This is a reading diary of a naïve complexity / computational social scientist’s first encounter with F. A. Hayek + Eastern Bloc tektology & cybernetics.
You might have heard about project Cybersyn? In 1970s Chile, Salvador Allende’s socialist regime was betting on a systems-theoretical approach to the complex decision-making that’s an inevitable consequence of a planned economy. Captain Kirk would feel at home as operators were rocking the latest cybernetic algorithms. That all ended with the US-backed military coup that installed Augusto Pinochet as a dictator. But was that also the end of complex-systems ideas in Chile’s government? Oh no! Pinochet called in economist F. A. Hayek—a vanguard of complexity economics and a firm believer in emergence and self-organization for the social good—to kick-start a Chilean free-market economy.
In its broadest sense, is complexity science spacious enough to support any ideology? Curious about that, I went on a weeklong tour to the border zone between complexity science and Austria, with a brief detour to Novosibirsk. Honestly, I’m still very much a novice at this topic—take this blog post as a travelogue. Hopefully, I will return to the theme with something more erudite.
Before this journey, I had seen Hayek mentioned as a complexity-science forerunner, one of the first to see emergence (“spontaneous order”) as a key to understanding society. Such sources also described him as a liberal ideologue and staunch advocate of the free market. Sometimes, I also read his Wikipedia article and remember his controversies: racist comments, defense of Pinochet’s dictatorship, and the condemnation of the international sanctions of South African apartheid. Oh, and that the apex of his life was when he met Queen Elizabeth II. Hmm, well, let’s go on with the science.
Tuesday: Hayek’s Nobel prize lecture “The pretence of knowledge”
Where else to start? This was Hayek in the limelight, touching on many of his ideas about complexity. This “pretence of knowledge,” Hayek argues, comes from approaching the social sciences like natural science. Hmm, this was my first surprise. (I later learned that rejecting formal models is a hallmark of the Austrian school—to which Hayek is usually counted.) Why, then, would he be a pioneer of complexity science (that wholly embraces the natural-scientific method)?
Hayek’s argument, same as published decades earlier in The Counter-Revolution of Science is that social processes are complex, with many hidden mechanisms that render them unpredictable from observables. Trusting data without understanding the mechanisms could lead to faulty conclusions. It is hard to disagree with that.
Hayek’s main target was orthodox, neo-classical economics, and his arguments are similar to Arthur-style complexity economics would use decades later. Would he be OK with the mechanistic modeling of the latter? Well, Hayek managed to lambast the (then two-year-old) Limits to Growth—unsurprisingly, since it calls for state interventions at many levels. Still, the systems dynamics model Limits to Growth relies on is not too far, in spirit, from modern complex systems modeling. On the other hand, Hayek uses “organized complexity,” referring to Warren Weaver’s 1948 paper where he predicts the aid of computers and interdisciplinary collaborations will be how to elucidate complex systems in the future. Hmm, how does this all come together?
Wednesday: Axtell’s “Hayek enriched by complexity enriched by Hayek”
Next stop, a paper by Robert Axtell, whose writing I’ve always admired. (The time I got to ride in Axtell’s vintage sports car, I probably felt as starstruck as Hayek meeting Queen Elizabeth.)
The essay’s premise is that complexity science could have helped Hayek and can still learn from Austrian economics. Axtell assumes that Hayek’s aversion to mathematical modeling does not extend to, e.g., agent-based models (ABMs) and proposes to rebuild Hayek’s theories within the framework of complexity economics. Thereby Austrian economics would have a sporting chance to break the orthodoxy because “it takes a model to beat a model.”
Axtell also claims that knowledge from Hayek would benefit today’s agent-based modelers. He lists some insights—e.g., “the conventional theory of general equilibrium is sufficiently incredible computationally that almost any market process story is preferable”—none of which seem unfamiliar to complexity scientists. On the other hand, it is reassuring that a prominent scholar of a different era and from different premises has reached the same insights.
Thursday: Hayek’s “The theory of complex phenomena”
From the title, this seems like a must-read for complexity scientists, but it turned out somewhat disappointing. It is not about how to theorize complex phenomena but how to not misunderstand them. Hayek points out that “statistics” of a few variables will not produce any laws like in the natural sciences since there would always be other processes lurking in the background. (Maybe Hayek would have liked deep learning more than regression.) Furthermore, statistical theories of complex phenomena “can only in the rarest of instances be turned into specific predictions of what will happen in a particular case, because we can hardly ever ascertain all the facts which will contribute to determine the outcome.”
