Mental models: the best way to make informed decisions - farnam

This guide explores all the information you need to know about mental models . When you're done , You will think better , Make fewer mistakes , Get better results .

Mental models are the way we understand the world . They not only shape the way we think and understand , And it shapes the connections and opportunities we see . Mental models are the way we simplify complexity , Why do we think that some things are more relevant than others , And how we reason .

A mental model is just a representation of how things work . We can't keep all the details of the world in our minds , So we use models to simplify complex things into understandable and organized blocks .

 

Mental model is not a mental model

We have some thinking models from our professional disciplines , But not a mental model ： Every expert has a different view . By default , A typical engineer thinks in a system ; Psychologists think in terms of motivation ; Biologists will think about evolution , By putting these disciplines in our minds , We can solve a problem in three dimensions . If we only look at things in one way , We have a blind spot . The blind spot will kill you .

To help you build a grid of mental models , So that you can make better decisions , We collected and summarized the most useful models we thought .

please remember ： Building your grid is a lifelong project . Hold the line , You will find yourself understanding the reality 、 The ability to make consistently correct decisions and help your loved ones will continue to improve .

 

Core mental model

 

1. The map is not territory

The map of reality is not reality . Even the best maps are not perfect . This is because they are the epitome of what they represent . If a map can perfectly represent territory , It is no longer a microcosm , So it is no longer useful to us . A map can also be a snapshot of a point in time , Represents something that no longer exists . As we think and make better decisions , This must be borne in mind .

2. Circle of ability

When self, not ability, drives what we do , We will have blind spots . If you know what you know , You know where you have an advantage over others . When you honestly tell others where your knowledge is lacking , You know where you are vulnerable , Where can you improve . Understanding your circle of competence can improve decision-making and results .

3. First principle thinking

First principle thinking is one of the best ways to reverse design complex situations and release creative possibilities . It is sometimes called reasoning from the first principle , It is a tool to help clarify complex issues , Separate basic ideas or facts from any assumptions based on them . The rest is the fundamentals . If you know the first principle of something , You can build the rest of your knowledge around these principles , Create something new .

4. Thought experiment

Thought experiments can be defined as " An imaginative device for studying the nature of things ". Many disciplines , Such as philosophy and physics , They all use thought experiments to study what they can know . In doing so , They can open up new avenues for inquiry and exploration . Thought experiments are powerful , Because they help us learn from our mistakes and avoid future mistakes . They make us take on the impossible , Assess the potential consequences of our actions , And reexamine history to make better decisions . They can help us figure out what we really want , And the best way to get there .

5. Second order thinking

Almost everyone can predict the direct results of their actions . This type of first-order thinking is easy and safe , But it's also a way to make sure you get the same results as others . Second order thinking is thinking further , It is a holistic thinking . It requires us not only to consider our actions and their immediate consequences , Also consider the subsequent impact of these actions . If we do not consider the second-order and third-order effects , Will release disaster .

6. Probabilistic thinking

Probabilistic thinking is essentially an attempt to use mathematical and logical tools to estimate the likelihood of any particular outcome . It is one of the best tools for us to improve the accuracy of decision-making . In this world , Every moment is determined by infinitely complex factors , Probabilistic thinking helps us determine the most likely outcome . When we know this , Our decisions can be more accurate and effective .

7. reverse

Reversal is a powerful tool to improve thinking , Because it can help you identify and remove obstacles to success . The root word of inversion is "invert", It means upside down or upside down . As a thinking tool , It means approaching a situation from the other end of the natural starting point . Most of us tend to think in one way ： forward . The inversion method allows us to turn the problem upside down , Think back . Sometimes it's good to start from scratch , But it might be more useful to start with the tail .

8. Okam razor

Simple explanations are more likely to be true than complex ones . This is the essence of Occam razor , It is a classic principle of logic and problem solving . Instead of wasting your time disputing complex solutions , You can make decisions more confidently by explaining them based on the least number of activities .

