If You Want to Learn, Ignore the Details
Why High-Level Thinking is Superior to Detailed Reasoning
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CONTEXT AND MEANING
There are 2 ways of thinking. There is detailed-oriented thinking and there is high-level thinking. One is concerned with understanding the specific details of a given situation and the other with abstract ideas and general knowledge. Modern society has rewarded the former far more than the latter. Detailed knowledge about something is considered “deeper”, since layers have been peeled back and the specific components of a situation uncovered. To understand the details is to know what goes into the phenomenon being studied, the guts or inner workings of the machine. If you want an expert in something you look for the person with detailed knowledge.
The idea that “deep” knowledge is superior comes from the industrial revolution and more foundationally the so-called Age of Enlightenment. The industrial revolution was spurred-on by the creation of simple, mechanical things. Simple in the sense that each component bumped up against another in a visually obvious chain of causality. The steam engines, rocket ships, bridges and office towers were/are all genuinely simple constructs that have causal chains of operation. These are the things that can be reverse engineered and understood.
The Age of Enlightenment is where it started. That intellectual and philosophical movement that brought sovereignty to reason and considered the evidence of the senses the primary source of knowledge. The Enlightenment emphasized the scientific method and reductionism, which posits we can understand something by inspecting its makeup; that looking into the individual components is to know the thing itself. For simple things like steam engines, rocket ships, bridges and office towers this of course makes sense. When the connection between pieces is wholly deterministic things are predictable and controllable. To know the inputs is to know the outputs.
But digging into the details comes at a cost, and that cost is a type of misunderstanding that increases dramatically with complexity. As the dimensionality of the situation increases the idea that digging deeper leads to more knowledge degrades. To dig deeper is to lose context. The act of stripping away and isolating removes the interactions, and the behavior of any real world system is determined by those interactions. As we home-in on the specifics we lose the view that matters most. The part of the phenomenon that actually interacts with the environment and affects our observations, and often our lives.
Under complexity, fixing on details relegates one’s awareness to sterile facts devoid of meaning. And this is the point. In real world situations details have meaning only by virtue of the environment they interact with. If you strip away the environment you’re left with inputs to a journey you know nothing about.
Imagine sitting on an airplane with your 2 year old and playing with little plastic dinosaurs you purchased at the dollar store. By themselves those little dinosaurs have no meaning. If you dropped one under the seat and lost it nobody would care. It cost 50 cents. But to your 2 year old they are his best friends. They mean everything to him. For you to drop one and lose it could ruin the entire trip. You’d be talking to neighbouring passengers trying to recover a small piece of plastic as if your child’s entire happiness depended on it. The dinosaurs acquire all of their meaning through context.
This is true of any real-world situation. The components that go into a system mean nothing without taking into account the circumstances, conditions, surroundings, factors, state of affairs. Only by considering a system’s components within the mess of their interactions do the details of a system have any meaning. The environment in which details play out their dance must be considered. This is true of any phenomenon with an appreciable amount of complexity.
Think about what this means for science. Science is built on the idea that knowledge is gained through isolation and extraction. It is by holding everything except what you’re interested in still that makes science possible. Everything from basic observations to randomized controlled trials is based off this premise. To understand the reasons behind things we must isolate the cause from everything else, and home-in on the single or few factors that supposedly dictate the outcome. This artificial narrowing of the lens of reality works wonders for simple systems, but is borderline nonsensical for the complex.
This changes everything. To truly learn about something cannot mean to study its details. It cannot mean to dig “deeper” into the so-called inner workings because nobody has access to those inner workings. Recall from my last article that complex things don’t condescend to show us how they come to be; that information is forever lost to the mechanism of multiple realizability. Understanding cannot come from the traditional notion of depth, rather it must come from something else.
That something else is movement. All we can do to learn about reasonably complex situations and phenomena is to take note of what doesn’t move when everything else does. Meaning comes from invariance. To understand something is to become familiar with its behavior, not its details. Instead of holding everything still and changing one thing as per the scientific method, we should be letting everything move and noticing what stays fixed naturally. This is the only way to deal with the fundamental epistemic uncertainty in all nontrivial situations. “Deep” understanding is largely narrative; what we need is meta understanding, which accepts that the only knowledge truly available are the high-level processes systems undergo.
And so what does all this have to do with high-level thinking? To operate at a high-level is to discard details, and I argue that discarding details is a far more powerful way to operate in the real world. By discarding details we encourage movement through the environment because we are allowing details to always exist in flux. As soon as details are decided on, our capacity to attempt many possibilities is severely limited. Recall that attempting many possibilities is the ONLY way complex problems get solved.
