by wjw on January 7, 2021

So after watching the US Capitol stormed by a hostile force for the first time since the War of 1812, and after hearing reporters bleating out their catchphrase, “Who could have predicted this? (usually employed when something happens that is completely predictable), I bethought myself of an article I first read in November of 2019, which opens thus:

In its first issue of 2010, the scientific journal Nature looked forward to a dazzling decade of progress. By 2020, experimental devices connected to the internet would deduce our search queries by directly monitoring our brain signals. Crops would exist that doubled their biomass in three hours. Humanity would be well on the way to ending its dependency on fossil fuels.

A few weeks later, a letter in the same journal cast a shadow over this bright future. It warned that all these advances could be derailed by mounting political instability, which was due to peak in the US and western Europe around 2020. Human societies go through predictable periods of growth, the letter explained, during which the population increases and prosperity rises. Then come equally predictable periods of decline. These “secular cycles” last two or three centuries and culminate in widespread unrest – from worker uprisings to revolution.

In recent decades, the letter went on, a number of worrying social indicators – such as wealth inequality and public debt – had started to climb in western nations, indicating that these societies were approaching a period of upheaval. The letter-writer would go on to predict that the turmoil in the US in 2020 would be less severe than the American civil war, but worse than the violence of the late 1960s and early 70s, when the murder rate spiked, civil rights and anti-Vietnam war protests intensified and domestic terrorists carried out thousands of bombings across the country.

The article was by Peter Turchin, a Russian-born biologist who in recent decades defected to the study of history, and who built on the work of mathematician-turned-historian Jack Goldstone, a pioneer of analyzing Big Data to describe history.

Goldstone recognised that the different components of a society – state, elites, masses – would respond differently to strain, but that they would also interact. In other words, he was dealing with a complex system whose behaviour was best captured mathematically. His model of why revolutions occur consists of a set of equations, but a crude verbal description goes something like this: as the population grows there comes a point where it outstrips the ability of the land to support it. The standard of living of the masses falls, increasing their potential for violent mobilisation. The state tries to counteract this – for example, by capping rents – but such measures alienate the elite whose financial interests they hurt. Since the elite has also been expanding, and competing ever more fiercely for a finite pool of high-status jobs and trappings, the class as a whole is less willing to accept further losses. So the state must tap its own coffers to quell the masses, driving up national debt. The more indebted it becomes, the less flexibility it has to respond to further strains. Eventually, marginalised members of the elite side with the masses against the state, violence breaks out and the government is too weak to contain it.

Goldstone suggested ways of measuring mass mobilisation potential, elite competition and state solvency, and defined something he called the political stress indicator (psi or Ψ), which was the product of all three. He showed that Ψ spiked prior to the French Revolution, the English civil war and two other major 17th-century conflicts – the Ottoman crisis in Asia Minor, and the Ming-Qing transition in China. In each case, however, there had been one more factor in the mix: chance. Some tiny rupture – a harvest failure, say, or a foreign aggression – that in other circumstances might have been absorbed easily, against a backdrop of rising Ψ caused conflict to erupt. Although you could not predict the trigger – meaning you could not know precisely when the crisis would occur – you could measure the structural pressures and hence, the risk of such a crisis . . . 

As Goldstone was putting the finishing touches to his magnum opus, Revolution and Rebellion in the Early Modern World, the Soviet Union was unravelling. He pointed out that Ψ had risen dramatically across the Soviet bloc in the two decades prior to 1989, and that it was persistently high in developing countries. He also wrote that: “It is quite astonishing the degree to which the United States today is, in respect of its state finances and its elites’ attitudes, following the path that led early modern states to crisis.”

Goldstone dealt with the early modern period, but Turchin started collecting data that went back to the Neolithic, and found evidence that these same cycles had been repeating for all of history.

Turchin updated Ψ to reflect the forces shaping a modern labour market, and chose new proxies appropriate to an industrialised world. These included real wages for the mobilisation potential of the masses; filibustering rates in the Senate and the cost of tuition at Yale for elite competition; and interest rates for state solvency. Then he calculated Ψ in the US from 1780 to the present day. It was low in the so-called Era of Good Feelings around 1820, high in the 1860s – around the American civil war – and low again in the years after the second world war. Since 1970 it had risen steadily. This did not mean we were doomed to crisis, though. Many societies had avoided disaster – and Turchin was building a model to find out how they had done it . . . 

2020 is nearly upon us, and lawmaking institutions in both the US and the UK are now so divided along ideological lines that they can barely function. In both countries, disgruntled members of the elite have taken power in the name of the people, while failing to address the underlying causes of the malaise: widening inequality, a swollen elite, a fragile state.

Turchin offers a degree of optimism, however.  Things will look a lot better once we’re through the crisis— in another decade or two.

{ 5 comments… read them below or add one }

Clyde January 9, 2021 at 10:59 pm

Very interesting, and very worrying.
It appears we have the dubious pleasure of living in interesting times.

Jerry January 11, 2021 at 4:37 pm

James Blish’s real-world degree was in biology, and he used the biological term “totipotent” to refer to reflections of reflections, as seen when you’re between parallel mirrors. Let me get this straight (if “straight” is the right term here). Peter Turchin, “a Russian-born biologist” used the work of “mathematician-turned-historian Jack Goldstone, a pioneer of analyzing Big Data to describe history.” Well, he wasn’t the first. The Good Doctor A – another Russian-born biologist – invented Hari Seldon, a mathemetician-turned-historian who used Big Data to describe history. Oh my aching head – are we talking about Cyclical History or Reflections of Reflections? Never mind, either phrase will work just as well, and just as eerily. Oh, and if I’m going to come, uh, full circle, James Blish explicitly used Toynbees’s writings on Cyclical History as a framework for “The Triumph of Time,” one of the books in his “Cities in Flight” magnum opus.

John Appel January 12, 2021 at 10:12 am

The part that’s interesting to me is the quantitative part, the use of data to forecast something akin to storm conditions in meteorology. The previous examples (Toynbee, Asimov, Blish, etc.) all seem to have been more qualitative, anecdotally based. Those models are certainly useful in spotting potential patterns in the first place. But tying this in with stuff like Piketty’s work means that we may have the tools to be able to make real headway in building effective guardrails into our political and economic systems to smooth out these cycles, as well as raising overall living standards.

Of course we have to overcome the tremendous cultural, social, and psychological barriers in the way, which isn’t going to happen quickly, possibly in any of our lifetimes. But it’s amazing what humans have been able to do once we know something is possible and have some decent markers on the path to making it so.

Jerry January 12, 2021 at 7:38 pm

John Appel, I don’t know anything about Piketty other than that course I just took at the University of Wikipedia, which makes it sound as if his economics are just statistics, but never mind. I understand what you’re saying: we may be close to achieving in the real world what was out-of-this-world speculation. It’s simultaneously both a nice and a terrifying prospect. Wrong hands and all that…. Oh, and btw, I realized that A.E. van Vogt’s “Voyage of the Space Beagle” (1939) also delves explicitly into a cyclical theory of history with “spring” through “winter” stages, and what world-views are held by individuals in each stage. Mr. Williams, do you know of any sci-fi theories of cyclical history before van Vogt’s? And are you personally doing anything to weather out the breaking tempest?

Privateiron January 12, 2021 at 11:39 pm

As someone with historical training, I can tell you that cyclical theories of history are like most historical theories, based on cherry-picked data arranged in an aesthetically pleasing narrative.

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