Category: Mental Models

Our Favorite Farnam Street Posts From 2020

At the end of each year, the FS team takes time to reflect on the work we did and what we learned from it. Here’s a selection of our favorite articles from 2020 – and why we think they’re worth a second read.

Much of what we do at FS is about reflection. Learning requires reflection; time to sit, think, and process. There is no doubt that 2020 was tumultuous and challenged us in unexpected ways. What we anticipated and planned for on January 1 was not what we faced the rest of the year. Many of us were busy adjusting and thus might not have had the opportunity to digest and reflect on ideas as much as in the past.

At FS, we know it’s hard to find a signal in all the noise we experience on a daily basis.

To close out the year on the blog, we have decided to look back and share our favorite posts, as well as why we connected with them or how they helped us. Here are each team member’s choices from our 2020 posts.

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Adam

In no way do I consider myself to be an athlete, but I do expect great results when it comes to my work. The article The Inner Game: Why Trying Too Hard can be Counterproductive brought to light some of the internal struggles I deal with when trying to achieve my goals. There are days when I can achieve a “flow-state” in my work, whether it’s shooting or editing video or something else. Other days it’s a battle with self-doubt and self-sabotage despite all the external obstacles I’ve overcome. Finding harmony between the two is on-going, and despite me not being an athlete I plan on winning the inner game.

‘It’s not where you take things from—it’s where you take them to.’ – Jean-Luc Godard

As someone whose job requires creativity I constantly struggle with “Not Invented Here Syndrome.” Trying to come up with an original idea, a different angle, some never before seen concept was just how I assumed all the world-renowned doers and thinkers thought. I never really considered the concept of Standing on the Shoulders of Giants and drawing on our experiences and the raw materials around us to create something. Reflecting on my body of work, it seems obvious now that most of my productions draw from people who I admire, who have taught me, or inspirations sparked by someone else’s creation. Going forward I want to continue to create and who knows, maybe one day I can provide a shoulder to stand on. After all, I’m 6’4”, so I’ve got the giant part down.

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Vicky

One of my favorite articles from this year is Appearances vs Experiences: What Really Makes Us Happy. For me, this article tells a tale of what I try to embrace in my day to day life. Getting caught up in what we think will make us happy can lead us to bypass what truly will. Sometimes we can base decisions and choices on the immediate pleasure we get or expect without looking at the bigger picture or long-term effects. The experience can put things into a perspective we can grasp, while an appearance can just be an illusion.

How do you “win the game of life”? By deciding how you’ll play. In Finite and Infinite Games: Two Ways to Play the Game of Life, I love the perspective shift I feel when I think about how you can play this game. What truly measures success? Does the game end there? By setting new goals and thinking that life can be infinite, we can win by playing, instead of playing to win. For me, this brings on a great perspective of acquiring experience and knowledge over wealth and possessions so I can keep playing.

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Rosie

Daniel Kahneman has said that the main lesson we should learn from surprising events is that the world is surprising. Yet when disasters happen, we often focus on particulars and miss that wider lesson. In the article Stop Preparing For The Last Disaster, we discussed how we can respond to unexpected events by becoming more resilient in general. History may well repeat itself, but we never know which rerun we’re watching until after the matter.

One theme we explored on the blog throughout this year was community and the connections we form with other people. We looked at what brings us together and what drives us apart – as well as what that costs us, how we can make peace with solitude, and how we can rebuild connections.

Muscular Bonding: How Dance Made Us Human is a personal favorite article from 2020. In it, we looked at William H. McNeill’s theory that dancing together to music creates powerful bonds between people, leading to social cohesion and cooperative behavior. I liked this article because McNeill’s ideas suggest a simple, free, universally useful way to overcome disconnection.

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Rhiannon

This year we started to write about more concrete examples of using mental models in common life situations. We so often hear from readers that they love the idea of mental models but have challenges in understanding how to apply them. Our first effort at exploring a situation through the lens of different mental models, how to use them in charged situations, was an exciting step in the evolution of the FS blog.

Like most people, the COVID-19 pandemic served as a backdrop to my year. The challenges were incredible, and the speed of the changes they required were sometimes overwhelming. It felt like so much uncharted territory. One of the reasons I enjoyed the article Why We Feel at Home in a Crisis, was the context it provided for tumultuous times. Reading about the Blitz, a period of history I have always found fascinating, as well as appreciating the good that can come from a crisis, was the perfect solution to the disorientation I experienced at the beginning of the pandemic.

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Shane

As much as this year was about responding to crisis, it was also a test of our resilience. It’s less about what happens to you and more about how you respond. At FS, I frequently thought about how well we’d built our margin of safety, and planned for a wide range of outcomes. 2020 reinforced how important it is to preserve optionality. In a crisis, the more options you have, the greater your chance of survival. Options are the most important resource you can store up.

As many of you know, one of our goals at FS is to master the best of what other people have already figured out. I drew inspiration from how others have kept their teams performing during challenges, including from this post on leadership lessons from Jean Renoir.

From the whole team at FS, thank you to all of our readers for your support and engagement! We know it’s been a busy year for everyone, and we don’t take a minute of the time you’ve spent with us for granted. It was amazing to know that, even in these times of uncertainty, you were on the journey with us to learn and grow. To become better people and live a more meaningful life.

Mental Models for Career Changes

Career changes are some of the biggest moves we will ever make, but they don’t have to be daunting. Using mental models to make decisions we determine where we want to go and how to get there. The result is a change that aligns with the person we are, as well as the person we want to be.

We’ve all been there: you’re at a job, and you know it’s not for you anymore. You come in drained, you’re not excited on a Monday morning, and you feel like you could be using your time so much better. It’s not the people, and it’s not the organization. It’s the work. It’s become boring, unfulfilling, or redundant, and you know you want to do something different. But what?

