Tag: Physics

The Nerds Were Right. Math Makes Life Beautiful.

Math has long been the language of science, engineering, and finance, but can math help you feel calm on a turbulent flight? Get a date? Make better decisions? Here are some heroic ways math shows up in our everyday life.


Sounds intellectually sophisticated, doesn’t it? Other than sounding really smart at after-work cocktails, what could be the benefit of understanding where math and physics permeate your life?

Well, what if I told you that math and physics can help you make better decisions by aligning with how the world works? What if I told you that math can help you get a date? Help you solve problems? What if I told you that knowing the basics of math and physics can help make you less afraid and confused? And, perhaps most important, they can help make life more beautiful. Seriously.

If you’ve ever been on a plane when turbulence has hit, you know how unnerving that can be. Most people get freaked out by it, and no matter how much we fly, most of us have a turbulence threshold. When the sides of the plane are shaking, noisily holding themselves together, and the people beside us are white with fear, hands clenched on their armrests, even the calmest of us will ponder the wisdom of jetting 38,000 feet above the ground in a metal tube moving at 1,000 km an hour.

Considering that most planes don’t fall from the sky on account of turbulence isn’t that comforting in the moment. Aren’t there always exceptions to the rule? But what if you understood why, or could explain the physics involved to the freaked-out person beside you? That might help.

In Storm in a Teacup: The Physics of Everyday Life, Helen Czerski spends a chapter describing the gas laws. Covering subjects from the making of popcorn to the deep dives of sperm whales, her amazingly accessible prose describes how the movement of gas is fundamental to the functioning of pretty much everything on earth, including our lungs. She reveals air to be not the static clear thing that we perceive when we bother to look, but rivers of molecules in constant collision, pushing and moving, giving us both storms and cloudless skies.

So when you appreciate air this way, as a continually flowing and changing collection of particles, turbulence is suddenly less scary. Planes are moving through a substance that is far from uniform. Of course, there are going to be pockets of more or less dense air molecules. Of course, they will have minor impacts on the plane as it moves through these slightly different pressure areas. Given that the movement of air can create hurricanes, it’s amazing that most flights are as smooth as they are.

You know what else is really scary? Approaching someone for a date or a job. Rejection sucks. It makes us feel awful, and therefore the threat of it often stops us from taking risks. You know the scene. You’re out at a bar with some friends. A group of potential dates is across the way. Do you risk the cringingly icky feeling of rejection and approach the person you find most attractive, or do you just throw out a lot of eye contact and hope that person approaches you?

Most men go with the former, as difficult as it is. Women will often opt for the latter. We could discuss social conditioning, with the roles that our culture expects each of us to follow. But this post is about math and physics, which actually turn out to be a lot better in providing guidance to optimize our chances of success in the intimidating bar situation.

In The Mathematics of Love, Hannah Fry explains the Gale-Shapley matching algorithm, which essentially proves that “If you put yourself out there, start at the top of the list, and work your way down, you’ll always end up with the best possible person who’ll have you. If you sit around and wait for people to talk to you, you’ll end up with the least bad person who approaches you. Regardless of the type of relationship you’re after, it pays to take the initiative.”

The math may be complicated, but the principle isn’t. Your chances of ending up with what you want — say, the guy with the amazing smile or that lab director job in California — dramatically increase if you make the first move. Fry says, “aim high, and aim frequently. The math says so.” Why argue with that?

Understanding more physics can also free us from the panic-inducing, heart-pounding fear that we are making the wrong decisions. Not because physics always points out the right decision, but because it can lead us away from this unproductive, subjective, binary thinking. How? By giving us the tools to ask better questions.

Consider this illuminating passage from Czerski:

We live in the middle of the timescales, and sometimes it’s hard to take the rest of time seriously. It’s not just the difference between now and then, it’s the vertigo you get when you think about what “now” actually is. It could be a millionth of a second, or a year. Your perspective is completely different when you’re looking at incredibly fast events or glacially slow ones. But the difference hasn’t got anything to do with how things are changing; it’s just a question of how long they take to get there. And where is “there”? It is equilibrium, a state of balance. Left to itself, nothing will ever shift from this final position because it has no reason to do so. At the end, there are no forces to move anything, because they’re all balanced. They physical world, all of it, only ever has one destination: equilibrium.

