The learning silos we leave behind
A temporary universe of learning
When I was completing my undergraduate degree, I put a lot of time, effort, and dollars into learning differential equations. I had several sources of motivation driving me to do well this class: it was required in order to graduate, I knew the reputation it had for being a difficult subject, and I simply liked the idea of adding depth to my background in mathematics.
It was a true grind, using every opportunity to scribble down equations and their solutions. I remember my students at the submarine training facility walking into the classroom after their lunch break to find their instructor sleeping at his desk, the whiteboard full of Laplace transforms, integral calculations, first and second-order equations and their solutions.
What do I have to show for it?
The undergraduate degree itself. You could argue that this alone pays for the resources I spent passing the class, since this milestone opened so many doors, unlocked so many opportunities.
The class's contribution to my high tolerance for struggling through hard problems.
A vague recollection of certain math jargon.
What I lost
The ability to solve differential equations. This is an acceptable outcome, since I don't want or need to solve them at this point in my life, and if I ever do, I can have a computer do it for me.
The higher-level, abstract explanations of what is going on with differential equations. This is the stuff I'd like to have retained. This is the stuff that unlocks ways of thinking about things, the metaphors, the cross-domain analyses, the transfer learning. The accumulation of these things is, for me, one of the central benefits of spending countless dollars, hours, and brain cycles on completing a degree in higher education.
The learning silos we leave behind
As we live our lives, we occasionally enter what I am calling learning silos, which are spaces, both physical and digital, where we spend valuable resources learning a thing or a set of things, and then leave them behind. We may or may not come out with some artifact representing what was done inside: a degree, a certificate, the ability to articulate something you couldn't before.
I call them silos because the term invokes a self-contained entity in the environment of one's life, highly disconnected from everything else in the environment. A university is one such silo, disconnected from your third job after graduation. You spend time in these silos learning, but the learning stops when you leave the silo. More importantly, your engagement with what you learned comes to a halt.
Some example learning silos
- Schools: grade school, university, trade school
- The courses the schools offer
- Online courses
- Books, both physical and digital
- Our jobs, and the roles within those jobs
- Side projects
- Ephemeral hobbies
- Podcasts
- Documentaries
- Conversations
- Software hackathons
As I'm sure you have noticed, almost anything could be described as a learning silo. The point is that we leave a lot of learning state behind when we separate from these entities.
Solving the learning silos problem
The second brain
It's obvious that many people have also noticed this, because there are many examples of attempts to stop forgetting everything we learn. One that stands out recently, and one that I've tried myself, is the maintenance of a "second brain." This is a name describing the various note-taking systems people have devised, with elegant organizational systems and linking between notes and different philosophies about the sizes and taxonomies of notes.
Some have taken this a step further, plugging these systems into AI/LLM tools, finding ways to keep that hard-earned knowledge always accessible and ways to discover new knowledge and connections within the notes themselves.
I think this is actually a pretty good start, especially with the emergence of modern LLM-based AI tooling. The important way this addresses the problem is that creates a habit and a system **for collecting the knowledge from each silo, and transferring this "state" between each silo.
What the second brain is missing
Maintaining a system as a hobby
The most common complaint about second brains I see is that maintaining the system becomes the point of maintaining the system, and its creator never or rarely uses it for its original purpose. People like the idea of keeping all this knowledge somewhere.
Stale knowledge
Another issue is that of stale knowledge. What happens when something external invalidates a whole bunch of stuff you have written down? How can you be aware when this happens and act upon it, updating those areas of your notes? This is, of course, a problem in any system involving data of any kind, and is certainly not a reason to avoid using a second brain.
A way to force engaging with the content
Some people use second brains with the understanding that they don't need to retain it, that's the point of the system. It's there when you need it.
But others truly want to retain more of what they learn. For this to happen, we need to engage with the content on some reasonable interval. We need to recall the critical components of what we learned.
The learning system we need
The second brain is a good start. But I think we can compound our returns with the following formula:
- A representation of our accumulated knowledge (second brain, knowledge graph, etc.)
- an intelligent way to recommend new things to learn based on current knowledge/state
- dynamic recall content on a spaced-repetition algorithm
- dynamic opportunities to engage with what we've learned and get high-quality feedback from that engagement