Nathan Labenz: evaluation

Transcript context

…Thank you so much for having me, Nathan. I'm looking forward to this conversation. I think. People like me who live very much in the AI bubble, which is kind of a social bubble, albeit a very online one, and also a day-to-day work bubble, that's just like how I use my computer, I think is kind of diverged pretty significantly from what the rest of the world is doing. I think people like me sort of run a bit of a risk of getting detached from, especially because I work by myself largely these days, kind of run a risk of getting detached from what's going on in the real world at real companies that are actually driving most of the economy and where not everybody has the luxury or the inclination to be a bleeding edge early adopter with all of the, I'd say more ups than downs, certainly, but certainly a mix of ups and downs that come with that. So today's conversation is going to be a really good exercise in grounding and calibrating myself and understanding in the bigger world, what is the current state of play? I would love to start just by getting a little bit of grounding from you, though. In terms of how you understand AI, I think so many AI conversations kind of diverge early or people can sort of talk past each other if they're expecting very different things in the near-term future of AI, and that's not necessarily put on the table beforehand. So what Is your kind of expectation like are you an AGI or short timelines AGI soon person? Do you make analogies to other technology waves? Give us kind of your zoomed out view and then we'll zoom in on the report itself. It's a great question. I think, in many ways, what we're seeing with AI is not unlike what we've seen with previous technologies, in particular when we think about the change management. And that is what we're seeing above all else. This is a human change just as it is a technology change. And as we've seen with every other technology change, we underestimate the human piece. We underestimate resistance. We underestimate fear. Now, AI has this very unique element in that the fear is more visceral. And I think, you know, in large part, as trivial as it might seem, the naming, you know, it comes back to the naming. The fact that we've named this thing artificial intelligence, etymology, it's fundamentally in tension with human intelligence. And I don't think organizations take that seriously enough. The fact that even if the technology works objectively, if employees don't see it as a teammate, if they don't see it in the context of something that can amplify or augment their skill set, well, they're going to either resist or if they're going to symbolically use the technology as opposed to meaningfully using it. And that's what we're seeing. That's what we're seeing on the ground is we're seeing pockets of excellence. We're seeing individuals, teams, and organizations fundamentally transform themselves with this technology in very, very exciting ways. But we're also seeing the vast majority of, in particular, teams and organizations struggle. Struggle to translate the individual productivity gains, which pretty much everyone is getting on some level to real business and team level outcomes.…

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