The ouruborus, short take
You’ve been there: you’ve got a nut to crack, it’s not budging, and you just keep staring at the information like there will be something new to see. Same information, stuck in time and place. Yet you persist in coming back to it like it’s going to change.
You’re not wrong. The better way to frame it, though, is that the perception of the information *could *change. A good detective — whatever they are troubleshooting, regardless of job role or conferred degree — knows that part of what to do when a nut isn’t cracking it to change the point of view. Look at the data from a different reference point.
When we are moving through the world, we have a reference point. We’re using it, with every step, interaction, breath, and thought. This moment is finite and necessary to move through to build all our moments into a whole. By nature of moment, it must be elegant and speedy, and once it’s gone, it’s done. Yes, you can go back and correct it; no mistake has to continue forward into all time to come. But the making of that mistake still becomes a part of history and a piece of data. It’s still a part of memory.
Leveraging our memory, sensing data, focus on what we think to be relevant, we process it. Basically, puzzle-piecing together what we’re experiencing and making a best bet for next moves. We experiment.
As those bets and experiments reach a desired or acceptable outcome, patterns form. We nuggetize what we’ve come to know or understand and place it in a high point in memory.
And it keeps feeding itself over and over again.
Let’s consider this against the everyday process of walking down a busy street
As we walk, there’s all the bits and bobs of data that we’re moving through. The streets, the cars, the people, the signs, our control over our own movement, the goals, survival and all the bits it takes, the ads. There might even be communications from our bosses, clients, coworkers, family, friends that we might have been prompted to watch out for (urgent! Stay in touch!). Data and data and more data, ad infinitum. Everything in those sentences detailing what data we’re moving through? They are all a part of our memory, even if only the recognition and naming of it: street. car. person. person. ad. flower. person. dog.
Our brains and eyes were developed to help us navigate in 3 dimensions, but we don’t see 360 of our center. We see in a forward cone. So, we pay attention to what’s in front of us. In certain circumstances — like turning left at a stop light — we learn to turn our head and look around, but for the most part our eyes stay pretty much in our forward field. That means that anything behind us, anything too far over to one side, doesn’t get captured as a possible data point.
On top of these visual cues, we’re very likely also trying to listen: screeching tires, honking, yelling all might be additional cues to increase the likelihood of survival. And we’re smelling, getting distracted by the cinnamon rolls being baked and gagging at the exhaust, old piss, and tar that is evident on many city streets.
So, we have a limited field of perception…that still leaves a huge amount of data to consider.
That’s where our cognitive biases step in and help us out. We pay more attention to some bits and bobs, and less attention to others. We pay more attention to the bits and bobs that we’ve successfully leveraged in the past. We pay less attention to what we consider dismissible. In other words, we’re making snap judgment calls on what is signal, and what is noise.
We’ll pay attention to the person right in front of us, especially if they are showing signs of stopping short suddenly or moving in a certain direction.
Sounds that are ‘far enough’ away get ignored. We ignore movement inside construction area that’s been marked off for days. We might ignore the busking homeless person; or the smell of coffee or donuts or eggs as something that we simply don’t have time for.
In short, our perceptive cone is limited, and we don’t acknowledge all of the data within it.
Then, we need to understand what the data means. We’re running background programs all the time to try to understand how things work. The most facile of these is to leverage what we understand from one concept and seeing if the process, or part of it, would help us understand an at-hand concept. This is mental modeling, and it’s one of our favorite ways to pull new processes and ideas into understanding.
If you watched someone roll out pie dough — taking the sticky, crumbly flour-lipid mixture and using an object with equally applied pressure to make the mixture flat and reasonably roundish — you have an idea of how rolling out pie dough worked. You can potentially fumble around and do it yourself.
While you’re walking down the street, you happen across a road crew laying down asphalt. You see the mounds of black pellets, the equipment, and it clicks: they are taking a crumbly, sticky mixture and using an object with equally applied pressure to make the mixture flat. Like a pie crust.
