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The OODA Loop: How Fighter Pilots Make Fast and Accurate Decisions

Reading Time: 11 minutes

The OODA Loop is a four-step process for making effective decisions in high-stakes situations. It involves collecting relevant information, recognizing potential biases, deciding, and acting, then repeating the process with new information. Read on to learn how to use the OODA Loop.

When we want to learn how to make rational decisions under pressure, it can be helpful to look at the techniques people use in extreme situations. If they work in the most drastic scenarios, they have a good chance of being effective in more typical ones.

Because they’re developed and tested in the relentless laboratory of conflict, military mental models have practical applications far beyond their original context. If they didn’t work, they would be quickly replaced by alternatives. Military leaders and strategists invest a great deal of time and resources into developing decision-making processes.

One such military mental model is the OODA Loop. Developed by strategist and U.S. Air Force Colonel John Boyd, the OODA Loop is a practical concept designed to function as the foundation of rational thinking in confusing or chaotic situations. “OODA” stands for “Observe, Orient, Decide, and Act.”

“What is strategy? A mental tapestry of changing intentions for harmonizing and focusing our efforts as a basis for realizing some aim or purpose in an unfolding and often unforeseen world of many bewildering events and many contending interests.” —John Boyd

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The four parts of the OODA Loop

Let’s break down the four parts of the OODA Loop and see how they fit together.

Don’t forget the “Loop” part. The process is intended to be repeated again and again until a conflict finishes. Each repetition provides more information to inform the next one, making it a feedback loop.

1: Observe

Step one is to observe the situation with the aim of building the most accurate and comprehensive picture of it possible.

For example, a fighter pilot might consider the following factors in a broad, fluid way:

  • What is immediately affecting me?
  • What is affecting my opponent?
  • What could affect either of us later on?
  • Can I make any predictions?
  • How accurate were my prior predictions?

Information alone is insufficient. The observation stage requires converting information into an overall picture with overarching meaning that places it in context. A particularly vital skill is the capacity to identify which information is just noise and irrelevant for the current decision.

If you want to make good decisions, you need to master the art of observing your environment. For a fighter pilot, that involves factors like the weather conditions and what their opponent is doing. In your workplace, that might include factors like regulations, available resources, relationships with other people, and your current state of mind.

To give an example, consider a doctor meeting with a patient in the emergency room for the first time to identify how to treat them. Their first priority is figuring out what information they need to collect, then collecting it. They might check the patient’s records, ask other staff about the admission, ask the patient questions, check vital signs such as blood pressure, and order particular diagnostic tests. Doctors learn to pick up on subtle cues that can be telling of particular conditions, such as a patient’s speech patterns, body language, what they’ve brought with them to the hospital, and even their smell. In some cases, the absence (rather than presence) of certain cues is also important. At the same time, a doctor needs to discard irrelevant information, then put all the pieces together before they can treat the patient.

2: Orient

“Orientation isn’t just a state you’re in; it’s a process. You’re always orienting.” —John Boyd

The second stage of the OODA Loop, orient, is less intuitive than the other steps. However, it’s worth taking the effort to understand it rather than skipping it. Boyd referred to it as the schwerpunkt, meaning “the main emphasis” in German.

To orient yourself is to recognize any barriers that might interfere with the other parts of the OODA Loop.

Orientation means connecting yourself with reality and seeing the world as it really is, as free as possible from the influence of cognitive biases and shortcuts. You can give yourself an edge over the competition by making sure you always orient before making a decision, instead of just jumping in.

Boyd maintained that properly orienting yourself can be enough to overcome an initial disadvantage, such as fewer resources or less information, to outsmart an opponent. He identified the following four main barriers that impede our view of objective information:

  1. Our cultural traditions – we don’t realize how much of what we consider universal behavior is actually culturally prescribed
  2. Our genetic heritage – we all have certain constraints
  3. Our ability to analyze and synthesize – if we haven’t practiced and developed our thinking skills, we tend to fall back on old habits
  4. The influx of new information – it is hard to make sense of observations when the situation keeps changing

Prior to Charlie Munger’s popularization of the concept of building a toolbox of mental models, Boyd advocated a similar approach for pilots to help them better navigate the orient stage of the OODA Loop. He recommended a process of “deductive destruction”: paying attention to your own assumptions and biases, then finding fundamental mental models to replace them.

Similar to using a decision journal, deductive destruction ensures you always learn from past mistakes and don’t keep on repeating them. In one talk, Boyd employed a brilliant metaphor for developing a latticework of mental models. He compared it to building a snowmobile, a vehicle comprising elements of several different devices, such as the caterpillar treads of a tank, skis, the outboard motor of a boat, and the handlebars of a bike.

Individually, each of these items isn’t enough to move you around. But combined they create a functional vehicle. As Boyd put it:

A loser is someone (individual or group) who cannot build snowmobiles when facing uncertainty and unpredictable change; whereas a winner is someone (individual or group) who can build snowmobiles, and employ them in an appropriate fashion, when facing uncertainty and unpredictable change.

To orient yourself, you have to build a metaphorical snowmobile by combining practical concepts from different disciplines. (For more on mental models, we literally wrote the book on them.) Although Boyd is regarded as a military strategist, he didn’t confine himself to any particular discipline. His theories encompass ideas drawn from various disciplines, including mathematical logic, biology, psychology, thermodynamics, game theory, anthropology, and physics. Boyd described his approach as a “scheme of pulling things apart (analysis) and putting them back together (synthesis) in new combinations to find how apparently unrelated ideas and actions can be related to one another.”

3: Decide

There are no surprises here. The previous two steps provide the groundwork you need to make an informed decision. If there are multiple options at hand, you need to use your observation and orientation to select one.

Boyd cautioned against first-conclusion bias, explaining that we cannot keep making the same decision again and again. This part of the loop needs to be flexible and open to Bayesian updating. In some of his notes, Boyd described this step as the hypothesis stage. The implication is that we should test the decisions we make at this point in the loop, spotting their flaws and including any issues in future observation stages

4: Act

There’s a difference between making decisions and enacting decisions. Once you make up your mind, it’s time to take action.

