Toby Ord

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1,415 appearances 1 recordings 1 series first heard Aug 2026 last heard 6 Aug

Toby Ord’s voice in public audio — every appearance, attributed to the second.

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80,000 Hours Podcast · #250 – Toby Ord on where AGI timelines go wrong · 6 Aug 2026 podcast

While the experiment's going off the rails, quickly pull the emergency stop button or something like that.

Or to learn other aspects about how it's progressing and to then kind of be attentive to them.

Maybe if you're planting a tree in your garden that you've never planted before, if you can go out every day and check on it and kind of see that its leaves are wilting a little bit and kind of adjust and so on, it's a lot easier to make that tree survive than if you had to build a machine that will appropriately measure out water for it every day or something and just turn that machine on and hope the whole thing works.

Yeah, so now there's a few different kinds of risks that come from this.

I think the fundamental thing is that everything's going a lot faster.

That's where a lot of the risk would come from.

So ultimately, speed itself is not quite the risk, although if it did bring forward some apocalypse by a few years, then all our lives would be shortened by a few years, which would actually be a pretty big deal.

But it's probably even bigger than that because probably what would happen is it would change the probability that things go off the rails and that we get a bad outcome.

And the way it could do that through sheer speed is that it could change the speed of the AI activities that are increasing risk, such as improving the capabilities of these systems, for

faster, you could make more of an impact on that than it makes on some of the processes that are reducing the risk, such as technical research on AI alignment or other aspects like AI governance work.

I don't think it's going to speed those things up as much as it would speed up the capabilities work of improving its own capabilities.

So if these things get out of whack, then what you'd expect is that for any particular level of capable AI systems,

that our ability to control them is lagging behind.

So we pass through all of these thresholds less prepared than we otherwise would be.

Yeah, so let's call that the second one, second source of risk.

And so if you imagine producing one AI system, let's call it GPT-7, and then that produces GPT-8, which produces GPT-9 and 10 and so on, that if any of those in that line were to be misaligned and to be able to scheme about...

what they want to achieve, then they would have an incentive to misalign the systems that they were building and to make sure that whatever its peculiar objectives were that differ from human objectives, that that was maintained in the future systems.

That's the second big source of risk, which is also a really big deal independently from the first.

It could have different remedies for it.

If you look at each of these different ways that self-improvement could be risky,

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