The reason nature gives us heuristics to navigate our complex world, rather than details, is because general rules of thumb work, details don’t. Details don’t work because they have no meaning prior to embarking on the journey. Details cannot assist in the finding of a solution because the right details and their meaning only exist once the situation is known. The environment must be sampled naively, under the absence of information, in order to remain fluid enough to allow solutions to precipitate. Only once the right solution emerges do the detailed components that go into a solution matter. Details acquire meaning only once we have entered the void.
DETAILS WERE MEANT TO DIE
Details have to be disregarded if they are to serve their proper purpose, which is as variation in problem solving. Look at any process that successfully navigates through complexity and you see variation and iteration. Variety is what allows for massive sampling, and iteration is what allows for recurring assessment of how well the system is converging. Take any high-level goal; to get there we must keep details in flux and only take actions that move us closer to the goal. It’s not for us to know why certain course adjustments work better, just that certain actions do.
So from a problem-solving perspective we can see that focusing on details is massively detrimental. But then why do we do it? Why is the entire academic narrative bent on this idea that textbook knowledge can help us solve real-world problems? Why is the Age of Enlightenment, a grossly outdated paradigm, still with us? The problem comes from what I will call the authority of simplicity.
The Authority of Simplicity
The problem with details is they look beautiful. They look smart. They look authoritative. As soon as we codify an idea with symbols, or give it a label, people tend to take the concept more seriously. Despite our natural capacity to work under uncertainty, the unknown makes us very uncomfortable. Concrete things give us comfort, and this happens regardless of how true those concrete things are.
We see this problem with mathematics all the time. As soon as something is mathematized it takes on a look of authority. Look at all those fancy equations. Someone must have really thought about this for them to encode the process with symbols. Math rarely gets challenged outside its own field because the language is esoteric. Nobody wants to look like an idiot.
But anything can be mathematized. There are no real guardrails for mapping math to phenomena. Just represent the details as symbols and assume whatever self-consistent operations math supports must also be supported by the phenomenon. Any narrative one wishes to encode can be encoded. Peer-review will hold the math itself accountable to allowable operations, and will check the math against similar systems that have been modelled. But beyond that nobody can argue a given equation doesn’t map to reality.
Sure we have prediction, but what is prediction? A highly dubious term; one that often means in-sample curve fitting (not really prediction) or an extension of mathematical operations under the assumption math natively maps to reality. We won’t get into the “is math discovered or invented” debate in this article, but needless to say, the idea that math is anything more than a codified version of our own thought process is debatable.
Regardless of one’s take on math, most would agree its appearance adds a note of authority, and when it comes to maneuvering through complex situations this is a problem. Authority makes it hard for things to die. Authority retards the ability of systems to leverage variation the way they’re supposed to. The only authority that should exist are the highest-level goals we are working towards. Everything else must be allowed to perish throughout the process. This is how information and problem solving works. It’s the reason variation and iteration are THE critical ingredients in making complex problems tractable.
The perception of authority keeps things alive that shouldn’t be. This goes against how problems get solved, which demands details are not preserved but rather are almost entirely destroyed, save the few that persist. Remember, the only way to assess what is true under complexity is to note what doesn’t move. The false authority of simplicity doesn’t allow details to die.
Occam and the True Purpose of Details
With all this talk of details dying one might wonder; what’s their purpose? Why even bother having details at all?
The reason for details to exist is to have something that isn’t vague so that it can be tested by the environment. This is the true reason behind Occam’s razor, which states “entities should not be multiplied beyond necessity.” It’s almost always inaccurately restated as “the simplest explanation is usually the best one.”
This is not the right way to think about Occam’s razor, since we are not after simplicity for simplicity’s sake, we are using simplicity because it’s easy to kill. In other words, we don’t want to choose the simple explanation just because it has less assumptions or because it’s easier to understand, but rather because simple things are easy to test and destroy.
The only way simple things survive is if there is something true or useful about them. Compare this to vague things that can survive even if they are complete nonsense. Vague things are ill-defined and difficult to challenge. Vagueness props things up longer than they should be because they are difficult to define. If we can’t define the thing how do we argue for or against it? Vague things linger, and accumulate authority over time despite adding little value to a given idea. When it comes to assessing what is true, it’s not enough for something to be long-lived, it must also be unprotected. It must be always open to attack so that its survival, if there, is a testament to genuine effectiveness. Continuity is not truth, survivability is.
