I disagree with this series in a number of places. For example, in the post “This Can’t Go On”, it says the following in the context of an airplane metaphor for our condition:
We’re going much faster than normal, and there isn’t enough runway to do this much longer … and we’re accelerating.
As argued above, in terms of economic growth rates, we’re in fact not accelerating, but instead seeing an unprecedented growth decline across doublings. Additionally, the piece, and the series as a whole, seems to neglect the possibility that growth rates might simply continue to decline very gradually, as they have over the last 5-6 decades.[1]
Relatedly, I would question some of the “growth-exploding” implications that the series implicitly assumes would follow from PASTA (“AI systems that can essentially automate all of the human activities needed to speed up scientific and technological advancement”). I’ve tried to explain some of my reservations here (more on this below).
This post relates to the PASTA point above; I guess the following is the key passage in this context:
AI potentially offers a way to convert money into researchers. Money = build more AIs = more research.
If this were true, then once AI comes around – even if it isn’t much smarter than humans – then as long as the computational power you can invest into researching a given field increases with the amount of money you have, hyperbolic growth is back on. Faster growth rates means more money means more AIs researching new technology means even faster growth rates, and so on …
I think this is by far the most plausible conjecture as to how growth rates could explode in the future. But I still think there are good reasons to be skeptical of such an explosion. For one, an AI-driven explosion of this kind would most likely involve a corresponding explosion in hardware (e.g. for reasons gestured at here and here), and there are both theoretical and empirical reasons to doubt that we will see such an explosion.
Indeed, growth rates are declining across various hardware metrics, and yet here we are not just talking about growth rates in hardware remaining at familiar levels, but presumably about an explosion in these growth rates. That seems to go against the empirical trends that we are observing in hardware, and against the impending end of Moore’s law that we can predict with reasonable confidence based on theory.
Relatedly, there is the point that explosive economic growth likely would imply an explosion in energy production, but it is likewise doubtful whether progress in software/computation could unleash such an explosion (as argued here). More generally, even if we made a lot of progress in both computer software and hardware, it seems likely that growth would become constrained by other factors to a degree that precludes an economic growth explosion (Bryan Caplan makes similar points in response to Hanson’s Age of Em; see point 9 here; see also Aghion et al., 2019, p. 260).
Moreover, as mentioned in an earlier comment, it is worth noting that the decline in growth rates that we have seen since the 1960s is not only due to decreasing population growth, as there are also other factors that have contributed, such as certain growth potentials that have been exhausted, and the consequent decline in innovations per capita.
One thing to notice about this model is that it conflicts with the historic decline in growth rates. In particular, the model is an ever worse fit with the observed growth rates of the last four decades. Roodman himself notes that his model has shortcomings in this regard:
… recent global growth has been slower and steadier than the model predicts from previous history. … Nevertheless, I think it is a virtue, and perhaps an inspiration for further work, that this rigorous model can quantify its own shortcomings.
(Perhaps also see Tom Davidson’s reflections on Roodman’s model.)
In other words, the model is not a good fit with the last 2-3 doublings of the world economy, and this is somewhat obscured when the model is evaluated across standard calendar time rather than across doublings; when looking at the model through the former lens, its recent mispredictions seem minor, but when seen across doublings — arguably the more relevant perspective — they become rather significant.
Given the historical data, it seems that a considerably better fit would be a model that predicts roughly symmetric growth rates around a peak growth rate found ca. 1960, as can be gleaned here (similar points are made in Modis, 2012, pp. 20-22). Such a model may be theoretically grounded in the expectation that there will be a point where innovations become increasingly harder to find. One would expect such a “peak growth rate” to occur at some point a priori, given the finite potential for growth (implying that the addition of a limiting factor that represents the finite nature of growth-inducing innovations would be a natural extension to Roodman’s model). And empirical data then tentatively suggests that this peak lies in the past. (But again, peak growth rates being in the past is still compatible with increasing growth in absolute terms.)
E.g. when it says: “We’re either going to speed up even more, or come to a stop, or something else weird is going to happen.” This seems to overlook the kind of future that I alluded to above, which would amount to staying at roughly the same pace, yet continuing to slow down growth rates very gradually. This is arguably not a particularly “weird” or “wild” prospect. (It’s also worth nothing that the “come to a stop” would occur faster in the “speed up even more” scenario, as it would imply that we’ll hit ultimate limits earlier; slower growth would imply that non-trivial growth rates end later.)