By taking action, you test your decision out. The results will hopefully indicate whether it was a good one or not, providing information for when you cycle back to the first part of the OODA Loop and begin observing anew.

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Why the OODA Loop works

“The ability to operate at a faster tempo or rhythm than an adversary enables one to fold the adversary back inside himself so that he can neither appreciate nor keep up with what is going on. He will become disoriented and confused.” —John Boyd

We’ve identified three key benefits of using the OODA Loop.

1: Deliberate speed

As we’ve established, fighter pilots have to make many decisions in fast succession. They don’t have time to list pros and cons or to consider every available avenue. Once the OODA Loop becomes part of their mental toolboxes, they should be able to cycle through it in a matter of seconds.

Speed is a crucial element of military decision-making. Using the OODA Loop in everyday life, we probably have a little more time than a fighter pilot would. But Boyd emphasized the value of being decisive, taking initiative, and staying autonomous. These are universal assets and apply to many situations.

2: Comfort with uncertainty

There’s no such thing as total certainty. If you’re making a decision at all, it’s because something is uncertain. But uncertainty does not always have to equate to risk.

A fighter pilot is in a precarious situation, one in which where there will be gaps in their knowledge. They cannot read the mind of the opponent and might have incomplete information about the weather conditions and surrounding environment. They can, however, take into account key factors such as the opponent’s type of airplane and what their maneuvers reveal about their intentions and level of training. If the opponent uses an unexpected strategy, is equipped with a new type of weapon or airplane, or behaves in an irrational way, the pilot must accept the accompanying uncertainty. However, Boyd belabored the point that uncertainty is irrelevant if we have the right filters in place.

If we can’t cope with uncertainty, we end up stuck in the observation stage. This sometimes happens when we know we need to make a decision, but we’re scared of getting it wrong. So we keep on reading books and articles, asking people for advice, listening to podcasts, and so on.

Acting under uncertainty is unavoidable. If we do have the right filters, we can factor uncertainty into the observation stage. We can leave a margin of error. We can recognize the elements that are within our control and those that are not.

In presentations, Boyd referred to three key principles to support his ideas: Gödel’s theorems, Heisenberg’s Uncertainty Principle, and the Second Law of Thermodynamics. Of course, we’re using these principles in a different way from their initial purpose and in a simplified, non-literal form.

Gödel’s theorems indicate any mental model we have of reality will omit certain information and that Bayesian updating must be used to bring it in line with reality. For fighter pilots, their understanding of what is going on during a battle will always have gaps. Identifying this fundamental uncertainty gives it less power over us.

The second concept Boyd referred to is Heisenberg’s Uncertainty Principle. In its simplest form, this principle describes the limit of the precision with which pairs of physical properties can be understood. We cannot know the position and the velocity of a body at the same time. We can know either its location or its speed, but not both.

Boyd moved the concept of the Uncertainty Principle from particles to planes. If a pilot focuses too hard on where an enemy plane is, they will lose track of where it is going and vice versa. Trying harder to track the two variables will actually lead to more inaccuracy!

Finally, Boyd made use of the Second Law of Thermodynamics. In a closed system, entropy always increases and everything moves towards chaos. Energy spreads out and becomes disorganized.

Although Boyd’s notes do not specify the exact applications, his inference appears to be that a fighter pilot must be an open system or they will fail. They must draw “energy” (information) from outside themselves or the situation will become chaotic. They should also aim to cut their opponent off, forcing them to become a closed system.

3: Unpredictability

When you act fast enough, other people view you as unpredictable. They can’t figure out the logic behind your decisions.

Boyd recommended making unpredictable changes in speed and direction, writing, “We should operate at a faster tempo than our adversaries or inside our adversaries[’] time scales.…Such activity will make us appear ambiguous (non predictable) [and] thereby generate confusion and disorder among our adversaries.” He even helped design planes that were better equipped to make those unpredictable changes.

For the same reason that you can’t run the same play seventy times in a football game, rigid military strategies often become useless after a few uses, or even one iteration, as opponents learn to recognize and counter them. The OODA Loop can be endlessly used because it is a formless strategy, unconnected to any particular maneuvers.

We know that Boyd was influenced by Sun Tzu (he owned seven thoroughly annotated copies of The Art of War) and drew many ideas from the ancient strategist. Sun Tzu depicts war as a game of deception where the best strategy is that which an opponent cannot preempt.

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Forty Second Boyd

“Let your plans be dark and impenetrable as night, and when you move, fall like a thunderbolt.” —Sun Tzu

Boyd was no armchair strategist. He developed his ideas through extensive experience as a fighter pilot. His nickname “Forty Second Boyd” speaks to his expertise: Boyd could win any aerial battle in less than forty seconds.

In a tribute written after Boyd’s death, General C.C. Krulak described him as “a towering intellect who made unsurpassed contributions to the American art of war. Indeed, he was one of the central architects of the reform of military thought.…From John Boyd we learned about competitive decision-making on the battlefield—compressing time, using time as an ally.”

Reflecting Robert Greene’s maxim that everything is material, Boyd spent his career observing people and organizations. How do they adapt to changeable environments in conflicts, business, and other situations?

Over time, he deduced that these situations are characterized by uncertainty. Dogmatic, rigid theories are unsuitable for chaotic situations. Rather than trying to rise through the military ranks, Boyd focused on using his position as a colonel to compose a theory of the universal logic of war.

Boyd was known to ask his mentees the poignant question, “Do you want to be someone, or do you want to do something?” In his own life, he certainly focused on the latter path and, as a result, left us ideas with tangible value. The OODA Loop is just one of many.

Boyd developed the OODA Loop with fighter pilots in mind, but like all good mental models, it works in other fields beyond combat. It’s used in intelligence agencies. It’s used by lawyers, doctors, businesspeople, politicians, law enforcement, marketers, athletes, coaches, and more.

If you have to work fast, you might want to learn a thing or two from fighter pilots. For them, a split-second of hesitation can cost them their lives. As anyone who has ever watched Top Gun knows, pilots have a lot of decisions and processes to juggle when they’re in dogfights (close-range aerial battles). Pilots move at high speeds and need to avoid enemies while tracking them and keeping a contextual knowledge of objectives, terrains, fuel, and other key variables.