The transition state from watching someone roll out pie dough to doing it yourself leverages mental modeling. The transition state from processing a floury crumbly-sticky mixture being similar to processing a tarry crumbly-sticky mixture ALSO leverages mental modeling. It’s part of what makes us able to learn. It’s taking adjacencies with key similarities and seeing if they can apply to new concepts.
It’s often wrong. It’s often right. We’ll scramble through a whole bunch of models whenever we notice something we want to wrap our heads around, shunting aside the ones that don’t seem to work and moving on to the next idea. It all happens faster than they can truly log into our conscious mind.
In short, we process the information that has made it past our filters through applicable mental models to develop a sense of recognition.
Then we get back to memory; actually, memory has never left us. We have leveraged it through data perception (deciding what data is relevant), into mental models (finding an applicable adjacency), and now we’re on to next steps. We have to remember what our goal is — getting to work on time — and suss out which data bits will help us get there, which data bobs might be future-useful if a pattern forms, and how our decisions might affect the surrounding data set. We leverage the data we have and decide between multiple potentialities to try to achieve a desired outcome.
Turn left, away from where we work, to avoid the construction site according to path of least resistance. Turn right, towards work, to avoid the source of baking cinnamon rolls that could set desire in motion, distract, and make us late.
Will I have the will to avoid sweet cinnamon desire? Is the left turn actually minimally invasive to the time parameter — cross the street, keep walking on that side, use the light up ahead to super-safely get back on the correct side, that is right in front of an alternative entrance to my workplace?
We make bets and experiment.
Over time we build up patterns of what has been successful for us, and mentally organize them into reference points. Patterns develop, and what seems to be prone to success is nuggetized and set high in memory.
To be clear, success itself is a multivariate data point.
‘Success’ in our society has become a byword for making enough money to pay for all the survival modalities with plenty left over for exploration, toys, and saving enough to survive for the understood future. But in our day to day ramblings through the world, success is much more trivial. It can be finding a path that lets you get to work on time. It can be the experienced joy of eating a cinnamon treat. It can be the successful avoidance of a cinnamon treat. You achieved your goal, and a cascade of happy chemicals bathed your nerves as a reward.
Patterns develop, are augmented by a biochemical reward system, which in turn urges us to repeat the patterns. They nuggetize: this is how I get to work. All the bits and bobs, their multivariate influences become part of a ‘known’ process, that in turn encapsulates into a simple concept: my path.
It’s still just as complex and potentially data-overwhelming as it was the first time you walked a congested city street. The difference now is that you have an idea of where you’re going, what to watch for, and have a set of avoidance factors. You’ve learned. You are now moving through the data with a set of knowledge/understanding, so you can pay more attention there and less attention here. You understand the experimented permutations. You grow to depend on that biochemical cascade as your due reward.
In short, we develop patterns that get a shorthand in our memory.
Our ouruborus can stultify
As we move through the world in this moment, we rarely reconsider the moments in retrospect. They have to somehow reach a higher state of priority: particularly successful, or painful, or stressful, or sparked our anger, something. If the moments don’t reach a priority state for later review, they simply continue building and layering according to how it was processed in that moment, and that one, and that one, etc., until we get to this one. We lose track of the underlying reasoning, if it was ever clear to the conscious mind.
Even if something happens that does reach a priority state, most of us most of the time will review that happening against a set of already existing understanding. We build preferred narratives and look to them to understand what’s happening. The world is against me. The world is my oyster. It’s all my fault. It’s never my fault.
In other words, we tend to leverage our ouruborus of perception to try to understand our ouruborus of perception.
We build memory. We also build cognitive pathways that are as easy to slip down as a slide, and as hard to change direction while in the middle of it.
Our perceptive mind is an ouruborus feeding on itself, with a tendency to confirm existing states and simplifying. We try to avoid creating extra states to run more data through.
If you want to see something different in the same data, the ouruborus needs to be cracked, even broken. See something different. Change your perspective, define a different set of relevant data bits and bobs, add to your toolbox. Broaden your horizons and your perception will change.
Suddenly, in the data set you’ve stared at for hours, days, months, or years, niggling with a sense of what am I missing, you see something you hadn’t seen before.
The data didn’t change. Your mind changed.