Just deciding to change careers doesn’t get you very far because there are more areas to work in than you know about. A big change often involves some retraining. A career shift will impact your personal life. At the end of it all, you want to be happier but know there are no guarantees. How do you find a clear path forward?

No matter how ready you think you are to make a move, career changes are daunting. The stress of leaving what you’re comfortable with to venture into foreign territory stops many people from taking the first step toward something new.

It doesn’t have to be this way.

Using mental models can help you clarify the direction you want to go and plan for how to get there. They are tools that will give you more control over your career and more confidence in your decisions. When you do the work up front by examining your situation through the lens of a few mental models, you set yourself up for fewer regrets and more satisfaction down the road.

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Get in touch with yourself

Before you can decide which change to make, you need to get in touch with yourself. No change will be the right one if it doesn’t align with what you want to get out of life.

First, do you know where you want to go? Are you moving with direction or just moving? As a mental model, velocity reminds us there is a difference between speed and direction. It’s easy to move fast without getting anywhere. We can stay busy all day without achieving our goals. Without considering our velocity, we run a huge risk of getting sidetracked by things that make us move faster (more money, a title on a business card) without that movement actually leading us where we want to end up.

As the old saying goes, we want to run to something, not from something. When you start articulating your desired direction, you give yourself clear purpose in your career. It will be easier to play the long game because you know that everything you are doing is leading somewhere you want to be.

When it comes to changing careers, there are a lot of options. Using the mental model of velocity will help you focus on and identify the best opportunities.

Once you know where you want to end up, it’s often useful to work backward to where you are now. This is known as inversion. Start at the end and carefully consider the events that get you there in reverse order.

For example, it could be something as simple as waking up happy and excited to work every day. What needs to be true in order for that to be a reality? Are you working from home, having a quiet cup of coffee as you prepare to do some creative work? Are you working on projects aligned with your values? Are you contributing to making the world a better place? Are you in an intense, collaborative team environment?

Doing an inversion exercise helps you identify the elements needed for you to achieve success. Once you identify your requirements, you can use that list to evaluate opportunities that come up.

Inversion will help you recognize critical factors, like finances or the support of your family, that will be necessary to get to where you want to go. If your dream direction requires you to learn a new skill or work at a junior level while you ramp up on the knowledge you’ll need, you might need to live off some savings in the short term. Inversion, combined with velocity, will help you create the foundation you need now to take action when the right time comes.

Finally, the last step before you start evaluating the career environment is taking stock of the skills you already have. Why do you need to do this? So you know what you can repurpose. Here, you’re using the concept of exaptation, which is part of the broader adaptation model in biology. Exaptation refers to traits that evolved for one purpose and then, through natural selection, were used for completely unrelated capabilities. For instance, feathers probably evolved for insulation. It was only much later that they turned out to be useful for flying.

History is littered with examples of technologies or tools invented for one purpose that later became the foundation for something completely different. Did you know that Play-Doh was originally created to clean coal soot off walls? And bubble wrap was originally envisioned as material for shower curtains.

Using this model is partly about getting out of the “functional fixedness” mindset. You want to look at your skills, talents, and knowledge and ask of each one: what else could this be used for?

Too often we fail to realize just how versatile the experience we’ve built up over the years is. We’re great at using forks to eat, but they can also be used to brush hair, dig in a garden, and pin things to walls. Being great at presenting the monthly status update doesn’t mean you’re good at presenting monthly status updates. Rather, it means you can articulate yourself well, parse information for a diverse audience, and build networks to get the right information. Now, what else can those skills be used for?

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Evaluate the environment

Looking at different careers, we’re usually in a situation where the “map is not the territory.” It’s hard to know how great (or terrible) a job is until you actually do it. We often have two types of maps for the careers we wish we had: maps of the highlights, success stories, and opinions of people who love the work and maps based on how much we love the field or discipline ourselves.

The territory of the day-to-day work of these careers, however, is very different from what those two maps tell us.

In order to determine if a particular career will work for us, we need better maps. For example, the reality of being an actor isn’t just the movies and programs you see them in. It’s audition after audition, with more rejections than roles. It’s intense competition and job insecurity. Being a research scientist at a university isn’t just immersing yourself in a subject you love. It’s grant applications and teaching and navigating the bureaucracy of academia.

In order to build a more comprehensive map of your dream job, do your research on as large a sample size as possible. Talk to people doing the job you want. Talk to people who work in the organization. Talk to the ones that enjoy it. Talk to the ones who quit. Try to get an accurate picture of what the day-to-day is like.

Very few jobs are one-dimensional. They involve things like administrative tasks, networking, project management, and accountability. How much of your day will be spent doing paperwork or updating your coworkers? How much of a connection do you need to maintain with people outside the organization? How many people will you be dependent on? What are they like? And who will you be working for?

It’s not a good idea to become a writer just because you want to tell stories, open a restaurant just because you like to cook, or become a landscape designer just because you enjoy being outside. Those motivations are good places to start—because it’s equally terrible to become a lawyer just because your parents wanted you to. But you can’t stop with what you like. There isn’t a job in the world that’s pleasurable and fulfilling 100% of the time.

You give yourself a much higher chance of being satisfied with your career change if you take the time to learn as much as you can about the territory beforehand.

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Elements of planning

You know which direction you’re heading in, and you’ve identified a great new career possibility. Now what?

Planning for change is a crucial component of switching careers. Two models, global and local maxima and activation energy, can help us identify what we need to plan.

Global and local maxima refers to the high values in a mathematical function. On a graph, it’s a wavy curve with peaks and valleys. The highest peak in a section is a local maximum. The highest peak across the entire graph is the global maximum. Activation energy comes from chemistry, and is the amount of energy needed to see a reaction through to its conclusion.

