Category: People

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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The High Price of Mistrust

Reading Time: 10 minutes

When we can’t trust each other, nothing works. As we participate in our communities less and less, we find it harder to feel other people are trustworthy. But if we can bring back a sense of trust in the people around us, the rewards are incredible.

There are costs to falling community participation. Rather than simply lamenting the loss of a past golden era (as people have done in every era), Harvard political scientist Robert D. Putnam explains these costs, as well as how we might bring community participation back.

First published twenty years ago, Bowling Alone is an exhaustive, hefty work. In its 544 pages, Putnam negotiated mountains of data to support his thesis that the previous few decades had seen Americans retreat en masse from public life. Putnam argued Americans had become disconnected from their wider communities, as evidenced by changes such as a decline in civic engagement and dwindling membership rates for groups such as bowling leagues and PTAs.

Though aspects of Bowling Alone are a little dated today (“computer-mediated communication” isn’t a phrase you’re likely to have heard recently), a quick glance at 2021’s social landscape would suggest many of the trends Putnam described have only continued and apply in other parts of the world too.

Right now, polarization and social distancing have forced us apart from any sense of community to a degree that can seem irresolvable.

Will we ever bowl in leagues alongside near strangers and turn them into friends again? Will we ever bowl again at all, even if alone, or will those gleaming aisles, too-tight shoes, and overpriced sodas fade into a distant memory we recount to our children?

The idea of going into a public space for a non-essential reason can feel incredibly out of reach for many of us right now. And who knows how spaces like bowling alleys will survive in the long run without the social scenes that fuelled them. Now is a perfect time to revisit Bowling Alone to see what it can still teach us, because many of its warnings and lessons are perhaps more relevant now than at its time of publication.

One key lesson we can derive from Bowling Alone is that the less we trust each other—something which is both a cause and consequence of declining community engagement—the more it costs us. Mistrust is expensive.

We need to trust the people around us in order to live happy, productive lives. If we don’t trust them, we end up having to find costly ways to formalize our relationships. Even if we’re not engaged with other people on a social or civic level, we still have to transact with them on an economic one. We still have to walk along the same streets, send our children to the same schools, and spend afternoons in the same parks.

To live our lives freely, we need to to find ways to trust that other people won‘t hurt us, rip us off, or otherwise harm us. Otherwise we may lose something too precious to put a price tag on.

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No person is an island

As community engagement declines, Putnam refers to the thing we are losing as “social capital,” meaning the sum of our connections with other individuals and the benefits they bring us.

Being part of a social network gives you access to all sorts of value. Putnam explains, “Just as a screwdriver (physical capital) or a college education (human capital) can increase productivity (both individual and collective), so too can social contacts affect the productivity of individuals and groups.” For example, knowing the right people can help you find a job where your skills are well utilized. If you don’t know many people, you might struggle to find work and end up doing something you’re overqualified for or be unemployed for a while.

To give another example, if you’re friends with other parents in your local neighborhood, you can coordinate with them to share childcare responsibilities. If you’re not, you’re likely to end up paying for childcare or being more limited in what you can do when your kids are home from school.

Both individuals and groups have social capital. Putnam also explains that “social capital also can have externalities that affect the wider community, so that not all of the costs and benefits of social connections accrue to the person making the contact . . . even a poorly connected individual may derive some of the spillover benefits from living in a well-connected community.” A well-connected community is usually a safer community, and the safety extends, at least partly, to the least connected members.

For example, the more neighbors know each other, the more they notice when something on the street is out of the norm and potentially harmful. That observation benefits everyone on the street—especially the most vulnerable people.

Having social capital is valuable because it undergirds certain norms. Our connections to other people require and encourage us to behave in ways that maintain those connections. Being well-connected is both an outcome of following social norms and an incentive to follow them. We adhere to “rules of conduct” for the sake of our social capital.

Social capital enables us to trust other people. When we’re connected to many others, we develop a norm of “generalized reciprocity.” Putnam explains this as meaning “I’ll do this for you without expecting anything specific back from you, in the confident expectation that someone else will do something for me down the road.” We can go for the delayed payoff that comes from being nice without an agenda. Generalized reciprocity makes all of our interactions with other people easier. It’s a form of trust.

Putnam goes on to write, “A society characterized by generalized reciprocity is more efficient than a distrustful society, for the same reason that money is more efficient than barter. If we don’t have to balance every exchange instantly, we can get a lot more accomplished. Trustworthiness lubricates social life.” Trust requires that we interact with the same people more than once, or at least think that we might.

Generalized reciprocity as a norm also enables us to work together to do things that benefit the whole group or even that don’t benefit us personally at all, rather than focusing on ourselves. If you live in a neighborhood with a norm of generalized reciprocity, you can do things like mowing a neighbor’s lawn for free because you know that when you need similar help, someone will come through. You can do things that wouldn’t make sense in an “every person for themselves” area.

Societies and groups with a norm of generalized reciprocity maintain that norm through “gossip and other valuable ways of cultivating reputation.”

When people are linked to each other, they know that news will spread if they deviate from norms. If one member of a bowling league cheats and another member notices, they’re likely to discuss it with others, and everyone will know to trust that member a little less. Knowing gossip will spread enables us to trust our perceptions of others, because if something were amiss we would have surely heard about it. It also nudges us towards behaving well—if something is amiss about us, others are sure to hear of that, too.

But with the decline of community participation comes the decline of trust. If you don’t know the people around you, how can you trust them? The more disconnected we are from each other, the less we can rely on each other to be good and nice. Without repeated interactions with the same people, we become suspicious of each other. This suspicion carries heavy costs.

