Why should you build a latticework of mental models? Can mental models help you deal with your cognitive biases?
Building a latticework of mental models will help you become a versatile problem solver. You will use multidisciplinary learning to combine ideas across different disciplines to find solutions. Mental models will also help you recognize the psychological biases that could influence you, leading to better decision-making.
Read on to discover how to build your own latticework of mental models.
On Mental Models
Charlie Munger has learned a lot about the world, and he calls the main ideas from the major fields “mental models.” He stresses the importance of multidisciplinary learning and connecting the major ideas together in a latticework, where the ideas can interact with each other.
We’ll discuss the general concept of a latticework of mental models, share a synthesized list of mental models he mentions throughout the book, then discuss specific models to see how they apply to the real world.
Latticework of Mental Models
The inferior way to learn is to learn isolated facts that exist entirely in separate silos. You can recite the facts, but you don’t know the ideas underlying them, and you can’t apply those ideas to solve problems in real life. This is a failure of rote learning, which is common in many national education systems.
Munger argues that the superior way to learn is to learn lots of mental models for decision making, then assemble them into a connected latticework of mental models.
What are Mental Models?
You can think of “mental models” as important ideas in a field that have broad relevance outside the field itself.
For example, the idea of “critical mass” comes from physics. Within the field of physics, the idea of critical mass relates specifically to the mass needed to sustain a nuclear chain reaction—if you have less than the critical mass, a chain reaction won’t perpetuate itself. But this concept applies generally outside of physics—metaphorically, it can apply to the minimal mass needed to start any virtuous cycle, like the minimum number of users needed to get a social networking app off the ground.
We’ll cover a list of mental models below, but to give a brief illustration, other examples include “margin of safety” from engineering, “compound interest” from math, and “feedback loops” from biology. All of these originated from a narrow field but have metaphorical relevance outside the field.
Learn Lots of Mental Models
Think of your latticework of mental models as tools in your toolkit. The more tools you have, the more you can draw upon to solve the problem.
In contrast, if you have only one or two tools, then you’ll contort the situation to be solved by just those tools, and you’ll arrive at a suboptimal solution. This is similar to the “hammer-and-nail” problem—for people who have a specific hammer they like to use, everything in the world looks like a nail.
Learn Models from Different Fields
The best ideas in the world exist in each of the major fields. No single academic department has all the answers to all the problems. To become the most versatile problem solver, you need to collect mental models from every major field of study.
Modern academia tends to silo fields of study into isolated departments. Ideas stay narrowly defined, and experts within the field stay largely within their lane. Munger argues this is why a literature professor can be esteemed in her field but be considered unwise in other aspects of life.
The same balkanization applies to many modern corporate environments. Individual functions, like marketing and product, are divided and siloed, so that they rarely communicate with each other and squabble over territory.
When you have models from different fields working together, this can yield surprising results that other people don’t see. (Shortform note: For example, many breakthrough ideas arose from the unusual combination of ideas from two different fields. Behavioral economics came from the combination of psychology and economics. Genomics came from the combination of molecular biology and computer science.)
Putting Your Models Together
As you collect more of these ideas, you will start relating them together. For example, you might see how stock market swings are a combination of psychological biases (loss aversion, social proof), feedback loops from biology, critical mass from physics, and random walks from math. These connected ideas form a latticework of mental models.
We’ve talked about lollapaloozas already, when multiple forces combine in the same direction to push behavior into an extreme state. By building a latticework of mental models from many different fields, you’ll be able to diagnose the constituent parts of lollapaloozas.
Combining Models in Interesting Ways
Practically, your latticework of mental models can be combined to solve problems in interesting ways. Munger gives an example of how the economic concepts of Ricardo’s comparative advantage and Adam Smith’s pin factory intersected. In brief, comparative advantage describes how, in a free market, agents that have an advantage in producing a good will tend to produce more of it. Adam Smith’s pin factory shows the advantage of division of labor. The two are very different in nature—comparative advantage arises without any central planner, while the pin factory arises through a central planner.
One of Berkshire Hathaway’s companies had a hotel property in Los Angeles that had seen itself and its neighborhood deteriorate due to gangs and drug trade. The property was worth nearly nothing since people refused to stay there. Had they tried to brute-force a way to solve this predicament, they likely would have researched all sorts of ways to renovate the property, market itself to new customers, and improve the neighborhood.