Thanks for this, it’s helpful. I do agree that declining growth rates is significant evidence for your view.
I disagree with your other arguments:
For one, an AI-driven explosion of this kind would most likely involve a corresponding explosion in hardware (e.g. for reasons gestured at here and here), and there are both theoretical and empirical reasons to doubt that we will see such an explosion.
I don’t have a strong take on whether we’ll see an explosion in hardware efficiency; it’s plausible to me that there won’t be much change there (and also plausible that there will be significant advances, e.g. getting 3D chips to work—I just don’t know much about this area).
But the central thing I imagine in an AI-driven explosion is an explosion in the amount of hardware (i.e. way more factories producing chips, way more mining operations getting the raw materials, etc), and an explosion in software efficiency (see e.g. here and here). So it just doesn’t seem to matter that much if we’re at the limits of hardware efficiency.
it is worth noting that the decline in growth rates that we have seen since the 1960s is not only due to decreasing population growth, as there are also other factors that have contributed, such as certain growth potentials that have been exhausted, and the consequent decline in innovations per capita.
I realize that I said the opposite in a previous comment thread, but right now it feels consistent with explosive growth to say that innovations per capita are going to decline; indeed I agree with Scott Alexander that it’s hard to imagine it being any other way. The feedback loop for explosive growth is output → people / AI → ideas → output, a core part of that feedback loop is about increasing the “population”.
(Though the fact that I said the opposite in a previous comment thread suggests I should really delve into the math to check my understanding.)
(The rest of this is nitpicky details.)
Incidentally, the graphs you show for the decline in innovations per capita start dropping around 1900 (I think, I am guessing for the one that has “% of people” as its x-axis), which is pretty different from the 1960s.
Also, I’m a bit skeptical of the graph showing a 5x drop. It’s based off of an analysis of a book written by Asimov in 1993 presenting a history of science and discovery. I’m pretty worried that this will tend to disadvantage the latest years, because (1) there may have been discoveries that weren’t recognized as “meeting the bar”, since their importance hadn’t yet been understood, (2) Asimov might not have been aware of the most recent discoveries (though this point could also go the other way), and (3) as time goes on, discoveries become more and more diverse (there are way more fields) and hard to understand without expertise, and so Asimov might not have noticed them.
Regarding explosive growth in the amount of hardware: I meant to include the scale aspect as well when speaking of a hardware explosion. I tried to outline one of the main reasons I’m skeptical of such an ‘explosion via scaling’ here. In short, in the absence of massive efficiency gains, it seems even less likely that we will see a scale-up explosion in the future.
Incidentally, the graphs you show for the decline in innovations per capita start dropping around 1900 … which is pretty different from the 1960s.
That’s right, but that’s consistent with the per capita drop in innovation being a significant part of the reason why growth rates gradually declined since the 1960s. I didn’t mean to deny that total population size has played a crucial role, as it obviously has and does. But if innovations per capita continue to decline, then even a significant increase in effective population size in the future may not be enough to cause a growth explosion. For example, if the number of employed robots continues to grow at current rates (roughly 12 percent per year), and if future robots eventually come to be the relevant economic population, then declining rates of innovation/economic productivity per capita would mean that the total economic growth rate still doesn’t exceed 12 percent. I realize that you likely expect robot populations to grow much faster in such a future, but I still don’t see what would drive such explosive growth in hardware (even if, in fact especially if, it primarily involves scaling-based growth).
Also, I’m a bit skeptical of the graph showing a 5x drop.
That makes sense.
On the other hand, it’s perhaps worth noting that individual human thinking was increasingly extended by computers after ca. 1950, and yet the rate of innovation per capita still declined. So in that sense, the decline in progress could be seen as being somewhat understated by the graphs, in that the rate of innovation per dollar/scientific instrument/computation/etc. has declined considerably more.
Currently humans are state-of-the-art at various tasks relevant to growth.