One of the things global and local maxima teaches us is that sometimes you have to go down a hill in order to climb up a new one. To move from a local maximum to a higher peak you have to go through a local minimum, a valley. Too often we just want to go higher right away, or at the very least we want to make a lateral move. We perceive going down as taking a step backward.

A common problem is when we tie our self-worth to our salary and therefore reject any opportunities that won’t pay us as much as we’re currently making. The same goes for job titles; no one wants to be a junior anything in their mid-forties. But it’s impossible to get to the next peak if we won’t walk through the valley.

If you look at your career change through the lens of global and local maxima, you will see that steps down can also be steps forward.

Activation energy is another great model to use in the planning phase because it requires you to think about the real effort required for sustained change. You need to plan not just for making a change but also for seeing it through until the new thing has time to take hold.

Do you have enough in the bank to support yourself if you need to retrain or take a pay cut? Do you have the emotional support to help you through the challenges of taking on a brand-new career?

Just like fires don’t start with one match and a giant log, you have to plan for what you need between now and your desired result. What do you need to keep that reaction going so the flame from the match leads to the log catching fire? The same kind of thinking needs to inform your planning. After you’ve taken the first step, what will you need to keep you moving in the direction you want to go?

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After you’ve done all the work

After getting in touch with yourself, doing all your research, identifying possible paths, and planning for what you need to do to walk them to the end, it can still be hard to make a decision. You’ve uncovered so many nuances and encountered so many ideas that you feel overwhelmed. The reality is, when it comes to career change, there often is no perfect decision. You likely have more than one option, and whatever you choose, there’s going to be a lot of work involved.

One final model you can use is probabilistic thinking. In this particular situation, it can be helpful to use a Bayesian casino.

A Bayesian casino is a thought experiment where you imagine walking up to a casino game, like roulette, and quantifying how much you would bet on any particular outcome.

Let’s say when investigating your career change, you’ve narrowed it down to two options. Which one would you bet on for being the better choice one year later? And how much would you part with? If you’d bet ten dollars on black, then you probably need to take a fresh look at the research you’ve done. Maybe go talk to more people, or broaden your thinking. If you’re willing to put down thousands of dollars on red, that’s very likely the right decision for you.

It’s important in this thought experiment to fully imagine yourself making the bet. Imagine the money in your bank account. Imagine withdrawing it and physically putting it down on the table. How much you’re willing to part with regarding a particular career choice says a lot about how good that choice is likely to be for you.

Probabilistic thinking isn’t a predictor of the future. With any big career move, there are inevitably a lot of unknowns. There are no guarantees that any choice is going to be the right one. The Bayesian casino just helps you quantify your thinking based on the knowledge you have at this moment in time.

As new information comes in, return to the casino and see if your bets change.

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Conclusion

Career changes are some of the biggest moves we will ever make, but they don’t have to be daunting. Using mental models helps us find both the direction we want to go and a path we can take to get there. The result is a change that aligns with the person we are, as well as the person we want to be.

How Julia Child Used First Principles Thinking

There’s a big difference between knowing how to follow a recipe and knowing how to cook. If you can master the first principles within a domain, you can see much further than those who are just following recipes. That’s what Julia Child, “The French Chef”, did throughout her career.

Following a recipe might get you the results you want, but it doesn’t teach you anything about how cooking works at the foundational level. Or what to do when something goes wrong. Or how to come up with your own recipes when you open the fridge on a Wednesday night and realize you forgot to go grocery shopping. Or how to adapt recipes for your own dietary needs.

Adhering to recipes will only get you so far, and it certainly won’t result in you coming up with anything new or creative.

People who know how to cook understand the basic principles that make food taste, look, and smell good. They have confidence in troubleshooting and solving problems as they go—or adjusting to unexpected outcomes. They can glance at an almost barren kitchen and devise something delicious. They know how to adapt to a guest with a gluten allergy or a child who doesn’t like green food. Sure, they might consult a recipe when it makes sense to do so. But they’re not dependent on it, and they can change it up based on their particular circumstances.

There’s a reason many cooking competition shows feature a segment where contestants need to design their own recipe from a limited assortment of ingredients. Effective improvisation shows the judges that someone can actually cook, not just follow recipes.

We can draw a strong parallel from cooking to thinking. If you want to learn how to think for yourself, you can’t just follow what someone else came up with. You need to understand first principles if you want to be able to solve complex problems or think in a unique, creative fashion. First principles are the building blocks of knowledge, the foundational understanding acquired from breaking something down into its most essential concepts.

One person who exemplifies first principles thinking is Julia Child, an American educator who charmed audiences with her classes, books, and TV shows. First principles thinking enabled Julia to both master her own struggles with cooking and then teach the world to do the same. In Something from the Oven, Laura Shapiro tells the charming story of how she did it. Here’s what we can learn about better thinking from the “French Chef.”

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Gustave Flaubert wrote that “talent is a long patience, ” something which was all too true for Julia. She wasn’t born with an innate skill for or even love of cooking. Her starting point was falling in love with her future husband, Paul Child, in Ceylon in 1944 when both were working for the Office of Strategic Services. Paul adored food, and his delight in it inspired Julia. When they each returned to their separate homes after the war, she decided she would learn to cook. Things got off to a bad start, as Shapiro explains:

“At first she tried to teach herself at home, but it was frustrating to bushwhack her way through one dish after another. She never knew whether she would find success or failure when she opened the oven door, and worst of all, she didn’t know why this recipe worked and that one didn’t.”

Seeking expert guidance, Julia started taking cooking classes three times a week at a Beverly Hills cooking school. Even that didn’t help much, however, and after she married Paul a year later, her experiments in their Washington, DC kitchen continued to go awry. Only when the couple moved to Paris did an epiphany strike. Julia’s encounters with French cooking instilled in her an understanding of the need for first principles thinking. Trying to follow recipes without comprehending their logic wasn’t going to produce delicious results. She needed to learn how food actually worked.