How can this change your decision-making process?

You might start to consider whether you are speeding up the goal of equilibrium (working with force) or trying to prevent equilibrium (working against force).  One option isn’t necessarily worse than the other. But the second one is significantly more work.

So then you will understand how much effort is going to be required on your part. Love that house with the period Georgian windows? Great. But know that you will have to spend more money fighting to counteract the desire of the molecules on both sides of the window to achieve equilibrium in varying temperatures than you will if you go with the modern bungalow with the double-paned windows.

And finally, curiosity. Being curious about the world helps us find solutions to problems by bringing new knowledge to bear on old challenges. Math and physics are actually powerful tools for investigating the possibilities of what is out there.

Fry writes that “Mathematics is about abstracting away from reality, not replicating it. And it offers real value in the process. By allowing yourself to view the world from an abstract perspective, you create a language that is uniquely able to capture and describe the patterns and mechanisms that would otherwise remain hidden.”

Physics is very similar. Czerski says, “Seeing what makes the world tick changes your perspective. The world is a mosaic of physical patterns, and once you’re familiar with the basics, you start to see how those patterns fit together.”

Math and physics enhance your curiosity. These subjects allow us to dive into the unknown without being waylaid by charlatans or sidetracked by the impossible. They allow us to tackle the mysteries of life one at a time, opening up the possibilities of the universe.

As Czerski says, “Knowing about some basics bits of physics [and math!] turns the world into a toybox.” A toybox full of powerful and beautiful things.

Inertia: The Force That Holds the Universe Together

Inertia is the force that holds the universe together. Literally. Without it, things would fall apart. It’s also what keeps us locked in destructive habits, and resistant to change.


“If it were possible to flick a switch and turn off inertia, the universe would collapse in an instant to a clump of matter,” write Peter and Neal Garneau in In the Grip of the Distant Universe: The Science of Inertia.

“…death is the destination we all share. No one has ever escaped it. And that is as it should be, because death is very likely the single best invention of life. It’s life’s change agent; it clears out the old to make way for the new … Your time is limited, so don’t waste it living someone else’s life.”

— Steve Jobs

Inertia is the force that holds the universe together. Literally. Without it, matter would lack the electric forces necessary to form its current arrangement. Inertia is counteracted by the heat and kinetic energy produced by moving particles. Subtract it and everything cools to -459.67 degrees Fahrenheit (absolute zero temperature). Yet we know so little about inertia and how to leverage it in our daily lives.

Inertia: The Force That Holds the Universe Together

The Basics

The German astronomer Johannes Kepler (1571–1630) coined the word “inertia.” The etymology of the term is telling. Kepler obtained it from the Latin for “unskillfulness, ignorance; inactivity or idleness.” True to its origin, inertia keeps us in bed on a lazy Sunday morning (we need to apply activation energy to overcome this state).

Inertia refers to resistance to change — in particular, resistance to changes in motion. Inertia may manifest in physical objects or in the minds of people.

We learn the principle of inertia early on in life. We all know that it takes a force to get something moving, to change its direction, or to stop it.

Our intuitive sense of how inertia works enables us to exercise a degree of control over the world around us. Learning to drive offers further lessons. Without external physical forces, a car would keep moving in a straight line in the same direction. It takes a force (energy) to get a car moving and overcome the inertia that kept it still in a parking space. Changing direction to round a corner or make a U-turn requires further energy. Inertia is why a car does not stop the moment the brakes are applied.

The heavier a vehicle is, the harder it is to overcome inertia and make it stop. A light bicycle stops with ease, while an eight-carriage passenger train needs a good mile to halt. Similarly, the faster we run, the longer it takes to stop. Running in a straight line is much easier than twisting through a crowded sidewalk, changing direction to dodge people.

Any object that can be rotated, such as a wheel, has rotational inertia. This tells us how hard it is to change the object’s speed around the axis. Rotational inertia depends on the mass of the object and its distribution relative to the axis.

