Overall, I think the right way to think about GDP growth in relation to utilons is that it’s a combination of removing trivial inconveniences for large numbers of people, while solving mission-critical problems for a few people, and occasionally creating positive or negative externalities through network effects that have to be analyzed on an individual basis.
There’s an argument out there that as the economy tackles low-hanging fruit, increasing innovation becomes harder to achieve. Stagnation sets in. I think this is an incomplete framing that is misleading over longer time scales.
When we think in terms of years, there are a set of tractable technological achievements, and the low-hanging fruit metaphor is appropriate here. There’s a set of problems we basically know how to solve. We put in the work to solve them roughly in order of priority, and see diminishing returns on our investment.
However, one of the knock-on effects of solving these problems is that they open up formerly intractable problems and inaccessible resources.
For example, sequencing the human genome was one an expensive and time-consuming project. It came half a century after the structure of DNA was determined, and represented the culmination of our understanding of the genome to that point.
Once we’d achieved that high-hanging fruit, however, the endeavor itself created a network of highly-skilled scientists with the knowhow to make the process cheaper and more reliable. Now it’s relatively cheap to sequence the genome. Cheap sequencing gives us access to massive amounts of genetic data. Cheap compute lets us gather and process big health data, and interpret it in the light of genetic data. All together, this lets us refocus our scientific efforts in more productive directions.
Doing all this would simply not have been possible at an earlier technological era. But the network effects that make the new wave of growth possible take time to accumulate. It takes time to build out the highway system or the internet, to figure out how to automate production of a useful product.
So we’ll see some time delay between inventing the tech that enables a network, the growth of that network to its full potential, and the harnessing of that network to drive a new wave of technological innovation.
We can’t assume that these “waves of innovation” have diminishing value over time, the way that we can assume that the automation of specific products produces diminishing value as more consumers gain access to them. They deliver value by two different mechanisms. Individual products solve particular problems. “Waves of innovation” give rise to entirely different classes of products, which may turn out to deliver widely varying average levels of utility. Even if a particular wave of innovation delivers a very high level of average utility, even an entirely efficient market can’t shortcut the technological and network growth barriers to implementing that wave. It just takes time, and the work has to be done in a certain order. The exact outcomes are not predictable in advance.
So from a local perspective on the order of years, we should focus on the diminishing returns story. On the order of decades, though, we should focus on the “waves of innovation” and network effects story, where diminishing returns is not operating.
Overall, I think the right way to think about GDP growth in relation to utilons is that it’s a combination of removing trivial inconveniences for large numbers of people, while solving mission-critical problems for a few people, and occasionally creating positive or negative externalities through network effects that have to be analyzed on an individual basis.
There’s an argument out there that as the economy tackles low-hanging fruit, increasing innovation becomes harder to achieve. Stagnation sets in. I think this is an incomplete framing that is misleading over longer time scales.
When we think in terms of years, there are a set of tractable technological achievements, and the low-hanging fruit metaphor is appropriate here. There’s a set of problems we basically know how to solve. We put in the work to solve them roughly in order of priority, and see diminishing returns on our investment.
However, one of the knock-on effects of solving these problems is that they open up formerly intractable problems and inaccessible resources.
For example, sequencing the human genome was one an expensive and time-consuming project. It came half a century after the structure of DNA was determined, and represented the culmination of our understanding of the genome to that point.
Once we’d achieved that high-hanging fruit, however, the endeavor itself created a network of highly-skilled scientists with the knowhow to make the process cheaper and more reliable. Now it’s relatively cheap to sequence the genome. Cheap sequencing gives us access to massive amounts of genetic data. Cheap compute lets us gather and process big health data, and interpret it in the light of genetic data. All together, this lets us refocus our scientific efforts in more productive directions.
Doing all this would simply not have been possible at an earlier technological era. But the network effects that make the new wave of growth possible take time to accumulate. It takes time to build out the highway system or the internet, to figure out how to automate production of a useful product.
So we’ll see some time delay between inventing the tech that enables a network, the growth of that network to its full potential, and the harnessing of that network to drive a new wave of technological innovation.
We can’t assume that these “waves of innovation” have diminishing value over time, the way that we can assume that the automation of specific products produces diminishing value as more consumers gain access to them. They deliver value by two different mechanisms. Individual products solve particular problems. “Waves of innovation” give rise to entirely different classes of products, which may turn out to deliver widely varying average levels of utility. Even if a particular wave of innovation delivers a very high level of average utility, even an entirely efficient market can’t shortcut the technological and network growth barriers to implementing that wave. It just takes time, and the work has to be done in a certain order. The exact outcomes are not predictable in advance.
So from a local perspective on the order of years, we should focus on the diminishing returns story. On the order of decades, though, we should focus on the “waves of innovation” and network effects story, where diminishing returns is not operating.