In 1949, at the age of 37, she enrolled in classes at the famous Cordon Bleu school of cooking. It changed her forever:

“Learning to cook at the Cordon Bleu meant breaking down every dish into its smallest individual steps and doing each laborious and exhausting procedure by hand. In time Child could bone a duck while leaving the skin intact, extract the guts of a chicken through a hole she made in the neck, make a ham mousse by pounding the ham to a pulp with a mortar and pestle, and turn out a swath of elaborate dishes from choucroute garnie to vol-au-vent financière. None of this came effortlessly but she could do it. She had the brains, the considerable physical strength it demanded, and her vast determination. Most important, she could understand for the first time the principles governing how and why a recipe worked as it did.”

Julia had found her calling. After six months of Cordon Bleu classes, she continued studying independently for a year. She immersed herself in French cooking, filled her home with equipment, and befriended two women who shared her passion, Simone Beck and Louisette Bertholle. In the early 1950s, they opened a tiny school together, with a couple of students working out of Julia’s kitchen. She was “adamant that the recipes used in class be absolutely reliable, and she tested every one of them for what she called ‘scientific workability.’” By this, Julia meant that the recipes needed to make sense per her understanding of the science of cooking. If they didn’t agree with the first principles she knew, they were out.

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When Paul transferred to Marseille, Julia was sad to leave her school. But she and her friends continued their collaboration, working at a distance on a French cookery book aimed at Americans. For what would become Mastering the Art of French Cooking, Julia focused on teaching first principles in a logical order, not copying down mere recipes.

She’d grown frustrated at opening recipe books to see instructions she knew couldn’t work because they contradicted the science of cooking—for example, recipes calling for temperatures she knew would burn a particular ingredient, or omitting key ingredients like baking soda, without which a particular effect would be impossible. It was clear no one had bothered to test anything before they wrote it down, and she was determined not to make the same mistake.

Mastering the Art of French Cooking came out in 1961. Shapiro writes, “The reviews were excellent, there was a gratifying burst of publicity all across the country, and the professional food world acknowledged a new star in Julia Child. What nobody knew for sure was whether everyday homemakers in the nation that invented the TV dinner would buy the book.” Though the book was far from a flop, it was the TV show it inspired that catapulted Julia and her approach to cooking to stardom.

The French Chef first aired in 1963 and was an enormous success from the start. Viewers adored how Julia explained why she did what she did and how it worked. They also loved her spontaneous capacity to adapt to unanticipated outcomes. It was usually only possible to shoot one take so Julia needed to keep going no matter what happened.

Her show appealed to every kind of person because it could make anyone a better cook—or at least help them understand the process better. Not only was Julia “a striking image of unaffected good nature,” the way she taught really worked. Viewers and readers who followed her guidance discovered a way of cooking that made them feel in control.

Julia “believed anybody could cook with distinction from scratch and that’s what she was out to prove.” Many of the people who watched The French Chef were women who needed a new way to think about cooking. As gender roles were being redefined and more women entered the workforce, it no longer seemed like something they were obligated by birth to do. At the same time, treating it as an undesirable chore was no more pleasant than treating it as a duty. Julia taught them another way. Cooking could be an intellectual, creative, enjoyable activity. Once you understood how it actually worked, you could learn from mistakes instead of repeating them again and again.

Shapiro explains that “Child was certainly not the first TV chef. The genre was almost as old as TV itself. But she was the first to make it her own and have an enduring societal impact.”

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If you can master the first principles within a domain, you can see much further than those who are just following recipes. That’s what Julia managed to do, and it’s part of why she stood out from the other TV chefs of her time—and still stands out today. By mastering first principles, you can find better ways of doing things, instead of having to stick to conventions. If Julia thought a modern piece of equipment worked better than a traditional one or that part of a technique was a pointless custom, she didn’t hesitate to make changes as she saw fit. Once you know the why of something, it is easy to modify the how to achieve your desired result.

The lessons of first principles in cooking are the same for the first principles in any domain. Looking for first principles is just a way of thinking. It’s a commitment to understanding the foundation that something is built on and giving yourself the freedom to adapt, develop, and create. Once you know the first principles, you can keep learning more advanced concepts as well as innovating for yourself.

Descriptions Aren’t Prescriptions

When we look at a representation of reality, we can choose to either see it as descriptive, meaning it tells us what the world is currently like, or as prescriptive, meaning it tells us how the world should be. Descriptions teach us, but they also give us room to innovate. Prescriptions can get us stuck. One place this tension shows up is in language.

In one chapter of The Utopia of Rules: On Technology, Stupidity, and the Secret Joys of Bureaucracy, David Graeber describes his experience of learning Malagasy, the national language of Madagascar. While the language’s writing system came about in the fifteenth century, it wasn’t until the early nineteenth century that missionaries documented the rules of Malagasy grammar for the purpose of translating scripture.

Of course, the “rules” of Malagasy the missionaries recorded weren’t rules at all. They were reflections of how people spoke at that point in time, as far as outside observers could tell. Languages don’t usually come into existence when someone invents the rules for them. Instead, languages evolve and change over time as speakers make modifications or respond to new needs.

However, those early nineteenth-century records remained in place as the supposed “official” version of Malagasy. Children learned the old form of grammar in school, even as they spoke a somewhat different version of the language at home. For Graeber, learning to speak the version of Malagasy people actually understood in conversation was a challenge. Native speakers he hired would instruct him on the nineteenth-century grammatical principles, then turn and speak to each other in a whole other fashion.

