toc: true layout: post title: The Great Mental Models - Shane Parrish categories: ['Book Notes'] descriptions: My notes image: https://i.imgur.com/5R9p5fy.png hide: false
<style> strong {background-color: yellow; font-weight:normal} .post-content #header-image img {width:40%}</style> --> > The quality of your thinking depends on the models in your head.
These book notes cover three volumes of The Great Mental Models by Shane Parrish of Farnham Street.
This book is about avoiding problems It is about understanding a problem accurately and seeing the secondary and subsequent consequences of any proposed action.
According to Charles Munger, "80 or 90 models will carry about 90% of the feight in making you a worldly-wise person. And of those, only a merge handful really carry very heaving freight"
A mental model is simply a representation of how something works
The book is about being able to draw on a repertoire of mental models that can help us minimise risk.
Flaws are
- not being open to other perspectives if we want to truly understand the results of our actions
- ego: being too invested in our opinions of ourselves to see the world's feedback. The feedback we need to update our beliefs about reality
- distance: the further we are from the results of our decisions, the easier it is to keep our current views rather than update them
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These flaws are the main reasons we keep repeating the same mistakes.
Three buckets of knowledge
- Bucket #1: Inorganic systems: all the laws of maths and physics, the entire physical universe
- Bucket #2: Organic systems. 3.5bn years of biology on Earth
- Bucket #3: human history (~20k years of recorded human behaviour)
As this book aims to present flaws that lead to blind spots, this chapter addresses the effect that "the map appears to us more real than the land" (D.H Lawrence)
When you are honest about where your knowledge is lacking, you know where you are vulnerable and where you can improve.
It encourages individuals to focus on what they know well, to continually learn and expand their knowledge, and to avoid making decisions based on incomplete or inaccurate information.
There are three key practices needed in order to build and maintain a circle of competence:
- curiosity
- a desire to learn
- a desire to learn
Falsification is the opposite of verification
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Science requires testability
[It's a] tool to help clarify complicated problems by separating the underlying ideas or facts from any assumptions based on them.
What remains are the essentials.
If we never learn to take something apart, test our assumptions about it, and reconstruct it, we end up bound by what other people tell us.
Estalish first principles by Socratic questioning.
It encourages individuals to focus on what they know well, to continually learn and expand their knowledge, and to avoid making decisions based on incomplete or inaccurate information.
- Clarify your thinking and explain the origins of your ideas (Why do I think this)
- Challenging assumptions (How do I know this is true)
- Looking for evidence (How can I back this up)
- Considering alternative perspectives
- Examining consequences and implications (What are the consequences if I'm wrong)
- Questions the original questions (Why did I think that. What conclusions can I draw from the reasoning process)
To improve something we need to understand why it is successful or not
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Otherwise we are just copying thoughts or behaviours without understanding why they worked. First principles thinking helps us avoid the problem of relying on someone else's tactics without understanding the rationale behind them
Many disciplines such as philosophy and physics make use of thought experiments to examine what can be known.
Much like the scientific method, the thought experiment generally has the steps:
- Ask a question
- Conduct Background research
- Construct hypothesis
- Test with (thought) experiments
- Analyse outcomes and draw conclusions
- Compare to hypothesis and adjust accordingly
What is not obvious is the gap between what is necessary to succeed and what is sufficient is often luck, change or some other factor beyond your direct control.
This is a useful model for seeing past immediate gains to identify long-term effects we want and realising long-term interests.
thinking farther ahead and thinking holistically
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It requires us to not only consider our actions and their immediate consequences, but the subsequent effects of those actions as well.
Arguments are more effective when we demonstrate that we have considered the second-order effects and put effort into verifying that these are desirable as well.
In essence, this is a the attempt at estimating, using mathematical tools and logic, the likelihood of any specific outcome coming to pass.
Three aspects of probability to integrate into your thinking:
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Bayesian thinking
- Adjusting probabilities when we encounter new data
- Use all relevant prior information in making decisions to put info in context
- Statisticians might call it a base rate - taking in outside information about past situtations like the ones you're in
- Rather than assigning a binary "yes/no", you assign a probability of it being true
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Fat-tailed curves
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In a distribution of events, ask how broad are the outliers? In a bell curve type of situation there is no cap on extreme events and the longer the tails of the curve will get.
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The more extreme events that are possible, the longer the tails get, and the ore extreme events that are possible, the higher the probability that one of them will occur.
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Deal with fat-tailed domains in the correct way, by positioning ourselves to survive or benefit from the wildly unpredictable future by being the only ones thinking correctly and planning for a world we don't understand.
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Asymmetries
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The "metaprobabiliy"
The probablility that your probability esimates are themselves, any good.
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