I’ve long been very suspicious of aggregate economic measures like GDP. But GDP is clearly measuring something, and whatever that something is it seems to increase remarkably smoothly despite huge technological revolutions. So I spent some time this morning reading up and playing with numbers and generally figuring out how to think about the smoothness of GDP increase.
Major takeaways:
When new tech makes something previously expensive very cheap, GDP mostly ignores it. (This happens in a subtle way related to how we actually compute it.)
Historical GDP curves mainly measure things which are expensive ~now. Things which are cheap now are mostly ignored. In other words: GDP growth basically measures the goods whose production is revolutionized the least.
Re: AI takeoff, the right way to extrapolate today’s GDP curve to post-AI is to think about things which will still be scarce post-AI, and then imagine the growth of production of those things.
Even a very sharp, economically-revolutionary AI takeoff could look like slow smooth GDP growth, because GDP growth will basically only measure the things whose production is least revolutionized.
Why am I harping on about technicalities of GDP? Well, I hear about some AI forecasts which are heavily based on the outside view that economic progress (as measured by GDP) is smooth, and this is so robust historically that we should expect it to continue going forward. And I think this is basically right—GDP, as we actually compute it, is so remarkably smooth that we should expect that to continue. Alas, this doesn’t tell us very much about how crazy or sharp AI takeoff will be, because GDP (as we actually compute it) systematically ignores anything that’s revolutionized.
In writing How much should we value life?, I spent some time digging into AI timeline stuff. It lead me to When Will AI Be Created?, written by Luke Muehlhauser for MIRI. He noted that there is reason not to trust expert opinions on AI timelines, and that trend extrapolation may be a good alternative. This point you’re making about GDP seems like it is real progress towards coming up with a good way to do trend extrapolation, and thus seems worth a full post IMO. (Assuming it isn’t already well known by the community or something, which I don’t get the sense is the case.)
My first reaction to the framing of the paper is to ask: growth in what? It’s important to keep in mind that concepts like “gross domestic product” and “world gross domestic product” were defined from an explicit anthropocentric perspective—they measure the total production of final goods within a certain time period. Final goods are what is either consumed by humans (e.g. food or human services) or what is invested into “capital goods” that last for multiple periods (e.g. a server farm) to produce consumption goods for humans.
Now imagine you are a highly intelligent AI system running on the cloud. Although the production of the server farms on which you depend enters into human GDP (as a capital good), most of the things that you absorb, for example energy, server maintenance, etc., count as “intermediate goods” in our anthropocentric accounting systems and do not contribute to human GDP. In fact, to the extent that the AI system drives up the price of scarce resources (like energy) consumed by humans, real human GDP may even decline.
As a result, it is conceivable (and, to be honest, one of the central scenarios for me personally) that an AI take-off occurs but anthropocentric GDP measures show relative stagnation in the human economy.
To make this scenario a bit more tangible, consider the following analogy: imagine a world in which there are two islands trading with each other, but the inhabitants of the islands are very different from each other—let’s call them humans and AIs. The humans sell primitive goods like oil to the AIs and their level of technology is relatively stagnant. The AIs sell amazing services to the humans, and their level of technology doubles every year. However, the AI services that humans consume make up only a relatively small part of the human consumption basket. The humans are amazed at what fantastic services they get from the AIs in exchange for their oil, and they experience improvements in their standard of living from these fantastic AI services, although they also have to pay more and more for their energy use every year, which offsets part of that benefit. The humans can only see what’s happening on their own island and develop a measure of their own well-being that they call human GDP, which increases modestly because the advances only occur in a relatively small part of their consumption basket. The AIs can see what’s going on on the AI island and develop a measure of their own well-being which they call AI GDP, and which almost doubles every year. The system can go on like this indefinitely.
For a fuller discussion of these arguments, let me refer you to my working paper on “The Rise of Artificially Intelligent Agents” (with the caveat that the paper is still a working draft).
In general, Baumol type effects (spending decreasing in sectors where productivity goes up), mean that we can have scenarios in which the economy is growing extremely fast on “objective” metrics like energy consumption, but GDP has stagnated because that energy is being spent on extremely marginal increases in goods being bought and sold.
I’ve long been very suspicious of aggregate economic measures like GDP. But GDP is clearly measuring something, and whatever that something is it seems to increase remarkably smoothly despite huge technological revolutions. So I spent some time this morning reading up and playing with numbers and generally figuring out how to think about the smoothness of GDP increase.
Major takeaways:
When new tech makes something previously expensive very cheap, GDP mostly ignores it. (This happens in a subtle way related to how we actually compute it.)
Historical GDP curves mainly measure things which are expensive ~now. Things which are cheap now are mostly ignored. In other words: GDP growth basically measures the goods whose production is revolutionized the least.
Re: AI takeoff, the right way to extrapolate today’s GDP curve to post-AI is to think about things which will still be scarce post-AI, and then imagine the growth of production of those things.
Even a very sharp, economically-revolutionary AI takeoff could look like slow smooth GDP growth, because GDP growth will basically only measure the things whose production is least revolutionized.
Why am I harping on about technicalities of GDP? Well, I hear about some AI forecasts which are heavily based on the outside view that economic progress (as measured by GDP) is smooth, and this is so robust historically that we should expect it to continue going forward. And I think this is basically right—GDP, as we actually compute it, is so remarkably smooth that we should expect that to continue. Alas, this doesn’t tell us very much about how crazy or sharp AI takeoff will be, because GDP (as we actually compute it) systematically ignores anything that’s revolutionized.
If you want a full post on this, upvote this comment.
In writing How much should we value life?, I spent some time digging into AI timeline stuff. It lead me to When Will AI Be Created?, written by Luke Muehlhauser for MIRI. He noted that there is reason not to trust expert opinions on AI timelines, and that trend extrapolation may be a good alternative. This point you’re making about GDP seems like it is real progress towards coming up with a good way to do trend extrapolation, and thus seems worth a full post IMO. (Assuming it isn’t already well known by the community or something, which I don’t get the sense is the case.)
Upvoted, but I mostly trust you to write the post if it seems like there’s an interesting meaty thing worth saying.
Eh, these were the main takeaways, the post would just be more details and examples so people can see the gears behind it.
A similar point is made by Korinek in his review of Could Advanced AI Drive Explosive Economic Growth:
In general, Baumol type effects (spending decreasing in sectors where productivity goes up), mean that we can have scenarios in which the economy is growing extremely fast on “objective” metrics like energy consumption, but GDP has stagnated because that energy is being spent on extremely marginal increases in goods being bought and sold.