And as any pilot who has been in one will tell you, dogfights are nasty. No one wants them to last longer than necessary because every second increases the risk of something going wrong. Pilots have to rely on their decision-making skills—they can’t just follow a schedule or to-do list to know what to do.

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Applying the OODA Loop

“We can’t just look at our own personal experiences or use the same mental recipes over and over again; we’ve got to look at other disciplines and activities and relate or connect them to what we know from our experiences and the strategic world we live in.” —John Boyd

In sports, there is an adage that carries over to business quite well: “Speed kills.” If you are able to be nimble, assess the ever-changing environment, and adapt quickly, you’ll always carry the advantage over any opponents.

Start applying the OODA Loop to your day-to-day decisions and watch what happens. You’ll start to notice things that you would have been oblivious to before. Before jumping to your first conclusion, you’ll pause to consider your biases, take in additional information, and be more thoughtful of consequences.

As with anything you practice, if you do it right, the more you do it, the better you’ll get. You’ll start making better decisions to your full potential. You’ll see more rapid progress. And as John Boyd would prescribe, you’ll start to do something in your life, and not just be somebody.

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We hope you’ve enjoyed our three week exploration of perspectives on decision making. We think there is value in juxtaposing different ideas to help us learn. Stay tuned for more topic specific series in the future.

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The Feynman Learning Technique

Reading Time: 23 minutes

If you’re after a way to supercharge your learning and become smarter, the Feynman Technique might just be the best way to learn absolutely anything. Devised by a Nobel Prize-winning physicist, it leverages the power of teaching for better learning.

The Feynman Learning Technique is a simple way of approaching anything new you want to learn.
Why use it? Because learning doesn’t happen from skimming through a book or remembering enough to pass a test. Information is learned when you can explain it and use it in a wide variety of situations. The Feynman Technique gets more mileage from the ideas you encounter instead of rendering anything new into isolated, useless factoids.

When you really learn something, you give yourself a tool to use for the rest of your life. The more you know, the fewer surprises you will encounter, because most new things will connect to something you already understand.

Ultimately, the point of learning is to understand the world. But most of us don’t bother to deliberately learn anything. We memorize what we need to as we move through school, then forget most of it. As we continue through life, we don’t extrapolate from our experiences to broaden the applicability of our knowledge. Consequently, life kicks us in the ass time and again.

To avoid the pain of being bewildered by the unexpected, the Feynman Technique helps you turn information into knowledge that you can access as easily as a shirt in your closet.

Let’s go.

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The Feynman Technique

“Any intelligent fool can make things bigger, more complex, and more violent. It takes a touch of genius—and a lot of courage—to move in the opposite direction.” —E.F. Schumacher

There are four steps to the Feynman Learning Technique, based on the method Richard Feynman originally used. We have adapted it slightly after reflecting on our own experiences using this process to learn. The steps are as follows:

  1. Pretend to teach a concept you want to learn about to a student in the sixth grade.
  2. Identify gaps in your explanation. Go back to the source material to better understand it.
  3. Organize and simplify.
  4. Transmit (optional).

Step 1: Pretend to teach it to a child or a rubber duck

Take out a blank sheet of paper. At the top, write the subject you want to learn. Now write out everything you know about the subject as if you were teaching it to a child or a rubber duck sitting on your desk. You are not teaching to your smart adult friend, but rather a child who has just enough vocabulary and attention span to understand basic concepts and relationships.

Or, for a different angle on the Feynman Technique, you could place a rubber duck on your desk and try explaining the concept to it. Software engineers sometimes tackle debugging by explaining their code, line by line, to a rubber duck. The idea is that explaining something to a silly-looking inanimate object will force you to be as simple as possible.

It turns out that one of the ways we mask our lack of understanding is by using complicated vocabulary and jargon. The truth is, if you can’t define the words and terms you are using, you don’t really know what you’re talking about. If you look at a painting and describe it as “abstract” because that’s what you heard in art class, you aren’t displaying any comprehension of the painting. You’re just mimicking what you’ve heard. And you haven’t learned anything. You need to make sure your explanation isn’t above, say, a sixth-grade reading level by using easily accessible words and phrases.

When you write out an idea from start to finish in simple language that a child can understand, you force yourself to understand the concept at a deeper level and simplify relationships and connections between ideas. You can better explain the why behind your description of the what.

Looking at that same painting again, you will be able to say that the painting doesn’t display buildings like the ones we look at every day. Instead it uses certain shapes and colors to depict a city landscape. You will be able to point out what these are. You will be able to engage in speculation about why the artist chose those shapes and those colors. You will be able to explain why artists sometimes do this, and you will be able to communicate what you think of the piece considering all of this. Chances are, after capturing a full explanation of the painting in the simplest possible terms that would be easily understood by a sixth-grader, you will have learned a lot about that painting and abstract art in general.

Some of capturing what you would teach will be easy. These are the places where you have a clear understanding of the subject. But you will find many places where things are much foggier.

Step 2: Identify gaps in your explanation

Areas where you struggle in Step 1 are the points where you have some gaps in your understanding.
Identifying gaps in your knowledge—where you forget something important, aren’t able to explain it, or simply have trouble thinking of how variables interact—is a critical part of the learning process. Filling those gaps is when you really make the learning stick.

Now that you know where you have gaps in your understanding, go back to the source material. Augment it with other sources. Look up definitions. Keep going until you can explain everything you need to in basic terms.

Only when you can explain your understanding without jargon and in simple terms can you demonstrate your understanding. Think about it this way. If you require complicated terminology to explain what you know, you have no flexibility. When someone asks you a question, you can only repeat what you’ve already said.

Simple terms can be rearranged and easily combined with other words to communicate your point. When you can say something in multiple ways using different words, you understand it really well.
Being able to explain something in a simple, accessible way shows you’ve done the work required to learn. Skipping it leads to the illusion of knowledge—an illusion that can be quickly shattered when challenged.

Identifying the boundaries of your understanding is also a way of defining your circle of competence. When you know what you know (and are honest about what you don’t know), you limit the mistakes you’re liable to make and increase your chance of success when applying knowledge.

