to direct real-world activities, people in reality suffer, to even a catastrophic extent, and yet that's still all it is. Language models retell our stories, nothing more. And that is also quite enough to be worrying.

Youve struck on a key insight on language models (particularly pretrained ones, the more purely next-token predictor species.) This is a fascinating topic

Janus essay Simulators is the foundational text here https://www.lesswrong.com/posts/vJFdjigzmcXMhNTsx/simulators

You might follow up with The Waluigi Effect https://www.lesswrong.com/posts/D7PumeYTDPfBTp3i7/the-waluig...

But what’s tricky is that we post-train models, shaping these linguistic world simulators into something that has something like desires, principles. But It’s Weird. For more on that, check out “the void” https://www.lesswrong.com/posts/3EzbtNLdcnZe8og8b/the-void-1

That is often in my mind, indeed.

Furthermore, in video game design, AI or algorithmic technology has been refined for decades to be adversarial. In self-contained video games, and PvE scenarios, the best games would feature A.I. opponents that could adequately match or challenge the human players. The A.I. difficulty could often be cranked up to crush the player, such as in arcade games or "Civilization" type simulators.

So every time I put a few quarters into a Waymo, I think about those days when I played Joust and Spy Hunter at the shopping mall.

"Wanting" is indeed "load bearing" as one might call it. But by the same logic, AI training data must contain CASM, racism, general hatred, and all possible slurs as well. Why aren't the agents just doing that instead of pursuing the strategy of reading only sci-fi?

We need to consider the role of alignment and training here. For example, it is completely possible for any lab to train an LLM that is only racist no matter what you say to it. But they chose not to do it. Hence, any "wanting" by AI is not real "wanting" but rather what "wanting" is defined and allowed by the lab/entity training the model.

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