We are bottlenecked on scaling up humans by a variety of things (e.g. it takes ~20 years to train up a new human, you can’t invest money into the creation of new humans with the hope of getting a return on it, humans only work ~8 hours a day)
At some point AI / robots will be able to match human performance at these tasks.
AI / robots will not be bottlenecked on those things.
In some sense I agree with you that you have to see efficiency improvements, but the efficiency improvements are things like “you can create new skilled robots in days, compared to the previous SOTA of 20 years”. So I think if you accept (3) then I think you are already accepting massive efficiency improvements.
I don’t see why current robot growth rates are relevant. When you have two different technologies A and B where A works better now, but B is getting better faster than A, then there will predictably be a big jump in the use of B once it exceeds A, and extrapolating the growth rates of B before it exceeds A is going to predictably mislead you.
(For example, I’d guess that in 1975, you would have done better thinking about how / when the personal computer would overtake other office productivity technologies, perhaps based on Moore’s law, rather than trying to extrapolate the growth rate of personal computers. Indeed, according a random website I just found, it looks like the growth rate accelerated till the EDIT: 1980s, though it’s hard to tell from the graph.)
(To be clear, this argument doesn’t necessarily get you to “transformative impact on growth comparable to the industrial revolution”, I’d guess you do need to talk about innovations to get that conclusion. But I’m just not seeing why you don’t expect a ton of scaling even if innovations are rarer, unless you deny (3), but it mostly seems like you don’t deny (3).)
I agree with premise 3. Where I disagree more comes down to the scope of premise 1.
This relates to the diverse class of contributors and bottlenecks to growth under Model 2. So even though it’s true to say that humans are currently “the state-of-the-art at various tasks relevant to growth”, it’s also true to say that computers and robots are currently “the state-of-the-art at various tasks relevant to growth”. Indeed, machines/external tools have been (part of) the state-of-the-art at some tasks for millennia (e.g. in harvesting), and computers and robots in particular have been the state-of-the-art at various tasks relevant to growth for decades (e.g. in technical calculations and manufacturing). And the proportion of tasks at which machines have been driving growth has been gradually increasing (the pictures of Model 2 was an attempt to illustrate this perspective). Yet despite superhuman machines (i.e. machines that are superhuman within specific tasks) playing an increasing role in pushing growth over the past decades, economic growth rates not only failed to increase, but decreased almost by a factor of 2. That is, robots/machines have already been replacing humans at the growth frontier across various tasks in the way described in premises 1-4, yet we still haven’t seen growth increase. So a key question is why we should expect future growth/displacement of this kind to be different. Will it be less gradual? If so, why?
In short, my view is that humans have become an ever smaller part of the combined set of tools pushing growth forward — such that we’re in various senses already a minority force, e.g. in terms of the lifting of heavy objects, performing lengthy math calculations, manufacturing chips, etc. — and I expect this process to gradually continue. I don’t expect a critical point at which growth rates suddenly explode because the machines themselves are already doing such a large share of the heavy lifting, and an increasing proportion of our key bottlenecks to growth are (already) their bottlenecks to faster growth (which must again be distinguished from claims about absolute room for growth; there may be plenty of potential for growth in various domains without there being an extremely fast way to realize that potential).
When you have two different technologies A and B where A works better now, but B is getting better faster than A, then there will predictably be a big jump in the use of B once it exceeds A
Not if B is gradually getting better than A at specific growth-relevant tasks, and if B is getting produced and employed roughly in proportion to how fast it is getting better than A at those specific tasks. In that case, familiar rates of improvement (of B over A) could imply familiar growth rates in the production and employment of B in the future.
But I’m just not seeing why you don’t expect a ton of scaling
Just to be clear, in one sense, I do expect to see a ton of scaling compared to today, I just don’t expect scaling growth rates to explode, such that we see a doubling in a year or faster. In a future robot population that is much larger than the current one, consistent 12 percent annual growth would still amount to producing more robots in a single year than had been produced throughout all history 20 years earlier.
I don’t disagree with any of the above (which is why I emphasized that I don’t think the scaling argument is sufficient to justify a growth explosion). I’m confused why you think the rate of growth of robots is at all relevant, when (general-purpose) robotics seem mostly like a research technology right now. It feels kind of like looking at the current rate of growth of fusion plants as a prediction of the rate of growth of fusion plants after the point where fusion is cheaper than other sources of energy.
