It will soon be two years since the US presidential elections of 2016, which should have made it clear to everybody that our society is in deep crisis. The technical term in the structural-demographic theory (SDT) for it is a revolutionary situation: when the established elites are still holding the levers of power, but the social pressures for crisis have built up to the point where something has to give.
What I found remarkable as we have lived through the past two years (indeed, the past eight years since I made my prediction of the impending crisis), is how precisely we today are following the trajectory into crisis that my colleagues and I saw in the historical societies we have studied. The explanation, probably, is that the three major mechanisms driving up social pressure for crisis in the SDT work in a mutually reinforcing way. The fundamental drive (a kind of a “pump” that drives up social pressure) is the oversupply of labor, which developed after the 1970s as a result of multiple interacting factors, and more recently was made acute by technological change driving automation and robotization. Oversupply of labor is the root cause for both popular immiseration and elite over-production/intra-elite competition. Both of those factors, then, contribute to the fiscal crisis of the state, because immiserated population can’t pay taxes, while the elites work to reduce the taxes on themselves.
We saw all those mechanisms operating in our current crisis. Immiseration of large swaths of the American population was what fueled the successful campaign of a counter-elite presidential candidate, Donald Trump. Intra-elite conflict has reached unprecedented heights (since the First American Civil War), as the established elites are using various means at their disposal to get rid of the counter-elite chief of state. At the same time, a weird coalition of Trump and the established elites (remember, laws must be approved by the Congress) legislates deep cuts into the taxes the elites will pay, bringing the fiscal crisis of the state much sooner. Political violence has also reached new heights, although thankfully mostly demonstrators and counter-demonstrators are beaten up, not killed (a major exception was Charlottesville a year ago).
Until last year I thought that we collectively have a decent chance of avoiding the crisis, but I now have abandoned this hope. A major reason for my pessimism is the resolute refusal by our ruling class (including its both Liberal and Conservative wings) to see the real causes of the crisis. They are internal, not external. As a result, the mid-term elections will be completely free of (largely mythical) Russian influence, but no attempt is made to address the deep structural-demographic causes. All these pressures continue to increase.
The major question on my mind now, instead, is how we could sail through the crisis without a major amount of bloodshed. This is where the “Ginkgo Model” may serve as a useful conceptual device. As I said earlier in this post, the trajectories of entry into structural-demographic crises are fairly narrowly channelized. But once the crisis breaks out, suddenly a much broader fan of possibilities opens up. It’s just like a Ginkgo leaf:
Some post-crisis trajectories go to a really dire territory: a bloody civil war, a revolution bringing an oppressive regime, or disintegration of the state into a number of territorial sections. Other post-crisis trajectories are less dire. In the best scenario, the elites manage to pull together and implement the reforms needed to defuse the pressures for crisis—reversing trends of immiseration and elite overproduction and restoring the fiscal health of the state.
However, unlike in the Ginkgo leaf analogy, the fan of probabilities of emerging from a crisis is heavily lopsided—and unfortunately in favor of really negative outcomes. Over the years I have studied about thirty cases of historical societies going into crisis, and emerging from it, ranging from Rome and China to France, Russia, and the United States. I scored the crisis severity in each by such parameters as the effect on the population (none, mild decline, catastrophic decrease), on the established elites (from mild downward social mobility to dispossession or even extermination), and on the state (territorial fragmentation, external conquest). Adding together these indicators, here’s the result:
As you see, the more positive outcomes (lower severity on the left side) are fairly rare (about 10% of historical cases), while the majority of outcomes cluster in the middle-high severity territory. In fact, this way of presenting outcomes is somewhat misleading, for the following reason. We know that the scale of collective violence in humans, measured by the number of people killed, is not “normally” distributed. Instead, it follows a power law. As an example from my own work, here’s the distribution of the severity of political violence events in the United States between 1780 and 2010:
The frequency distributions of war severity, including both external, inter-state wars and internal, civil wars have the same shape. What it means in non-mathematical terms is that there is no “typical” scale for outcomes of societal crisis. We cannot say that “on average 10,000 people are killed when a civil war breaks out.” The idea of “average” is misleading. A civil war can kill 100, 1000, 10 000, 100 000, 1 000 000 people and even more. The probability of a really severe conflict (e.g., more than 1 mln people killed) is fairly low, but it is much higher than what a naïve person would estimate. This point is admirably discussed by Nassim Nicholas Taleb in The Black Swan and other writings.
What it means for us here in the United States is that the severity of the troubles to come in the next few years to a decade is really impossible to predict. It could be as mild as the late 1960s–early 1970s, with the violent urban riots and a fairly ineffectual terrorist campaign by the Weather Underground. Or it could be as bad as the First American Civil War. Once again, a real catastrophic collapse of our society may not be highly probable, but it is much more probable than we think.