Rob Wiblin

How much human labor is going to safety versus capabilities?

And how much internal AI inference is going to safety versus capabilities?

How much fine tuning effort is going to safety versus capabilities?

And I think they have a much better shot if they're stepping it up over time on some kind of schedule.

Yeah, I think that for now, the biggest thing we need to do is very similar to the biggest thing I think society needs to do for preparing for the intelligence explosion, which is really trying to track where we're at right now in terms of how useful AIs are for the work that we do and the work our grantees do.

I think pushing ourselves to automate ourselves and pushing our grantees to automate themselves and tracking...

You know, how good is AI at the stuff Forethought does?

How good is AI at the stuff that Redwood Research or Apollo does?

How good is AI at the stuff that our policy grantees do?

And I think that that is just like one thing is just like just socializing within ourselves like that.

Hey, like.

it's probably a big deal when the AIs start to get really good at any given good thing we're funding.

And once we start to see signs of life there, we should be prepared to potentially go really big on that.

And like you said earlier, I do think crunch time isn't 100% a special thing.

We absolutely shouldn't be waiting until crunch time to do anything at all.

It's just the prediction that crunch time is the point when a lot of things that were hard to automate before become easier to automate.

So if it turns out, for example, that AI is really good at math research, which I think is plausible, then maybe we should be trying to deliberately shift our technical grant making towards more mathy kinds of technical grant making because that is an area where you can churn a lot more.

That's just so much more tractable.

So I think just having a function that is looking out for these things and is maybe just poking OpenPhil and OpenPhil's grantees

to consider shifting their work towards more easily automatable things like consider repeatedly testing whether their work can be automated is a big thing.