(If you were talking about the rate of growth of machines in general I’d find that more relevant.)
By “I am confused by your argument against scaling”, I thought you meant the argument I made here, since that was the main argument I made regarding scaling; the example with robots wasn’t really central.
I’m also a bit confused, because I read your arguments above as being arguments in favor of explosive economic growth rates from hardware scaling and increasing software efficiency. So I’m not sure whether you believe that the factors mentioned in your comment above are sufficient for causing explosive economic growth. Moreover, I don’t yet understand why you believe that hardware scaling would come to grow at much higher rates than it has in the past.
I don’t yet understand why you believe that hardware scaling would come to grow at much higher rates than it has in the past.
If we assume innovations decline, then it is primarily because future AI and robots will be able to automate far more tasks than current AI and robots (and we will get them quickly, not slowly).
Imagine that currently technology A that automates area X gains capabilities at a rate of 5% per year, which ends up leading to a growth rate of 10% per year.
Imagine technology B that also aims to automate area X gains capabilities at a rate of 20% per year, but is currently behind technology A.
Generally, at the point when B exceeds A, I’d expect growth rates of X-automating technologies to grow from 10% to >20% (though not necessarily immediately, it can take time to build the capacity for that growth).
For AI, the area X is “cognitive labor”, technology A is “the current suite of productivity tools”, and technology B is “AI”.
For robots, the area X is “physical labor”, technology A is “classical robotics”, and technology B is “robotics based on foundation models”.
That was just assuming hardware scaling, and it justifies a growth in some particular growth rates, but not a growth explosion. If you add in the software efficiency, then I think you are just straightforwardly generating lots of innovations (what else is leading to the improved software efficiency?) and that’s how you get the growth explosion, at least until you run out of software efficiency improvements to make.
To be clear, I don’t mean to claim that we should give special importance to current growth rates in robotics in particular. I just picked that as an example. But I do think it’s a relevant example, primarily due to the gradual nature of the abilities that robots are surpassing, and the consequent gradual nature of their employment.
Unlike fusion, which is singular in its relevant output (energy), robots produce a diversity of things, and robots cover a wide range of growth-relevant skills that are gradually getting surpassed already. It is this gradual nature of their growth-related abilities that makes them relevant, imo — because they are already doing a lot of work and already contributing a fair deal to the growth we’re currently seeing. (To clarify, I mostly have in mind industrial robots, such as these, the future equivalents of which I also expect to be important to growth; I’d agree that it wouldn’t be so relevant if we were only talking about some prototypes of robots that don’t yet contribute meaningfully to the economy.)
I wrote earlier that I might write a more elaborate comment, which I’ll attempt now. The following are some comments on the pieces that you linked to.
I disagree with this series in a number of places. For example, in the post “This Can’t Go On”, it says the following in the context of an airplane metaphor for our condition:
As argued above, in terms of economic growth rates, we’re in fact not accelerating, but instead seeing an unprecedented growth decline across doublings. Additionally, the piece, and the series as a whole, seems to neglect the possibility that growth rates might simply continue to decline very gradually, as they have over the last 5-6 decades.[1]
Relatedly, I would question some of the “growth-exploding” implications that the series implicitly assumes would follow from PASTA (“AI systems that can essentially automate all of the human activities needed to speed up scientific and technological advancement”). I’ve tried to explain some of my reservations here (more on this below).
This post relates to the PASTA point above; I guess the following is the key passage in this context:
I think this is by far the most plausible conjecture as to how growth rates could explode in the future. But I still think there are good reasons to be skeptical of such an explosion. For one, an AI-driven explosion of this kind would most likely involve a corresponding explosion in hardware (e.g. for reasons gestured at here and here), and there are both theoretical and empirical reasons to doubt that we will see such an explosion.
Indeed, growth rates are declining across various hardware metrics, and yet here we are not just talking about growth rates in hardware remaining at familiar levels, but presumably about an explosion in these growth rates. That seems to go against the empirical trends that we are observing in hardware, and against the impending end of Moore’s law that we can predict with reasonable confidence based on theory.