And so details are important, but not as concepts to dig into for deep knowledge, but as testable pieces that allow knowledge to be gained by observing what lives and what dies. The details that matter are the ones that don’t move throughout the process of interest; the meaning that is carved out by invariance. The key point is that the right details, and what they mean, cannot be known until the solution becomes apparent. Only once the solution emerges through trial-and-error do the details have any meaning. This is why the reductionist take from The Age of Enlightenment is so deeply flawed, and wholly inapplicable in today’s complex economy.
CONNECTIONS OCCUR AT THE SURFACE
Abstraction and Overlap
If I am in the woods trying to survive I won’t last long sitting there hoping for the best. I must move throughout the terrain to find resources that enable me to build shelters and gather food and water. Movement is how overlaps between my actions and the environment are made. It is movement through the woods that makes surviving possible.
If I remain focused on how specific shelters are constructed I may find myself in trouble. The materials I studied may not be present in these woods. I might have detailed knowledge on which plants are safe to consume but the plants I studied may not be in season when I get there, or not native to the area. It’s tempting to say “well I’d know where I’m going and what’s there, so I’d simply study up on the right things” but this is naive. Any set of details can easily prove worthless to survival. What matters is putting one’s self in opportunity’s way and learning in the moment. It’s not preparation one needs, it’s adaptability. Fixed, sterile knowledge about individual things is not that useful.
Upfront details fail to enable survival because there are countless situations that can play out. The environment is convoluted, interconnected, with many things affecting many things. There is no way to anticipate all that will happen, and it only takes one major event to wipe out all other advantages (recall The Rich Don’t Penny Pinch). Any “solution” someone brings to the woods from their “deep” knowledge is more likely to solve something that never needed solving; a solution looking for a problem.
But surely a navy seal or trained survivalist would fare better? It depends. If they do it’s not because of what they learned from books on the topic it’s because of their experience. They’ve picked up on those ineffable attributes that make survival possible, and they’ve done so over years. They will have lots of details to talk about regarding survival, but remember, those are after-the-fact details.
If survival was always the same nobody would find it very exciting. What keeps people like navy seals and survivalists engaged is the ever-changing nature of the effort. This of course is true of any area of interest. Also, watch any show on those competing to survive and it’s often the non-trained individual that comes out on top. This shouldn’t be surprising, but to many it is.
To solve the problems that matter one must enter the void naively, and course-correct en-route. The uncertainty is far too high to go in prepared. The only true preparation is the acceptance of extreme uncertainty. This doesn’t mean we shouldn’t arrive with tools. Tools increase our ability to move through the possibility space. Knifes allow us to cut through brush and fashion additional tools. Ropes will help us bind branches and set traps. Tools are not fixed ideas about how things work, they are apparatuses that enable movement through the environment.
But the only tools worth packing are those that fall into the highest category of abstraction. Don’t bring a knife specific to cutting rope or shaving bark, bring the most general purpose knife possible. Thinking about the details will have us packing for very conceivable contingency, weighing us down. Details are not mobile, they are viscous.
Generality is achieved through abstraction, and it is generality that enables overlap with the environment. We can understand this informationally in terms of connections between disparate things. As I’ve written previously, at the highest level of abstraction everything is the same. At the lowest, everything is different. When people disagree they are usually just cutting the line of abstraction at different points.
Higher levels of abstraction mean more details gets subsumed into fewer categories. All the different cars get subsumed into the category “car” and all the trucks, cars, crossovers, SUVs, etc. get categorized into “vehicles.” The fewer categories that exist the more chances there are for details to get connected, since they fall under the same category.
We want there to be a connection between our actions and the environment. The more general purpose our tooling the higher the probability our tools will find use in our environment. Abstraction, generality, is what makes overlap between our actions and the environment possible.
This is how analogy works to make connections between seemingly disparate things. Humans use analogy to connect areas that appear different when the focus is on details. When the level of abstraction is increased it means more details that would have been kept separate are now connected in conceptual space.
Less Likely to Tackle Real Problems
A consequence of people becoming attracted to the comforting concreteness of details is they are less likely to tackle genuine problems. This is because of the abstraction overlap mechanism I just talked about. Genuine challenges are the problems that exist when one is immersed in the environment. But getting into the environment means overlap, and THAT means abstraction. Only through generalities do we enter into the place where true problem solving happens.
High-level thinking is what brings people into the realm of genuine challenges, and this is why high-level thinkers are more likely to deal with problems that actually need solving. It’s also the reason why high-level thinkers tend to understand the situation, and the details that matter, better than detail-oriented individuals. Detail-oriented people will have more to say about details, but much of what they’re saying is disconnected from what matters. We don’t need what sounds smart, we need what is smart.