Inertia is Newton’s first law of motion, a fundamental principle of physics. Newton summarized it this way: “The vis insita, or innate force of matter, is a power of resisting by which every body, as much as in it lies, endeavors to preserve its present state, whether it be of rest or of moving uniformly forward in a straight line.”

When developing his first law, Newton drew upon the work of Galileo Galilei. In a 1624 letter to Francesco Ingoli, Galileo outlined the principle of inertia:

I tell you that if natural bodies have it from Nature to be moved by any movement, this can only be a circular motion, nor is it possible that Nature has given to any of its integral bodies a propensity to be moved by straight motion. I have many confirmations of this proposition, but for the present one alone suffices, which is this.

I suppose the parts of the universe to be in the best arrangement so that none is out of its place, which is to say that Nature and God have perfectly arranged their structure… Therefore, if the parts of the world are well ordered, the straight motion is superfluous and not natural, and they can only have it when some body is forcibly removed from its natural place, to which it would then return to a straight line.

In 1786, Immanuel Kant elaborated further: “All change of matter has an external cause. (Every body remains in its state of rest or motion in the same direction and with the same velocity, if not compelled by an external cause to forsake this state.) … This mechanical law can only be called the law of inertia (lex inertiæ)….”

Now that we understand the principle, let’s look at some of the ways we can understand it better and apply it to our advantage.

Decision Making and Cognitive Inertia

We all experience cognitive inertia: the tendency to stick to existing ideas, beliefs, and habits even when they no longer serve us well. Few people are truly able to revise their opinions in light of disconfirmatory information. Instead, we succumb to confirmation bias and seek out verification of existing beliefs. It’s much easier to keep thinking what we’ve always been thinking than to reflect on the chance that we might be wrong and update our views. It takes work to overcome cognitive dissonance, just as it takes effort to stop a car or change its direction.

When the environment changes, clinging to old beliefs can be harmful or even fatal. Whether we fail to perceive the changes or fail to respond to them, the result is the same. Even when it’s obvious to others that we must change, it’s not obvious to us. It’s much easier to see something when you’re not directly involved. If I ask you how fast you’re moving right now, you’d likely say zero, but you’re moving 18,000 miles an hour around the sun. Perspective is everything, and the perspective that matters is the one that most closely lines up with reality.

“Sometimes you make up your mind about something without knowing why, and your decision persists by the power of inertia. Every year it gets harder to change.”

— Milan Kundera, The Unbearable Lightness of Being

Cognitive inertia is the reason that changing our habits can be difficult. The default is always the path of least resistance, which is easy to accept and harder to question. Consider your bank, for example. Perhaps you know that there are better options at other banks. Or you have had issues with your bank that took ages to get sorted. Yet very few people actually change their banks, and many of us stick with the account we first opened. After all, moving away from the status quo would require a lot of effort: researching alternatives, transferring balances, closing accounts, etc. And what if something goes wrong? Sounds risky. The switching costs are high, so we stick to the status quo.

Sometimes inertia helps us. After all, questioning everything would be exhausting. But in many cases, it is worthwhile to overcome inertia and set something in motion, or change direction, or halt it.

The important thing about inertia is that it is only the initial push that is difficult. After that, progress tends to be smoother. Ernest Hemingway had a trick for overcoming inertia in his writing. Knowing that getting started was always the hardest part, he chose to finish work each day at a point where he had momentum (rather than when he ran out of ideas). The next day, he could pick up from there. In A Moveable Feast, Hemingway explains:

I always worked until I had something done and I always stopped when I knew what was going to happen next. That way I could be sure of going on the next day.

Later on in the book, he describes another method, which was to write just one sentence:

Do not worry. You have always written before and you will write now. All you have to do is write one true sentence. Write the truest sentence that you know. So, finally I would write one true sentence and go on from there. It was easy then because there was always one true sentence that I knew or had seen or had heard someone say. If I started to write elaborately, or like someone introducing or presenting something, I found that I could cut that scrollwork or ornament out and throw it away and start with the first true simple declarative sentence I had written.

