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Our failures to update from interacting with reality spring primarily from three things: not having the right perspective or vantage point, ego-induced denial, and distance from the consequences of our decisions.

Think of it this way. In a bell curve type of situation, like displaying the distribution of height or weight in a human population, there are outliers on the spectrum of possibility, but the outliers have a fairly well-defined scope. You'll never meet a man who is ten times the size of an average man. But in a curve with fat tails, like wealth, the central tendency does not work the same way. You may regularly meet people who are ten, 100, or 10,000 times wealthier than the average person. That is a very different type of world.

A mental model is simply a representation of how something works. We cannot keep all of the details of the world in our brains, so we use models to simplify the complex into understandable and organizable chunks.

The second thing we can do is to learn how to fail properly. Failing properly has two major components. First, never take a risk that will do you in completely. (Never get taken out of the game completely.) Second, develop the personal resilience to learn from your failures and start again. With these two rules, you can only fail temporarily.

We can think about three categories of objects: Ones that are harmed by volatility and unpredictability, ones that are neutral to volatility and unpredictability, and finally, ones that benefit from it. The latter category is antifragile--like a package that wants to be mishandled. Up to a point, certain things benefit from volatility, and that's how we want to be. Why? Because the world is fundamentally unpredictable and volatile, and large events--panics, crashes, wars, bubbles, and so on--tend to have a disproportionate impact on outcomes.

You've got to hang experience on a latticework of models in your head."

The core of Bayesian thinking (or Bayesian updating, as it can be called) is this: given that we have limited but useful information about the world, and are constantly encountering new information, we should probably take into account what we already know when we learn something new. As much of it as possible. Bayesian thinking allows us to use all relevant prior information in making decisions. Statisticians might call it a base rate, taking in outside information about past situations like the one you're in.

When understanding is separated from reality, we lose our powers. Understanding must constantly be tested against reality and updated accordingly.

Korzybski, Alfred. 1879-1950 - Polish-American independent scholar who developed the field of general semantics. He argued that knowledge is limited by our physical and language capabilities.

The first flaw is perspective. We have a hard time seeing any system that we are in.

Learning everything on your own is costly and slow. You are one person. Learning from the experiences of others is much more productive.

The third flaw is distance. The further we are from the results of our decisions, the easier it is to keep our current views rather than update them.

Second-Order Problem Warren Buffett used a very apt metaphor once to describe how the second-order problem is best described by a crowd at a parade: Once a few people decide to stand on their tip-toes, everyone has to stand on their tip-toes. No one can see any better, but they're all worse off.

we're so afraid about what others will say about us that we fail to put our ideas out there and subject them to criticism. This way we can always be right. Second, if we do put our ideas out there and they are criticized, our ego steps in to protect us. We become invested in defending instead of upgrading our ideas.

I joke with my kids that if you want to suck up someone's brain, you should simply read a book. All the great wisdom of humanity is written down somewhere.

The second flaw is ego. Many of us tend to have too much invested in our opinions of ourselves to see the world's feedback--the feedback we need to update our beliefs about reality.

We need maps and models as guides. But frequently, we don't remember that our maps and models are abstractions and thus we fail to understand their limits. We forget there is a territory that exists separately from the map. This territory contains details the map doesn't describe.

Peter Bevelin, put it best: "I don't want to be a great problem solver. I want to avoid problems--prevent them from happening and doing it right from the beginning."

As Confucius said, "A man who has committed a mistake and doesn't correct it, is committing another mistake."

I believe in the discipline of mastering the best of what other people have figured out. Charlie Munger

<> Anonymous

There are two approaches to applying inversion in your life. Start by assuming that what you're trying to prove is either true or false, then show what else would have to be true. Instead of aiming directly for your goal, think deeply about what you want to avoid and then see what options are left over.

Avoiding stupidity is easier than seeking brilliance.

<> Margaret Atwood