Occultism and esoterica can be a very fun topic–but the etymology of the word occult and occlusion, simply means that which is difficult to see.

Let’s start with a silly concept: there’s an apple on a nearby table. But the apple is a cosmic void–trying to perceive it directly just results in seeing a big ole chunk of nothing. How can we get the apple off the table? Well you can still see the table. You can see a big existential horror gap where the apple seems to be. You can see everything around that is not the apple. Therefore you can reason about this odd artifact and still manage to pick it up1.

Sciences are an endless example of real problems which are difficult to see. Without the work of Ohm, Volta, Ampère, Faraday, and others, electricity is a completely unfathomable force of pure magic2. Very specific metals cast in to specific shapes or else your spell results in either nothing or melting. Even today these forces can’t be directly perceived3 in action by human senses. Yet they do seem to exist and we have made them work to our own ends.

The book Flatland4 makes the explicit attempt to explain what reasoning beyond your perception is qualitatively like:

  1. A society of 2D shapes exists: lines, squares, circles
  2. The shapes are unaware the third dimension exists–they have no means to perceive it
  3. Humans can simply see all the shapes all at once. We have the advantage of being able to stand over the table and watch them
  4. The story is told from the perspective of the shapes who can’t see what we do

If this still doesn’t make much sense: the world is huge for ants finding sugar water. Humans simply see them drinking our canned soda.

Reasoning the Unseen#

if we know the rules of how something should behave: given some missing parts, we can still predict what it is doing.

Mathematicians work around this problem by creating books of logical rules which carry proofs that the rule applies for any given domain. A domain is simply the list of meta-rules for which these rules hold true within. Hard mathematics get to enjoy certainty about these–they aren’t making claims about the world, so Hume’s fork5 doesn’t eat their dinners. Experimental scientists, however, don’t have that luxury.

These books of rules, when to use them, and how to bend them or tape them together form the basis of “mental models.” Mental models allow you to transfer rules that are known to work for something and conjecture that it should work here too. Sometimes they do. Developing an intuition for which model to use for a given problem is a key skill for the hard sciences6.

So mathematics gives us forms like Ohm’s Law describing the relationship of electrical resistance, voltage, and current. It also gives us forms like the famous rocket equation7. But the less tedious point: if we know the rules of how something should behave: given some missing parts, we can still predict what it is doing.

Learning to See#

Learning to draw is really a matter of learning to see - and that means a good deal more than merely looking with the eye. –Kimon Nicolaides

The good news is that you do not need divine intellect8 to learn patterns. Anyone can learn anything–but the amount of suffering involved will vary by individual. This process of “learning how to learn” is called metalearning. Once a legitimate topic of classical education–its been lost9 and slowly rediscovered by writers like Ferriss10, Adler11, and Pólya.

Skills in the general sense are little more than patterns and rules about where the pattern is useful. These form applied pattern languages12. Language, business13, maths, sciences, everything humans reason about is just a rulebook of patterns. The certainty requirements vary by field of course but it works the same way. We even have a scientific field–statistics–that creates patterns about how we can reason about uncertainty itself.

The classical trivium14 was a doctrine from antiquity that packages this process as a teachable process:

  1. Grammar: first figure out what your basic symbols or words are.
  2. Logic: next figure out how they relate. Identify concepts that agree or conflict and root them out.
  3. Rhetoric: finally tell the narrative and make it memorable.

Completed rhetoric becomes grammar for more complicated topics. This process runs in a continuous loop until you have mastered a subject15.

Patterns Without End#

Perception is not limited to hard sciences. It can and has been effectively, systematized and applied to every conceivable problem humanity faces. I’m including some of my more favored cases here as further examples.

Inventive problem solving#

In the 1940s a soviet scientist, Genrich Altshuller, had an interesting idea: American technological innovations must have a pattern grammar to them. After studying hundreds of patents16 he created what is now called the theory of inventive problem solving or “TRIZ.”

