Rob Wiblin

So I guess we have a lot of people in the AI industry and philanthropists as well in the audience.

Do you want to give them a pitch for potentially working at Law Zero?

I don't know whether there's other organizations that have similar ideas, but I guess also potentially for pitching and financially.

If you saw a significant increase in interest in the project among the most capable people, the best people in AI, and you had an influx of financing, what sort of stuff might you be able to accomplish over the next three, six, nine, 12 months?

Reading the output from the main companies, I get the impression of just an absolutely frenetic pace and an incredible degree of focus on just advancing the frontier models.

I'm slightly concerned that even if you did have very good experimental results that came out in the near future, I'm not sure they would even have the capacity to pay attention and to reflect on how that could affect their plans or how maybe the kind of models that you're training could be a useful additional monitor.

Is there anything you can do about that?

I mean, do you share that concern?

Yeah, my impression is that the people at the companies are both pretty happy and impressed with their mundane alignment techniques, how well they're going, but also appreciate that, in a sense, they're losing control or they're losing the safety guarantees that they used to have because the models are going to be much more capable of potentially outsmarting them and are much more evaluation aware and so on.

And so in a way, they're both self-satisfied with what they've done and also scared, I think, of what is to come.

And that, I guess, starts to create an opening for you.

So it seems like it would be good for the Scientist AI proposal, and I guess for our chances in general, if we could make things go a little bit slower, especially, I guess, if we didn't leap into fully automating AI R&D at the very first opportunity, which is kind of what it seems like we're on track to do.

What are your main requests, I guess, for governments and for companies in terms of buying us a bit of extra time to assess how these things are going and consider alternatives?

So for companies,

I think you must have just not been paying attention to think that, but yeah, I guess many people aren't.

I mean, I guess, so there's lots of examples of this kind of thing that would convince you and me, but I suppose people will dismiss them saying, well, you can see how we accidentally, you can see it maybe that it was a misunderstanding on the model's part.

It thought that we wanted X when we wanted Y, or you can see how we did the training mistakenly.

So it induced this goal that we didn't want it to have, or I suppose they might just deny it outright in some cases.

But are there any experiments you think that we could do that would be much harder for people to dismiss, even if they're coming from a skeptical starting point?

Yeah.