KNAWLEDGE is Overrated for Decision Making, or is it?

What is knowledge?

3 different women go to the doctor, the first one tells the doctor "I have this symptom, what should I do?". The doctor explains what the disease is, and gives a receipt for the woman to buy the right medicine in the pharmacy.

She takes the receipt home, puts it on an altar, and bows down to it 108 times a day. She doesn't get cured.

The second woman goes to the same doctor, and says "I have this symptom, what should I do?". The doctor explains what the disease is, and gives a receipt to buy the right medicine at the pharmacy. The woman now knows about her disease and knows that the medicine will cure her if she takes it as the doctor prescribed it.

She gets home, and starts arguing amongst her family and neighbors "I have the best doctor, he is good because he knows my disease and how to cure it, this receipt proves how good he is and why he is better than your doctors". She also doesn't get cured.

The third woman comes in and tells the doctor that she has a symptom. The doctor explains to her the disease and gives her a receipt to buy the right medicine and how to take it.

The third woman takes the receipt, goes to the pharmacy, buys the medicine, and takes it just like the doctor prescribed it. You get where I'm going with it, right? The third lady is the only one of the three that was cured.

This story was told to me by a monk when I was in a Vipassana retreat. It was meant to explore how different types of knowledge exist and to point out how experience is the peak to determine whether someone "understood" something, and not just "believed" or "memorized the words".

It takes time and experience to fully "understand" something. This was told to the whole group in a group session in the temple. And it was meant to explain the lack of "philosophizing" in the 10-day meditation course. It was a 100% hands-on course, with no talking other than the night lectures, and everything was meant to make it easier to learn the Vipassana technique.

That was in 2018, and it changed my life and my further understanding of what truly is "knowledge".

Years later I learned terms to describe each type of knowledge that the women in the story represent.

The ancient Greeks (why do I get the feeling it's always them) have created words to describe these different types of knowledge.

dogma -> the belief in something.

episteme -> the knowledge of "what something is".

techne -> the knowledge of "how to do something".

They created also a hierarchy on which type of knowledge is more "trustworthy" (hint, it was techne).

But I am not a philosopher, I'm not a monk, I'm a software engineer, a blogger, and a gamer, why do I care about definitions of knowledge?

Well, In one word?

Betting

I am constantly making decisions on tasks in my work, investments, side hustles(such as this blog), and day-to-day life. And I know making decisions based on the right "data" is the way to avoid many headaches in life.

And making decisions based on incomplete data is how we all make them. There's a word for it. Betting.

Because we can never be 100% sure of the results of our actions. Maybe a task that I thought was easy turns out to lead to dependency hell and the scope becomes way bigger than what I anticipated.

Maybe a family member will need me to take them to a hospital, maybe I will need to withdraw an account to pay for emergencies.

Life is filled with such decisions and unexpected stuff happening. And on top of all of it, you might be going about your decisions with data that is not just incomplete, but wrong!

That's why it helps a LOT to have a quick heuristic on the type of data you are operating with. Some folks use "experience", but how do you use "experience" if you're still early in your career?

Let me introduce you to some dudes.

The Dudes

The first one is called Karl Popper. He is a philosopher of science(apparently it is a real thing). He developed a central core idea of scientific endeavor that we know today. The concept of "falsifiability".

I've told the story of Thanksgiving Turkey before on this blog, but I can always tell it again.

Over the course of 1000 days, the turkey wakes up, sees a happy and caring human being gives it food, and caters to its needs.

As each day passes, the induction reasoning of the turkey further cements that on the next day, the same thing will happen again, a happy human will give it food and care for it. However, on the 1001 day its Thanksgiving, and the turkey will face information that will break its previous belief.

This turkey is operating on the assumption that you can "prove that something is true". And therefore finds no reason to suspect anything will disprove its reasoning in the future, it's already proven to be true NOW.

Falsifiability

Falsifiability is the fundamental idea that you can never prove something is True(Einstein's relativity showed holes in Newton's theory of gravitation, there are holes we know in relativity and Newton also showed holes in precious theories, and on and on).

Falsifiability operates in the assumption that the only proof we can generate is "the proof of something being false".