***

Rising transaction costs

In economics, a “transaction cost” refers to the cost of making some sort of trade within a market. Transaction costs are the price we pay in order to exchange value. They’re in addition to the cost of producing or otherwise providing that value.

For example, when you make a credit card purchase in a shop, the shop likely pays a processing fee to the card company. It’s part of the cost of doing business with you. Another cost is that the shop needs people working in it to ensure you pay. They can’t just rely on you popping the right money in the till then leaving.

Putnam explains later in the book that being able to trust people as a result of a norm of generalized reciprocity in our social lives leads to reduced transaction costs. It means we can relax around other people and not be distracted by “worrying whether you got back the right change from the clerk to double-checking that you locked the car door.” We can easily be honest if we know others will do the same.

With the decline of social capital comes rising transaction costs. We can’t rely on other people to treat us as they would like to be treated because we don’t know them and haven’t built the opportunities to engage in reciprocal relationships.

Much like trusting trustworthy people has great benefits, trusting untrustworthy people has enormous costs. No one likes being exploited or ripped off because they assumed good faith in the wrong person.

If we’re uncertain, we default to mistrust. You can see the endpoint of a loss of trust in societies and groups which must rely on the use or threat of force to get anything done because everyone is out to rip off everyone else.

At a certain point, transaction costs can cancel out the benefits of transacting at all. If lending a leaf blower to a neighbor requires a lawyer to set up a contract stipulating the terms of its use, then borrowing it doesn’t save them any money. They might as well hire someone or buy their own.

We don’t try new things when we can’t trust other people. So we have to find additional ways of making transactions work. One way we do this is through “the rule of law—formal contracts, courts, litigation, adjudication, and enforcement by the state.” During the period since the 1970s when Putnam considers social capital to have declined, the ratio of lawyers to other professions increased more than any other profession: “After 1970 the legal profession grew three times faster than the other professions as a whole.”

While we can’t attribute that solely to a decline in social capital, it seems clear that mistrusting each other makes us more likely to prefer to get things in writing. We are “forced to rely increasingly on formal institutions, and above all the law, to accomplish what we used to accomplished through informal networks reinforced by generalized reciprocity—that is, through social capital.”

***

The high price of mistrust

The cost of mistrust doesn’t just show up in the form of bills from lawyers. It poisons everything we do and further drives us apart.

Mistrust drives us to install remote monitoring software on our employees’ laptops and ask them to fill in reports on every tiny task to prove they’re not skiving off. It drives us to make excuses when a friend asks for help moving or a lift to the airport because no one was available last time we needed that same help. It drives us to begrudgingly buy a household appliance or tool we’ll only use once because we don’t even consider borrowing it from a neighbor.

Mistrust nudges us to peek at the search history of a partner or to cross-reference what a child says. It causes us to keep our belongings close in public, to double-lock the doors, to not let our kids play in the street, and a million other tiny changes.

Mistrust costs us time and money, sure. But it also costs us a little bit of our humanity. We are sociable animals, and seeing the people around us as a potential threat, even a small one, wears on us. Constant vigilance is exhausting. So is being under constant suspicion.

One lesson we can take from Bowling Alone is that anything we can do to increase trust between people will have tremendous knock-on benefits. Trust allows us to relax, delay gratification, and generally be nicer to everyone. It makes for a nicer day-to-day existence. We don’t need to spend so much time and money checking up on others. Ultimately, it’s worth investing in trust whenever possible, as opposed to investing in more ways of monitoring and controlling people.

That’s not to say that there was ever a golden utopia when everyone trusted everyone. People have always abused the trust of others. And people on the fringes of society have always been unfairly mistrusted and struggled to trust that others would act in good faith. Nonetheless, whenever we go to install some mechanism intended to replace trust, it’s worth asking if there’s a different way.

The ingredients for trust are simple. We need to repeatedly interact with the same people, know that others will warn us about their bad behavior, and feel secure in the knowledge we’ll be helped when and if we need it. At the same time, we need to know others will be warned if we behave badly and that everything we give to others will come back to us, perhaps multiplied.

If you want people to trust you, the best place to start is by trusting them. That isn’t always easy to do, especially if you’ve paid the price for it in the past. But it’s the best place to start. Then you need to combine it with repeat interactions, or the possibility thereof. In the iterated Prisoner’s Dilemma, a game that reveals how cooperation works, the best strategy to adopt is tit for tat. In the first round you cooperate, then in subsequent rounds do whatever the other player did last.

How might that play out in real life? If you want your employees to trust you, then you might start by trusting them—while also making it clear that you’re not going to fire them suddenly and you want them to stick around.

Mistrust is expensive. But trusting the wrong people can sometimes seem too risky. The lesson we can take from Bowling Alone is that building trust is absolutely worthwhile—and that the only way to do it is by finding ways to get out there and engage with other people.

We can create trust by contributing to existing communities and creating new ones. The more we show up and are willing to have faith in others, the more we’ll get back in return.

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The Best of The The Knowledge Project 2020

Reading Time: 2 minutes

One of the best ways to learn is a good conversation.

While there are many advantages to a good conversation, perhaps the best is that you can benefit from the lessons that other people have already paid the price for. Of course, that’s not all. Good conversations can also offer a new way to interpret your past experiences, discover something new, and remind us of something we already know.

A good conversation updates the software in your brain. But not all updates are the same. Learning more isn’t simply a matter of having more conversations, but rather getting more out of each conversation that you are apart of. Deep conversations with ‘people that do’ offer the richest source of learning. Conversations that skim the surface, on the other hand, only offer the illusion of learning.