We can learn a lot from Hemingway’s approach to tackling inertia and apply it in areas beyond writing. As with physics, the momentum from getting started can carry us a long way. We just need to muster the required activation energy and get going.

Status Quo Bias: “When in Doubt, Do Nothing”

Cognitive inertia also manifests in the form of status quo bias. When making decisions, we are rarely rational. Faced with competing options and information, we often opt for the default because it’s easy. Doing something other than what we’re already doing requires mental energy that we would rather preserve. In many areas, this helps us avoid decision fatigue.

Many of us eat the same meals most of the time, wear similar outfits, and follow routines. This tendency usually serves us well. But the status quo is not necessarily the optimum solution. Indeed, it may be outright harmful or at least unhelpful if something has changed in the environment or we want to optimize our use of time.

“The great enemy of any attempt to change men’s habits is inertia. Civilization is limited by inertia.”

— Edward L. Bernays, Propaganda

In a paper entitled “If you like it, does it matter if it’s real?” Felipe De Brigard[1] offers a powerful illustration of status quo bias. One of the best-known thought experiments concerns Robert Nozick’s “experience machine.” Nozick asked us to imagine that scientists have created a virtual reality machine capable of simulating any pleasurable experience. We are offered the opportunity to plug ourselves in and live out the rest of our lives in permanent, but fake enjoyment. The experience machine would later inspire the Matrix film series. Presented with the thought experiment, most people balk and claim they would prefer reality. But what if we flip the narrative? De Brigard believed that we are opposed to the experience machine because it contradicts the status quo, the life we are accustomed to.

In an experiment, he asked participants to imagine themselves woken by the doorbell on a Saturday morning. A man in black, introducing himself as Mr. Smith, is at the door. He claims to have vital information. Mr. Smith explains that there has been an error and you are in fact connected to an experience machine. Everything you have lived through so far has been a simulation. He offers a choice: stay plugged in, or return to an unknown real life. Unsurprisingly, far fewer people wished to return to reality in the latter situation than wished to remain in it in the former. The aversive element is not the experience machine itself, but the departure from the status quo it represents.


Inertia is a pervasive, problematic force. It’s the pull that keeps us clinging to old ways and prevents us from trying new things. But as we have seen, it is also a necessary one. Without it, the universe would collapse. Inertia is what enables us to maintain patterns of functioning, maintain relationships, and get through the day without questioning everything. We can overcome inertia much like Hemingway did — by recognizing its influence and taking the necessary steps to create that all-important initial momentum.


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End Notes

[1] https://www.tandfonline.com/doi/abs/10.1080/09515080903532290

Understanding Speed and Velocity: Saying “NO” to the Non-Essential

It’s tempting to think that in order to be a valuable team player, you should say “yes” to every request and task that is asked of you. People who say yes to everything have a lot of speed. They’re always doing stuff but never getting anything done. Why? Because they don’t think in terms of velocity. Understanding the difference between speed and velocity will change how you work.

I once worked for someone who offered me the opportunity to work on a new project nearly every day. These projects were not the quick ones, where you spend 15 minutes and crank out a solution. They were crap work. And there were strings: my boss wanted to be informed about everything, and there was no way I’d get credit for anything.

I remember my response: “That sounds amazing, but it’s not for me. I’m busy enough.”

Saying no to your boss, especially as often as I did, was thought to be risky to your career. I was the new kid, which is why I was getting all of these shit jobs thrown at me.

The diversity of skill sets needed to accomplish them would have made me look bad (perhaps the subtle point of this initiation). Furthermore, my already heavy workload would have gotten heavier with projects that didn’t move me forward. This was my first introduction to busywork.

My well-intentioned colleagues were surprised. “You’re not going to get anywhere with that attitude,” they’d pull me aside to tell me. The problem was that I wasn’t going to get anywhere by saying yes to a lot of jobs that consumed a lot of time, were not the reason I was hired, and left me no time to develop the craft of programming computers, which is what I wanted to do.