When asked why they couldn’t teach him the version of the language they spoke, Graeber’s Malagasy teachers responded that they were just using slang. Asked why no one seemed to speak the official version, they said people were too lazy. Graeber writes, “Clearly the problem was that the entire population had failed to memorize their lessons properly. But what they were actually denying was the legitimacy of collective creativity, the free play of the system. ” While the official rules stayed the same over the decades, the language itself kept evolving. People assumed the fault of not speaking “proper” Malagasy lay with them, not with the outdated dictionary and grammar. They confused a description for a prescription. He writes:

It never seems to occur to anyone—until you point it out—that had the missionaries came and written their books two hundred years later, current usages would be considered the correct ones, and anyone speaking as they had two hundred years ago would themselves be assumed to be in error.

Graeber sees the same phenomenon playing out in other languages for which grammars and dictionaries only came into existence a century or two ago. Often, such languages were mostly spoken and, like Malagasy, no one made formal records until the need arose for people from elsewhere to make translations. Instead of treating those records as descriptive and outdated, those teaching the language treat them as prescriptive—despite knowing they’re not practical for everyday use.

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Why don’t people talk “proper”?

So why can’t people just speak a language per the official rules? If someone has gone to all the effort of identifying and recording the rules and people received instruction on them in school, why not follow them? Why keep changing things up?

If languages didn’t evolve, it would make life a lot easier for historians looking at texts from the past. It would also simplify matters for people learning the language, for those coming from different areas, and even for speakers across generations. Yet all languages change all the time.

Graeber suggests the reason for this is because people like to play. We find it dull to speak according to the official rules of our language. We seek out novelty in our everyday lives and do whatever it takes to avoid boredom. Even if each person only plays a little bit once in a while, the results compound. Graeber explains that “this playing around will have cumulative effects.”

Languages still need conventions so people can understand each other. The higher the similarity between the versions of a language different people speak, the more they can communicate. At the same time, they cannot remain rigid. Trying to follow an unyielding set of strict rules will inevitably curtail the usefulness of a language and prevent it from developing in interesting and necessary ways. Languages need a balance: enough guidance to help everyone understand each other and provide an entry point for learners, and enough flexibility to keep updating the rules as actual usage changes.

As a result, languages call into question our idea of freedom: “It’s worth thinking about language for a moment, because one thing it reveals, probably better than any other example, is that there is a basic paradox in our very idea of freedom. On the one hand, rules are by their nature constraining. Speech codes, rules of etiquette, and grammatical rules, all have the effect of limiting what we can and cannot say. ” On the other hand, no rules whatsoever mean no one can understand each other.

Languages need frameworks, but no amount of grammar classes or official dictionaries will prevent people from playing and having fun with their speech.

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The dictionary is not the language

“The map is not the territory” means that any representation of reality has to be a simplification that may contain errors, become outdated, or reflect biases. Maps remove details that aren’t necessary for their intended use. Representations of complex systems may show expected behavior or ideal behavior. For example, the London Underground map doesn’t reflect the distances between stations because this information isn’t important to most commuters. If a map represented its territory without reducing anything, it would be identical to the territory and therefore would be useless. In fact, the simplest maps can be the most useful because they’re the easiest to understand and remember.

Sometimes maps are descriptive, and sometimes they’re prescriptive; often they’re a bit of both. We run into problems when we confuse one type for another and try to navigate an idealized territory or make the real territory fit an idealized image.

A language’s grammar and dictionary are a sort of map. They take a complex system—a language spoken by what could be tens of millions of people—and aim to represent it with something which is, by comparison, simple. The official rules are not the language itself, but they provide guidance for navigating it. Much like a map of a city needs periodic updates as parts are torn down, built up, renamed, destroyed, added, and so on, the official rules need updating as the language changes. Trying to learn Malagasy using grammar rules written two hundred years ago is like trying to navigate Antananarivo using a street map made two hundred years ago.

A map of a complex system, like a language, is meant to help us find our way by giving us a sense of how things looked at one point in time—it’s usually descriptive. It doesn’t necessarily tell us how that system should look, and we may run into problems if we try to make it conform to the map, ignoring the system’s own adaptive properties. Even if the cartographer never intended this, we can end up treating a map as a prescription. We try to make reality conform to the map. This is what occurs with languages. Graeber calls this the “grammar-book effect”:

People do not invent languages by writing grammars, they write grammars—at least, the first grammars to be written for any given language—by observing the tacit, largely unconscious rules that people seem to be employing when they speak. Yet once a book exists, and especially once it is employed in schoolrooms, people feel that the rules are not just descriptions of how people do talk, but prescriptions for how they should talk.

As we’ve seen, one reason the map is not the territory with language is because people feel compelled to play and experiment. When we encounter representations of systems involving people, we should keep in mind that while we may need rules for the sake of working together and understanding each other, we’re always pushing up against and reshaping those rules. We find it boring to follow a rigid prescription.

For instance, imagine some of the documents you might receive upon starting a role at a new company. Process documents showing step by step how to do the main tasks you’ll be expected to perform. But when the person you’re replacing shows you how to do those same tasks, you notice they don’t follow the listed steps at all. When you ask why, they explain that the process documents were written before they started actually carrying out those tasks, meaning they discovered more efficient ways afterward.

Why keep the process documents, then? Because for someone filling in or starting out, it might make sense to follow them. It’s the most defensible option. Once you truly know the territory and won’t change something without considering why it was there in the first place, you can play with the rules. Those documents might be useful as a description, but they’re unlikely to remain a prescription for long.

The same is true for laws. Sometimes aspects of them are just descriptive of how things are at one point in time, but we end up having to keep following them to the letter because they haven’t been updated. A law might have been written at a time when documents needed sending by letter, meaning certain delays for shipping. Now they can be sent by email. If the law hasn’t been updated, those delay allowances turn from descriptions into prescriptions. Or a law might reflect what people were permitted to do at the time, but now we assume people should have the right to do that thing even if we have new evidence it’s not the best idea. We are less likely to change laws if we persist in viewing them as prescriptive.

