I don’t think this argument is sound in general, no. GPT-4 may have only arrived a few months after ChatGPT-3.5, but it’s economic impacts will also unfold over the same next however many years. I don’t think it will take longer than adapting to just ChatGPT-3.5 would have. Only that impact will be greater, and no one in the meantime will have invested (wasted?) money on procedures and infrastructure adapting to less capable tools first.
I think there are versions of similar arguments that are sound. If you gave the ancient Romans a modern tank or a solar panel it would be useless to them, there’s too many missing pieces for them to adapt to it at all. But if you want back to 1960 and gave NASA a big crate of TI-89 calculators, well, they knew math, they knew programming, and they had AAA batteries. It could have been a big help pretty quickly. A crate of laptops would probably be more helpful, and take a bit longer to adapt to fully, but I still think they’d start getting benefit almost right away.
The economy, in general, adapts much slower than it in principle could to new technologies. Usually because no one forces anyone’s hand, so the efficient route is to keep using old tech until it’s time to replace it. Emerging economies adapt several times faster, because they know what they’re trying to catch up to. IDK where the adaptation frontier for LLMs would be, exactly? Or how that changes as capabilities increase.
The economy is a complex adaptative system which, like all complex adaptive systems, can handle perturbations over the same timescale as the interal homostatic processes. Beyond that regime, the system will not adapt. If I tap your head, you’re fine. If you knock you with an anvil, you’re dead.
Yes, absolutely. The question is where that line lies for each combination of system + perturbation. I agree with most of your claims in the article—just not the claim that each AI iteration is sufficiently different from an economic perspective as to require it’s own independent 5-10 yr adjustment period. MMy guess is that some companies will start earlier and some later, some will copy best practices and not bother with some generations/iterations, and that this specific issue will not be more of a problem than, say, Europe and then Japan rebuilding after WWII with more modern factories and steel mills and so on than America had. Probably less, since the software is all handled on the back end and the costs of switching should be relatively low.
Countries that were on the frontier of the Industrial Revolution underwent massive economic, social, and political shocks, and it would’ve been better if the change had been smoothed over about double the duration.
Countries that industrialised later also underwent severe shocks, but at least they could copy the solutions to those shocks along with the technology.
Novel general-purpose technology introduces problems, and there is a maximum rate at which problems can be fixed by the internal homeostasis of society. That maximum rate is, I claim, at least 5–10 years for ChatGPT-3.5.
ChatGPT-3.5 would’ve led to maybe a 10% reallocation of labour — this figure doesn’t just include directly automated jobs, but also all the second- and third-order effects. ChatGPT-4, marginal on ChatGPT-3.5 would’ve led to maybe a 4% reallocation of labour.
It’s better to “flatten the curve” of labour reallocation over 5–10 years rather than 3 months because massive economic shocks (e.g. unemployment) have socio-economic risks and costs.
That’s possible. Have you read Robin Hanson’s 2000 paper on economic growth over the past 2 million years? If not, you might find it interesting. Talks in part about how new modes of spreading knowledge and invention may explain past transitions in the economic growth rate.
It doesn’t mention AI at all (though Hanson has made the connection multiple times since), but does say that if the data series trend continues, that suggests a possible transition to a new growth mode some time in the next couple of decades with a doubling time of a few days to a few years. To me, AI in some form seems like a reasonable candidate for that, to the extent it can take human limits on adaptation speed out of the equation.
Yep, just as developing countries don’t bother with landlines, so to will companies, as they overcome inertia and embrace AI, choose to skip older outdated models and jump to the frontier, wherever that may lie. No company embracing LLMs in 2024 is gonna start by trying to first integrate GPT2, then 3, then 4 in an orderly and gradual manner.
I don’t think this argument is sound in general, no. GPT-4 may have only arrived a few months after ChatGPT-3.5, but it’s economic impacts will also unfold over the same next however many years. I don’t think it will take longer than adapting to just ChatGPT-3.5 would have. Only that impact will be greater, and no one in the meantime will have invested (wasted?) money on procedures and infrastructure adapting to less capable tools first.
I think there are versions of similar arguments that are sound. If you gave the ancient Romans a modern tank or a solar panel it would be useless to them, there’s too many missing pieces for them to adapt to it at all. But if you want back to 1960 and gave NASA a big crate of TI-89 calculators, well, they knew math, they knew programming, and they had AAA batteries. It could have been a big help pretty quickly. A crate of laptops would probably be more helpful, and take a bit longer to adapt to fully, but I still think they’d start getting benefit almost right away.
The economy, in general, adapts much slower than it in principle could to new technologies. Usually because no one forces anyone’s hand, so the efficient route is to keep using old tech until it’s time to replace it. Emerging economies adapt several times faster, because they know what they’re trying to catch up to. IDK where the adaptation frontier for LLMs would be, exactly? Or how that changes as capabilities increase.
The economy is a complex adaptative system which, like all complex adaptive systems, can handle perturbations over the same timescale as the interal homostatic processes. Beyond that regime, the system will not adapt. If I tap your head, you’re fine. If you knock you with an anvil, you’re dead.
Yes, absolutely. The question is where that line lies for each combination of system + perturbation. I agree with most of your claims in the article—just not the claim that each AI iteration is sufficiently different from an economic perspective as to require it’s own independent 5-10 yr adjustment period. MMy guess is that some companies will start earlier and some later, some will copy best practices and not bother with some generations/iterations, and that this specific issue will not be more of a problem than, say, Europe and then Japan rebuilding after WWII with more modern factories and steel mills and so on than America had. Probably less, since the software is all handled on the back end and the costs of switching should be relatively low.
Countries that were on the frontier of the Industrial Revolution underwent massive economic, social, and political shocks, and it would’ve been better if the change had been smoothed over about double the duration.
Countries that industrialised later also underwent severe shocks, but at least they could copy the solutions to those shocks along with the technology.
Novel general-purpose technology introduces problems, and there is a maximum rate at which problems can be fixed by the internal homeostasis of society. That maximum rate is, I claim, at least 5–10 years for ChatGPT-3.5.
ChatGPT-3.5 would’ve led to maybe a 10% reallocation of labour — this figure doesn’t just include directly automated jobs, but also all the second- and third-order effects. ChatGPT-4, marginal on ChatGPT-3.5 would’ve led to maybe a 4% reallocation of labour.
It’s better to “flatten the curve” of labour reallocation over 5–10 years rather than 3 months because massive economic shocks (e.g. unemployment) have socio-economic risks and costs.
That’s possible. Have you read Robin Hanson’s 2000 paper on economic growth over the past 2 million years? If not, you might find it interesting. Talks in part about how new modes of spreading knowledge and invention may explain past transitions in the economic growth rate.
It doesn’t mention AI at all (though Hanson has made the connection multiple times since), but does say that if the data series trend continues, that suggests a possible transition to a new growth mode some time in the next couple of decades with a doubling time of a few days to a few years. To me, AI in some form seems like a reasonable candidate for that, to the extent it can take human limits on adaptation speed out of the equation.
Yep, just as developing countries don’t bother with landlines, so to will companies, as they overcome inertia and embrace AI, choose to skip older outdated models and jump to the frontier, wherever that may lie. No company embracing LLMs in 2024 is gonna start by trying to first integrate GPT2, then 3, then 4 in an orderly and gradual manner.