9. Hanlong's razor

It is difficult to trace the origin of Hanlong razor , It points out that we should not attribute those things that are easier to interpret as stupid to malice . In a complex world , Using this model can help us avoid bigotry and ideology . By not assuming in general that bad results are the fault of bad actors , We look for choices instead of missing opportunities . This model reminds us , People do make mistakes . It requires us to ask whether there is another reasonable explanation for what has happened . The most likely correct explanation is the one with the least intention .

 

A mental model of systematic thinking

1. Feedback loop  

All complex systems have positive and negative feedback loops ,A cause B,B It also affects A（ and C）, Go on like this -- The continuous motion of the circuit often produces high-order effects . In a homomorphic system ,A Changes in are often B The opposite change of pull back , To maintain the balance of the system , Just like the temperature of human body or the behavior of organizational culture . The automatic feedback loop maintains a " static state " Environment , Unless an external force changes the loop . One " Runaway feedback loop " Describes a situation , That is, the output of a reaction becomes its own catalyst （ Autocatalytic ）.

2. Balance

Balance is a process , The system adjusts itself through this process , To maintain a state of equilibrium , Make it work in a changing environment . Most of the time , They will be a little above or below it , It has to be constantly adjusted . It's like a pilot flying a plane , The system deviates from the route more than it does on the route . Everything in a static system helps keep it in balance , therefore , It is important to understand the limits of scope .

3. bottleneck

Bottleneck means （ Tangible or intangible ） Where flow is blocked , Thus limiting its continuous motion . It's like a blocked artery or a blocked sewer , The bottleneck in the production of any goods or services may be small , But if it's on the critical path , Will have a disproportionate impact . However , Bottlenecks can also be a source of inspiration , Because it forces us to reconsider whether there are other ways to succeed .

4. scale

One of the most important principles of the system is , They are sensitive to scale . When you expand or shrink them , attribute （ Or behavior ） It often changes . When studying complex systems , We must always quantify roughly -- At least in the order of magnitude -- We observe 、 Analyze or predict the scale of the system .

5. Margin of safety  

similarly , Engineers have also developed the habit of adding errors to all calculations . In an unknown world , Put one 9500 A bus weighs just over a hundred pounds 9600 Pound Bridge , Rarely considered a wise move . therefore , in general , Few modern bridges fail . In real life outside of Physical Engineering , We can often advantageously leave ourselves as strong as the bridge system .

6. Loss

Insurance companies and subscription services are well aware of the concept of loss -- Every year, a certain number of customers will be lost , Must be replaced . Standing still is equivalent to losing , As is called in " The red queen effect " As seen in the model of .Churn It exists in many commercial and human systems . A constant number is periodically lost , Any new number must be replaced before it can be added to it .

7. Algorithm

Although it is difficult to define precisely , But the algorithm is usually an automated set of rules or " The blueprint ", Guide a series of steps or actions , To produce a desired result , And often in a series of " If → that " A statement in the form of a sentence . Algorithms are best known for their applications in modern computing , But it is also a feature of biological life . for example , Human DNA It includes the algorithm for building human beings .

8. Critical mass

When a system is about to jump discretely from one phase to another , It becomes critical . The marginal utility of the last unit before the phase change is much higher than that of any previous unit . A frequently cited example is when water is heated to a specific temperature , From liquid to steam ." Critical mass " It refers to the quality required for the occurrence of critical events , Most common in nuclear systems .

9. Emergence Emergence

High level behaviors tend to emerge from the interaction of low-level components . The result is often not linear -- It is not a simple addition problem -- But non-linear , Or exponential . An important result of emergent behavior is , It cannot be predicted from simple research components .

10. Non repeatability  

We found that , In most systems, there are irreducible quantitative attributes , Such as complexity 、 minimum value 、 Time and length . Below the irreducible level , The desired result will never happen . It's impossible to get several women pregnant to reduce the time it takes to have a baby , It is impossible to simplify a successfully manufactured car into a single part . These results , At a certain point , Is irreducible .

11. The law of diminishing returns

Related to scale , Most important real-world outcomes are affected by the ultimate reduction in incremental value . A good example is a poor family . Give them enough money to thrive , They are no longer poor . But after a certain point , The extra money will not improve their fate ; At some roughly quantifiable point , The return on the extra money diminishes significantly . Usually , The law of diminishing returns tends to be in the negative -- Receive too much money  

 

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