Step 3. Organize and simplify

Now you have a set of hand-crafted notes containing a simple explanation. Organize them into a narrative that you can tell from beginning to end. Read it out loud. If the explanation sounds confusing at any point, go back to Step 2. Keep iterating until you have a story that you can tell to anyone who will listen.

If you follow this approach over and over, you will end up with a binder full of pages on different subjects. If you take some time twice a year to go through this binder, you will find just how much you retain.

Step 4: Transmit (optional)

This part is optional, but it’s the logical result of everything you’ve just done. If you really want to be sure of your understanding, run it past someone (ideally someone who knows little of the subject). The ultimate test of your knowledge is your capacity to convey it to another. You can read out directly what you’ve written. You can present the material like a lecture. You can ask your friends for a few minutes of their time while you’re buying them dinner. You can volunteer as a guest speaker in your child’s classroom or your parents’ retirement residence. All that really matters is that you attempt to transmit the material to at least one person who isn’t that familiar with it.

The questions you get and the feedback you receive are invaluable for further developing your understanding. Hearing what your audience is curious about will likely pique your own curiosity and set you on a path for further learning. After all, it’s only when you begin to learn a few things really well do you appreciate how much there is to know.

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The Feynman Technique is not only a wonderful recipe for learning but also a window into a different way of thinking that allows you to tear ideas apart and reconstruct them from the ground up.
When you’re having a conversation with someone and they start using words or relationships that you don’t understand, ask them to explain it to you like you’re twelve.

Not only will you supercharge your own learning, but you’ll also supercharge theirs.

Feynman’s approach intuitively believes that intelligence is a process of growth, which dovetails nicely with the work of Carol Dweck, who describes the difference between a fixed and growth mindset.

“If you can’t reduce a difficult engineering problem to just one 8-1/2 x 11-inch sheet of paper, you will probably never understand it.” —Ralph Peck

What does it mean to “know?”

Richard Feynman believed that “the world is much more interesting than any one discipline.” He understood the difference between knowing something and knowing the name of something, as well as how, when you truly know something, you can use that knowledge broadly. When you only know what something is called, you have no real sense of what it is. You can’t take it apart and play with it or use it to make new connections and generate new insights. When you know something, the labels are unimportant, because it’s not necessary to keep it in the box it came in.

“The person who says he knows what he thinks but cannot express it usually does not know what he thinks.” —Mortimer Adler

Feynman’s explanations—on why questions, why trains stay on the tracks as they go around a curve, how we look for new laws of science, or how rubber bands work—are simple and powerful. Here he articulates the difference between knowing the name of something and understanding it.

“See that bird? It’s a brown-throated thrush, but in Germany it’s called a halzenfugel, and in Chinese they call it a chung ling, and even if you know all those names for it, you still know nothing about the bird. You only know something about people: what they call the bird. Now that thrush sings, and teaches its young to fly, and flies so many miles away during the summer across the country, and nobody knows how it finds its way.”

Knowing the name of something doesn’t mean you understand it. We talk in fact-deficient, obfuscating generalities to cover up our lack of understanding.

How then should we go about learning? On this Feynman echoes Albert Einstein and proposes that we take things apart. He describes a dismal first-grade science book that attempts to teach kids about energy by showing a series of pictures about a wind-up dog toy and asking, “What makes it move?” For Feynman, this was the wrong approach because it was too abstract. Saying that energy made the dog move was equal to saying “that ‘God makes it move,’ or ‘spirit makes it move,’ or ‘movability makes it move.’ (In fact, one could equally well say ‘energy makes it stop.’)”

Staying at the level of the abstract imparts no real understanding. Kids might subsequently get the question right on a test, if they have a decent memory. But they aren’t going to have any understanding of what energy actually is.

Feynman then goes on to describe a more useful approach:

“Perhaps I can make the difference a little clearer this way: if you ask a child what makes the toy dog move, you should think about what an ordinary human being would answer. The answer is that you wound up the spring; it tries to unwind and pushes the gear around.

What a good way to begin a science course! Take apart the toy; see how it works. See the cleverness of the gears; see the ratchets. Learn something about the toy, the way the toy is put together, the ingenuity of people devising the ratchets and other things. That’s good.”

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After the Feynman Technique

“We take other men’s knowledge and opinions upon trust; which is an idle and superficial learning. We must make them our own. We are just like a man who, needing fire, went to a neighbor’s house to fetch it, and finding a very good one there, sat down to warm himself without remembering to carry any back home. What good does it do us to have our belly full of meat if it is not digested, if it is not transformed into us, if it does not nourish and support us?” —Michel de Montaigne

The Feynman Technique helps you learn stuff. But learning doesn’t happen in isolation. We learn not only from the books we read but also the people we talk to and the various positions, ideas, and opinions we are exposed to. Richard Feynman also provided advice on how to sort through information so you can decide what is relevant and what you should bother learning.

In a series of non-technical lectures in 1963, memorialized in a short book called The Meaning of It All: Thoughts of a Citizen Scientist, Feynman talks through basic reasoning and some of the problems of his day. His method of evaluating information is another set of tools you can use along with the Feynman Learning Technique to refine what you learn.

Particularly useful are a series of “tricks of the trade” he gives in a section called “This Unscientific Age.” These tricks show Feynman taking the method of thought he learned in pure science and applying it to the more mundane topics most of us have to deal with every day.

Before we start, it’s worth noting that Feynman takes pains to mention that not everything needs to be considered with scientific accuracy. It’s up to you to determine where applying these tricks might be most beneficial in your life.

Regardless of what you are trying to gather information on, these tricks help you dive deeper into topics and ideas and not get waylaid by inaccuracies or misunderstandings on your journey to truly know something.

As we enter the realm of “knowable” things in a scientific sense, the first trick has to do with deciding whether someone else truly knows their stuff or is mimicking others:

“My trick that I use is very easy. If you ask him intelligent questions—that is, penetrating, interested, honest, frank, direct questions on the subject, and no trick questions—then he quickly gets stuck. It is like a child asking naive questions. If you ask naive but relevant questions, then almost immediately the person doesn’t know the answer, if he is an honest man. It is important to appreciate that.

