I remember that dreadful feeling. It always resurfaced at the beginning of each semester while my profs outlined their syllabuses and reviewed prerequisite material from previous courses — sometimes material from the most recent semester — and they would say something along the lines of: “You should all remember this stuff. You’ve already learned it.”
Looking at the concepts, diagrams, equations, or whatever else was on the board, I would usually have a vague memory of the material, but nothing solid, nothing clear, and hardly internalized in any meaningful way. It was deeply discouraging; if all of these concepts were so important to properly understand new course material, why didn’t I have a better grasp of them in my memory?
It felt like something was fundamentally wrong. Even though I was a dedicated student, prioritizing my academic performance above many other things (probably too much), I felt like I wasn’t properly learning course material in any meaningful way.
Ideally, key ideas from all my courses would somehow embed themselves in my long-term memory and help me make sense of any new material that was built off prior concepts. Additionally, it would have been great to gain a bigger picture perspective of all the material I learned, clearly seeing all the relationships and interconnections between concepts and theories. In reality, though, course content would fade so rapidly from my memory, I had to go through cycles of re-learning material. In doing so, I usually only managed to maintain a surface level understanding of many concepts and theories — enough to do well on tests and exams, but not nearly enough to profoundly shape my broader understanding of the world — and that would drift away from my memory by the lightest breeze of time.
These repeated dreadful starts of each semester lead me to believe that I simply did not have “good” memory. I had a vague sense that this was a much more fundamental problem that needed to be addressed, although I never made the time to really dig into it while I was a student. Instead, I went about my entire degree mostly using sheer willpower and my intuitive learning abilities to get by.
It wasn’t until after I graduated that I had the time and motivation to explore these issues in more depth. Almost by complete coincidence, I stumbled across the world of personal knowledge management (check out my article on getting started with PKM if you haven’t yet). This chance discovery opened up a whole new world of tools and techniques for effective learning. Most specifically, networked note-taking (for building up rich, interconnected knowledge-bases of digital notes across all areas of interest and learning) and memory training (to memorize and internalize units of knowledge that provide the foundation for understanding new and more advanced knowledge).
The more I thought about and experimented with these tools, the more I realized how powerful they were for long-term, comprehensive learning — the kind of learning that helps one build deep knowledge and expertise over a lifetime. More importantly, they seemed like the kinds of learning tools that help one navigate the vastness of cyberspace without becoming completely overloaded with information. It was becoming clear to me that I had made a revolutionary discovery that would forever change the way I learn. Perhaps I would never have to experience that dreadful start-of-semester feeling ever again.
Linear vs. exponential learning
Recently, the true implications of these discoveries became much more clear: such tools enable one to become an exponential learner. When I was a linear learner, I hardly developed a solid enough understanding of old material to act as a foundation for learning new material. It didn’t feel like my ability to learn new material increased as my knowledge and understanding of older material grew.
With PKM and related tools, however, it feels a lot more akin to exponential learning. As I process new information and develop new understanding, I have a rich knowledge-base (both internalized and externalized) to build off of, helping to connect the dots in more intuitive ways and enabling me to see the bigger picture of my accumulating knowledge. Now, as I learn new material, my ability to learn it improves since I can more effectively make use of all prior learned material.
Understanding exponential learning through analogy
Learning is like swimming in a vast ocean of knowledge. When I was a student, my degree told me what direction to swim in and where to visit, but it was mostly up to me to figure out how exactly to navigate this vast ocean — what tools and equipment should I bring with me, how fast should I be swimming, etc.
Without much guidance and the pressure of balancing many responsibilities, I tended to swim through this vast ocean of knowledge as fast as I possibly could. I’d be able to glance around, get a sense of the knowledge landscape, hoping that by stuffing my perception with a rushed memory of the landscape I would somehow be “learning”.
What this looked like in practice, mostly, was attending classes and taking rough handwritten notes. Every once in a while I would review these notes (usually only before tests or exams) and try to consolidate my learning in some intuitive way. Basically, I would return to the same part of the knowledge ocean, trying to retain enough memory of the landscape to regurgitate it on my next test.
During this process, I would only collect enough floating units of knowledge to build flimsy structures of understanding — enough to get a decent mark on my tests. But, these structures were so weak that they would crumble quickly. With each new course and semester, I would have to re-collect units of knowledge and re-build structures of understanding — rarely feeling like I was building a resilient tower of understanding that could remain standing in the long term.
For an exponential learner, this process changes completely. Rather than swimming through vast oceans of knowledge as quickly as possible, it’s more like dragging a huge net and scanning the landscape with a powerful mapping device.
The net collects many drifting units of knowledge from the ocean on the first pass, meaning I won’t have to return nearly as often to gather any materials I may have left behind. These collected units of knowledge form the building blocks for constructing resilient towers of understanding, ones that can be built up over long periods of time and provide new perspectives with each subsequent floor.
