Wouldn’t it be great if you could assess each and every situation, interaction and decision on the merits of unbiased clear thinking?
Over time I’ve found that having a repertoire of mental models to fall back on has helped me steer clear of some serious errors.
In recent years these models have been gaining popularity due to Elon Musk, Charlie Munger etc. providing some insight into what makes them tick — stating that having a collection, or latticework, of models in your head enables you to make more sense of the world around you.
Trying to remember all the facts is not a winning strategy.
So what is a mental model?
A mental model is a construct you use to help explain things.
An easy one to start with would be Occam’s Razor — “Among competing hypotheses, the one with the fewest assumptions should be selected.”
In the context of real life; let’s say you’ve got a flat tire — some possible explanations would include (a) A screw got stuck in the tire wall and let all the air out, or (b) serial tire-flatteners sliced it open with a laser scalpel creating an imperceptible hole, then inserted the screw in another way to mark their victory… explanation (a) is more likely.
How have mental models helped me?
As a founder of startups…
Mental models helped me make decisions, solve problems and see the world in an entirely new way. They are like apps for my brain — making it more useful. As a startup founder you are hit with fifty plus problems each and every day to solve or make a decision on. Being able to compartmentalise and approach each problem in the right way means your batting average should go up.
In building out artificial intelligence products…
More recently when I am thinking about how to apply advanced machine learning and natural language processing within the financial markets — a lot of these models help me frame and think about what I want from various production models.
In general life….
Being able to think clearly in times of stress, as well as how to frame problems, is invaluable. It’s something I continue to practice on a daily basis — and I’m far from perfect.
What are some of the models that have helped me?
You’ll soon discover that there are a plethora of models out there, below is just a sample.
So that you don’t become overwhelmed; and thus, this whole exercise lose its purpose, you are going to have to actively sort the models into buckets, and actively use them in daily life. Furthermore, at the start, I’d encourage you to journal and reflect upon the usage so that it all starts to become automatic.
The text that is used to describe each is mainly from Wikipedia.
Regret minimisation framework
This framework helps you make tough decisions by projecting to your future self and looking backward on your current decision. RMF will help you leave your job and build the thing you’ve been thinking about for the past few years.
“I knew that when I was 80 I as not going to regret having tried this. I was not going to regret trying to participate in this thing called the Internet that I thought was going to be a really big deal. I knew that if I failed I wouldn’t regret that, but I knew the one thing I might regret is not ever having tried” — Jeff Bezos
“Never attribute to malice that which is adequately explained by carelessness”
Tendencies to think in a certain ways can lead to systematic deviations from a standard of rationality or good judgements. There’s a list of cognitive biases.
Minimal viable product
A process for testing assumptions and making sure there’s a need for your idea. The process: (1) What’s my riskiest assumption? (2) What is the smallest experiment I can do to test this assumption?
A type of thinking where you tend to notice or look for what confirms your beliefs rather than what contradicts them. This type of thinking is very dangerous as you move through an MVP process.
Jobs to be done
Helps you understand why a customer may choose your product. Knowing this will help you more accurately develop and market to customer needs.
“If you understand the job, how to improve the product becomes just obvious” — Clayton Christensen
Arguing from First Principles
A first principle is a basic, foundational, self-evident proposition or assumption that cannot be deduced from any other proposition or assumption.
Considers some hypothesis, theory, or principle for the purpose of thinking through its consequences.
By taking the overall system as well as its parts into account, systems thinking is designed to avoid potentially contributing to further development of unintended consequences.
A systematic approach to estimating strengths and weaknesses of alternatives that satisfy transactions, activities or functional requirements for a business.
The study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be apportioned to different sources of uncertainty in its inputs.
The selection of individuals, groups or data for analysis in such a way that proper randomisation is not achieved, thereby ensuring that the sample obtained is not representative of the population intended to be analysed.
The logical error of concentrating on the people or things that ‘survived’ some process and inadvertently overlooking those that did not because of their lack of visibility.
A common continuous probability distribution. Physical quantities that are expected to be the sum of many independent processes (such as measurement error) often have distributions that are nearly normal.
A states of allocation of resources in which it is impossible to age any one individual better off without making at least one individual worse off. A Pareto improvement is defined to be a change to a different allocation that make at least one individual better off without making any other individual worse off, given a certain initial allocation of goods among a set of individuals.
False positives & false negatives
A false positive is a result that indicates a given condition has been fulfilled, when it actually has not been fulfilled. A false negative is where a test result indicates that a condition failed, while it was actually successful.
Describes probability of an event, based on conditions that might be related to the event. For example, suppose one is interested in whether a person has cancer, and knows the person’s age. If cancer is related to age, then, using Bayes’ theorem, information about the person’s age can be used to more accurately assess the probability they have cancer.
Regression to the mean
The phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on the second measurement.
The value of the best alternative forgone where, given limited resources, a choice needs to be made between several mealy exclusive alternatives. Assuming the best choice is made, it is the ‘cost’ incurred by not enjoying the benefit that would have been had by taking the second best available choice.
Peoples tendency to strongly prefer avoiding losses to acquiring gains.
The third story
The third story is one an impartial observer, such as a mediator, would tell; it’s a version of events both sides can agree on
The force amplification achieved by using a tool, mechanical device or system.
Solving problems through an indirect creative approach, using reasoning that is not immediately obvious and involving ideas that may not be obtainable by using only traditional step-by-step logic.
Divergent thinking vs. convergent thinking
Mental models have helped me achieve more in lifeDivergent thinking is a thought process or method used to generate creative ideas by exploring many possible solutions. It is often used in conjunction with its cognitive opposite, convergent thinking, which follows a particular set of logical steps to arrive at one solution, which in some cases is a ‘correct’ solution.