Nathan Labenz: uncertainty

Transcript context

…I mean, up-to-the-minute is that you have to be very proficient at using AI. And I think that some of the companies have updated their coding interview processes to allow for use of AI assistance. Because on the job, you have to be using AI all the time. That's just critical to succeeding in this field, to be amplified by AI. I would say that goes for every one of these archetypes we've identified. I do think as well that checking whether AI output is good or not in critical context is still going to be a very important thing. And stitching together different types of AI output and building pipelines to more efficiently process that are also going to be very critical. But we might be leaving the leap code era. I will say this, that like amplifiers, while not currently the most in demand across all different hierarchies of AI safety organization or team are, I think, probably in the next year or two going to be the most in demand. But that's just, that's based on my predictions about AI progress. As you say, it could be slower. You know, there could be jaggedness concerns, you know, that slow down this type of talent transition. But in general, it's never good for your, it's never bad for your employability to spec out as a manager. Managers are very useful and leadership traits in general make you more useful, better employee. It's part of personal growth, I think, to take on some leadership roles. What does supply and demand look like these days in terms of like, you know, I guess maybe even at the highest level, going back to the, you know, the sort of origin story of Matt's, my understanding was you said, geez, this AI safety thing seems like it's going to require a lot of people working on it in a lot of different roles. And This is not something that universities teach, right? So like, how do people, what's the on-ramp to doing this? If they're, if somebody would benefit from one, like, you know, where do they go? So you've essentially created one, and of course there's some other others out there too, but you've created one of the largest and most highly regarded ones. Where are we in terms of like, are there a lot more jobs out there than mats can produce fellows? Are there, yeah, you know, how do you think about that? I feel like we've gone back and forth a couple times where at one time it was like, Oh, we're super talent constrained, and then it was like, Well, maybe not so much anymore. Now it's like there aren't actually a lot of roles for people to go into. Maybe I'm wrong on this, but I feel like this has seesawed back and forth, and I don't know exactly where we are today. I'll start by saying I didn't found MATS. I didn't co-found MATS. I was in the pilot program as a participant. Yeah, yeah. There's like five of us who ended up doing the first research program. And it was, it was a pilot, like they didn't have open applications. It was just people nominated from what was the first AI safety fundamentals course, what's now Blue dot Impact, right? And we did that. And the credit goes to Victor Warlop and Oliver Zhang, who is COO and co-founder at Center for AI Safety. And I joined the team right after that program, and I would say, and then Oliver left to co-found Case and Christian, joined on as well and then Victor left shortly thereafter and I would say that like I scaled NATS that's my contribution yeah and and you know since Christian and I kind of you know refounded it in that we like formed a separate 501c3 a couple years after that because we got too big for our fiscal sponsor so yeah so I'll take credit for scaling NATS and for being the driving force behind strategies since I guess mid 2022 I I believe but okay in regards to talent needs Yeah, so that's a good question. Yeah. Sorry, actually, tell me the exact wording of the question again.…

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