“I don't think that alignment is an engineering problem. I think it's a science problem. It's not that we haven't got the resources or we're not trying hard enough. We don't know how. That's what the problem is with alignment.”

I was a translator embedded in our safety team, and my primary responsibility was the technical documentation that we publish, the reports that we publish about why we believe that our deployments are safe. And I don't think that we or our peers, really anyone in the industry, is being safe enough. I think OpenAI Insider its peers are now producing a technology that is more capable and poses more risk than what was being made even six months ago. And I'm not a scientist. I'm a writer. What I know is what the execution environment looks like for our safety work. And we're operating, and I believe the industry is operating, like a startup still, more so than makes sense. Not maybe completely like a brand new startup, but we're too close to that end of the spectrum for really dangerous systems that could pose risks. You know, loss of control is one example. Risks that if that did happen, we're talking about a harm that's much larger, for example, than a single nuclear power station melting down. And the internal controls and safety and redundancies are just nowhere near what the world expects for a nuclear power facility. Now, some of this is known, right? OpenAI has publicly reported on safety problems, obviously Hugging Face, but also other ones, including more recently. And Anthropic, by the way, also has reported on including an instance in which their safeguards were accidentally misconfigured. So I think people do have some evidence already externally that things are not as they ought to be. But I also think that if you were watching from the outside, you might imagine that we have a more robust safety setup than we actually do.

So I think there are a couple levels worth trying to take this conversation in. And I want to maybe map them out here before we get into them. So one level is something you're pointing towards here, which is, are these companies set up? Do they have the structures, the redundancies? Are they encircled in the regulations and the incentives to act carefully, safely, to resist kind of market pressure to do? Something too fast. That's a, I think in the language of this debate, a question of organizational excellence and engineering. Then there's this question of what is the technology and do we even know how to make it safe at a high level of engineering excellence, which is a somewhat related but actually separate question. And then there's a question of like, what is the right metaphor? Is it nuclear power or something like that? And I think I want to do all of these. I want to interject

maybe start there for a minute. When you say that at this point, and particularly over the last six months, what is being built is really dangerous, that we're dealing with things where a loss of control or some other catastrophe could be worse than a nuclear meltdown. I want to understand what it is you saw that got you to that point. So tell me a bit about how you came to work at OpenAI.

I joined in May of 2023, the day after Sam first testified in the Senate.

Some months after ChatGPT first into the world.