My initial impulses on the stagnation issue were different from the direction I ended up taking in my first post in response to the recent paper by Bloom, Jones, Van Reenen, and Webb [1]. Here’s what I said in a note to Tyler Cowen:
I’ve been working my way through the Bloom, Jones et al. article linked from this interview. Interesting stuff. And, yes, of course, measuring ideas is a puzzle. Memeticists have discussed the problem, but memetics has never managed intellectual seriousness very well. [...]
There seems to be an implicit assumption that unit ideas, whatever they may be, are more or less independent entities. Unit ideas aside, actual ideas aren’t at all independent of one another. There are asymmetric dependencies and codependencies, some of which can be guessed at by looking at citation patterns. And there surely is path dependence & the longer you go on in a specific line of investigation, the longer and longer the path leading to the latest useful idea. And that useful idea may well depend on long paths emanating from a half dozen different sources, so you’ve also got a coordination problem as no one person knows all the hinterlands feeding streams into this particular delta. You’ve got to have a team and they have to talk with one another, etc.
Why? Because that’s how the world is?
I ended up concentrating on “how the world is” without saying much about the structure of ideas. Of course, it is the way of the world to force proliferation and complexity in the structure of ideas.
Now that I’ve said a bit about how the world is, I’d like to say bit about ideas. First of all I simply want to reiterate what I’ve said above: ideas are not in fact atomic entities bouncing around. They’re intimately intertwined with one another. We all know this; it’s there in the citation structure of the article, books, and monographs we publish. And we know that some ideas, whatever they are, are more important that others. That too is obvious in the citation structure. BJV&W know it too, not simply as tacit knowledge about the academy, but as foreground knowledge in their research.
Let me cite two passage of moderate length, both from their methodological preliminaries. In this passage they’re discussing their choice of case studies (pp. 3-4):
Our selection of cases is driven primarily by the requirement that we are able to obtain data on both the “idea output” and the corresponding “research input.” We looked into a large number of possible cases to study, only a few of which have made it into this paper; indeed, we wanted to report as many cases as possible. For example, we also considered the internal combustion engine, the speed of air travel, the efficiency of solar panels, the Nordhaus (1997) “price of light” evidence, and the sequencing of the human genome. We would have loved to report results for these cases. In all of them, however, it was relatively easy to get an “idea output” measure. However, it proved impossible to get a series for the research input that we felt corresponded to the idea output. For example, the Nordhaus price of light series would make a great additional case. However, many different types of research contribute to the falling price of light, including the development of electric generators, the discovery of compact fluorescent bulbs, and the discovery of LEDs. We simply did not know how to construct a research series that would capture all the relevent R&D. The same problem applies to the other cases we considered but could not complete. For example, it is possible to get R&D spending by the government and by a few select companies on sequencing the human genome. But it turns out that Moore’s Law is itself an important contributor to the fall in the price of gene sequencing. How should we combine these research inputs? In the end, we report the cases in which we felt most confident.
There it is, right there in the middle in their discussion of Nordhaus (which sounds fascinating): “many different types of research contribute to the falling price of light”. Right. To some degree or another it’s all like that.
A bit later they bring up the problem of measurement (p. 5):
Even as simple a question as “What are the units of ideas?” is troublesome. We follow much of the literature — including Aghion and Howitt (1992), Grossman and Helpman (1991), and Kortum (1997) — and define ideas to be in units so that a constant flow of new ideas leads to constant exponential growth in A. For example, each new idea raises incomes by a constant percentage (on average), rather than by a certain number of dollars. This is the standard approach in the quality ladder literature on growth: ideas are proportional improvements in productivity. The patent statistics for most of the 20th century are consistent with this view; indeed, this was a key piece of evidence motivating Kortum (1997). This definition means that the left hand side of equation (1) corresponds to the flow of new ideas. However, this is clearly just a convenient definition, and in some ways a more accurate title for this paper would be “Is exponential growth getting harder to achieve?”
They aren’t discussing ideas in any psychologically, linguistically, or, for that matter, philosophically robust sense. They’re just a unit of measure and what they measure would seem to be something like research effort.
They’re right about their suggestion for a better title. It is more accurate. But I suppose they’re contributing to (contending with?) a research tradition that has its conventions, and talk of ideas is one of them.
And so I ask: What’s the point of that convention? And I ask that question as an outsider. I’m not an economist, so of course I’m an outsider. But that’s not what I mean. I am now playing the role of an outsider, an ethnographer of anthropology if you will, and I want to know what the natives are up to. I’ve not been in this role long so what I have to say is speculative, to say the least. But still...
Of course ideas, whatever they may be, ARE involved, so there’s (at least) that. But the thing about ideas are that they’re within the human realm. We have some measure of control over them. We even have various kinds of legal regulation of ideas, freedom of speech with all that entails, and intellectual property of various kinds. So maybe there’s something we can do that will get the ideas flowing again and make exponential growth more tractable.
Is that it? How would I know, I just thought it up. Moreover, as I’ve remarked in earlier posts in this series, I think that the problem that has been identified in this literature has to do with the structure of the world, and I mean that in the fullest sense. It’s not simply the world “out there” exclusive of us humans. It is THAT plus us. What these economists are staring at is the cost of gaining ever deeper knowledge of the world.
Here is a (crudely drawn) logistics curve:
The further you move up that curve, the more difficult it gets. That’s what’s being measure in this literature. The proliferation of papers, and the complex linkage between ideas, the sense of “learning more and more about less and less”, that’s what happens as we move up that curve.
And when we get to the top, what then? It’s a new world, with new challenges. Maybe we rest; maybe we just ramble about on the plateau. But sooner or later, it’s up the hill. But a different hill. Like so:
By my count, not just mine, but mine and Dave Hays’s (but really, many others as well), we’ve made it up three levels and we’re climbing the fourth [2]. The commonest term for that next plateau is The Singularity, which is generally taken to imply superintelligent computers programming themselves to exponentially increasing levels of “intelligence”, whatever that is. I think that’s, if not nonsense, something pretty close (not even wrong?). I expect amazing things from computers. But I also expect much deeper knowledge about them, and many other things, in us [3].
And that will be the subject of Stagnation 2.0: [some appropriate subtitle].
References
[1] Nicholas Bloom, Charles I. Jones, John Van Reenen, and Michael Webb, Are Ideas Getting Harder to Find? March 5, 2018, https://web.stanford.edu/~chadj/IdeaPF.pdf.
[2] William Benzon, Mind-Culture Coevolution: Major Transitions in the Development of Human Culture and Society, Version 2, November 29, 2018, 10 pp., https://www.academia.edu/37815917/Mind-Culture_Coevolution_Major_Transitions_in_the_Development_of_Human_Culture_and_Society.
[3] William Benzon, Redefining the Coming Singularity – It’s not what you think, Version 2, November 2015, pp. 14, https://www.academia.edu/8847096/Redefining_the_Coming_Singularity_It_s_not_what_you_think.
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