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Conclusion

Descriptions of reality are practical for helping us navigate it, while also giving us room to change things. Prescriptions are helpful for giving us ways of understanding each other and providing enough structure for shared conventions, but they can also become outdated or end up limiting flexibility. When you encounter a representation of something, it’s useful to consider which parts are descriptive and which parts are prescriptive. Remember that both prescriptions and descriptions can and should change over time.

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The FS team were saddened to hear of David Graeber’s passing, shortly after we completed this article. We hope his books will continue to inspire and educate new readers for many years to come.

What Sharks Can Teach Us About Survivorship Bias

Survivorship bias refers to the idea that we get a false representation of reality when we base our understanding only on the experiences of those who live to tell their story. Taking a look at how we misrepresent shark attacks highlights how survivorship bias distorts reality in other situations.

When asked what the deadliest shark is to humans, most people will say the great white. The lasting influence of the movie Jaws, reinforced by dozens of pop culture references and news reports, keeps that species of shark at the top of the mind when one considers the world’s most fearsome predators. While it is true that great white sharks do attack humans (rarely), they also leave a lot of survivors. And they’re not after humans in particular. They usually just mistake us for seals, one of their key food sources.

We must be careful to not let a volume of survivors in one area blind us to the stories of a small number of survivors elsewhere. Most importantly, we need to ask ourselves what stories are not being told because no one is around to tell them. The experiences of the dead are necessary if we want an accurate understanding of the world.

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Before we drill down into some interesting statistics, it’s important to understand that great whites are one member of a class of sharks with many common characteristics. Great whites are closely related to tiger and bull sharks. They all have similar habitats, physiology, and instincts. They are also all large, with an average size over ten feet long.

Tiger and bull sharks rarely attack humans, and to someone being bit by one of these huge creatures, there isn’t all that much difference between them. The Florida Museum’s International Shark Attack file explains that “positive identification of attacking sharks is very difficult since victims rarely make adequate observations of the attacker during the ‘heat’ of the interaction. Tooth remains are seldom found in wounds and diagnostic characters for many requiem sharks [of which the great white is one] are difficult to discern even by trained professionals.”

The fatality rate in known attacks is 21.5% for the bull shark, 16% for the great white, and 26% for the tiger shark. But in sheer volume, attacks attributed to great whites outnumber the other two species three to one. So there are three times as many survivors to tell the story of their great white attack.

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When it comes to our picture of reality of the most dangerous shark, there are other blind spots. Not all sharks have the same behaviors as those three, such as swimming close to shore and being around enough prey to develop a preference for fat seals versus bony humans. Pelagic sharks live in the water desert that is the open ocean and have to eat pretty much whatever they can find. The oceanic white tip is a pelagic shark that is probably far more dangerous to humans—we just don’t come into contact with them as often.

There are only fifteen documented attacks by an oceanic white tip, with three of those being fatal. But since most attacks occur in the open ocean in more isolated situations (e.g., a couple of people on a boat versus five hundred people swimming at a beach), we really have no idea how dangerous oceanic white tips are. There could be hundreds of undocumented attacks that left behind no survivors to tell the tale.

One famous survivor story gives us a glimpse of how dangerous oceanic white tips might be. In 1945, a Japanese submarine shot down the USS Indianapolis. For a multitude of reasons, partly due to the fact that the Indianapolis was on a top secret mission and partly due to tragic incompetence, a rescue ship was not sent for four days. Those who survived the ship’s sinking had to then try to survive in the open ocean with little gear until rescue arrived. The water was full of sharks.

In Indianapolis: The True Story of the Worst Sea Disaster in US Naval History and the Fifty-Year Fight to Exonerate an Innocent Man, Lynn Vincent and Sara Vladic quote Boatswain’s Mate Second Class Eugene Morgan as he described part of his experience: “All the time, the sharks never let up. We had a cargo net that had Styrofoam things attached to keep it afloat. There were about fifteen sailors on this, and suddenly, ten sharks hit it and there was nothing left. This went on and on.” These sharks are believed to have been oceanic white tips. It’s unknown how many men died from shark attacks. Many also perished due to exposure, dehydration, injury, and exhaustion. Of the 1,195 crewmen originally aboard the ship, only 316 survived. It represents the single biggest loss of life from a single ship in US naval history.

Because humans are rarely in the open ocean in large numbers, not only are attacks by this shark less common, there are also fewer survivor stories. The story of the USS Indianapolis is a rare, brutal case that provides a unique picture.

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Our estimation of the shark that could do us the most harm is often formed by survivorship bias. We develop an inaccurate picture based on the stories of those who live to tell the tale of their shark attack. We don’t ask ourselves who didn’t survive, and so we miss out on the information we need to build an accurate picture of reality.

The point is not to shift our fear to oceanic white tips, which are, in fact, critically endangered. Our fear of sharks seems to make us indifferent to what happens to them, even though they are an essential part of the ocean ecosystem. We are also much more of a danger to sharks than they are to us. We kill them by the millions every year. Neither should we shift our fear to other, more lethal animals, which will likely result in the same indifference to their role in the ecosystem.

The point is rather to consider how well you make decisions when you only factor in the stories of the survivors. For instance, if you were to try to reduce instances of shark attacks or try to limit their severity, you will not likely get the results you are after if you only pay attention to the survivor stories. You need to ask who didn’t make it and try to figure out their stories as well. If you try to implement measures aimed only at great whites near beaches, your measures might not be effective against other predatory sharks. And if you conclude that swimmers are better off in the open ocean because sharks seem to only attack near beaches, you’d be completely wrong.

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Survivorship bias crops up all over our lives and impedes us from accurately assessing danger. Replace “dangerous sharks” with “dangerous cities” or “dangerous vacation spots” and you can easily see how your picture of a certain location might be skewed based on the experiences of survivors. We can’t be afraid of a tale if no one lives to tell it. More survivors can make something seem more dangerous rather than less dangerous because the volume of stories makes them more memorable.