TRIZ posits that technological invention revolves around a grammar of creating a contradiction between a tool and intended purpose. Then a table of forty rules suggests how to resolve the contradiction. By learning and propagating the process individuals can be taught to invent new technological solutions. It may involve grinding through a table of operators to get there–but relatively uncreative people can be made to do what is otherwise a “creative” problem.

Once more the classical trivium has been reinvented and packaged as a sellable system.

Social circuitry#

The oft-maligned field of Cybernetics tackles a much more controversial topic: first making control theory subject to pattern learning, and then noting that human society is itself just a control problem.

  • Norbert Wiener wrote the original books with Human Use of Humans
  • Ashby made the control science accessible with Introduction to Cybernetics
  • Stafford Beer both operationalized it with Project Cybersyn17 and later wrote about the human aspects with Brain of the Firm.
  • W. Edwards Deming wrote Out of The Crisis which while never once citing a cyberneticist embodies the philosophy completely. He operationalized it in post-WW2 Japan18.
  • Donnela Meadows wrote a more recent and relaxed introduction with Thinking in Systems. I found the book quite watered down in comparison–but that might make it more approachable.

Once more the concept of intentional study of feedback loops is both derived and demonstrated to be highly effective.

Afterword#

I hope in some way this has helped you become less helpless. You will never “not know where to start.” There is always some pattern or system–however incomplete–to perceive the unknown.

The edge of perception is not the end–it’s exactly where science begins.

Footnotes#

  1. Although picking up cosmic aberrations might be ill advised. ↩︎

  2. Practical Electronics for Inventors is often cited as one of the most approachable books for learning electrical engineering. ↩︎

  3. Well, unless you believe in stuff like the Ferrocell ↩︎

  4. Flatland was Abbot’s attempt to explain the experience of not understanding hyper-dimensions. It’s a difficult undertaking. ↩︎

  5. A famous philosophical argument truncated as “statements may either be 100% certain, or about the world, and never both.” ↩︎

  6. How to Solve It is a classic text on the importance of rules of thumb, heuristics, and solving problems by making the most of what you can get your hands on. ↩︎

  7. The “tyranny of the rocket equation” is a phrase from aeronautics. The amount of fuel needed for current rocket technology to put an amount of grams of stuff in to space is a hard ratio. You can’t negotiate with it. ↩︎

  8. The book Outliers notes that humans regularly confound “I can’t figure out how to go from my skill level to the professional’s skill level, therefore it must be [some external force.]” They are usually wrong. ↩︎

  9. A topic that deserves its own article if not a book. There is active conspiratorial malice that needs to be handled seriously. ↩︎

  10. 4 Hour Chef by Timothy Feriss is a pop book ostensibly about learning to cook–but is actually about Tim’s process of learning how to learn how to cook. ↩︎

  11. How to Read a Book by Adler & Doren is an amusingly named book that clasps at the classical trivium. They do not name it but share suspiciously similar commentary on how one should approach reading complex topics. ↩︎

  12. A Pattern Language is a famous book from Christopher Alexander, a deceased architectural philosopher, on this topic–even artistic pursuits are simply books of recurring habits about shapes. ↩︎

  13. James Clear has posted about mental models in professional business contexts. ↩︎

  14. Sister Miriam’s The Trivium is one of few available textbooks on the classical trivium. ↩︎

  15. John Boyd also framed this strategy as “Observe, Orient, Decide, Act” or “the OODA loop.” Though it seems he may have independently reinvented it from experience. ↩︎

  16. A tricky thing to do at the time. Soviet Russia’s authoritarianism clashes with academic inquiry pretty severely. ↩︎

  17. Beer’s Cybersyn built an internet out of abandonded telex systems on a shoestring budget in a beleaguered country. It’s believed to have non-factored at least one foreign intelligence attempt to interfere with socialist Chile’s economy. Shortly after, Pinochet violently overthrew the country and burned it down. ↩︎

  18. Deming ended up informing post-WW2 Japan’s management culture instead. This is directly responsible for cyberpunk tropes in the 1990s: quality based, humane, scientific engineering lead to Japan’s economic dominance of the times. People thought Japan was about to buy out the USA at the time. ↩︎