And I think that I can illustrate one unscientific aspect of the world which would be probably very much better if it were more scientific. It has to do with politics. Suppose two politicians are running for president, and one goes through the farm section and is asked, “What are you going to do about the farm question?” And he knows right away—bang, bang, bang.

Now he goes to the next campaigner who comes through. “What are you going to do about the farm problem?” “Well, I don’t know. I used to be a general, and I don’t know anything about farming. But it seems to me it must be a very difficult problem, because for twelve, fifteen, twenty years people have been struggling with it, and people say that they know how to solve the farm problem. And it must be a hard problem. So the way that I intend to solve the farm problem is to gather around me a lot of people who know something about it, to look at all the experience that we have had with this problem before, to take a certain amount of time at it, and then to come to some conclusion in a reasonable way about it. Now, I can’t tell you ahead of time what conclusion, but I can give you some of the principles I’ll try to use—not to make things difficult for individual farmers, if there are any special problems we will have to have some way to take care of them, etc., etc., etc.””

If you learn something via the Feynman Technique, you will be able to answer questions on the subject. You can make educated analogies, extrapolate the principles to other situations, and easily admit what you do not know.

The second trick has to do with dealing with uncertainty. Very few ideas in life are absolutely true. What you want is to get as close to the truth as you can with the information available:

“I would like to mention a somewhat technical idea, but it’s the way, you see, we have to understand how to handle uncertainty. How does something move from being almost certainly false to being almost certainly true? How does experience change? How do you handle the changes of your certainty with experience? And it’s rather complicated, technically, but I’ll give a rather simple, idealized example.

You have, we suppose, two theories about the way something is going to happen, which I will call “Theory A” and “Theory B.” Now it gets complicated. Theory A and Theory B. Before you make any observations, for some reason or other, that is, your past experiences and other observations and intuition and so on, suppose that you are very much more certain of Theory A than of Theory B—much more sure. But suppose that the thing that you are going to observe is a test. According to Theory A, nothing should happen. According to Theory B, it should turn blue. Well, you make the observation, and it turns sort of a greenish. Then you look at Theory A, and you say, “It’s very unlikely,” and you turn to Theory B, and you say, “Well, it should have turned sort of blue, but it wasn’t impossible that it should turn sort of greenish color.”

So the result of this observation, then, is that Theory A is getting weaker, and Theory B is getting stronger. And if you continue to make more tests, then the odds on Theory B increase. Incidentally, it is not right to simply repeat the same test over and over and over and over, no matter how many times you look and it still looks greenish, you haven’t made up your mind yet. But if you find a whole lot of other things that distinguish Theory A from Theory B that are different, then by accumulating a large number of these, the odds on Theory B increase.”

Feynman is talking about grey thinking here, the ability to put things on a gradient from “probably true” to “probably false” and how we deal with that uncertainty. He isn’t proposing a method of figuring out absolute, doctrinaire truth.

Another term for what he’s proposing is Bayesian updating—starting with a priori odds, based on earlier understanding, and “updating” the odds of something based on what you learn thereafter. An extremely useful tool.

Feynman’s third trick is the realization that as we investigate whether something is true or not, new evidence and new methods of experimentation should show the effect of getting stronger and stronger, not weaker. Knowledge is not static, and we need to be open to continually evaluating what we think we know. Here he uses an excellent example of analyzing mental telepathy:

“A professor, I think somewhere in Virginia, has done a lot of experiments for a number of years on the subject of mental telepathy, the same kind of stuff as mind reading. In his early experiments the game was to have a set of cards with various designs on them (you probably know all this, because they sold the cards and people used to play this game), and you would guess whether it’s a circle or a triangle and so on while someone else was thinking about it. You would sit and not see the card, and he would see the card and think about the card and you’d guess what it was. And in the beginning of these researches, he found very remarkable effects. He found people who would guess ten to fifteen of the cards correctly, when it should be on the average only five. More even than that. There were some who would come very close to a hundred percent in going through all the cards. Excellent mind readers.

A number of people pointed out a set of criticisms. One thing, for example, is that he didn’t count all the cases that didn’t work. And he just took the few that did, and then you can’t do statistics anymore. And then there were a large number of apparent clues by which signals inadvertently, or advertently, were being transmitted from one to the other.

Various criticisms of the techniques and the statistical methods were made by people. The technique was therefore improved. The result was that, although five cards should be the average, it averaged about six and a half cards over a large number of tests. Never did he get anything like ten or fifteen or twenty-five cards. Therefore, the phenomenon is that the first experiments are wrong. The second experiments proved that the phenomenon observed in the first experiment was nonexistent. The fact that we have six and a half instead of five on the average now brings up a new possibility, that there is such a thing as mental telepathy, but at a much lower level. It’s a different idea, because, if the thing was really there before, having improved the methods of experiment, the phenomenon would still be there. It would still be fifteen cards. Why is it down to six and a half? Because the technique improved. Now it still is that the six and a half is a little bit higher than the average of statistics, and various people criticized it more subtly and noticed a couple of other slight effects which might account for the results.

It turned out that people would get tired during the tests, according to the professor. The evidence showed that they were getting a little bit lower on the average number of agreements. Well, if you take out the cases that are low, the laws of statistics don’t work, and the average is a little higher than the five, and so on. So if the man was tired, the last two or three were thrown away. Things of this nature were improved still further. The results were that mental telepathy still exists, but this time at 5.1 on the average, and therefore all the experiments which indicated 6.5 were false. Now what about the five? . . . Well, we can go on forever, but the point is that there are always errors in experiments that are subtle and unknown. But the reason that I do not believe that the researchers in mental telepathy have led to a demonstration of its existence is that as the techniques were improved, the phenomenon got weaker. In short, the later experiments in every case disproved all the results of the former experiments. If remembered that way, then you can appreciate the situation.”

We must refine our process for probing and experimenting if we’re to get at real truth, always watching out for little troubles. Otherwise, we torture the world so that our results fit our expectations. If we carefully refine and re-test and the effect gets weaker all the time, it’s likely to not be true, or at least not to the magnitude originally hoped for.

