Chaos & Attractors
Equilibrium is death—so how do you escape it?
There’s an interesting quirk about complex adaptive systems that is quite mind-bending: they operate best at the edge of chaos. When a system is too stable and too deterministic, it dies. Likewise, when it’s too chaotic and unstable, it also dies.
You can think of the lifecycle of a complex adaptive system as a progression from chaos to order. When it first comes online, it’s often a jumbled mess of components that barely work together. The overall function of the system may not be clear at first, but the system accomplishes something.
Trending Towards Order
This is similar the first stages of a business, when you make your first bit of money and realize you might be onto something. In many cases, the revenue comes as a surprise—you planned to profit in one way, but ended up doing something else. But no matter what, at this stage everything feels like it’s on fire and nobody knows what they’re doing.
This is a dangerous phase for any system to stay within. If this initial high level of chaos is not reined in at all, the system will die. Chaos will overwhelm even the most resilient parts and collapse becomes an inevitability.
Complex adaptive systems that survive tend towards increasing order, by adapting to the environment and exploiting any beneficial resources they come across in that environment. To use the business example again, this is your first few hires, or the first impactful automations you create to cut down on your daily workload.
But when a system leans too hard into this orderly tendency, it becomes fragile and risks implosion, just like the initial chaotic stages. This is comparable to when businesses become sluggish and instead focus entirely inward. Bureaucracies get built, MBAs take over, and suddenly an enterprise that had real potential becomes a cesspit of incompetent politicians who seal the company’s long-term fate.
Attractors
This happens because of what are called attractors, which are pathways a system naturally falls into as it progresses towards order. It's a form of maximization, where one variable (or a very small number of them) dominates the rest of the system. This variable/set of variables drives the system towards a specific state, which can then blow up the system if it's addressed.
To understand attractors, imagine a landscape filled with hills and valleys. This landscape represents the possible actions a system can take, with hills and valleys representing different courses of action.
Attractors are those deep valleys that, once a system starts heading towards them, become incredibly difficult, if not impossible, to avoid. A system is attracted to it and in some sense wants to fall into it, in many cases for objectively good reasons (although this is not always the case).
The bottom of the valley is known as an attractor basin, and it represents a stable equilibrium state for the system. Because order is what the system tends towards, it’s natural for a system to hit these basins and stay there until they die—regardless of where the system started.
Think of a large vase that you drop a marble into. No matter how you place the marble into the vase, it will eventually settle into the bottom and then stay put. That bottom of the vase is an attractor basin, and the marble stopping on there represents equilibrium.
Attractor basins are those comfortable places a system goes to die, and it requires some kind of energy expenditure to escape them. Equilibrium is death for any complex adaptive system, since by definition it represents a steady, unchanging state. In a world of constant change, this is an unacceptable phase to stay within.
This is what is meant by the concept of the "edge of chaos." It is that state of being out of equilibrium, but not so far out of it that the whole thing falls apart. Living at the edge of chaos requires resources and is an effortful activity—when all effort ceases, the system will find its way into an equilibrium death.
Escaping from Attractor Basins
How do you escape from attractor basins? In some sense, you don’t escape from the attractors themselves, because attractors exist for very good reasons. They represent behaviors that work in a given environment, so you shouldn’t ignore them or try to kill them off completely. The hard part is recognizing when you’ve fallen into the basin and are approaching equilibrium, which, again, represents a comfortable death.
It’s normal and healthy for attractors to draw you in and for you to exploit what they represent. What’s also normal (but unhealthy) is allowing attractors to drag you into a deep basin, where you stop adapting.
The problem with basins can be seen when you visualize the basin itself: you can’t see the rest of the landscape. You may be circling around the basin at this very moment and not realize it, because from your perspective inside that basin, you’re blind. All you know is that you’re doing something that works and feels good, so why bother leaving that soothing bed of equilibrium?
This presents two pressing issues:
You’re stuck in a basin, so you aren’t adapting to the landscape.
You can’t get out of it on your own, since you can’t see where else to go.
Since you’re dealing with a complex adaptive system, the behaviors that lead to attractor basins are self-organized and emerge in the process of interaction with the environment. Complicating this all even further is that the landscape itself is not static - the hills and valleys shift, sometimes rapidly, over time. You may fall into a basin, get out of it, and realize that the landscape is radically different!
Disturbances & Perturbations
Your goal then is to not just avoid attractor basins as much as possible, but when you do fall into one, get out as fast as possible. This is accomplished with randomness, delivered through disturbances and perturbations.
A disturbance is some kind of external input that causes a shift in the state of the system. A perturbation is the effect of the disturbance, a result that cascades across the system. Disturbances can be deliberate (think of a poking something with a stick to see what happens), or they can show up randomly as a result of interactions with an environment.
Perturbations within a complex adaptive system tend to be extremely difficult, if not impossible, to predict ahead of time. Because CAS exhibit nonlinear behavior, disturbances of any size can generate one of three primary types of perturbations:
Neutral: No effects.
Minor: Small effects.
Major: Big effects.
What can be so difficult to wrap your mind around is the fact that there can be mismatches between disturbances and perturbations. This is akin to putting months into some big project, then releasing it to crickets, or throwing together something over a weekend and watching it explode into a massive hit. You just never know what kind of perturbation you're in for when you throw a disturbance at a CAS.
So to get yourself or a system out of an attractor basin, there must be some kind of disturbance that generates a perturbation with a large enough effect to knock you out of that steady state. If it's only a minor perturbation and you're in a deep basin, chances are you'll stay stuck. But if it's a major effect—either imposed by you intentionally or by the environment randomly—you're on your way to a new horizon.
Crises
Have you ever made a significant change in your life just because someone told you to? If you're being honest with yourself, chances are high that the answer is "no." Maybe it's happened a once or twice, but more often than not, changes happen as a result of crises.
This is the attractor-disturbance-perturbation dynamic in action in your personal life: you need to change, but weak disturbances (words of other people) don't create an adequate perturbation (meaningful change). It's often only with the arrival of serious threats to your survival, imposed at inopportune times, that you (as a CAS) adapt in a meaningful way.
The real challenge behind this book, behind all of my work in reality, is to get you to make changes before you hit a crisis point. It's overwhelmingly common for people to come to me and say "Oh my god, everything is broken, what do I do?" The world has imposed a significant disturbance-perturbation combination on you at the worst possible time.
Knowing all this, chances are you still won't make the changes you need to. But if you learn from experience, you'll start to pick up on the pattern: it's always better to perturb yourself than it is to have the world perturb you.
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