“I think if you are a safety researcher, a security researcher in a lab, your most likely route to the Nobel Prize for making AI go well is that you are the one who develops the verification tools that enable a deal.”
80,000 Hours Podcast · October 2026
Asked how optimistic to be about verifying an international AI deal, Milton says the problem is tractable but not solved and still needs a moonshot R&D push. He compares it to the people who built seismology equipment and satellites for nuclear arms control.
Transcript
there are already track twos happening. Yeah. I think those kinds of efforts are what's needed. And I think this is to mostly academics is the first landing point for these kinds of things. But I think it would be valuable to think about how to make it most legible to Chinese counterparts. But
…the prototype and you describe that this works, should I be thinking, oh yeah, this is something which we are technically on track to achieve or is this like still miles away? Like I don't have the kind of expertise to know to know this. What should I like? What should my position be? Yeah,
…victory. And right now, the people who work on this could completely change the field. A marginal person here is going to really accelerate progress. The thing that I'd be most excited about are significant lab efforts happening. The thing that would most help me sleep at night is if the major AI developers had dozen person teams who are focused on making sure that verifiable deals can happen. I think if you are a safety researcher, a security researcher in a lab, your most likely route to the Nobel Prize for making AI go well is that you are the one who develops the verification tools that enable a deal. There was someone who pioneered seismology equipment for nuclear deals. There were people who made these satellites. The team who are going to actually make international deals and AI verifiable are yet not yet defined. And I think sometimes we should find this worrying. We should also find it exciting that you can have a real counterfactual impact on the outcome of AI by putting your effort…
why does it matter so much that it's people at the labs that are doing it just because they understand everything about how the infrastructure works? Yeah, so I think it
is important that stuff happens outside the labs as well. And I'm excited about the work we're doing, excited about the work that other teams are doing. But inside the lab, you have a few advantages. You have access to the frontier. You know how fast the frontier of AI is going. You can get…
Yeah, okay, that's very convincing. And the final thing I really want to wrap my head around here also is like, how true is it that so many of these theories to victory do route through verification mechanisms? You know, you mentioned, okay, if export controls are comprehensive enough and expansive…
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