The fourth trick is to ask the right question, which is not “Could this be the case?” but “Is this actually the case?” Many get so caught up with the former that they forget to ask the latter:

“That brings me to the fourth kind of attitude toward ideas, and that is that the problem is not what is possible. That’s not the problem. The problem is what is probable, what is happening.

It does no good to demonstrate again and again that you can’t disprove that this could be a flying saucer. We have to guess ahead of time whether we have to worry about the Martian invasion. We have to make a judgment about whether it is a flying saucer, whether it’s reasonable, whether it’s likely. And we do that on the basis of a lot more experience than whether it’s just possible, because the number of things that are possible is not fully appreciated by the average individual. And it is also not clear, then, to them how many things that are possible must not be happening. That it’s impossible that everything that is possible is happening. And there is too much variety, so most likely anything that you think of that is possible isn’t true. In fact that’s a general principle in physics theories: no matter what a guy thinks of, it’s almost always false. So there have been five or ten theories that have been right in the history of physics, and those are the ones we want. But that doesn’t mean that everything’s false. We’ll find out.”

The fifth trick is a very, very common one, even 50 years after Feynman pointed it out. You cannot judge the probability of something happening after it’s already happened. That’s cherry-picking. You have to run the experiment forward for it to mean anything:

“A lot of scientists don’t even appreciate this. In fact, the first time I got into an argument over this was when I was a graduate student at Princeton, and there was a guy in the psychology department who was running rat races. I mean, he has a T-shaped thing, and the rats go, and they go to the right, and the left, and so on. And it’s a general principle of psychologists that in these tests they arrange so that the odds that the things that happen by chance is small, in fact, less than one in twenty. That means that one in twenty of their laws is probably wrong. But the statistical ways of calculating the odds, like coin flipping if the rats were to go randomly right and left, are easy to work out.

This man had designed an experiment which would show something which I do not remember, if the rats always went to the right, let’s say. He had to do a great number of tests, because, of course, they could go to the right accidentally, so to get it down to one in twenty by odds, he had to do a number of them. And it’s hard to do, and he did his number. Then he found that it didn’t work. They went to the right, and they went to the left, and so on. And then he noticed, most remarkably, that they alternated, first right, then left, then right, then left. And then he ran to me, and he said, “Calculate the probability for me that they should alternate, so that I can see if it is less than one in twenty.” I said, “It probably is less than one in twenty, but it doesn’t count.”

He said, “Why?” I said, “Because it doesn’t make any sense to calculate after the event. You see, you found the peculiarity, and so you selected the peculiar case.”

The fact that the rat directions alternate suggests the possibility that rats alternate. If he wants to test this hypothesis, one in twenty, he cannot do it from the same data that gave him the clue. He must do another experiment all over again and then see if they alternate. He did, and it didn’t work.”

The sixth trick is one that’s familiar to almost all of us, yet almost all of us forget about every day: the plural of anecdote is not data. We must use proper statistical sampling to know whether or not we know what we’re talking about:

“The next kind of technique that’s involved is statistical sampling. I referred to that idea when I said they tried to arrange things so that they had one in twenty odds. The whole subject of statistical sampling is somewhat mathematical, and I won’t go into the details. The general idea is kind of obvious. If you want to know how many people are taller than six feet tall, then you just pick people out at random, and you see that maybe forty of them are more than six feet so you guess that maybe everybody is. Sounds stupid.

Well, it is and it isn’t. If you pick the hundred out by seeing which ones come through a low door, you’re going to get it wrong. If you pick the hundred out by looking at your friends, you’ll get it wrong, because they’re all in one place in the country. But if you pick out a way that as far as anybody can figure out has no connection with their height at all, then if you find forty out of a hundred, then in a hundred million there will be more or less forty million. How much more or how much less can be worked out quite accurately. In fact, it turns out that to be more or less correct to 1 percent, you have to have 10,000 samples. People don’t realize how difficult it is to get the accuracy high. For only 1 or 2 percent you need 10,000 tries.”

The last trick is to realize that many errors people make simply come from lack of information. They don’t even know they’re missing the tools they need. This can be a very tough one to guard against—it’s hard to know when you’re missing information that would change your mind—but Feynman gives the simple case of astrology to prove the point:

“Now, looking at the troubles that we have with all the unscientific and peculiar things in the world, there are a number of them which cannot be associated with difficulties in how to think, I think, but are just due to some lack of information. In particular, there are believers in astrology, of which, no doubt, there are a number here. Astrologists say that there are days when it’s better to go to the dentist than other days. There are days when it’s better to fly in an airplane, for you, if you are born on such a day and such and such an hour. And it’s all calculated by very careful rules in terms of the position of the stars. If it were true it would be very interesting. Insurance people would be very interested to change the insurance rates on people if they follow the astrological rules, because they have a better chance when they are in the airplane. Tests to determine whether people who go on the day that they are not supposed to go are worse off or not have never been made by the astrologers. The question of whether it’s a good day for business or a bad day for business has never been established. Now what of it? Maybe it’s still true, yes.

On the other hand, there’s an awful lot of information that indicates that it isn’t true. Because we have a lot of knowledge about how things work, what people are, what the world is, what those stars are, what the planets are that you are looking at, what makes them go around more or less, where they’re going to be in the next 2,000 years is completely known. They don’t have to look up to find out where it is. And furthermore, if you look very carefully at the different astrologers they don’t agree with each other, so what are you going to do? Disbelieve it. There’s no evidence at all for it. It’s pure nonsense.

The only way you can believe it is to have a general lack of information about the stars and the world and what the rest of the things look like. If such a phenomenon existed it would be most remarkable, in the face of all the other phenomena that exist, and unless someone can demonstrate it to you with a real experiment, with a real test, took people who believe and people who didn’t believe and made a test, and so on, then there’s no point in listening to them.”

 

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Conclusion

Knowing something is valuable. The more you understand about how the world works, the more options you have for dealing with the unexpected and the better you can create and capitalize on opportunities. The Feynman Learning Technique is a great method to develop mastery over sets of information. Once you do, the knowledge becomes a powerful tool at your disposal.

