Rob Wiblin

And that was that was a really interesting experience.

And I discovered I like there were elements of it I really liked.

But there were also there's just like something about the way you made grants where you just really couldn't.

dig into any particular thing very much, especially in the context of something like the FTX emergency, you just had to be like making these decisions really quickly.

But, but I felt like, um, I had thoughts about how grant making could be done with like more, at least in the technical AI safety space could be done with like more inside view justification for the like research directions we were funding than we had previously.

Um, and so in.

Early, mid-2023, I sort of tried to go down that path.

Yeah.

So I was focused on grants to technical researchers.

So these are often often academics, sometimes safety nonprofits.

And they would be working on, you know, often interpretability or some kind of adversarial robustness.

And they seemed like, you know, reasonable research bets.

But I felt kind of unsatisfied.

And I think this is going to be like a theme of like me and my career.

I felt kind of unsatisfied about how.

the theory of change hadn't been really ground out and spelled out as to how this type of interpretability research would lead to this type of technique or ability we have, and then that could fit into a plan to prevent AI takeover in this way, or similarly for any of the other research streams we were funding.

And this had been actually the big thing that

deterred me from like getting involved in OpenPhil's technical AI safety grant making for a long time, even though I was one of the few people on staff that thought about technical AI safety outside of that team.

It was because like in the end, it seemed like most grant decisions in this 2015 to 2022 period turned on like heuristics about this person's a cool researcher and they care about AI safety, which is like totally reasonable.

But I think I wanted to like