With that in mind, we’d like to invite you to join us in the top conversations we had on The Knowledge Project in 2020.

It’s time to listen and learn.

  • Episode 82: Bill Ackman: Getting Back Up — Legendary activist investor, Bill Ackman talks about lessons he’s learned growing up, raising a family, what drives him forward and back up from failure, consuming information and ideas, and facing criticism.
  • Episode 94: Chamath Palihapitiya: Understanding Yourself — Founder and CEO of Social Capital, Chamath Palihapitiya sits down with Shane Parrish to chat about what it means to be an observer of the present, how to think in first principles, the psychology of successful investing, his thoughts on the best public company CEOs and much more.
  • Episode 74: Embracing Confusion with Jeff Hunter — CEO of Talentism, Jeff Hunter, teaches how to rewrite damaging narratives that hold us back, how to give and receive helpful feedback, and why confusion can be a good thing.
  • Episode 80: Developing the Leader in You with John Maxwell — Leadership expert John Maxwell breaks down the four traits every successful person possesses and how to awaken the leader within you, no matter what your job title says.
  • Episode 85: Bethany McLean: Crafting a Narrative — Best-selling author of The Smartest Guys in the Room and All the Devils are Here, Bethany McLean, discusses how to write a story, the behaviors of CEO’s, visionaries and fraudsters and so much more.

Honorary mention to Derek Sivers: Innovation Versus Imitation [The Knowledge Project Ep. #88], who was only 131 downloads away from making the list.

—

In other news this year, we released a TKP youtube channel with full-length videos of our conversations so you can see the guest, as well as a “Clips” channel, where we are building the world’s best repository of nugget-sized information you can use in work and life.

If you’re still curious, check out the 2019 list.

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Aim For What’s Reasonable: Leadership Lessons From Director Jean Renoir

Reading Time: 4 minutes

Directing a film involves getting an enormous group of people to work together on turning the image inside your head into a reality. In this 1970 interview, director Jean Renoir dispenses time-tested wisdom for leaders everywhere on humility, accountability, goal-setting, and more.

***

Many of us end up in leadership roles at some point in our career. Most of us, however, never get any training or instruction on how to actually be a good leader. But whether we end up offering formal or informal leadership, at some point we need to inspire or motivate people towards accomplishing a shared vision.

Directors are the leaders of movie productions. They assemble their team, they communicate their vision, and they manage the ups and downs of the filming process. Thus the experience of a successful director offers great insight into the qualities of a good leader. In 1970, film director Jean Renoir gave an interview with George Stevens Jr. of the American Film Institute where he discussed the leadership aspects of directing. His insights illustrate some important lessons. Renoir started out making silent films, and he continued filmmaking through to the 1960s. His two greatest cinematic achievements were the films The Grand Illusion (1937) and The Rules of the Game (1939). He received a Lifetime Achievement Academy Award in 1975 for his contribution to the motion picture industry.

In the interview, Renoir speaks to humility in leadership when he says, “I’m a director who has spent his life suggesting stories that nobody wanted. It’s still going on. But I’m used to it and I’m not complaining, because the ideas which were forced on me were often better than my own ideas.”

Leadership is not necessarily coming up with all the answers; it’s also important to put aside your own ego to cultivate and support the contributions from your team. Sometimes leaders have the best ideas. But often people on their team have excellent ones as well.

Renoir suggests that the role of a director is to have a clear enough vision that you can work through the imperfections involved in executing it. “A picture, often when it is good, is the result of some inner belief which is so strong that you have to show what you want, in spite of a stupid story or difficulties about the commercial side of the film.”

Good leaders don’t require perfection to achieve results. They work with what they have, often using creativity and ingenuity to fill in when reality doesn’t conform to the ideal image in their head. Having a vision is not about achieving exactly that vision. It’s about doing the best you can once you come into contact with reality.

When Renoir says, “We directors are simply midwives,” he implies that effective leadership is about giving shape to the talents and capabilities that already exist. Excellent leaders find a way to challenge and develop those on their team. In explaining how he works with actors, he says, “You must not ask an actor to do what he cannot do.” Rather, you need to work with what you have, using clear feedback and communication to find a way to bring out the best in people. Sometimes getting out of people’s way and letting their natural abilities come out is the most important thing to do.

Although Renoir says, “When I can, I shoot my scenes only once. I like to be committed, to be a slave to my decision,” he further explains, “I don’t like to make the important decisions alone.” Good leaders know when to consult others. They know to take in information from those who know more than they do and to respect different forms of expertise. But they still take accountability for their decisions because they made the final choice.

Good leaders are also mindful of the world outside the group or organization they are leading. They don’t lead in a vacuum but are sensitive to all those involved in achieving the results they are trying to deliver. For a director, it makes no sense to conceive of a film without considering the audience. Renoir explains, “I believe that the work of art where the spectator does not collaborate is not a work of art.” Similarly, we all have groups that we interact with outside of our organization, like clients or customers. We too need to run our teams with an understanding of that outside world.

No one can be good at everything, and thus effective leadership involves knowing when to ask for help. Renoir admits, “That’s where I like to have my friends help me, because I am very bad at casting.” Knowing your weaknesses is vital, because then you can find people who have strengths in those areas to assist you.

Additionally, most organizations are too complex for any one person to be an expert at all of the roles. Leaders show hubris when they assume they can do the jobs of everyone else well. Renoir explains this notion of knowing your role as a leader: “Too many directors work like this. They tell the actor, ‘Sit down, my dear friends, and look at me. I am going to act a scene, and you are going to repeat what I just did.’ He acts a scene and he acts it badly, because if he is a director instead of an actor, it’s probably because he’s a bad actor.”