But as Feynman himself showed, being willing and able to question your knowledge and the knowledge of others is how you keep improving. Learning is a journey.

If you want to learn more about Feynman’s ideas and teachings, we recommend:

Surely You’re Joking, Mr. Feynman!: Adventures of a Curious Character

The Pleasure of Finding Things Out: The Best Short Works of Richard Feynman

What Do You Care What Other People Think?: Further Adventures of a Curious Character

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Highlights From 2020’s Farnam Street “Ask Me Anything” Sessions

Reading Time: 3 minutes

Each month, Farnam Street members receive an exclusive chance to get personalized advice and answers to their burning questions from an expert guest. In 2020, we hosted “Ask Me Anything” (AMA) sessions with guests from a wide range of fields, including journalism, psychology, baking, business, and more. In this post, we’ve picked out a selection of highlights from their most practical and insightful answers. To gain access to 25+ past AMA sessions and participate in future ones, become a Farnam Street member. If you’re already a member, you can view all AMAs here.

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AMA Highlights Part 1

Shane Parrish, FS Founder – Jan 2020

I don’t want to optimize for work, and I don’t want to optimize for family time. I want to optimize for life. I get one life and I don’t want to look back at ninety yelling at myself because I regret doing or not doing something. I always try to keep that end in mind.

Anese Cavanaugh, IEP Method Founder – Feb 2020

Culture is the energy, the container, we create together to do our best work, show up as our best selves, be productive, and feel safe. It’s how we feel when we’re doing our work together.

Jeff Hunter, Talentism Founder – March 2020

All of us do work that matters. It may matter in a little way, it may matter in a big way. We’re surrounded by signals all the time that say some work is more valuable than others. But as I like to say, the person who cleans the bathroom and does that excellently is probably more valuable than somebody who’s the head of an organization and does it terribly.

Katherine Eban, Investigative Journalist – April 2020

As a journalist doing a book, it’s like a marriage; and I know this sounds a little cynical but,
marriages only get worse as they go along so you have to be really in love to start with. So, there’s got to be a real love there with the topic because the project and the reporting and the work is only going to get deeper and worse the further you get into the project. Start from a good strong place.

Ozan Varol, Law Professor – May 2020

Research shows that the most original breakthrough creative ideas tend to come up in those moments of slack, when you’re letting your subconscious work, as opposed to moments of hard labor.

Tarek Malouf, Hummingbird Bakery Founder – June 2020

Before worrying about having 50 items on your menu, make sure you’re doing the first 10 items really well… Your product has to be great and you have to believe in the product and you need to be true to it. Don’t try and do too much.

Marc Tarpenning, Tesla Co-Founder – July 2020

Long-term thinking is really this idea of always keeping as much optionality in the future as you can. Because you don’t know what the future is going to bring. So what you don’t want to do is constrain your future possible options because you’re on some trajectory.

Jesse Mecham, YNAB Founder – August 2020

Budgeting just means you’re deciding. We don’t want people spending less, we really want people spending without guilt. That approach of thinking you’re going to push through and restrict yourself just fits and starts. People do that again and again. Give yourself room to learn how you spend money and learn what you care about, and slowly as you work the four rules, you’ve found something sustainable.

Gretchen Rubin, Happiness Project Author – Sept 2020

People who have habits that work for them have a happier, healthier, more productive, more creative life. People whose habits don’t work for them have a lot more challenges. It’s a question of thinking more about how to make something [which makes you happier] into a habit.

Stefanie Johnson, Management Professor – Oct 2020

One of the amazing things about inclusion is that it’s really something that any of us can do. It’s not like you have to be a leader to make someone feel seen. Any of us can do that.

Laura Vanderkam, Time Management Expert – Dec 2020

I really suggest that people [track] an entire week, all 168 hours. You do not need to look for a particularly typical week because there are no typical weeks. What we will learn in the course of tracking any week is what finds space in your life, even when things are not typical. And figuring out what a typical week looks like is more of a judgment call than it is a statement about reality. Just choose any week.

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Check out the Farnam Street Youtube channel for part 2 and part 3.

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Using Models to Stay Calm in Charged Situations

Reading Time: 6 minutes

When polarizing topics are discussed in meetings, passions can run high and cloud our judgment. Learn how mental models can help you see clearly from this real-life scenario.

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Mental models can sometimes come off as an abstract concept. They are, however, actual tools you can use to navigate through challenging or confusing situations. In this article, we are going to apply our mental models to a common situation: a meeting with conflict.

A recent meeting with the school gave us an opportunity to use our latticework. Anyone with school-age kids has dealt with the bureaucracy of a school system and the other parents who interact with it. Call it what you will, all school environments usually have some formal interface between parents and the school administration that is aimed at progressing issues and ideas of importance to the school community.

The particular meeting was an intense one. At issue was the school’s communication around a potentially harmful leak in the heating system. Some parents felt the school had communicated reasonably about the problem and the potential consequences. Others felt their child’s life had been put in danger due to potential exposure to mold and asbestos. Some parents felt the school could have done a better job of soliciting feedback from students about their experiences during the previous week, and others felt the school administration had done a poor job about communicating potential risks to parents.

The first thing you’ll notice if you’re in a meeting like this is that emotions on all sides run high. After some discussion you might also notice a few more things, like how many people do the following:

Any of these occurrences, when you hear them via statements from people around the table, are a great indication that using a few mental models might improve the dynamics of the situation.

The first mental model that is invaluable in situations like this is Hanlon’s Razor: don’t attribute to maliciousness that which is more easily explained by incompetence. (Hanlon’s Razor is one of the 9 general thinking concepts in The Great Mental Models Volume One.) When people feel victimized, they can get angry and lash out in an attempt to fight back against a perceived threat. When people feel accused of serious wrongdoing, they can get defensive and withhold information to protect themselves. Neither of these reactions is useful in a situation like this. Yes, sometimes people intentionally do bad things. But more often than not, bad things are the result of incompetence. In a school meeting situation, it’s safe to assume everyone at the table has the best interests of the students at heart. School staff and administrators usually go into teaching motivated by a deep love of education. They genuinely want their schools to be amazing places of learning, and they devote time and attention to improving the lives of their students.

