> 1. I am saying that the claim "it is easy to find goals that are extinction-level bad" with regards to the AI tech that we can see today is incorrect. LLMs can understand context, and seem to generally understand that when you give them a goal of e.g. "increase revenue," that also includes various sub-goals like "don't kill everyone" that are implicit and don't need stating. Scaling LLMs to be smarter, to me, does not seem like it would reduce their ability to implicitly understand sub-goals like that.

I agree with both of these claims (A) it is hard to find goals that are extinction-level bad for current SOTA LLMs, and (B) current SOTA LLMs understand at least some important context around the requests made to them.

But I'm also skeptical that they understand _all_ of the important context around requests made to them. Do you believe that they understand _all_ of the important context? If so, why?

> P2 states that "superhuman" AI will be uncontrollable — once again, I do not think that is obvious, and depends on your definition of superhuman. Does "superhuman" mean dramatically better at every mental task, e.g. a human compared to a slug? Does it mean "average at most tasks, but much better at a few?" Well, then it depends what few tasks it's better at.

I take "superhuman" to mean dramatically better than humans at every mental task.

> Similarly, it anthropomorphizes these systems and assumes they want to "escape" or not be controlled; it is not obvious that a superhumanly-intelligent system will "want" anything; Stockfish is superhuman at chess, but does not "want" to escape or do anything at all: it simply analyzes and predicts the best next chess move. The idea of "desire" on the part of the programs is a large unstated assumption that I think does not necessarily hold.

Would you have less of a problem with this premise if instead it talked about "Superhuman AI agents"? I agree that some systems seem more like oracles rather than agents, that is, they just answer questions rather than pursuing goals in the world.

Consider self-driving cars, regardless of whether or not self-driving cars 'really want' to avoid hitting pedestrians, they do in fact avoid hitting pedestrians. And then P2 is roughly asserting, regardless of whether or not a superhuman AI agent 'really wants' to escape control by humans, it will in fact not be controllable by humans.

> Finally, P3 asserts that AI will be "misaligned by default" and that "misaligned" means that it will produce extinction or extinction-level results, which to me feels like a very large assumption. How much misalignment is required for extinction? Yud has previously made very off-base claims on this, e.g. believing that instruction-following would mean that an AI would kill your grandmother when tasked with getting a strawberry (if your grandmother had a strawberry), whereas current tech can already implicitly understand your various unstated goals in strawberry-fetching like "don't kill grandma." The idea that any degree of "misalignment" will be so destructive that it would cause extinction-level events is a) a stretch to me, and b) not supported by the evidence we have today.

I'm often unsure whether you are making claims about all future AI systems or just future LLMs.

> In fact a pretty simple thought experiment in the converse is: a superhumanly-intelligent system that is misaligned on many important values, but is aligned on creating AI that aligns with human values, might help produce more-intelligent and better-aligned systems that would filter out the misaligned goals — so even a fair degree of misalignment doesn't seem obviously extinction-creating.

Maybe. Or the misaligned system will just disinterestedly and indirectly kill everyone by repurposing the Earth's surface into a giant lab and factory for making the aligned AI.

> Furthermore, it is not obvious that we will produce misaligned AI by default. If we're training AI by giving it large corpuses of human text (or images, etc), and evaluating success by the model producing human-like output that matches the corpus, that... is already a form of an alignment process: how well does the model align to human thought and values in the training corpus?

I believe it is likely that this process does some small amount of alignment work. But I would still expect the system to be mostly confused about what humans want.

Is this roughly the argument that you are making?

(P1) Current SOTA LLMs are good at understanding implicit context.
(P2) A system must be extremely misaligned in order to cause a catastrophe.
(C) So, it will be easy to sufficiently align future more powerful LLMs.