As in the Nobel lecture (and The Counter-Revolution of Science), there is little constructive in terms of how to understand complex systems. Nearly all the discussion goes to show how incapable we are
Friday: Hayek’s “The use of knowledge in society”
This is one of his most influential works, an instant classic which allegedly turned the tide against planned economies in some circles of American economists. Hayek’s main argument is that it is futile trying to make society more efficient through central modeling, data analysis, and calculation. Since data is inevitably incomplete and models perfunctory, they would never be able to compete with market forces able to tap into the collective intelligence and integrate local knowledge, tacit or not.
After reading The use of knowledge, I wonder if Axtell would manage to recruit (a time-transported) Hayek to his ABM project. Parametrizing ABMs to optimally price all products, hmm, that sounds like a tall order. Of course, the usual questions for ABMs are sketchier, but would they interest Hayek? Aren’t conclusions from ABM scenario testing the general kind of statements Hayek denounced in The theory of complex phenomena?
Furthermore, Hayek did know that simulating social systems was an option but must have thought writing lengthy essays was a better methodology. If I meet him on the other side of the river, the first thing I would ask is that: if he has a theory in words but can’t turn it into a simulation model that reproduces reality, then why should I trust him? To that, he at least wouldn’t be able to retort that he can reach the same conclusions by deductive reasoning, because to that, he has given the perfect counterarguments.
Saturday: Is SFI a neoliberal think tank?
Looking for Hayek papers also led me to some intriguing 2022 papers from the field of science and technology studies:
- F Li Vigni, Hayek at the Santa Fe Institute: Origins, models, and organization of the cradle of complexity sciences
- E Baker. The ultimate think tank: The rise of the Santa Fe Institute libertarian.
Both point out that science and management at the SFI are coevolving and are at the service of neoliberal stakeholders. “[T]here exists a liaison between complexity science and the theories and practices of liberalism.” Hmm, I think most of the liberalism you can see in SFI’s management has exogenous reasons. Given that it is an American institute relying on private funding, what can one expect? And the science? Yeah, slime molds are pretty laissez-faire when you think about it. The game of life doesn’t evolve into a socialist utopia. (Or does it?) I.e., I’m skeptical that there is much politics in the bulk of SFI’s science, but please read these papers and make up your mind.
Sunday: Cybernetics in Soviet
Let’s go back to the other side of the political spectrum. Systems science, cybernetics, and those more engineering-minded fields related to, or overlapping with, complexity science have a stronger focus on controlling (rather than explaining) complex systems (cf. Project Cybersyn above). Clearly, they should be interesting for planning / commanding economies. Interestingly, such ideas never took off in the governance of the Soviet Union. Cybernetics was introduced with some resistance, and by the time it reached the actual administration, it was so watered down that it had little practical influence.
Scientifically, there were significant developments at the Novosibirsk State University, sufficiently distanced from Moscow, under the leadership of Leonid Kantorovich, who (closing the circle) was awarded the Nobel economics prize the year after Hayek. That is on my reading list, and this paper could be a good start.
For the final day of this tour, we stay in Russia but return to the time around the Bolshevik revolution.
Who was first with the ideas of complexity and systems science? It’s an impossible question to answer precisely since the further back in time we go, the more generous we can be with the similarity to modern ideas. One of those very early contenders is Alexander Bogdanov. His “Essays in tektology: The universal organizational science” indeed has many commonalities with the complexity science of today. One point that impressed me is that Bogdanov sees the need for integrative, multidisciplinary science and that such science inevitably has to do with organization (which I read as, down the line, network science). It’s also fascinating just how general he imagined the applications of his tektology to be—from anthropology to interstellar space, from disordered magnets to comparative linguistics.
Bogdanov was a Bolshevik but still critical of Lenin. (Guess how Bogdanov died? . . . No. Actually, by poisoning himself in an experiment to stop aging.) So tektology also had applications to contemporary politics (the theme of this post), the organization of the proletariat, etc. Those passages are, however, hard to parse over a century later with little contextual knowledge.
After-trip photo album slide show
After this journey, I still think ideas and results of the complexity and systems sciences are so broad that anyone politically inclined can find content to appropriate. Evidently, for some (Hayek), political motives can also be a scientific driving force.
I have more questions than answers about this topic. The biggest is very general—how does the politics of the day shape science, and how does this change with the times and topics? Of course, this is nothing new, meaning there are plenty of books to read, including a new Hayek biography.
The videos below give some feeling for two of the key characters in this post. I’m tempted to call Beer the “Orson Welles of cybernetics,” but what would the corresponding epithet be for Hayek?