We see this in software, where those dedicated to documentation and best practices don’t seem to create anything real. They are like cogs focused on programming minutia rather than building something people want to use. Most computer science graduates have never created an end-to-end piece of software. They can talk forever about for-loops, programming language design, methodology and data structures but most are inept at crafting actual applications. One will be quick to argue that those cog-style details are needed as a foundation going forward. I disagree.
To create software is to move quickly and craft things people might want. To create things that add to the economy one must enter the economy, and this demands abstraction. Once there, after-the-fact details can be understood in terms of how they contribute to the situations and users we now understand. Again, the details that matter could not have been known upfront, and the only technical understanding that matters is how they relate to the problem being solved.
This is true of all real-world situations. Just as dedication to programming minutia will prevent one from entering the economy and solving real problems, so to will upfront dedication to details prevent exposure to genuine environments in any domain. “Deep” knowledge so often attributed to “experts” is anything but; those details are sterile, devoid of meaning, and uncorrelated to the kinds of outputs we need to create.
THE DIRECTIONALITY OF LEARNING
If genuine challenges only arise inside an environment accessible through abstraction, what does this mean for learning? It means if you want to learn something you should not be delving into the details, rather you should be operating at the highest-level of abstraction and entering the environment accordingly. Think about what I discussed towards the beginning with regards to context and meaning. Understanding the details properly can only come from proper context, and proper context can only come from facing genuine challenges. Genuine challenges only exist in real environments, whose price for entrance is high-level thinking.
Again, so-called “knowledge” of details prior to embarking on the journey means little. The only details that matter are the ones that survived the process of discovery, as per Occam’s razor. And the way to know what those details mean requires we are embedded in the right environment. To be clear, all of the learning that matters can only come AFTER you have naively entered the environment knowing little about its nature. It is high-level thinking that gets you there, allowing you to call upon details at the last possible moment when they mean something.
Stop Asking What Books to Read
Previously I used the example of sitting on the airplane with your 2 year old and losing one of his plastic dinosaurs. This example shows not only how meaning is achieved through context. but that it’s ONLY achieved in one direction. The details don’t inform the situation. Plastic dinosaurs by themselves mean nothing. The information doesn’t flow from dinosaurs to the situation, they flow from the situation to the dinosaurs.
To study details prior to embarking on a task is incoherent. There is no mapping of fundamentals to situation under complexity. To create what is new is to go head-first into that which you know little about. You will have lots of detailed knowledge after the fact, but only after-the-fact. This directionality of learning is missed by many, and one of the reasons people seeking advice for their personal and professional lives ask what books to read or what courses to take. This is a mistake. It’s based off the false premise that reading will impart knowledge despite being entirely stripped of any real-world context. One must have entered the environment of which the book speaks in order to understand the details the book discusses.
When someone asks what book to read or what course to take they’re getting the directionality of information wrong. I’m not saying books and courses are worthless, but if you don’t recognize most things in a textbook the first time you touch it you’re doing things backwards. Whatever details are discussed will only mean something to you if you’re struggling through something real. No textbook or course can give you context; only a true struggle against the stressors of a genuine problem.
OPERATING AT THE SURFACE
Today, we create things that are massively interconnected and opaque. The discoveries we make don’t look like steam engines, rocket ships, bridges or office towers. Our economy thrives off of entangled information, not clean causal components that bump up against each other.
High-level thinking is superior because it doesn’t define knowledge in terms of isolation and extraction, rather it enters the void where context and meaning live. It leaves the identification and discussion of details until after the discovery has emerged. High-level thinking looks only for behavior and invariance, not static ingredients devoid of meaning. High-level thinking understands interactions implicitly rather than details mindlessly. High-level thinking allows details to die, operating the only way complex problem solving does; via variation and iteration.
High-level thinking isn’t susceptible to the authority of simplicity. It doesn’t look to anchor truth on specific sets of assumed inputs. By operating at the surface it allows swarms of details to make conceptual connections that detailed-oriented people fail to make. Critically, high-level thinking is what brings people into the environments where real problems exist. Whereas the detail-oriented remain caught in the weeds, high-level thinkers embrace abstraction, and this is the only way to expose oneself to the stressors that teach us what’s worth learning.
The next generation will need to learn to operate at the surface, letting go of history’s denigration of high-level thinking. Detailed knowledge can no longer mean “deep” understanding, rather it must now be considered disconnected thinking; thinking that lacks context.
Beware those who are quick to discuss the details, as there’s a good chance they have a bad solution looking for a problem that doesn’t exist.
They say the devil’s in the details. If that’s true, the angels must work above them. I suggest you work with the angels.