Relatedly, there is the point that explosive economic growth likely would imply an explosion in energy production, but it is likewise doubtful whether progress in software/computation could unleash such an explosion (as argued here). More generally, even if we made a lot of progress in both computer software and hardware, it seems likely that growth would become constrained by other factors to a degree that precludes an economic growth explosion (Bryan Caplan makes similar points in response to Hanson’s Age of Em; see point 9 here; see also Aghion et al., 2019, p. 260).
Moreover, as mentioned in an earlier comment, it is worth noting that the decline in growth rates that we have seen since the 1960s is not only due to decreasing population growth, as there are also other factors that have contributed, such as certain growth potentials that have been exhausted, and the consequent decline in innovations per capita.
One thing to notice about this model is that it conflicts with the historic decline in growth rates. In particular, the model is an ever worse fit with the observed growth rates of the last four decades. Roodman himself notes that his model has shortcomings in this regard:
(Perhaps also see Tom Davidson’s reflections on Roodman’s model.)
In other words, the model is not a good fit with the last 2-3 doublings of the world economy, and this is somewhat obscured when the model is evaluated across standard calendar time rather than across doublings; when looking at the model through the former lens, its recent mispredictions seem minor, but when seen across doublings — arguably the more relevant perspective — they become rather significant.
Given the historical data, it seems that a considerably better fit would be a model that predicts roughly symmetric growth rates around a peak growth rate found ca. 1960, as can be gleaned here (similar points are made in Modis, 2012, pp. 20-22). Such a model may be theoretically grounded in the expectation that there will be a point where innovations become increasingly harder to find. One would expect such a “peak growth rate” to occur at some point a priori, given the finite potential for growth (implying that the addition of a limiting factor that represents the finite nature of growth-inducing innovations would be a natural extension to Roodman’s model). And empirical data then tentatively suggests that this peak lies in the past. (But again, peak growth rates being in the past is still compatible with increasing growth in absolute terms.)
I think my main comments on this model are captured above.
Thanks again for engaging, and feel free to comment on any points you disagree with. :)
E.g. when it says: “We’re either going to speed up even more, or come to a stop, or something else weird is going to happen.” This seems to overlook the kind of future that I alluded to above, which would amount to staying at roughly the same pace, yet continuing to slow down growth rates very gradually. This is arguably not a particularly “weird” or “wild” prospect. (It’s also worth nothing that the “come to a stop” would occur faster in the “speed up even more” scenario, as it would imply that we’ll hit ultimate limits earlier; slower growth would imply that non-trivial growth rates end later.)
Thanks for this, it’s helpful. I do agree that declining growth rates is significant evidence for your view.
I disagree with your other arguments:
I don’t have a strong take on whether we’ll see an explosion in hardware efficiency; it’s plausible to me that there won’t be much change there (and also plausible that there will be significant advances, e.g. getting 3D chips to work—I just don’t know much about this area).
But the central thing I imagine in an AI-driven explosion is an explosion in the amount of hardware (i.e. way more factories producing chips, way more mining operations getting the raw materials, etc), and an explosion in software efficiency (see e.g. here and here). So it just doesn’t seem to matter that much if we’re at the limits of hardware efficiency.
I realize that I said the opposite in a previous comment thread, but right now it feels consistent with explosive growth to say that innovations per capita are going to decline; indeed I agree with Scott Alexander that it’s hard to imagine it being any other way. The feedback loop for explosive growth is output → people / AI → ideas → output, a core part of that feedback loop is about increasing the “population”.
(Though the fact that I said the opposite in a previous comment thread suggests I should really delve into the math to check my understanding.)
(The rest of this is nitpicky details.)
Incidentally, the graphs you show for the decline in innovations per capita start dropping around 1900 (I think, I am guessing for the one that has “% of people” as its x-axis), which is pretty different from the 1960s.
Also, I’m a bit skeptical of the graph showing a 5x drop. It’s based off of an analysis of a book written by Asimov in 1993 presenting a history of science and discovery. I’m pretty worried that this will tend to disadvantage the latest years, because (1) there may have been discoveries that weren’t recognized as “meeting the bar”, since their importance hadn’t yet been understood, (2) Asimov might not have been aware of the most recent discoveries (though this point could also go the other way), and (3) as time goes on, discoveries become more and more diverse (there are way more fields) and hard to understand without expertise, and so Asimov might not have noticed them.
