In a previous blog post, I talked about taking notes in a more serious way in Obsidian, but what would a serious note looks like?
In this post, I describe the benefits of developing notes. I also hypothesize why we need to develop evergreen notes, rather than just regular notes. Finally, I make a case for why an evergreen note has to be atomic, concept-oriented, and densely linked. (I’ll update the references later)
I’d have to let the author speak for himself:
Andy Matuschak – Evergreen notes
Externalization helps you think better
Thinking is difficult. To quote Jordan Peterson, it means being able to divide your mind into different people with different personalities and withstanding the tension of them battling it out.
Because our brain is powerful a processor but poor storage, and it’s within the interplay and contrast between ideas that productive thinking takes place, we should externalize as much as possible to focus our brainpower on resolving tensions between ideas. By externalizing symbols out to the notes, we can spend more brainpower on the productive part of thinking.
But regular notes are not appropriate externalizations
A note, ideally, is an externalization of the idea that it captures. This is arguably where the strength of note-taking comes from, at least in its full potential: by manipulating notes which are concrete entities, we can manipulate ideas that are abstract entities.
However, if we don’t design a note so that it captures an idea in a particular way, it will not be an appropriate externalization. This is why evergreen notes are valuable. The development of evergreen notes is necessary to our quest of leveraging evergreen notes to obtain insights. The next section elaborates why.
Notes should become chunks that we use to parse situations or problems
We perceive a problem or a situation using a set of chunks. For example, when we look at an office, we don’t see in detail the individuals who are residing on a physical structure that supports a particular posture, we see people sitting on chairs. “People” and “chairs” are chunks. The more sophisticated our chunks are, the better we perceive a situation/concept/problem.
There are two methods that we currently know that can lead to insights:
- Constraint relaxation.
- chunk decomposition.
Constraint relaxation is when we relax unnecessary constraints of the problem imposed by trickery or by our limited reading of the problem/situation. A famous example is the 9-dot problem where the key insight is that we have to relax the constraint of the line being drawn must reside within the box.
Another way that we can obtain insights is to decompose a chunk into different sets of chunks. For example, the infamous matchstick problem in which the key insight is that we must decompose the equal operator into two matchsticks that can be moved around.
A note should ideally become a chunk that we use to parse a situation or a problem.
Notes need to be atomic, concept-oriented to become chunks
It is worth noting that a regular note does not correspond to a useful chunk. We can’t use a meeting note, a quick jot-down, a sentence from a book, to parse a situation/problem, because it lacks the proper attributes. What are these attributes? Let’s take a deeper look at chunk.
A chunk is a concept built from other concepts, and which can be used in a way that does not require its deconstruction into smaller concepts. We don’t have to substitute “people” for “Jane, Dick, Grayson, and those who possess similar traits” when we want to use the term to refer to the concept of a general group of individuals. For a note to be a chunk, it must also be useful on its own without having to refer to other notes. This explains why evergreen notes need to be atomic.
A chunk also represents a concept. Even if it’s made up of other concepts or smaller details. Back to the analogy above, a “person” is an abstraction referring to any particular human being, without specifying who it is exactly. Abstraction is the defining characteristics of human thinking, and whatever externalization of thoughts are, it must have the same characteristics. Therefore, a note must also represent a concept.
In short, chunk is concept-oriented and atomic. If a note is to correspond to a chunk, it must also be concept-oriented and atomic. A note, over time, should become a chunk that we use to reason about the world.
Once we represent a problem with a set of evergreen notes, then chunk decomposition amounts to going into each evergreen note and see what it’s made of (or connected to). But there’s a final attribute: evergreen notes need to be densely linked.
Evergreen notes need to be densely linked
A loose chunk is defined by psychologists as that which can be decomposed into meaningful chunks. From experiments, we know that loose chunks are much more likely to be decomposed before tight chunks. This provides an important basis as to why evergreen notes need to be densely linked.
A densely linked evergreen note corresponds to a loose chunk. It is easier to decompose such a note to meaningful constituent notes. Chunk decomposition is necessary if we are to perceive the world in any novel way. If we can’t decompose the chunk “person” into the actual human being that we refer to in our mind, we can never distinguish and identify individuals. We can’t develop social relationships with anyone. All human beings would be the same, without any individuality.
When we parse a problem/situation using a novel set of chunks, we significantly increase the likelihood of looking at it in a new way from which a novel solution follows. This is possible only if there are ways in which we can break a chunk into a set of chunks. This is what linking evergreen notes do: enabling an evergreen note to be like a chunk in that it can be decomposed.
In summary, atomic, concept-oriented and densely linked evergreen notes facilitate insights by converting the problem of chunk decomposition into a much more soluble problem that is (evergreen) note decomposition..
Knoblich, Günther & Ohlsson, Stellan & Haider, Hilde & Rhenius, Detlef. (1999). Constraint Relaxation and Chunk Decomposition in Insight Problem Solving. Journal of Experimental Psychology: Learning, Memory, and Cognition. 25. 1534-1555. 10.1037/0278-7318.104.22.1684.