***

Although leadership can be all encompassing, we shouldn’t be intimidated by the ideal list of qualities and behaviors a good leader displays. Focus on how you can improve. Set goals. Reflect on your failures, and recognize your success.

“You know, there is an old slogan, very popular in our occidental civilization: you must look to an end higher than normal, and that way you will achieve something. Your aim must be very, very high. Myself, I am absolutely convinced that it is mere stupidity. The aim must be easy to reach, and by reaching it, you achieve more.”

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Job Interviews Don’t Work

Reading Time: 13 minutes

Better hiring leads to better work environments, less turnover, and more innovation and productivity. When you understand the limitations and pitfalls of the job interview, you improve your chances of hiring the best possible person for your needs.

***

The job interview is a ritual just about every adult goes through at least once. They seem to be a ubiquitous part of most hiring processes. The funny thing about them, however, is that they take up time and resources without actually helping to select the best people to hire. Instead, they promote a homogenous workforce where everyone thinks the same.

If you have any doubt about how much you can get from an interview, think of what’s involved for the person being interviewed. We’ve all been there. The night before, you dig out your smartest outfit, iron it, and hope your hair lies flat for once. You frantically research the company, reading every last news article based on a formulaic press release, every blog post by the CEO, and every review by a disgruntled former employee.

After a sleepless night, you trek to their office, make awkward small talk, then answer a set of predictable questions. What’s your biggest weakness? Where do you see yourself in five years? Why do you want this job? Why are you leaving your current job? You reel off the answers you prepared the night before, highlighting the best of the best. All the while, you’re reminding yourself to sit up straight, don’t bite your nails, and keep smiling.

It’s not much better on the employer’s side of the table. When you have a role to fill, you select a list of promising candidates and invite them for an interview. Then you pull together a set of standard questions to riff off, doing a little improvising as you hear their responses. At the end of it all, you make some kind of gut judgment about the person who felt right—likely the one you connected with the most in the short time you were together.

Is it any surprise that job interviews don’t work when the whole process is based on subjective feelings? They are in no way the most effective means of deciding who to hire because they maximize the role of bias and minimize the role of evaluating competency.

What is a job interview?

“In most cases, the best strategy for a job interview is to be fairly honest, because the worst thing that can happen is that you won’t get the job and will spend the rest of your life foraging for food in the wilderness and seeking shelter underneath a tree or the awning of a bowling alley that has gone out of business.”

— Lemony Snicket, Horseradish

When we say “job interviews” throughout this post, we’re talking about the type of interview that has become standard in many industries and even in universities: free-form interviews in which candidates sit in a room with one or more people from a prospective employer (often people they might end up working with) and answer unstructured questions. Such interviews tend to focus on how a candidate behaves generally, emphasizing factors like whether they arrive on time or if they researched the company in advance. While questions may ostensibly be about predicting job performance, they tend to better select for traits like charisma rather than actual competence.

Unstructured interviews can make sense for certain roles. The ability to give a good first impression and be charming matters for a salesperson. But not all roles need charm, and just because you don’t want to hang out with someone after an interview doesn’t mean they won’t be an amazing software engineer. In a small startup with a handful of employees, someone being “one of the gang” might matter because close-knit friendships are a strong motivator when work is hard and pay is bad. But that group mentality may be less important in a larger company in need of diversity.

Considering the importance of hiring and how much harm getting it wrong can cause, it makes sense for companies to study and understand the most effective interview methods. Let’s take a look at why job interviews don’t work and what we can do instead.

Why job interviews are ineffective

Discrimination and bias

Information like someone’s age, gender, race, appearance, or social class shouldn’t dictate if they get a job or not—their competence should. But that’s unfortunately not always the case. Interviewers can end up picking the people they like the most, which often means those who are most similar to them. This ultimately means a narrower range of competencies is available to the organization.

Psychologist Ron Friedman explains in The Best Place to Work: The Art and Science of Creating an Extraordinary Workplace some of the unconscious biases that can impact hiring. We tend to rate attractive people as more competent, intelligent, and qualified. We consider tall people to be better leaders, particularly when evaluating men. We view people with deep voices as more trustworthy than those with higher voices.

Implicit bias is pernicious because it’s challenging to spot the ways it influences interviews. Once an interviewer judges someone, they may ask questions that nudge the interviewee towards fitting that perception. For instance, if they perceive someone to be less intelligent, they may ask basic questions that don’t allow the candidate to display their expertise. Having confirmed their bias, the interviewer has no reason to question it or even notice it in the future.

Hiring often comes down to how much an interviewer likes a candidate as a person. This means that we can be manipulated by manufactured charm. If someone’s charisma is faked for an interview, an organization can be left dealing with the fallout for ages.

The map is not the territory

The representation of something is not the thing itself. A job interview is meant to be a quick snapshot to tell a company how a candidate would be at a job. However, it’s not a representative situation in terms of replicating how the person will perform in the actual work environment.

For instance, people can lie during job interviews. Indeed, the situation practically encourages it. While most people feel uncomfortable telling outright lies (and know they would face serious consequences later on for a serious fabrication), bending the truth is common. Ron Friedman writes, “Research suggests that outright lying generates too much psychological discomfort for people to do it very often. More common during interviews are more nuanced forms of deception which include embellishment (in which we take credit for things we haven’t done), tailoring (in which we adapt our answers to fit the job requirements), and constructing (in which we piece together elements from different experiences to provide better answers.)” An interviewer can’t know if someone is deceiving them in any of these ways. So they can’t know if they’re hearing the truth.