Regarding explosive growth in the amount of hardware: I meant to include the scale aspect as well when speaking of a hardware explosion. I tried to outline one of the main reasons I’m skeptical of such an ‘explosion via scaling’ here. In short, in the absence of massive efficiency gains, it seems even less likely that we will see a scale-up explosion in the future.
That’s right, but that’s consistent with the per capita drop in innovation being a significant part of the reason why growth rates gradually declined since the 1960s. I didn’t mean to deny that total population size has played a crucial role, as it obviously has and does. But if innovations per capita continue to decline, then even a significant increase in effective population size in the future may not be enough to cause a growth explosion. For example, if the number of employed robots continues to grow at current rates (roughly 12 percent per year), and if future robots eventually come to be the relevant economic population, then declining rates of innovation/economic productivity per capita would mean that the total economic growth rate still doesn’t exceed 12 percent. I realize that you likely expect robot populations to grow much faster in such a future, but I still don’t see what would drive such explosive growth in hardware (even if, in fact especially if, it primarily involves scaling-based growth).
That makes sense.
On the other hand, it’s perhaps worth noting that individual human thinking was increasingly extended by computers after ca. 1950, and yet the rate of innovation per capita still declined. So in that sense, the decline in progress could be seen as being somewhat understated by the graphs, in that the rate of innovation per dollar/scientific instrument/computation/etc. has declined considerably more.
I am confused by your argument against scaling.
My understanding of the scale-up argument is:
Currently humans are state-of-the-art at various tasks relevant to growth.
We are bottlenecked on scaling up humans by a variety of things (e.g. it takes ~20 years to train up a new human, you can’t invest money into the creation of new humans with the hope of getting a return on it, humans only work ~8 hours a day)
At some point AI / robots will be able to match human performance at these tasks.
AI / robots will not be bottlenecked on those things.
In some sense I agree with you that you have to see efficiency improvements, but the efficiency improvements are things like “you can create new skilled robots in days, compared to the previous SOTA of 20 years”. So I think if you accept (3) then I think you are already accepting massive efficiency improvements.
I don’t see why current robot growth rates are relevant. When you have two different technologies A and B where A works better now, but B is getting better faster than A, then there will predictably be a big jump in the use of B once it exceeds A, and extrapolating the growth rates of B before it exceeds A is going to predictably mislead you.
(For example, I’d guess that in 1975, you would have done better thinking about how / when the personal computer would overtake other office productivity technologies, perhaps based on Moore’s law, rather than trying to extrapolate the growth rate of personal computers. Indeed, according a random website I just found, it looks like the growth rate accelerated till the EDIT: 1980s, though it’s hard to tell from the graph.)
(To be clear, this argument doesn’t necessarily get you to “transformative impact on growth comparable to the industrial revolution”, I’d guess you do need to talk about innovations to get that conclusion. But I’m just not seeing why you don’t expect a ton of scaling even if innovations are rarer, unless you deny (3), but it mostly seems like you don’t deny (3).)
I agree with premise 3. Where I disagree more comes down to the scope of premise 1.
This relates to the diverse class of contributors and bottlenecks to growth under Model 2. So even though it’s true to say that humans are currently “the state-of-the-art at various tasks relevant to growth”, it’s also true to say that computers and robots are currently “the state-of-the-art at various tasks relevant to growth”. Indeed, machines/external tools have been (part of) the state-of-the-art at some tasks for millennia (e.g. in harvesting), and computers and robots in particular have been the state-of-the-art at various tasks relevant to growth for decades (e.g. in technical calculations and manufacturing). And the proportion of tasks at which machines have been driving growth has been gradually increasing (the pictures of Model 2 was an attempt to illustrate this perspective). Yet despite superhuman machines (i.e. machines that are superhuman within specific tasks) playing an increasing role in pushing growth over the past decades, economic growth rates not only failed to increase, but decreased almost by a factor of 2. That is, robots/machines have already been replacing humans at the growth frontier across various tasks in the way described in premises 1-4, yet we still haven’t seen growth increase. So a key question is why we should expect future growth/displacement of this kind to be different. Will it be less gradual? If so, why?
