- The highway to serfdom (pdf) Gus DiZerega, Cosmos + Taxis
- Russia’s greatest river Farah Abdessamad, ARB
- A marketplace and a temple (h/t Michalis) Michael Kulikowski, LRB
- “politics are now entirely a consumer-branding exercise” Antonio Garcia-Martinez, TPR
- The politics of self-esteem Mikko Tolonen, Liberty Matters
- Between Allah and America Farzana Shaikh, Literary Review
- A history of the Russian bathhouse Rachel Polonsky, NYRB
- But when will Conor Friedersdorf leave the Atlantic?
Like some of my role models, I am inspired by Isaac Asimov’s vision. However, for years, the central ability at the heart of the Foundation series–‘psychohistory,’ which enables Hari Seldon, the protagonist, to predict broad social trends across thousands of galaxies over thousands of years–has bothered me. Not so much because of its impact in the fictional universe of Foundation, but for how closely it matches the real-life ideas of predictive modeling. I truly fear that the Seldon Fallacy is spreading, building up society’s exposure to negative, unpredictable shocks.
The Seldon Fallacy: 1) It is possible to model complex, chaotic systems with simplified, non-chaotic models; 2) Combining chaotic elements makes the whole more predictable.
The first part of the Seldon Fallacy is the mistake of assuming reducibility, or more poetically, of NNT’s Procustean Bed. As F.A. Hayek asserted, no predictive model can be less complex than the model it predicts, because of second-order effects and accumulation of errors of approximation. Isaac Asimov’s central character, Hari Seldon, fictionally ‘proves’ the ludicrous fallacy that chaotic systems can be reduced to ‘psychohistorical’ mathematics. I hope you, reader, don’t believe that…so you don’t blow up the economy by betting a fortune on an economic prediction. Two famous thought experiments disprove this: the three-body problem and the damped, driven oscillator. If we can’t even model a system with three ‘movers’, because of second-order effects, how can we model interactions between millions of people? Basically, with no way to know which reductions in complexity are meaningful, Seldon cannot know whether, in laying his living system into a Procustean bed, he has accidentally decapitated it. Using this special ability, while unable to predict individuals’ actions precisely, Seldon can map out social forces with such clarity that he correctly predicts the fall of a 10,000-year empire. Now, to turn to the ‘we can predict social, though not individual futures’ portion of the fallacy: that big things are predictable even if their consituent elements are not.
The second part of the Seldon Fallacy is the mistake of ‘the marble jar.’ Not all randomnesses are equal: drawing white and black marbles from a jar (with replacement) is fundamentally predictable, and the more marbles drawn, the more predictable the mix of marbles in the jar. Many models depend on this assumption or similar ones–that random events distribute normally (in the Gaussian sense) in a way that increases the certainty of the model as the number of samples increases. But what if we are not observing independent events? What if they are not Gaussian? What if someone tricked you, and tied some marbles together so you can’t take out only one? What if one of them is attached to the jar, and by picking it up, you inadvertently break the jar, spilling the marbles? Effectively, what if you are not working with a finite, reducible, Gaussian random system, but an infinite, Mandelbrotian, real-world random system? What if the jar contains not marbles, but living things?
I apologize if I lean too heavily on fiction to make my points, but another amazing author answers this question much more poetically than I could. Just in the ‘quotes’ from wise leaders in the introductions to his historical-fantasy series, Jim Butcher tells stories of the rise and fall of civilizations. First, on cumulative meaning:
“If the beginning of wisdom is in realizing that one knows nothing, then the beginning of understanding is in realizing that all things exist in accord with a single truth: Large things are made of smaller things.
Drops of ink are shaped into letters, letters form words, words form sentences, and sentences combine to express thought. So it is with the growth of plants that spring from seeds, as well as with walls built from many stones. So it is with mankind, as the customs and traditions of our progenitors blend together to form the foundation for our own cities, history, and way of life.
Be they dead stone, living flesh, or rolling sea; be they idle times or events of world-shattering proportion, market days or desperate battles, to this law, all things hold: Large things are made from small things. Significance is cumulative–but not always obvious.”
–Gaius Secundus, Academ’s Fury
Second, on the importance of individuals as causes:
“The course of history is determined not by battles, by sieges, or usurpations, but by the actions of the individual. The strongest city, the largest army is, at its most basic level, a collection of individuals. Their decisions, their passions, their foolishness, and their dreams shape the years to come. If there is any lesson to be learned from history, it is that all too often the fate of armies, of cities, of entire realms rests upon the actions of one person. In that dire moment of uncertainty, that person’s decision, good or bad, right or wrong, big or small, can unwittingly change the world.