One reason why we think job interviews are representative is the fundamental attribution error. This is a logical fallacy that leads us to believe that the way people behave in one area carries over to how they will behave in other situations. We view people’s behaviors as the visible outcome of innate characteristics, and we undervalue the impact of circumstances.

Some employers report using one single detail they consider representative to make hiring decisions, such as whether a candidate sends a thank-you note after the interview or if their LinkedIn picture is a selfie. Sending a thank-you note shows manners and conscientiousness. Having a selfie on LinkedIn shows unprofessionalism. But is that really true? Can one thing carry across to every area of job performance? It’s worth debating.

Gut feelings aren’t accurate

We all like to think we can trust our intuition. The problem is that intuitive judgments tend to only work in areas where feedback is fast and cause and effect clear. Job interviews don’t fall into that category. Feedback is slow. The link between a hiring decision and a company’s success is unclear.

Overwhelmed by candidates and the pressure of choosing, interviewers may resort to making snap judgments based on limited information. And interviews introduce a lot of noise, which can dilute relevant information while leading to overconfidence. In a study entitled Belief in the Unstructured Interview: The Persistence of an Illusion, participants predicted the future GPA of a set of students. They either received biographical information about the students or both biographical information and an interview. In some of the cases, the interview responses were entirely random, meaning they shouldn’t have conveyed any genuine useful information.

Before the participants made their predictions, the researchers informed them that the strongest predictor of a student’s future GPA is their past GPA. Seeing as all participants had access to past GPA information, they should have factored it heavily into their predictions.

In the end, participants who were able to interview the students made worse predictions than those who only had access to biographical information. Why? Because the interviews introduced too much noise. They distracted participants with irrelevant information, making them forget the most significant predictive factor: past GPA. Of course, we do not have clear metrics like GPA for jobs. But this study indicates that interviews do not automatically lead to better judgments about a person.

We tend to think human gut judgments are superior, even when evidence doesn’t support this. We are quick to discard information that should shape our judgments in favor of less robust intuitions that we latch onto because they feel good. The less challenging information is to process, the better it feels. And we tend to associate good feelings with ‘rightness’.

Experience ≠ expertise in interviewing

In 1979, the University of Texas Medical School at Houston suddenly had to increase its incoming class size by 50 students due to a legal change requiring larger classes. Without time to interview again, they selected from the pool of candidates the school chose to interview, then rejected as unsuitable for admission. Seeing as they got through to the interview stage, they had to be among the best candidates. They just weren’t previously considered good enough to admit.

When researchers later studied the result of this unusual situation, they found that the students whom the school first rejected performed no better or worse academically than the ones they first accepted. In short, interviewing students did nothing to help select for the highest performers.

Studying the efficacy of interviews is complicated and hard to manage from an ethical standpoint. We can’t exactly give different people the same real-world job in the same conditions. We can take clues from fortuitous occurrences, like the University of Texas Medical School change in class size and the subsequent lessons learned. Without the legal change, the interviewers would never have known that the students they rejected were of equal competence to the ones they accepted. This is why building up experience in this arena is difficult. Even if someone has a lot of experience conducting interviews, it’s not straightforward to translate that into expertise. Expertise is about have a predictive model of something, not just knowing a lot about it.

Furthermore, the feedback from hiring decisions tends to be slow. An interviewer cannot know what would happen if they hired an alternate candidate. If a new hire doesn’t work out, that tends to fall on them, not the person who chose them. There are so many factors involved that it’s not terribly conducive to learning from experience.

Making interviews more effective

It’s easy to see why job interviews are so common. People want to work with people they like, so interviews allow them to scope out possible future coworkers. Candidates expect interviews, as well—wouldn’t you feel a bit peeved if a company offered you a job without the requisite “casual chat” beforehand? Going through a grueling interview can make candidates more invested in the position and likely to accept an offer. And it can be hard to imagine viable alternatives to interviews.

But it is possible to make job interviews more effective or make them the final step in the hiring process after using other techniques to gauge a potential hire’s abilities. Doing what works should take priority over what looks right or what has always been done.

Structured interviews

While unstructured interviews don’t work, structured ones can be excellent. In Thinking, Fast and Slow, Daniel Kahneman describes how he redefined the Israel Defense Force’s interviewing process as a young psychology graduate. At the time, recruiting a new soldier involved a series of psychometric tests followed by an interview to assess their personality. Interviewers then based their decision on their intuitive sense of a candidate’s fitness for a particular role. It was very similar to the method of hiring most companies use today—and it proved to be useless.

Kahneman introduced a new interviewing style in which candidates answered a predefined series of questions that were intended to measure relevant personality traits for the role (for example, responsibility and sociability). He then asked interviewers to give candidates a score for how well they seemed to exhibit each trait based on their responses. Kahneman explained that “by focusing on standardized, factual questions I hoped to combat the halo effect, where favorable first impressions influence later judgments.” He tasked interviewers only with providing these numbers, not with making a final decision.

Although interviewers at first disliked Kahneman’s system, structured interviews proved far more effective and soon became the standard for the IDF. In general, they are often the most useful way to hire. The key is to decide in advance on a list of questions, specifically designed to test job-specific skills, then ask them to all the candidates. In a structured interview, everyone gets the same questions with the same wording, and the interviewer doesn’t improvise.

Tomas Chamorro-Premuzic writes in The Talent Delusion:

There are at least 15 different meta-analytic syntheses on the validity of job interviews published in academic research journals. These studies show that structured interviews are very useful to predict future job performance. . . . In comparison, unstructured interviews, which do not have a set of predefined rules for scoring or classifying answers and observations in a reliable and standardized manner, are considerably less accurate.

