The Theory of Stability
Stability is a function of my day-to-day — eating the same foods for every meal, my yoga practice, my running, work hours — it’s nearly(ish) identical every day of the week (with some measured variability). My habits are ingrained, and I operate accordingly.
For me, stability was doing through doing the same things, each day, knowing that there would be little changes in those events, and that they should occur in relatively the same order, all the time.
Stability = Repetition + Predictability + Sequencing
Stability is an interesting thing to pursue. It reminds me a lot of the one-legged yoga poses. You’re balancing, supported by half of what your body is used to. You wobble. You wiggle. You fall over.
But as you continue to practice, the myofibrils in the muscle fibers in your leg grow in response to contracting and shortening. Your body gets used to you asking it to do one-legged poses. You begin to grow daring in the pose — perhaps going up on the tiptoes of the standing leg, or bringing the floating leg further up into the air.
The feedback loop stabilizes systems. As your body makes those microadjustments, it gives you information about how you should stand, where your toes should grip, and how tight your core should be.
It’s just like life. The above diagram is the process of a thermostat. It takes in the information from the room, and adjusts accordingly, warming and cooling when the temperature reaches a certain point. It takes in feedback, and stabilizes.
But its not to say that all feedback is immediately implemented. These one-legged poses can be frustrating.
I sometimes wiggle more than I did the day before. Become frustrated. Fall down. Other times, it feels effortless.
Progress is not linear.
But as you continue to practice these one-legged poses, you are teaching myself stability. I am teaching myself that I to operate with only half of what I am used to.
An excellent paper, Stability of democracies: a complex systems perspective, written by K Wiesner et al described the ‘robustness’ of stability in the context of machine learning.
“A robust learning algorithm is one whose performance P is not altered substantially when slight modifications are made to its experience E”,
This means that the algorithm can continue to perform well, despite any changes or perturbations — allowing it to perform on new experiences.
I know that there is always a probability that I will fall over. I focus on strengthening the parts that I can control, focus on the fluidity of the movement — but I know that the pose must change.
Life is like this.
We think that there is a positive correlation between stability and happiness. The more stable we are, the more happy we should be, theoretically. Stability comes in many different forms — a promotion, a raise, a relationship — but stability can also be the loss of these things.
Stability can be leaving a job to start a business, creating a second income source through investing, or leaving a toxic relationship behind. Despite the momentary uncertainty, stability isn’t never falling. It’s knowing that if we do fall, we are strong enough to get back up again. Balance isn’t staying perfectly still — it’s knowing that the little movements won’t completely throw you off track. It’s being flexible in the flow.
The consistency of the effort creates the stability.
Build a foundation. Our world is always going to be a balancing act, standing on one-leg when we really need two. Sometimes, people might even push you over as you wobble.
The important thing is that you stand back up. That you trust in yourself to lead the balance, to build the strength, to fall countless times.
Life is a function of risk and opportunity. Every time that you lean into something new, something challenging, you are risking a fall. But those falls can teach us so much. Opportunities only come when we seek them — when we are wobbling, we must search deep — we must come face to face with ourselves.
After all, change comes, even if we stand completely still.
Trust in yourself. Trust in your power. Trust that every time you fall, you are going to stand back up again, stronger than ever.