In practice, this takes the form of writing lots of spaced-repetition flashcards as I consume new information. The purpose of the flashcards is to help me internalize and memorize units of knowledge from various perspectives (for example, writing multiple flashcards for the same concept), such that I can configure each unit in the most suitable way while building a tower of understanding.
While units of knowledge are being collected by my net of flashcards, I am simultaneously scanning the environment to generate a high-resolution map of the ocean. The net won’t catch absolutely everything and it doesn’t need to. Having a detailed map of the knowledge landscape means that I can find exactly what I need when I need it. If ever certain areas of the ocean need to be returned to, having a detailed map enables the navigation to be much more precise — and if any remaining units of knowledge seem important, I’ve got my handy net.
The map is also helpful when navigating new spaces because well-mapped landmarks can be used to orient oneself in new terrain. Even when it comes to building towers of understanding, these maps can help in determining the best arrangement for the units of knowledge — for example, which ones might be best as foundation material or which blocks fit best together.
In practice, the mapping is a process of creating an interconnected knowledge-base of networked notes. The networking aspect is critical, as it allows for many of the underlying relationships between knowledge to be explicit — enabling one to be more intimately aware of the patterns behind the knowledge we are trying to learn (patterns which are essential to developing resilient, broad understanding).
Dragging a net and all this mapping equipment is a lot of work; it can feel clunky and even like a waste of time. It’s easy to become impatient and feel unproductive when we can’t zip through the ocean of knowledge. But speed is not the goal. Are you navigating the ocean of knowledge as an impatient sightseer or as a meticulous cartographer and curious forager?
Being an exponential learner doesn’t mean you consume information faster. In fact, it probably means you consume information slower. Rather, it’s about building a knowledge base and internalizing units of knowledge that enable you to learn and understand at a much faster rate. Ultimately, it can be the difference between feeling smart and being smart.
Why it’s hard to get started as an exponential learner
Getting started with the tools to become an exponential learner is a lot of work. It takes patience and lots of deliberate practice. Not only that, the results may not be clear right away. In fact, depending on how the “learning” is being measured, one might experience slower “learning” at first. For example, a student trying to write quality flashcards and well-structured interconnected notes may not have the time to get through all the material before the next test. On the other hand, a different student may be able to rush through all the material, cramming it in their memory just long enough to do well on the test, perhaps even better than the other student attempting to implement exponential learning practices.
In the beginning, exponential functions are slower than linear functions.Without the patience or foresight to recognize that an exponential function will eventually outpace a linear function, it can be challenging to adopt such habits. However, for those who persevere long enough to reach the inflection point, there’s no turning back.
Exponential learning for an epistemic crisis
I’m using the term exponential in a qualitative, subjective sense. I can’t tell you the quantitative effect on learning these tools have. Nonetheless, I think it serves as a useful framing to illustrate the profound effects just a few key changes in tools and workflow can make. My point is not to quantify the precise effects of these learning tools but to vividly express the importance of them for anyone committed to life-long learning in an increasingly complex world.
The epistemic reality of the 21st century is mind-boggling. Technology is advancing exponentially and knowledge itself is becoming more interconnected and complex. Not only is the complexity of understanding knowledge increasing at a seemingly exponential rate (including understanding the risks of things like hyperobjects) the internet, in its current form, has managed to cast a spell on billions of people, hacking our attention and downgrading our cognitive abilities. These two trends are a dangerous combination, leading some to describe it as an epistemic crisis. Without drastic improvements to our learning abilities at scale, we simply will not have the collective epistemic capacities to navigate the reality of the 21st century proactively.
Although much innovation in the space of educational technology is still required, networked note-taking and spaced-repetition flashcards exist today and can already make a significant difference. Additionally, they are both relatively straightforward habits to adopt. If adopted at scale (say, they were taught in public education systems), I believe we would fundamentally improve our collective sense-making capacities.
When we think of something like exponential learning technology, we probably think of brain-computer interfaces like neuralink. Perhaps, one day, some of us will integrate our brain activity with computers and AI at such a direct, physical level. Surprisingly, though, few seem to be talking about how the technology already exists to create high-bandwidth mind-computer interfaces. Our notes can be structured in a way that enables nearly seamless navigation of knowledge and flow-inducing augmented cognition. On top of that, our long-term memory can be hacked with flashcards, helping us internalize units of knowledge that form the basis of comprehensive understanding.
Steve Jobs used to say that computers are like bicycles for the mind. I would agree, although with a caveat: we first need to learn how to ride the mind-bike. In this article, I’ve offered some training wheels, but it’s up to you to put in the deliberate practice. Whether you’re prepared or not, the 21st century is going to be a wild ride.