Why does it help if everyone hears the same questions? Because, as we learned previously, interviewers can make unconscious judgments about candidates, then ask questions intended to confirm their assumptions. Structured interviews help measure competency, not irrelevant factors. Ron Friedman explains this further:

It’s also worth having interviewers develop questions ahead of time so that: 1) each candidate receives the same questions, and 2) they are worded the same way. The more you do to standardize your interviews, providing the same experience to every candidate, the less influence you wield on their performance.

What, then, is an employer to do with the answers? Friedman says you must then create clear criteria for evaluating them.

Another step to help minimize your interviewing blind spots: include multiple interviewers and give them each specific criteria upon which to evaluate the candidate. Without a predefined framework for evaluating applicants—which may include relevant experience, communication skills, attention to detail—it’s hard for interviewers to know where to focus. And when this happens, fuzzy interpersonal factors hold greater weight, biasing assessments. Far better to channel interviewers’ attention in specific ways, so that the feedback they provide is precise.

Blind auditions

One way to make job interviews more effective is to find ways to “blind” the process—to disguise key information that may lead to biased judgments. Blinded interviews focus on skills alone, not who a candidate is as a person. Orchestras offer a remarkable case study in the benefits of blinding.

In the 1970s, orchestras had a gender bias problem. A mere 5% of their members were women, on average. Orchestras knew they were missing out on potential talent, but they found the audition process seemed to favor men over women. Those who were carrying out auditions couldn’t sidestep their unconscious tendency to favor men.

Instead of throwing up their hands in despair and letting this inequality stand, orchestras began carrying out blind auditions. During these, candidates would play their instruments behind a screen while a panel listened and assessed their performance. They received no identifiable information about candidates. The idea was that orchestras would be able to hire without room for bias. It took a bit of tweaking to make it work – at first, the interviewers were able to discern gender based on the sound of a candidate’s shoes. After that, they requested that people interview without their shoes.

The results? By 1997, up to 25% of orchestra members were women. Today, the figure is closer to 30%.

Although this is sometimes difficult to replicate for other types of work, blind auditions can provide an inspiration to other industries that could benefit from finding ways to make interviews more about a person’s abilities than their identity.

Competency-related evaluations

What’s the best way to test if someone can do a particular job well? Get them to carry out tasks that are part of the job. See if they can do what they say they can do. It’s much harder for someone to lie and mislead an interviewer during actual work than during an interview. Using competency tests for a blinded interview process is also possible—interviewers could look at depersonalized test results to make unbiased judgments.

Tomas Chamorro-Premuzic writes in The Talent Delusion: Why Data, Not Intuition, Is the Key to Unlocking Human Potential, “The science of personnel selection is over a hundred years old yet decision-makers still tend to play it by ear or believe in tools that have little academic rigor. . . . An important reason why talent isn’t measured more scientifically is the belief that rigorous tests are difficult and time-consuming to administer, and that subjective evaluations seem to do the job ‘just fine.’”

Competency tests are already quite common in many fields. But interviewers tend not to accord them sufficient importance. They come after an interview, or they’re considered secondary to it. A bad interview can override a good competency test. At best, interviewers accord them equal importance to interviews. Yet they should consider them far more important.

Ron Friedman writes, “Extraneous data such as a candidate’s appearance or charisma lose their influence when you can see the way an applicant actually performs. It’s also a better predictor of their future contributions because unlike traditional in-person interviews, it evaluates job-relevant criteria. Including an assignment can help you better identify the true winners in your applicant pool while simultaneously making them more invested in the position.”

Conclusion

If a company relies on traditional job interviews as its sole or main means of choosing employees, it simply won’t get the best people. And getting hiring right is paramount to the success of any organization. A driven team of people passionate about what they do can trump one with better funding and resources. The key to finding those people is using hiring techniques that truly work.

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Standing on the Shoulders of Giants

Reading Time: 11 minutes

Innovation doesn’t occur in a vacuum. Doers and thinkers from Shakespeare to Jobs, liberally “stole” inspiration from the doers and thinkers who came before. Here’s how to do it right.

***

“If I have seen further,” Isaac Newton wrote in a 1675 letter to fellow scientist Robert Hooke, “it is by standing on the shoulders of giants.”

It can be easy to look at great geniuses like Newton and imagine that their ideas and work came solely out of their minds, that they spun it from their own thoughts—that they were true originals. But that is rarely the case.

Innovative ideas have to come from somewhere. No matter how unique or unprecedented a work seems, dig a little deeper and you will always find that the creator stood on someone else’s shoulders. They mastered the best of what other people had already figured out, then made that expertise their own. With each iteration, they could see a little further, and they were content in the knowledge that future generations would, in turn, stand on their shoulders.

Standing on the shoulders of giants is a necessary part of creativity, innovation, and development. It doesn’t make what you do less valuable. Embrace it.

Everyone gets a lift up

Ironically, Newton’s turn of phrase wasn’t even entirely his own. The phrase can be traced back to the twelfth century, when the author John of Salisbury wrote that philosopher Bernard of Chartres compared people to dwarves perched on the shoulders of giants and said that “we see more and farther than our predecessors, not because we have keener vision or greater height, but because we are lifted up and borne aloft on their gigantic stature.”

Mary Shelley put it this way in the nineteenth century, in a preface for Frankenstein: “Invention, it must be humbly admitted, does not consist in creating out of void but out of chaos.”

