Nora Belrose

Head of Interpretability @ EleutherAI
177 karmaJoined May 2022Working (0-5 years)


So, I definitely don't have the Solomonoff prior in mind when I talk about simplicity. I'm actively doing research at the moment to better characterize the sense in which neural nets are biased toward "simple" functions, but I would be shocked if it has anything to do with Kolmogorov complexity.

Anticipating the argument that, since we're doing the training, we can shape the goals of the systems - this would certainly be reason for optimism if we had any idea what goals we would see emerge while training superintelligent systems, and had any way of actively steering those goals to our preferred ends.  We don't have either, right now.

What does this even mean? I'm pretty skeptical of the realist attitude toward "goals" that seems to be presupposed in this statement. Goals are just somewhat useful fictions for predicting a system's behavior in some domains. But I think it's a leaky abstraction that will lead you astray if you take it too seriously / apply it out of the domain in which it was designed for.

We clearly can steer AI's behavior really well in the training environment. The question is just whether this generalizes. So it becomes a question of deep learning generalization. I think our current evidence from LLMs strongly suggests they'll generalize pretty well to unseen domains. And as I said in the essay I don't think the whole jailbreaking thing is any evidence for pessimism— it's exactly what you'd expect of aligned human mind uploads in the same situation.

The positive case is just super obvious, it's that we're trying very hard to make these systems aligned, and almost all the data we're dumping into these systems is generated by humans and is therefore dripping with human values and concepts.

I also think we have strong evidence from ML research that ANN generalization is due to symmetries in the parameter-function map which seem generic enough that they would apply mutatis mutandis to human brains, which also have a singular parameter-function map (see e.g. here).

I do in fact think that evidence from evolution suggests that values are strongly contingent on the kinds of selection pressures which produced various species.

Not really sure what you're getting at here/why this is supposed to help your side

I'm not conditioning on the global governance mechanism— I assign nonzero probability mass to the "standard treaty" thing— but I think in fact you would very likely need global governance, so that is the main causal mechanism through which tyranny happens in my model

And you've already agreed that it's implausible that these efforts would lead to tyranny, you think they will just fail.

I think that conditional on the efforts working, the chance of tyranny is quite high (ballpark 30-40%). I don't think they'll work, but if they do, it seems quite bad.

And since I think x-risk from technical AI alignment failure is in the 1-2% range, the risk of tyranny is the dominant effect of "actually enforced global AI pause" in my EV calculation, followed by the extra fast takeoff risks, and then followed by "maybe we get net positive alignment research."

I have now made a clarification at the very top of the post to make it 1000% clear that my opposition is disjunctive, because people repeatedly get confused / misunderstand me on this point.

Please stop saying that mind-space is an "enormously broad space." What does that even mean? How have you established a measure on mind-space that isn't totally arbitrary?

What if concepts and values are convergent when trained on similar data, just like we see convergent evolution in biology?

I think this post is best combined with my post. Together, these posts present a coherent, disjunctive set of arguments against pause.

My opposition is disjunctive!

I both think that if it's possible to stop the building of dangerously large models via international regulation, that would be bad because of tyranny risk, and I also think that we very likely can't use international regulation to stop building these things, so that any local pauses are not going to have their intended effects and will have a lot of unintended net-negative effects.

(Also, reread my piece - I call for action to regulate and stop larger and more dangerous models immediately as a prelude to a global moratorium. I didn't say "wait a while, then impose a pause for a while in a few places.")

This really sounds like you are committing the fallacy I was worried about earlier on. I just don't agree that you will actually get the global moratorium. I am fully aware of what your position is.

In my essay I don't make an assumption that the pause would immediate, because I did read your essay and I saw that you were proposing that we'd need some time to prepare and get multiple countries on board.

I don't see how a delay before a pause changes anything. I still think it's highly unlikely you're going to get sufficient international backing for the pause, so you will either end up doing a pause with an insufficiently large coalition, or you'll back down and do no pause at all.

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