If fewer people survived shark attacks we wouldn’t have survivor stories influencing our perception about how dangerous sharks are. In all likelihood we would attribute some of the ocean deaths to other causes, like drowning, because it wouldn’t occur to us that sharks could be responsible.

Understanding survivorship bias prompts us to look for the stories of those who weren’t successful. A lack of visible survivors with memorable stories might mean we view other fields as far safer and easier than they are.

For example, a field of business where people who experience failures go on to do other things might seem riskier than one where people who fail are too ashamed to talk about it. The failure of tech start-ups sometimes feels like daily news. We don’t often, however, hear about the real estate agent who has trouble making sales or who keeps getting outbid on offers. Nor do we hear much about architects who design terrible houses or construction companies who don’t complete projects.

Survivorship bias prompts us to associate more risk with industries that exhibit more public failures. But the failures from industries or businesses that aren’t shared are equally important. If we focus only on the survivor stories, we might think that being a real estate agent or an architect is safer than starting a technology company. It might be, but we can’t only base our understanding on which career option is the best bet on the widely shared stories of failure.

If we don’t factor survivorship bias into our thinking we end up in a classic map is not the territory problem. The survivor stories become a poor navigational tool for the terrain.

Most of us know that we shouldn’t become a writer based on the results achieved by J.K Rowling and John Grisham. But even if we go out and talk to other writers, or learn about their careers, or attend writing seminars given by published authors, we are still only talking to the survivors.

Yes, it’s super inspiring to know Stephen King got so many rejections early in his career that the stack of them was enough to pull a nail out of the wall. But what about the writers who got just as many rejections and never published anything? Not only can we learn a lot from them about the publishing industry, we need to consider their experiences if we want to anticipate and understand the challenges involved in being a writer.

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Not recognizing survivorship bias can lead to faulty decision making. We don’t see the big picture and end up optimizing for a small slice of reality. We can’t completely overcome survivorship bias. The best we can do is acknowledge it, and when the stakes are high or the result important, stop and look for the stories of those who were unsuccessful. They have just as much, if not more, to teach us.

The next time you’re assessing risk, ask yourself: am I paying too much attention to the great white sharks and not enough to the oceanic white tips?

Mental Models For a Pandemic

Mental models help us understand the world better, something which is especially valuable during times of confusion, like a pandemic. Here’s how to apply mental models to gain a more accurate picture of reality and keep a cool head.

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It feels overwhelming when the world changes rapidly, abruptly, and extensively. The changes come so fast it can be hard to keep up—and the future, which a few months ago seemed reliable, now has so many unknown dimensions. In the face of such uncertainty, mental models are valuable tools for helping you think through significant disruptions such as a pandemic.

A mental model is simply a representation of how something works. They are how we simplify complexity, why we consider some things more relevant than others, and how we reason. Using them increases your clarity of understanding, providing direction for the choices you need to make and the options you want to keep open.

Models for ourselves

During a pandemic, a useful model is “the map is not the territory.” In rapidly changing situations like a global health crisis, any reporting is an incomplete snapshot in time. Our maps are going to be inaccurate for many reasons: limited testing availability, poor reporting, ineffective information sharing, lack of expertise in analyzing the available information. The list goes on.

If past reporting hasn’t been completely accurate, then why would you assume current reporting is? You have to be careful when interpreting the information you receive, using it as a marker to scope out a range of what is happening in the territory.

In our current pandemic, we can easily spot our map issues. There aren’t enough tests available in most countries. Because COVID-19 isn’t fatal for the majority of people who contract it, there are likely many people who get it but don’t meet the testing criteria. Therefore, we don’t know how many people have it.

When we look at country-level reporting, we can also see not all countries are reporting to the same standard. Sometimes this isn’t a matter of “better” or “worse”; there are just different ways of collating the numbers. Some countries don’t have the infrastructure for widespread data collection and sharing. Different countries also have different standards for what counts as a death caused by COVID-19.

In other nations, incentives affect reporting. Some countries downplay their infection rate so as to not create panic. Some governments avoid reporting because it undermines their political interests. Others are more worried about the information on the economic map than the health one.

Although it is important to be realistic about our maps, it doesn’t mean we shouldn’t seek to improve their quality. Paying attention to information from experts and ignoring unverified soundbites is one step to increasing the accuracy of our maps. The more accurate we can get them, the more likely it is that we’ll be able to unlock new possibilities that help us deal with the crisis and plan for the future.

There are two models that we can use to improve the effectiveness of the maps we do have: “compounding” and “probabilistic thinking.”

Compounding is exponential growth, something a lot of us tend to have a poor intuitive grasp on. We see the immediate linear relationships in the situation, like how one test diagnoses one person, while not understanding the compounding effects of that relationship. Increased testing can lead to an exponential decrease in virus transmission because each infected person usually passes the virus onto more than just one other person.

One of the clearest stories to illustrate exponential growth is the story of the man who asked to be paid in rice. In this story, a servant is to be rewarded for his service. When asked how he wanted to be paid, he asks to be paid in rice, using a chessboard to determine the final amount. Starting with one grain, the amount of rice is to be doubled for each square. One grain on the first square looks pathetic. But halfway through the chessboard, the servant is making a good yearly living. And after doubling the rice sixty-four times, the servant is owed more rice than the whole world can produce.

Improving our ability to think exponentially helps us understand how more testing can lead to both an exponential decrease in testing prices and an exponential increase in the production of those tests. It also makes clear just how far-reaching the impact of our actions can be if we don’t take precautions with the assumption that we could be infected.

Probabilistic thinking is also invaluable in helping us make decisions based on the incomplete information we have. In the absence of enough testing, for example, we need to use probabilistic thinking to make decisions on what actions to pursue. We ask ourselves questions like: Do I have COVID-19? If there’s a 1% chance I have it, is it worth visiting my grandparents?