The reasons are multiple for this, but one is that to prove something is True scientifically, we'd need to know for sure how the future will play out and if no one will ever find holes in the current theory of whatever it is we are studying.

But how does that play out in making fast decisions under incomplete, and possibly false data?

The second dude I already talked about at length in this blog, is Nassim Taleb. He became rich investing in options for businesses he claimed were "fragile".

He capitalized on these bad businesses during the 2008 great financial crisis.

He has a radical idea of how to deal with imperfect data/information/knowledge.

Firstly, If you must understand something, you should be able to test it(see if it's false in a series of tests -> falsifiability at play).

Secondly, understanding is not always needed to make decisions, as long as you understand your "exposure to risk".

I went in more depth on mapping risk and how to take advantage of risk in other blog posts, but I'll give you a summary.

Decisions with or without Knowledge

If you need to make decisions with data you don't yet understand, you can weigh in how fast you need to make this decision against "deciding with knowledge" and "deciding with risk assessment".

Deciding with knowledge means understanding the data you have, it's best if you are able to test the data and your assumptions, that way you understand the data more and checks if it is false at that time.

Deciding with risk assessment means understanding your environment.

You need to know if you are in an environment where the unknowns are positive. That usually means you are under some sort of "insurance", meaning "paying a regular cost to protect yourself against unknown unknowns".

If you're in that situation, taking risks with decisions will not completely bankrupt you. An example would be financial options. If you buy options, that means you get to pay for an asset in the future for a price declared in the present, with an agreed-upon monthly cost.

Notice how "option" means you also get to not pay it if you don't think it's advantageous to you in the future.

The opposite side of this bet is someone that sells the option. They are obliged to sell you the asset in the future at whatever price you agreed for today.

The option buyer is in an environment where the unknown benefits him/her. They can choose not to buy something in the future, or buy something far below market price. Win-win.

The option seller is in the opposite environment, they are in the "insurance seller" environment, they get money now, but if the unknown future fluctuates the asset price is too high, they will lose money when they sell.

Notice how making decisions based on predicting unknowns are far more challenging than being "insured" in case things don't work out so well.

The option seller makes money by correctly mapping future unknowns. The option buyer makes money when unpredictable stuff happens.

It's far better to be on the buyer's side if you ask me.

Knowledge as a Differentiator

It's one thing to not depend on knowledge but still have it, it increases your odds of great decisions, and it all falls back on the three ladies' story.

The third lady could take the medicine without really understanding her disease and the medicine's effects on it. She would still be cured, in that particular situation.

But if we make the situation a bit more complex, where the doctor could be wrong, then she might need to reassess if she needs to go to another doctor or not, and for that, she will need either knowledge or insurance.

That's where elementary biology classes play a difference for people, and why it is convex(advantageous to be exposed to this knowledge vs not being exposed to it) for people to learn in school about basic things about the human body. You never know when you might need this knowledge.

Another option is she, without knowledge could at least see a couple of different doctors just to get a "second opinion" to "insure" herself against iatrogenics.

In this case both knowledge and "insurance" work alongside each other, one can influence another and allow you to make better bets(or decisions).

Evaluating News and "Facts"

After this post, I hope you learn to trust less in what "consensus-based" people are thinking and learned a thing or two about deciding if a piece of information is a "so so trustworthy", "trustworthy" or "not trustworthy at all" type.

Also, I hope you understand the power of insurance in case your knowledge isn't complete(it never really is).

A summary:

dogma -> requires belief and isn't falsifiable. Meaning we will never know for a fact whether it is true or not. It's a matter of faith.

episteme -> Knowledge of "what something is"(book knowledge) requires multiple tests to create a theory but can be falsified by future theories.

techne -> requires direct experience with something. Knowledge of "how to do something".  Is easily falsified(testable).

Now to each their own, but I trust more information I can test, and if I can't test some information, I try to expose myself to convex situations(situations where I'm insured in case of bad random events occurring), where the unknowns favor me.

Now tell me, how do you analyze the information you receive day to day? Did this post help you out? Or did you already know this stuff? Let me know in the comments 😊!

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