It makes no sense to assume a school’s administration would deliberately withhold harmful information. Yes, it could happen. But, in either case, you are going to obtain more valuable information if you assume poor decisions were the result of incompetence versus maliciousness.

When we feel people are malicious toward us, we instinctively become a negatively coiled spring, waiting for the right moment to take them down a notch or two. Removing malice from the equation, you give yourself emotional breathing room to work toward better solutions and apply more models.

The next helpful model is relativity, adapted from the laws of physics. This model is about remembering that everyone’s perspective is different from yours. Understanding how others see the same situation can help you move toward a more meaningful dialogue with the people in the meeting. You can do this by looking around the room and asking yourself what is influencing people’s approaches to the situation.

In our school meeting, we see some people are afraid for their child’s health. Others are influenced by past dealings with the school administration. Authorities are worried about closing the school. Teachers are concerned about how missed time might impact their students’ learning. Administrators are trying to balance the needs of parents with their responsibility to follow the necessary procedures. Some parents are stressed because they don’t have care for their children when the school closes. There is a lot going on, and relativity gives us a lens to try to identify the dynamics impacting communication.

After understanding the different perspectives, it becomes easier to incorporate them into your thinking. You can diffuse conflict by identifying what it is you think you hear. Often, just the feeling of being heard will help people start to listen and engage more objectively.

Now you can dive into some of the details. First up is probabilistic thinking. Before we worry about mold levels or sick children, let’s try to identify the base rates. What is the mold content in the air outside? How many children are typically absent due to sickness at this time of year? Reminding people that severity has to be evaluated against something in a situation like this can really help diffuse stress and concern. If 10% of the student population is absent on any given day, and in the week leading up to these events 12% to 13% of the population was absent, then it turns out we are not actually dealing with a huge statistical anomaly.

Then you can evaluate the anecdotes with the model of the Law of Large Numbers in mind. Small sample sizes can be misleading. The larger your group for evaluation, the more relevant the conclusions. In a situation such as our school council meeting, small sample sizes only serve to ratchet up the emotion by implying they are the causal outcomes of recent events.

In reality, any one-off occurrence can often be explained in multiple ways. One or two children coming home with hives? There are a dozen reasonable explanations for that: allergies, dry skin, reaction to skin cream, symptom of an illness unrelated to the school environment, and so on. However, the more children that develop hives, the more it is statistically possible the cause relates to the only common denominator between all children: the school environment.

Even then, correlation does not equal causation. It might not be a recent leaky steam pipe; is it exam time? Are there other stressors in the culture? Other contaminants in the environment? The larger your sample size, the more likely you will obtain relevant information.

Finally, you can practice systems thinking and contribute to the discussion by identifying the other components in the system you are all dealing with. After all, a school council is just one part of a much larger system involving governments, school boards, legislators, administrators, teachers, students, parents, and the community. When you put your meeting into the bigger context of the entire system, you can identify the feedback loops: Who is responding to what information, and how quickly does their behavior change? When you do this, you can start to suggest some possible steps and solutions to remedy the situation and improve interactions going forward.

How is the information flowing? How fast does it move? How much time does each recipient have to adjust before receiving more information? Chances are, you aren’t going to know all this at the meeting. So you can ask questions. Does the principal have to get approval from the school board before sending out communications involving risk to students? Can teachers communicate directly with parents? What are the conditions for communicating possible risk? Will speculation increase the speed of a self-reinforcing feedback loop causing panic? What do parents need to know to make an informed decision about the welfare of their child? What does the school need to know to make an informed decision about the welfare of their students?

In meetings like the one described here, there is no doubt that communication is important. Using the meeting to discuss and debate ways of improving communication so that outcomes are generally better in the future is a valuable use of time.

A school meeting is one practical example of how having a latticework of mental models can be useful. Using mental models can help you diffuse some of the emotions that create an unproductive dynamic. They can also help you bring forward valuable, relevant information to assist the different parties in improving their decision-making process going forward.

At the very least, you will walk away from the meeting with a much better understanding of how the world works, and you will have gained some strategies you can implement in the future to leverage this knowledge instead of fighting against it.

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Finite and Infinite Games: Two Ways to Play the Game of Life

Reading Time: 2 minutes

If life is a game, how do you play it? The answer will have a huge impact on your choices, your satisfaction, and how you achieve success.

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James Carse, the Director of Religious Studies at New York University, wrote a book, Finite and Infinite Games, that explores the difference between approaching life as a game with an end, or a game that goes on forever. According to Carse, playing to win isn’t nearly as satisfying as playing to keep the game going.

For starters, what do you do after you win a finite game? You have to sign yourself up for another one, and you must find a way to showcase your past winnings. Finite players have to parade around their wealth and status. They need to display the markers of winning they have accumulated so that other players know whom they are dealing with. Carse argues that these players spend their time in the past, because that’s where their winning is.

Infinite players, in contrast, look to the future. Because their goal is to keep the game going, they focus less on what happened, and put more effort into figuring out what’s possible. By playing a single, non-repeatable game, they are unconcerned with the maintenance and display of past status. They are more concerned with positioning themselves to deal effectively with whatever challenges come up.

Thus, how you play the game of life will define the learning you pursue. Finite players need training. Infinite players need education. Why? According to Carse, “to be prepared against surprise is to be trained. To be prepared for surprise is to be educated.” If you play life as a finite game, you train for the rules. If life is instead an infinite game, you focus on being educated to adapt to unknowns.

“What will undo any boundary is the awareness that it is our vision, and not what we are viewing, that is limited.”

Whether you choose the finite or infinite game will also determine how you define success, and what you need to achieve it. Finite players need power. Power gives them the best chance to win in each successive contest. Infinite players need endurance. They need attributes to keep them going. Carse explains, “let us say that where the finite player plays to be powerful, the infinite player plays with strength.”

Ultimately, approaching life as a finite game or infinite game impacts your daily attitude. Carse asserts that “the finite play for life is serious; the infinite play of life joyous.” Considering your life through this frame helps you determine if you are making the right choices to be successful at the kind of game you want to play.

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