Chapter Content
Okay, so, like, you know how sometimes things just seem… chaotic? Like, totally unpredictable? Well, that's kinda what I want to talk about today. It's about this idea of a "human swarm," and how it relates to these crazy, unexpected events that we call, uh, Black Swans.
So, picture this: back in the, uh, 1800s, there was this insane locust plague. I mean, it was HUGE. Like, California-sized huge. This swarm of locusts just, like, descended on the United States, devouring everything. Farmers were, like, totally freaked out. It looked like a hailstorm or a prairie fire from a distance, but then, bam! Trillions of locusts.
And these things ate everything. Crops, trees, even the wool off sheep! People tried everything to stop them, but nothing worked. I mean, it caused, like, billions of dollars in damage in today's money. Laura Ingalls Wilder even wrote about it in her book. It was, like, biblical.
Now, you might be thinking, "Okay, locusts, so what?" But here's the thing. Scientists use the term "marching" to describe how these locusts move together in a swarm. And, well, in a way, we humans are kinda like that too. We're all part of this big, coordinated, regimented society. But even though it looks all ordered and structured, it's actually super erratic and prone to shocks. We live in a swarm that's constantly, like, teetering on the edge of chaos.
So, locusts, they're, like, Dr. Jekyll and Mr. Hyde. Most of the time, they're just harmless grasshoppers, you know? But when they get crowded together – usually because of food shortages – they transform into this "gregarious" state. They change color, they get aggressive, and they start swarming.
Scientists have been trying to figure out why swarms form, and it seems to come down to density. When there aren't many locusts around, they just do their own thing. But when there's a certain number per square meter, they start to group together. And when it hits a certain threshold – it’s some specific number, like, 73.7 locusts per square meter – bam, they start marching as a unified swarm. It’s this tipping point. It’s really quite something.
And here's the crazy part. Even though these swarms are incredibly ordered, it's impossible to predict where they're going to go next. It’s random. Like, totally random. It's this paradox. Out of chaos comes order, but the overall movement is still unpredictable.
Now, we're not insects, obviously. But over time, humans have moved from these small, isolated groups to this huge, interconnected swarm. Think about it. Fifty thousand years ago, people lived in small bands. They rarely encountered other groups. Now, we're all connected, all living in this enormous society.
We used to have more global stability, even if day-to-day life was unpredictable. Now, we have more local stability – like, you can predict where someone will be most of the time – but more global instability. We’re seeing those Black Swans. I mean, one study shows that people can actually predict your whereabouts most of the time these days because we’re all creatures of habit. It’s amazing, isn’t it?
Modern society is, like, super ordered. You can order the same McDonald's hamburger in, like, a hundred countries. But everything can change in an instant. Financial crises, pandemics, wars… these things disrupt our lives constantly. We get blindsided by these unexpected events.
And that's the paradox of the swarm. Human society has become both more ordered and more contingent at the same time. It seems predictable, but it's also fundamentally uncertain.
So, what's going on? Well, our brains evolved to live in a simpler world. Back in the day, all we needed to know was, like, "saber-toothed tiger = death." Now, the world is full of feedback loops, tipping points, and seemingly insignificant ripples that turn out to matter a lot.
That's where complexity science comes in. It's this relatively new field that studies systems that are between order and disorder, control and anarchy. And, you know, modern human society is definitely a complex system.
Through the old lens, a lot of researchers used models that were largely relied on misleading linear systems with a single point of equilibrium. But the real world, the economy, it isn’t like that!
These old models make a few assumptions that just aren't true. Like, they assume that every effect has a specific cause that you can see. Or that you can understand something by just understanding its parts. Or that patterns from the past will help you understand the future. But in complex systems, none of that holds true.
So, what makes something "complex"? Well, complex systems involve diverse, interacting, and interconnected parts that adapt to one another. The system is constantly changing. Change one thing, and other parts adjust, creating something new. It’s all interconnected.
These systems are path dependent. One choice affects future choices. They're decentralized and self-organized. It's the aggregation of a zillion adjustments that determine how the system operates, not some overarching rule.
And that's where emergence comes in. It's when individuals or components organize themselves in a way that produces something different from the sum of their parts. Like, a locust swarm is fundamentally different from a solo locust.
Complex systems also have these things called basins of attraction. These are particular outcomes that a system tends to converge toward. Like, the flow of traffic on a highway. Cars start at different speeds, but they tend to organize themselves at roughly the same speed.
But basins of attraction can also change, creating instability. For example, you know, the US political system has two main basins of attraction for partisan identity: Republicans and Democrats. But, like, every so often there are splits like Donald Trump splitting the Republican party. And stuff like that increases that risk of shocks.
When society seems stable, it's often because the basins of attraction are stable. But the problem is, modern society only produces the illusion of stability. We've designed many systems to have basins of attraction that are on the edge of a cliff, near tipping points. It’s, like, we’re obsessed with efficiency.
So, another way to think of it is like a paper bowl with a marble inside. Sometimes the marble will just rest at the bottom of the bowl, you know? But what happens if the bowl is inverted into a cone? The marble is precariously balanced. Even the tiniest gust of wind will send the marble tumbling down. And that's kind of how modern society is. We keep building this cone, on the edge of chaos.
Because complex systems are nonlinear, small changes can produce major events. These events are often the result of cascades, which are difficult to anticipate.
For example, when wolves were reintroduced to Yellowstone National Park, it triggered this unexpected trophic cascade. The whole ecosystem adjusted because of this small change.
In human terms, you know, cascades take many forms. Like, when Martin Luther nailed his 95 Theses to the church door, it sparked a religious revolution. It broke the dominance of Catholicism.
These days, we end up on the edge of chaos more easily. Before the 2008 financial crisis, the mortgage industry offered risky mortgages to people who couldn't afford them. It climbed to a new basin of attraction. Then, bam! Tipping point. The avalanche wiped out countless livelihoods.
When systems are approaching the edge of chaos, they can show warning signs. One is critical slowing down. Basically, it’s when a system takes longer to return to normal after a disturbance. Ecologists noticed this happening in forests before insect explosions.
So, why do these cascades happen? Well, it could be something known as self-organized criticality. A physicist named Per Bak showed how this applies to grains of sand in a sandpile. The grains build up slowly, until one grain triggers an avalanche.
Locust swarms also exist in this "critical" state. A tiny perturbation to the movement of a few insects can redirect the entire swarm. It leads to a mind-boggling conclusion: A farmer's livelihood could be wiped out by the slightest flit of a single insect.
Now, no single locust can direct the swarm. But each individual influences everything. And the same is true of us. We’re often lulled into a false sense of security. We delude ourselves into believing we're in control, until we’re hit by a crisis. We label it an external shock, but it was the inevitable culmination of events. It was bound to happen.
So, what do we do? We learn about complex systems. We understand how our world works. We build systems with a little more flexibility, a little less optimization.
The internet has also drastically increased connectivity and made the world more likely to be in a state of criticality. As one historian puts it, “Ideas are the main motors of change in human cultures and… the pace of change is a function of the mutual accessibility of ideas.”
And our swarm is speeding up. Think about economic trading. It's all about milliseconds. But with great speed, financial systems more often drift toward dangerous criticality.
So, complex-systems thinking can teach us important lessons. We focus on predictable patterns, but we need to pay attention to accidents, outliers, and chance fluctuations. We live in a world that's far more unstable and uncertain than we'd like to imagine. But, as I'm going to try to convince you, uncertainty can actually have some hidden upsides. But, like, we can talk about that later.