But history can be quite the slattern. One never knows who that person is, where he might be, or what decision he might make.
It is almost enough to make me believe in Destiny.”
–Gaius Primus, Furies of Calderon
If you are not convinced by the wisdom of fiction, put down your marble jar, and do a real-world experiment. Take 100 people from your community, and measure their heights. Then, predict the mean and distribution of height. While doing so, ask each of the 100 people for their net worth. Predict a mean and distribution from that as well. Then, take a gun, and shoot the tallest person and the richest person. Run your model again. Before you look at the results, tell me: which one do you expect shifted more?
I seriously hope you bet on the wealth model. Height, like marble-jar samples, is normally distributed. Wealth follows a power law, meaning that individual datapoints at the extremes have outsized impact. If you happen to live in Seattle and shot a tech CEO, you may have lowered the mean income in the group by more than the average income of the other 99 people!
So, unlike the Procustean Bed (part 1 of the Seldon Fallacy), the Marble Jar (part 2 of the Seldon Fallacy) is not always a fallacy. There are systems that follow the Gaussian distribution, and thus the Marble Jar is not a fallacy. However, many consequential systems–including earnings, wars, governmental spending, economic crashes, bacterial resistance, inventions’ impacts, species survival, and climate shocks–are non-Gaussian, and thus the impact of a single individual action could blow up the model.
The crazy thing is, Asimov himself contradicts his own protagonist in his magnum opus (in my opinion). While the Foundation Series keeps alive the myth of the predictive simulation, my favorite of his books–The End of Eternity (spoilers)–is a magnificent destruction of the concept of a ‘controlled’ world. For large systems, this book is also a death knell even of predictability itself. The Seldon Fallacy–that a simplified, non-chaotic model can predict a complex, chaotic reality, and that size enhances predictability–is shown, through the adventures of Andrew Harlan, to be riddled with hubris and catastrophic risk. I cannot reduce his complex ideas into a simple summary, for I may decapitate his central model. Please read the book yourself. I will say, I hope that as part of your reading, I hope you take to heart the larger lesson of Asimov on predictability: it is not only impossible, but undesirable. And please, let’s avoid staking any of our futures on today’s false prophets of predictable randomness.
Recently, I came across this outstanding interview with Eugene Fama published by The Market / NZZ. Besides the main subject discussed -the inability of central banks to control inflation-, the interview is intertwined with gripping assertions about the limits of knowledge, such as the following ones:
Bubbles are things people see in hindsight. They don’t identify them in advance. Sure, you can look at the behavior of prices, and you may be able to identify cases where they are too high. But if you only look back and say: «Oh, stocks went down a lot, so that was a bubble», then that’s 20/20 hindsight. At the time, there was no evidence that there was a bubble.
I don’t say markets are completely efficient, but they’re efficient for most questions that I address. Models are never a 100 % true. If they were, we would call them reality, not models. But for almost all purposes, market efficiency is a very good approximation.
The real question is: How do you pick Warren Buffett? The way you pick him is after the fact, since he has done very well. Now, suppose I take 100,000 investors and say: Let’s let them run for 30 years and pick out the winner. Because you roll the dice so many times, even if none of them is a good or bad investor, many investors will do well and many will do poorly purely by chance. Statistically there is also going to be a big winner, but solely due to chance. In other words: There will be extremely good outcomes and extremely bad outcomes, but you just can’t tell who is successful because of luck and who because of skill.
This quotations resemble the distinction made by Friedrich Hayek between relative and absolute limits to explanation (The Sensory Order, 1952):
8.67. Apart from these practical limits to explanation, which we may hope continuously to push further back, there also exists, however, an absolute limit to what the human brain can ever accomplish by way of explanation -a limit which is determined by the nature of the instrument of explanation itself, and which is particularly relevant to any attempt to explain particular mental processes.
8.68. If our account of the process of explanation is correct, it would appear that any apparatus or organism which is to perform such operations must possess certain properties determined by the properties of the events which it is to explain. If explanation involves that kind of joint classification of many elements which we have described as “model-building”, the relation between the explaining agent and the explained object must satisfy such formal relations as must exist between any apparatus of classification and the individual objects which it classifies (Cf. 5.77-5.91).