There are giants in every field. Don’t be intimidated by them. They offer an exciting perspective. As the film director Jim Jarmusch advised, “Nothing is original. Steal from anywhere that resonates with inspiration or fuels your imagination. Devour old films, new films, music, books, paintings, photographs, poems, dreams, random conversations, architecture, bridges, street signs, trees, clouds, bodies of water, light, and shadows. Select only things to steal from that speak directly to your soul. If you do this, your work (and theft) will be authentic. Authenticity is invaluable; originality is non-existent. And don’t bother concealing your thievery—celebrate it if you feel like it. In any case, always remember what Jean-Luc Godard said: ‘It’s not where you take things from—it’s where you take them to.’”

That might sound demoralizing. Some might think, “My song, my book, my blog post, my startup, my app, my creation—surely they are original? Surely no one has done this before!” But that’s likely not the case. It’s also not a bad thing. Filmmaker Kirby Ferguson states in his TED Talk: “Admitting this to ourselves is not an embrace of mediocrity and derivativeness—it’s a liberation from our misconceptions, and it’s an incentive to not expect so much from ourselves and to simply begin.”

There lies the important fact. Standing on the shoulders of giants enables us to see further, not merely as far as before. When we build upon prior work, we often improve upon it and take humanity in new directions. However original your work seems to be, the influences are there—they might just be uncredited or not obvious. As we know from social proof, copying is a natural human tendency. It’s how we learn and figure out how to behave.

In Antifragile: Things That Gain from Disorder, Nassim Taleb describes the type of antifragile inventions and ideas that have lasted throughout history. He describes himself heading to a restaurant (the likes of which have been around for at least 2,500 years), in shoes similar to those worn at least 5,300 years ago, to use silverware designed by the Mesopotamians. During the evening, he drinks wine based on a 6,000-year-old recipe, from glasses invented 2,900 years ago, followed by cheese unchanged through the centuries. The dinner is prepared with one of our oldest tools, fire, and using utensils much like those the Romans developed.

Much about our societies and cultures has undeniably changed and continues to change at an ever-faster rate. But we continue to stand on the shoulders of those who came before in our everyday life, using their inventions and ideas, and sometimes building upon them.

Not invented here syndrome

When we discredit what came before or try to reinvent the wheel or refuse to learn from history, we hold ourselves back. After all, many of the best ideas are the oldest. “Not Invented Here Syndrome” is a term for situations when we avoid using ideas, products, or data created by someone else, preferring instead to develop our own (even if it is more expensive, time-consuming, and of lower quality.)

The syndrome can also manifest as reluctance to outsource or delegate work. People might think their output is intrinsically better if they do it themselves, becoming overconfident in their own abilities. After all, who likes getting told what to do, even by someone who knows better? Who wouldn’t want to be known as the genius who (re)invented the wheel?

Developing a new solution for a problem is more exciting than using someone else’s ideas. But new solutions, in turn, create new problems. Some people joke that, for example, the largest Silicon Valley companies are in fact just impromptu incubators for people who will eventually set up their own business, firm in the belief that what they create themselves will be better.

The syndrome is also a case of the sunk cost fallacy. If a company has spent a lot of time and money getting a square wheel to work, they may be resistant to buying the round ones that someone else comes out with. The opportunity costs can be tremendous. Not Invented Here Syndrome detracts from an organization or individual’s core competency, and results in wasting time and talent on what are ultimately distractions. Better to use someone else’s idea and be a giant for someone else.

Why Steve Jobs stole his ideas

“Creativity is just connecting things. When you ask creative people how they did something, they feel a little guilty because they didn’t really do it. They just saw something. It seemed obvious to them after a while; that’s because they were able to connect experiences they’ve had and synthesize new things.” 

— Steve Jobs

In The Runaway Species: How Human Creativity Remakes the World, Anthony Brandt and David Eagleman trace the path that led to the creation of the iPhone and track down the giants upon whose shoulders Steve Jobs perched. We often hail Jobs as a revolutionary figure who changed how we use technology. Few who were around in 2007 could have failed to notice the buzz created by the release of the iPhone. It seemed so new, a total departure from anything that had come before. The truth is a little messier.

The first touchscreen came about almost half a century before the iPhone, developed by E.A. Johnson for air traffic control. Other engineers built upon his work and developed usable models, filing a patent in 1975. Around the same time, the University of Illinois was developing touchscreen terminals for students. Prior to touchscreens, light pens used similar technology. The first commercial touchscreen computer came out in 1983, soon followed by graphics boards, tablets, watches, and video game consoles. Casio released a touchscreen pocket computer in 1987 (remember, this is still a full twenty years before the iPhone.)

However, early touchscreen devices were frustrating to use, with very limited functionality, often short battery lives, and minimal use cases for the average person. As touchscreen devices developed in complexity and usability, they laid down the groundwork for the iPhone.

Likewise, the iPod built upon the work of Kane Kramer, who took inspiration from the Sony Walkman. Kramer designed a small portable music player in the 1970s. The IXI, as he called it, looked similar to the iPod but arrived too early for a market to exist, and Kramer lacked the marketing skills to create one. When pitching to investors, Kramer described the potential for immediate delivery, digital inventory, taped live performances, back catalog availability, and the promotion of new artists and microtransactions. Sound familiar?

Steve Jobs stood on the shoulders of the many unseen engineers, students, and scientists who worked for decades to build the technology he drew upon. Although Apple has a long history of merciless lawsuits against those they consider to have stolen their ideas, many were not truly their own in the first place. Brandt and Eagleman conclude that “human creativity does not emerge from a vacuum. We draw on our experience and the raw materials around us to refashion the world. Knowing where we’ve been, and where we are, points the way to the next big industries.”