In short, my view is that humans have become an ever smaller part of the combined set of tools pushing growth forward — such that we’re in various senses already a minority force, e.g. in terms of the lifting of heavy objects, performing lengthy math calculations, manufacturing chips, etc. — and I expect this process to gradually continue. I don’t expect a critical point at which growth rates suddenly explode because the machines themselves are already doing such a large share of the heavy lifting, and an increasing proportion of our key bottlenecks to growth are (already) their bottlenecks to faster growth (which must again be distinguished from claims about absolute room for growth; there may be plenty of potential for growth in various domains without there being an extremely fast way to realize that potential).
Not if B is gradually getting better than A at specific growth-relevant tasks, and if B is getting produced and employed roughly in proportion to how fast it is getting better than A at those specific tasks. In that case, familiar rates of improvement (of B over A) could imply familiar growth rates in the production and employment of B in the future.
Just to be clear, in one sense, I do expect to see a ton of scaling compared to today, I just don’t expect scaling growth rates to explode, such that we see a doubling in a year or faster. In a future robot population that is much larger than the current one, consistent 12 percent annual growth would still amount to producing more robots in a single year than had been produced throughout all history 20 years earlier.
I don’t disagree with any of the above (which is why I emphasized that I don’t think the scaling argument is sufficient to justify a growth explosion). I’m confused why you think the rate of growth of robots is at all relevant, when (general-purpose) robotics seem mostly like a research technology right now. It feels kind of like looking at the current rate of growth of fusion plants as a prediction of the rate of growth of fusion plants after the point where fusion is cheaper than other sources of energy.
(If you were talking about the rate of growth of machines in general I’d find that more relevant.)
By “I am confused by your argument against scaling”, I thought you meant the argument I made here, since that was the main argument I made regarding scaling; the example with robots wasn’t really central.
I’m also a bit confused, because I read your arguments above as being arguments in favor of explosive economic growth rates from hardware scaling and increasing software efficiency. So I’m not sure whether you believe that the factors mentioned in your comment above are sufficient for causing explosive economic growth. Moreover, I don’t yet understand why you believe that hardware scaling would come to grow at much higher rates than it has in the past.
If we assume innovations decline, then it is primarily because future AI and robots will be able to automate far more tasks than current AI and robots (and we will get them quickly, not slowly).
Imagine that currently technology A that automates area X gains capabilities at a rate of 5% per year, which ends up leading to a growth rate of 10% per year.
Imagine technology B that also aims to automate area X gains capabilities at a rate of 20% per year, but is currently behind technology A.
Generally, at the point when B exceeds A, I’d expect growth rates of X-automating technologies to grow from 10% to >20% (though not necessarily immediately, it can take time to build the capacity for that growth).
For AI, the area X is “cognitive labor”, technology A is “the current suite of productivity tools”, and technology B is “AI”.
For robots, the area X is “physical labor”, technology A is “classical robotics”, and technology B is “robotics based on foundation models”.
That was just assuming hardware scaling, and it justifies a growth in some particular growth rates, but not a growth explosion. If you add in the software efficiency, then I think you are just straightforwardly generating lots of innovations (what else is leading to the improved software efficiency?) and that’s how you get the growth explosion, at least until you run out of software efficiency improvements to make.
To be clear, I don’t mean to claim that we should give special importance to current growth rates in robotics in particular. I just picked that as an example. But I do think it’s a relevant example, primarily due to the gradual nature of the abilities that robots are surpassing, and the consequent gradual nature of their employment.
Unlike fusion, which is singular in its relevant output (energy), robots produce a diversity of things, and robots cover a wide range of growth-relevant skills that are gradually getting surpassed already. It is this gradual nature of their growth-related abilities that makes them relevant, imo — because they are already doing a lot of work and already contributing a fair deal to the growth we’re currently seeing. (To clarify, I mostly have in mind industrial robots, such as these, the future equivalents of which I also expect to be important to growth; I’d agree that it wouldn’t be so relevant if we were only talking about some prototypes of robots that don’t yet contribute meaningfully to the economy.)