Instead, the company put the hotel up for sale to see if the free market had a better plan for it. In came an entrepreneur, who had an unusual business model: He built hotels for senior citizens who flew in and wanted to visit tourist attractions in Los Angeles, like Disneyland. All its guests were bused from the hotel to the attractions, so they didn’t care what the surrounding neighborhood felt like. The guests were completely insulated from start to finish. This man was willing to pay more than anyone for the hotel.
Munger found this an amusing combination of the two economic models—this man had an optimized pin factory that the company didn’t have, but the company found the man through the free market.
How to Use Your Latticework of Mental Models
How is a latticework of mental models useful to decision-making? Munger suggests a two-step process:
- Recognize which models are at work in the situation at hand.
- Recognize which psychological biases might be influencing your conclusions.
Your latticework of mental models help simplify a complex chaotic situation into a series of simple, perennial principles. Once you see a problem this way, it might become easier to spot the solution.
Munger gives the example of early-20th century geneticist Thomas Hunt Morgan, who banned calculators in his department. While many other geneticists at the time used calculators to study all sorts of statistics, Morgan thought this led to an unproductively insular narrow approach that focused too much on minute details. By removing calculators, scientists would free themselves to focus on the big ideas that would lead to big advancements.
Notes on Specific Mental Models
Throughout his speeches, Munger comments on specific mental models and how they work.
Our brains evolved over millions of years, but mathematics and calculations came about only relatively recently, in the past thousands of years. Simply put, mathematics isn’t natural for our brains. We tend to use simple heuristics and approximations instead of rationally calculating numbers. Because it’s unnatural, you need to practice it regularly, the same way you need to practice a swimming stroke that feels unnatural at first.
In chemistry, autocatalysis occurs when a chemical reaction produces a catalyst for the same reaction. More generally, you can see this as a kind of positive feedback loop—the more the reaction runs, the faster the reaction runs.
For a business example, Munger discusses Disney’s valuable intellectual property. When a new medium arrives, like videocassettes and DVDs, Disney doesn’t need to invent anything new. It can simply reissue its movies on the new medium and make a lot of money simply. (Shortform note: Munger doesn’t quite complete the logic into how this forms a catalytic loop, but you could imagine that Disney could take the money from selling its media on the new medium to invest in creating new movies, which can then likewise be propagated into new media.)
Second, Third-Order Effects
When studying the effects of a change, people often study the immediate, direct effects—called the “first-order effects.” They ignore, however, the cascading effects that can result afterward—the effects of the effects, and the effects of those effects. These can be called “second-order” and “third-order” effects. This can lead to unintended consequences that sometimes defeat the purpose of the change to begin with.
Munger gives an example of planning the budget for creating Medicare in 1965. All the supposedly smart economists and experts looked at how much healthcare cost in the past, then extrapolated it to estimate the cost of covering all the newly enrolled patients. This estimate, however, was off by an order of magnitude. What these planners had neglected to do was think about the second-order effects—by providing generous healthcare benefits and new incentives, Medicare changed the behavior of patients and of medical practitioners. Medicine came up with all sorts of new treatments that would be covered by the richly funded programs, and patients sought them out. As a result, costs ballooned to over 1000% more than previously expected.
Munger gives another example of the consequences of trading with China back when it was still a poor developing country. From the perspective of Ricardo’s comparative advantage, this would seem like a no-brainer—a rich country like the United States would benefit from the labor and talent of a billion-plus people in China. Both countries seem to prosper. But China was arguably benefiting more from the trade than the rich countries were—it was absorbing all the technology that had given the rich countries their advantage. Soon, China would predictably surpass the rich nations it traded with. Munger foresaw this outcome and tried to talk to economists, who recoiled from the messy second- and third-order effects. The best response he got was from economist and cabinet member George Shultz, who explained that the United States had no real choice—if it didn’t trade with China, then other countries would, and given that the United States couldn’t stop the rise of China, it might as well get what it could out of the situation. Munger found this a difficult predicament.
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Here's what you'll find in our full Poor Charlie's Almanack summary :
- A collection of Charlie Munger’s best advice given over 30 years
- Why you need to know what you’re good at and what you’re bad at to make decisions
- Descriptions of the 25 psychological biases that distort how you see the world