Mental Models


Briefly on mental models — concepts, representations, and other tools for thinking in standard analogies.

The material here is mostly based on a collection of mental models assembled by the Farnam Street collective (FS). See their publications for more on the subject.

This piece is a reheating of the FS blog post, with a concise description for each model in the collection.


As Douglas Hofstadter would have it, analogies are the "fuel and fire of thinking" — A is to B as C is to D. We are continuously creating analogies as we pass through life observing similarities between seemingly unrelated events. As we encounter new things in the world, our past experiences shape our approach.

Similarly, when we encounter a new idea, the best way we can begin evaluating its potential is to view it in terms of some other mental construct we already understand. We need a pool of ideas to draw insight from, and the more toys we have in the pool, the better the party.

The motivation behind the study of mental models is that our thought processes do not always produce good results. Our naked cognition doesn't always work in the intended way: the idea pool is empty or in bad keep. For various reasons we simply fail to understand, we miss the answers, we make mistakes. Fortunately, just as we have learned to build tools to extend the abilities of our physical bodies, so, too, have we learned to work with ideas to increase the reach of our mercurial minds.

Tools for thought come in many shapes. Over time, as we have mastered the natural domains with which we interact every day, we have come across various kinds of useful ideas. These thinking tools, these concepts and principles and representations, are in a sense common and shared by all humans. The Great Mental Models collection presented here is a library of standard ideas and analogies that can be applied in a variety of contexts.

The argument goes that an awareness of mental models, and a basic understanding of how and where to apply them, may improve our thinking, may help us make the most of our cognitive abilities. Mental models capture the essence of some useful notion in a way that may have broader utility.

The selection process for this collection — again, based on the FS blog post — is somewhat arbitrary. It doesn't really matter what is or isn't a valid mental model. The items listed below do not all function in the same way, or meet any particular purpose, but rather each one aims to provide some kind of valuable insight. The point is that an awareness of these concepts can help us avoid pitfalls in our thinking and may aid our understanding. Mental models are a particularly nutritious kind of food for thought.

More broadly, there's two additional reasons to be interested in mental models. Firstly, mental models are the foundation of all digital tools. As users we manipulate the internal state of software systems through some kind of a user interface, which has to match our expectations, or otherwise we easily get confused. It is essential that the representation presented to us is compatible with our mental models of not just the system, but the original problem domain. Furthermore, the very best systems open up entirely new mental models for the user to explore. Great tools enable us to work in entirely new application areas and to make use of new capabilities, find new ways of doing things with a computer — and new things to do.

Secondly, mental models give us a flavour of the subtlety of human cognition and the analogy process. Mental models feature all kinds of fascinating concepts and representations that each would, for example, present a challenge to simulate or reproduce in AI systems. In a sense, mental models are some of our best representations for intangible things that we still consider to be real. A solid understanding of mental models and their relation with human cognition should prove a useful stepping stone on the path to building artificial minds.

Mental models are all those invisible constructs with which we try to make sense of the world. They help us make new connections and find new opportunities, and they help us decide what is relevant and salient. Mental models simplify complexity and point us in the direction of better reasoning and better thinking.

Mental Models

The collection here is grouped into several categories. We begin by looking at the human mind with its numerous heuristics and biases, followed by a brief review of human nature from feelings and instincts to other colourful facets of our fateful condition. Next up is abstract thinking, a powerful set of ideas with which we try to balance out the immediacy of our minds.

We then turn to the phenomena of the natural world. We'll first look at physics, chemistry, and biology, and then slowly turn our attention to man-made systems and mathematical wonders. We conclude the survey with some examples drawn from economics, and the art of war.

Again, all this is based on the excellent Farnam Street compilation. I've shuffled and structured the entries in a way that I find more accessible. Each entry is described by a succinct statement or two, in lieu of a deeper explanation.

This is by no means an exhaustive list of mental models, that's not the point at all. This is merely a beginner's guide, more of a highlights tour. Do check out Farnam Street for more details, including the Great Mental Models books in which they dedicate a full chapter to each model.

Human Judgement

Human Nature

Abstract Thinking

Fat-tailed processes: Abnormal black swan events are surprisingly common

Bayesian updating: Using data to update beliefs

“Don’t attribute to malice what can be explained by stupidity”

  • The Map is Not the Territory: Our perception of reality is not the same as reality

Maps are reductions
Maps are imperfect representations
Maps are useful precisely because they don’t show everything
Maps are point-in-time, perishable

Physics & Chemistry







“The best language [today] seems to be more colorless and glib than some of the language of [centuries past]. There's a vividness, a willingness to use metaphor and literary flourishes that you are less likely to see today. [..] It may be that because we have so many technical terms available to us, that we don't reach for the metaphor and that will drain prose of some of its vitality, even though it kind of makes it [easier] to convey abstract ideas." — Steven Pinker on contemporary language, during a Q&A for a talk based on his book The Sense of Style (2014)

"All models are wrong, but some are useful." — Statistics lore, popularised by George Box