Being able to evaluate reasonable probability has huge impacts on how we approach physical distancing. Combining the models of probabilistic thinking and map is not the territory suggests our actions need to be guided by infection numbers much higher than the ones we have. We are likely to make significantly different social decisions if we estimate the probability of infection as being three people out of ten instead of one person out of one thousand.

Bayesian updating can also help clarify the physical distancing actions you should take. There’s a small probability of being part of a horrendous chain of events that might not just have poor direct consequences but also follow you for the rest of your life. Evaluating how responsible you are being in terms of limiting transmission, would you bet a loved one’s life on it?

Which leads us to Hanlon’s Razor. It’s hard not to get angry at reports of beach parties during spring break or at the guy four doors down who has his friends over to hang out every night. For your own sanity, try using Hanlon’s Razor to evaluate their behavior. They are not being malicious and trying to kill people. They are just exceptionally and tragically ignorant.

Finally, on a day-to-day basis, trying to make small decisions with incomplete information, you can use inversion. You can look at the problem backwards. When the best way forward is far from clear, you ask yourself what you could do to make things worse, and then avoid doing those things.

Models for society

Applying mental models aids in the understanding the dynamics of the large-scale social response.

Currently we are seeing the counterintuitive measures with first-order negatives (closing businesses) but second- and third-order positives (reduced transmission, less stress on the healthcare system). Second-order thinking is an invaluable tool at all times, including during a pandemic. It’s so important that we encourage the thinking, analysis, and decision-making that factors in the effects of the effects of the decisions we make.

In order to improve the maps that our leaders have to make decisions, we need to sort through the feedback loops providing the content. If we can improve not only the feedback but also the pace of iterations, we have a better chance of making good decisions.

For example, if we improve the rate of testing and the speed of the results, it would be a major game-changer. Imagine if knowing whether you had the virus or not was a $0.01 test that gave you a result in less than a minute. In that case, we could make different decisions about social openness, even in the absence of a vaccine (however, this may have invasive privacy implications, as tracking this would be quite difficult otherwise).

As we watch the pandemic and its consequences unfold, it becomes clear that leadership and authority are not the same thing. Our hierarchical instincts emerge strongly in times of crisis. Leadership vacuums, then, are devastating, and disasters expose the cracks in our hierarchies. However, we also see that people can display strong leadership without needing any authority. A pandemic provides opportunities for such leadership to emerge at community and local levels, providing alternate pathways for meeting the needs of many.

One critical model we can use to look at society during a pandemic is Ecosystems. When we think about ecosystems, we might imagine a variety of organisms interacting in a forest or the ocean. But our cities are also ecosystems, as is the earth as a whole. Understanding system dynamics can give us a lot of insight into what is happening in our societies, both at the micro and macro level.

One property of ecosystems that is useful to contemplate in situations like a pandemic is resilience—the speed at which an ecosystem recovers after a disturbance. There are many factors that contribute to resilience, such as diversity and adaptability. Looking at our global situation, one factor threatening to undermine our collective resilience is that our economy has rewarded razor-thin efficiency in the recent past. The problem with thin margins is they offer no buffer in the face of disruption. Therefore, ecosystems with thin margins are not at all resilient. Small disturbances can bring them down completely. And a pandemic is not a small disturbance.

Some argue that what we are facing now is a Black Swan: an unpredictable event beyond normal expectations with severe consequences. Most businesses are not ready to face one. You could argue that an economic recession is not a black swan, but the particular shape of this pandemic is testing the resiliency of our social and economic ecosystems regardless. The closing of shops and business, causing huge disruption, has exposed fragile supply chains. We just don’t see these types of events often enough, even if we know they’re theoretically possible. So we don’t prepare for them. We don’t or can’t create big enough personal and social margins of safety. Individuals and businesses don’t have enough money in the bank. We don’t have enough medical facilities and supplies. Instead, we have optimized for a narrow range of possibilities, compromising the resilience of systems we rely on.

Finally, as we look at the role national borders are playing during this pandemic, we can use the Thermodynamics model to gain insight into how to manage flows of people during and after restrictions. Insulation requires a lot of work, as we are seeing with our borders and the subsequent effect on our economies. It’s unsustainable for long periods of time. Just like how two objects of different temperatures that come into contact with each other eventually reach thermal equilibrium, people will mix with each other. All borders have openings of some sort. It’s important to extend planning to incorporate the realistic tendencies of reintegration.

Some final thoughts about the future

As we look for opportunities about how to move forward both as individuals and societies, Cooperation provides a useful lens. Possibly more critical to evolution than competition, cooperation is a powerful force. It’s rampant throughout the biological world; even bacteria cooperate. As a species, we have been cooperating with each other for a long time. All of us have given up some independence for access to resources provided by others.

Pandemics are intensified because of connection. But we can use that same connectivity to mitigate some negative effects by leveraging our community networks to create cooperative interactions that fill gaps in the government response. We can also use the cooperation lens to create more resilient connections in the future.

Finally, we need to ask ourselves how we can improve our antifragility. How can we get to a place where we grow stronger through change and challenge? It’s not about getting “back to normal.” The normal that was our world in 2019 has proven to be fragile. We shouldn’t want to get back to a time when we were unprepared and vulnerable.

Existential threats are a reality of life on earth. One of the best lessons we can learn is to open our eyes and integrate planning for massive change into how we approach our lives. This will not be the last pandemic, no matter how careful we are. The goal now should not be about assigning blame or succumbing to hindsight bias to try to implement rules designed to prevent a similar situation in the future. We will be better off if we make changes aimed at increasing our resilience and embracing the benefits of challenge.

Still curious? Learn more by reading The Great Mental Models.