How Shakespeare got his ideas

“Nothing will come of nothing.”  

— William Shakespeare, King Lear

Most, if not all, of Shakespeare’s plays draw heavily upon prior works—so much so that some question whether he would have survived today’s copyright laws.

Hamlet took inspiration from Gesta Danorum, a twelfth-century work on Danish history by Saxo Grammaticus, consisting of sixteen Latin books. Although it is doubtful whether Shakespeare had access to the original text, scholars find the parallels undeniable and believe he may have read another play based on it, from which he drew inspiration. In particular, the accounts of the plight of Prince Amleth (which has the same letters as Hamlet) involves similar events.

Holinshed’s Chronicles, a co-authored account of British history from the late sixteenth century, tells stories that mimic the plot of Macbeth, including the three witches. Holinshed’s Chronicles itself was a mélange of earlier texts, which transferred their biases and fabrications to Shakespeare. It also likely inspired King Lear.

Parts of Antony and Cleopatra are copied verbatim from Plutarch’s Life of Mark Anthony. Arthur Brooke’s 1562 poem The Tragicall Historye of Romeus and Juliet was an undisguised template for Romeo and Juliet. Once again, there are more giants behind the scenes—Brooke copied a 1559 poem by Pierre Boaistuau, who in turn drew from a 1554 story by Matteo Bandello, who in turn drew inspiration from a 1530 work by Luigi da Porto. The list continues, with Plutarch, Chaucer, and the Bible acting as inspirations for many major literary, theatrical, and cultural works.

Yet what Shakespeare did with the works he sometimes copied, sometimes learned from, is remarkable. Take a look at any of the original texts and, despite the mimicry, you will find that they cannot compare to his plays. Many of the originals were dry, unengaging, and lacking any sort of poetic language. J.J. Munro wrote in 1908 that The Tragicall Historye of Romeus and Juliet “meanders on like a listless stream in a strange and impossible land; Shakespeare’s sweeps on like a broad and rushing river, singing and foaming, flashing in sunlight and darkening in cloud, carrying all things irresistibly to where it plunges over the precipice into a waste of waters below.”

Despite bordering on plagiarism at times, he overhauled the stories with exceptional use of the English language, bringing drama and emotion to dreary chronicles or poems. He had a keen sense for the changes required to restructure plots, creating suspense and intensity in their stories. Shakespeare saw far further than those who wrote before him, and with their help, he ushered in a new era of the English language.

Of course, it’s not just Newton, Jobs, and Shakespeare who found a (sometimes willing, sometimes not) shoulder to stand upon. Facebook is presumed to have built upon Friendster. Cormac McCarthy’s books often replicate older history texts, with one character coming straight from Samuel Chamberlain’s My Confessions. John Lennon borrowed from diverse musicians, once writing in a letter to the New York Times that though the Beatles copied black musicians, “it wasn’t a rip off. It was a love in.”

In The Ecstasy of Influence, Jonathan Lethem points to many other instances of influences in classic works. In 1916, journalist Heinz von Lichberg published a story of a man who falls in love with his landlady’s daughter and begins a love affair, culminating in her death and his lasting loneliness. The title? Lolita. It’s hard to question that Nabokov must have read it, but aside from the plot and name, the style of language in his version is absent from the original.

The list continues. The point is not to be flippant about plagiarism but to cultivate sensitivity to the elements of value in a previous work, as well as the ability to build upon those elements. If we restrict the flow of ideas, everyone loses out.

The adjacent possible

What’s this about? Why can’t people come up with their own ideas? Why do so many people come up with a brilliant idea but never profit from it? The answer lies in what scientist Stuart Kauffman calls “the adjacent possible.” Quite simply, each new innovation or idea opens up the possibility of additional innovations and ideas. At any time, there are limits to what is possible, yet those limits are constantly expanding.

In Where Good Ideas Come From: The Natural History of Innovation, Steven Johnson compares this process to being in a house where opening a door creates new rooms. Each time we open the door to a new room, new doors appear and the house grows. Johnson compares it to the formation of life, beginning with basic fatty acids. The first fatty acids to form were not capable of turning into living creatures. When they self-organized into spheres, the groundwork formed for cell membranes, and a new door opened to genetic codes, chloroplasts, and mitochondria. When dinosaurs evolved a new bone that meant they had more manual dexterity, they opened a new door to flight. When our distant ancestors evolved opposable thumbs, dozens of new doors opened to the use of tools, writing, and warfare. According to Johnson, the history of innovation has been about exploring new wings of the adjacent possible and expanding what we are capable of.

A new idea—like those of Newton, Jobs, and Shakespeare—is only possible because a previous giant opened a new door and made their work possible. They in turn opened new doors and expanded the realm of possibility. Technology, art, and other advances are only possible if someone else has laid the groundwork; nothing comes from nothing. Shakespeare could write his plays because other people had developed the structures and language that formed his tools. Newton could advance science because of the preliminary discoveries that others had made. Jobs built Apple out of the debris of many prior devices and technological advances.

The questions we all have to ask ourselves are these: What new doors can I open, based on the work of the giants that came before me? What opportunities can I spot that they couldn’t? Where can I take the adjacent possible? If you think all the good ideas have already been found, you are very wrong. Other people’s good ideas open new possibilities, rather than restricting them.

As time passes, the giants just keep getting taller and more willing to let us hop onto their shoulders. Their expertise is out there in books and blog posts, open-source software and TED talks, podcast interviews, and academic papers. Whatever we are trying to do, we have the option to find a suitable giant and see what can be learned from them. In the process, knowledge compounds, and everyone gets to see further as we open new doors to the adjacent possible.

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