If increases in basic AI intelligence were fully halted at 2027 levels, economic growth would still accelerate to something comfortably above 5%/year, due to continuing adaptations of AI to things like robotics.
I’m very skeptical of this claim, and I don’t see why you think it’s true. Can you explain your intuitions here?
Are you assuming that an AI pause would not halt progress in creating general-purpose robots that can flexibly perform manual labor?
Yes. Current AIs have enough general intelligence that I expect they’re sufficient to replace a fair amount of manual labor.
There are still some expensive engineering problems, but they’re relatively ordinary problems such as figuring out which robot models ought to be mass produced (without mass production, they’ll be too expensive), substantial training to instill domain-specific knowledge, and maybe some need for more energy efficient GPUs.
As long as general-purpose AI is making rapid progress, it probably makes some sense for the robot industry to wait another year or two before choosing the specifics of what kinds of robots to mass-produce—AIs of 2028 are likely to learn domain-specific knowledge faster and more flexibly. But even if we get an AI pause by 2027, I expect at least 10% of manual labor to be replaced by robots by 2030.
But even if we get an AI pause by 2027, I expect at least 10% of manual labor to be replaced by robots by 2030.
I don’t anticipate 10% of current manual labor being replaced by robots by 2030, with or without an AI pause. I’m pretty confident about that.[1]
That said, I think your prediction reveals a key ambiguity in what “AI pause” means. As I understand it, most pause advocates propose limiting the supply of GPUs available to AI companies. This wouldn’t just affect LLM training runs. It would also affect robotic training runs, since training advanced robotic systems requires large amounts of compute as well, and this will likely become increasingly true for more sophisticated robotic systems. Higher GPU prices would make general-purpose robotics projects more expensive.
It’s true that robotics progress would be less affected than LLM progress, because robotics is much more heavily bottlenecked by data collection than by raw compute. But even this distinction is blurrier than it first appears, because one of the main ways to collect robotic training data is to generate it in simulation, which is itself a compute-intensive process. So limiting GPU supply would still slow robotics progress, just less directly and severely.
Also, of course, limiting the GPU supply isn’t the only AI pause proposal, just the most prominent and salient one.
I don’t know how you’re operationalizing this claim. If we interpret the claim to be something like, “Robots at the beginning of 2030 fully substitute for at least 10% of all physical labor tasks that were performed entirely manually by human workers in the US at the beginning of 2026” then I disagree. I might, however, agree with weaker operationalizations of the claim.
I’m very skeptical of this claim, and I don’t see why you think it’s true. Can you explain your intuitions here?
Are you assuming that an AI pause would not halt progress in creating general-purpose robots that can flexibly perform manual labor?
Yes. Current AIs have enough general intelligence that I expect they’re sufficient to replace a fair amount of manual labor.
There are still some expensive engineering problems, but they’re relatively ordinary problems such as figuring out which robot models ought to be mass produced (without mass production, they’ll be too expensive), substantial training to instill domain-specific knowledge, and maybe some need for more energy efficient GPUs.
As long as general-purpose AI is making rapid progress, it probably makes some sense for the robot industry to wait another year or two before choosing the specifics of what kinds of robots to mass-produce—AIs of 2028 are likely to learn domain-specific knowledge faster and more flexibly. But even if we get an AI pause by 2027, I expect at least 10% of manual labor to be replaced by robots by 2030.
I don’t anticipate 10% of current manual labor being replaced by robots by 2030, with or without an AI pause. I’m pretty confident about that.[1]
That said, I think your prediction reveals a key ambiguity in what “AI pause” means. As I understand it, most pause advocates propose limiting the supply of GPUs available to AI companies. This wouldn’t just affect LLM training runs. It would also affect robotic training runs, since training advanced robotic systems requires large amounts of compute as well, and this will likely become increasingly true for more sophisticated robotic systems. Higher GPU prices would make general-purpose robotics projects more expensive.
It’s true that robotics progress would be less affected than LLM progress, because robotics is much more heavily bottlenecked by data collection than by raw compute. But even this distinction is blurrier than it first appears, because one of the main ways to collect robotic training data is to generate it in simulation, which is itself a compute-intensive process. So limiting GPU supply would still slow robotics progress, just less directly and severely.
Also, of course, limiting the GPU supply isn’t the only AI pause proposal, just the most prominent and salient one.
I don’t know how you’re operationalizing this claim. If we interpret the claim to be something like, “Robots at the beginning of 2030 fully substitute for at least 10% of all physical labor tasks that were performed entirely manually by human workers in the US at the beginning of 2026” then I disagree. I might, however, agree with weaker operationalizations of the claim.