5.90. The model building by such an apparatus of classification simplifies the task and extends the scope of successful adaptation in two ways: it selects some elements from a complex environment as relevant for the prediction of events which are important for the persistence of the structure, and it treats them as instances of classes of events. But while in this way a model building apparatus (and particularly one that can be constantly improved by learning) is of much greater efficiency than could be any more mechanical apparatus which contained, as it were, a few fixed models of typical situations, there will clearly still exist definite limits to the extent to which such a microcosm can contain an adequate reproduction of the significant factors of the macrocosm.
8.69. The proposition which we shall attempt to establish is that any apparatus of classification must possess a structure of a higher degree of complexity than is possessed by the objects which it classifies; and that, therefore, the capacity of any explaining agent must be limited to objects with a structure possessing a degree of complexity lower than its own. […]
Being confronted with an absolute limit to explanation does not mean that chaos lies outside those limits. Indeed, what we have beyond the scope of our models is a complex order -in this case, efficient markets. A kind of order whose “[…] existence need not manifest itself to our senses but may be based on purely abstract relations which we can only mentally reconstruct” (F. A. Hayek, “Law, Legislation, and Liberty”, Chapter II; 1973), and because of that its explanation finds not practical limits but absolute ones. For example, in this field, “passive investing” would be homologous to a law-abiding behaviour or to the moral saying “being honest is the best policy”. Of course, for such systems -economic, legal or moral- to evolve there have to be some “prices”, i.e.: people who trade in the short term or who perform innovative behaviours which establish a new legal precedent or a new habit.
But for this innovation to happen it is indispensable for the agents to count on a framework of stable regularities -usually called abstract or spontaneous orders- upon which they could draw their own “maps”, create new expectations, and coordinate their plans with other agents. That indicates that we have already spent enough ink writing about the economic way of looking at the law, and perhaps it is time to start pondering markets as complex normative systems.
- How Communist is China today? Rong Jian, Reading the China Dream
- Women in academia and Parisian literary life Ann Smith, Dublin Review of Books
- Hayek, international organization, and Covid-19 (video) Edwin van de Haar, Institute of Economic Affairs
- “Hayekian Spontaneous Order and the International Balance of Power” Edwin van de Haar, Independent Review
- Greco-Roman civilisation has dominated ancient history for too long Philip Womack, Spectator
- The reaction against the End of History Nick Nielsen, Grand Strategy Annex
- Hayek at the hospital; the Use of Knowledge in hospital discharge decisions Irfan Khawaja, Policy of Truth
- Don’t mistake the immediate for the important Michael Koplow, Ottomans & Zionists
Just to inform all NOL-readers out there, if you like the subject, please register and join the IEA webinar I’ll give next wednesday, 13.00 hours, London time.
Institute of Economic Affairs > Events
13:00 – 14:00
Although it was never the subject of a book, Friedrich Hayek wrote a lot about international relations during his long career and had rather firm views on international order and how it could be achieved. In this webinar, these Hayekian views are presented in the context of the current COVID-crisis. What was Hayek’s opinion about the existence and the role of international governmental organizations, such as the World Health Organization?
Dr. Edwin van de Haar (www.edwinvandehaar.com) is an independent scholar who specializes in the liberal tradition in international political theory. He has been a (visiting) lecturer at Brown University, Leiden University and Ateneo de Manila University. Van de Haar is the author of Classical Liberalism and International Relations Theory. Hume, Smith, Mises and Hayek (2009), Beloved Yet Unknown. The Political Philosophy of Liberalism (2011, in Dutch) and Degrees of Freedom. Liberal Political Philosophy and Ideology (2015). Among others, he contributed to The Oxford Handbook of Adam Smith (2013) and a forthcoming book on The Liberal International Theory Tradition in Europe, while his articles on liberal ideas and liberal thinkers appeared among others in Review of International Studies, International Relations, International Politics, Independent Review and Economic Affairs.
Van de Haar got his PhD in International Politcial Theory from Maastricht Universit in 2008, and holds master degrees in international relations (London School of Economics and Political Science) and in political science (Leiden University).
(Ooops, lol. I hope all of NOL‘s American readers had a good Memorial Day, and that everybody else had a good Monday. The Glasner piece is an excellent discussion of the Austrian School of Economics.)
- An Austrian (School) tragedy David Glasner, Uneasy Money
- An Austrian (School) tragedy David Glasner, Uneasy Money