I had turned down a job offer for three times what I was being paid at this job because I wanted to work with the best people in the world on a very particular skill — a skill I couldn’t get anywhere but at an intelligence agency. Anything that got in the way of honing that craft was the enemy.

Over my first seven years, I’d barely leave my desk, working 12- to 16-hour days for six days a week. Working that hard with incredible people was amazing and motivating. I’ve never learned so much in such a short period of time.

“The difference between successful people and very successful people is that very successful people say ‘no’ to almost everything.”

— Warren Buffett

Certainly, offers of work are good problems to have. A lot of people struggle to find work, and here I was, a few weeks out of university, saying no to my boss. But saying yes to everything is a quick road to mediocrity. I took a two-thirds pay cut to work for the government so I could work with incredibly smart people on a very narrow skill (think cyber). I was willing to go all in. So no, I wasn’t going say yes to things that didn’t help me hone the craft I’d given up so much to work on.

“Instead of asking how many tasks you can tackle given your working hours,” writes Morten Hansen in Great at Work, “ask how many you can ditch given what you must do to excel.” I did what I needed to do to keep my job. As John Stuart Mill said, “as few as you can, as many as you must.”

Doing more isn’t always moving you ahead. To see why, let’s go back to first-year physics.

The Difference Between Speed and Velocity

Velocity and speed are different things. Speed is the distance traveled over time. I can run around in circles with a lot of speed and cover several miles that way, but I’m not getting anywhere. Velocity measures displacement. It’s direction-aware.

Think of it this way: I want to get from New York to L.A. Speed is flying circles around Manhattan, and velocity is hopping on a direct flight from JFK to LAX.

“People think focus means saying yes to the thing you’ve got to focus on. But that’s not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully. I’m actually as proud of the things we haven’t done as the things I have done. Innovation is saying ‘no’ to 1,000 things.”

— Steve Jobs

When you’re at work, you need to know what you need to do to keep your job. You need to know the table stakes. Then you need to distinguish between tasks that offer a lot of speed and those that offer velocity.

Here are three ways you can increase your velocity:

  1. To the extent possible, ruthlessly shave away the unnecessary tasks, priorities, meetings, and BS. Put all your effort into the projects that really matter.
  2. Don’t rely on your willpower to say no; instead, create systems that help you fend off distractions. I have two friends who were about the same weight several years ago. Around that time, one of them was diagnosed with celiac (gluten intolerance). He immediately started to lose weight after changing his diet. Upon seeing this, my other friend decided that he, too, would go on a diet to lose weight. Because they both ate out a lot, they both were frequently in situations where they would have to make healthy choices. The person with celiac developed “automatic behavior“; he had to avoid gluten if he wanted to stay healthy and pain-free. The other person, however, had to keep making positive choices and ended up falling down after a few weeks and reverting to his previous eating habits. Another example: One of my management principles was “no meeting mornings.” This rule allowed the team to work, uninterrupted, on the most important things. Of course, there were exceptions to this rule, but the default was that each day you had a three-hour chunk of time when you were at your best to really move the needle.
  3. And finally, do as I did, and say “no” to your boss. The best way I found to frame this reply was actually the same technique that negotiation expert Chris Voss mentioned in a recent podcast episode: simply ask, “how am I supposed to do that?” given all the other stuff on your plate. Explain that saying no means that you’re going to be better at the tasks that are most important to your job, and tie those tasks to your boss’s performance.

Members can discuss this post on the Learning Community Forum.

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  • 1

    The difference between speed and velocity first came to me from Peter Kaufman.

Friction: The Hidden Reality of What Holds People Back

How is it that two people delivering the same value to organizational outcomes, in the same role at the same pay, can have a massively different value to the organization itself?


Here’s a common problem that a lot of people are unaware of: John is a remarkable employee. He delivers day in and day out. Jane is equally remarkable and delivers just as well. They’re identical twins except for one difference. That one difference makes Jane incredibly valuable to the organization and makes John much less valuable.

That difference is friction.

To get John to do what he’s supposed to do, his boss comes in and hits him over the head every day. John can’t keep track of what he’s supposed to do, and he does things only when instructed.

Jane, on the other hand, shows up knowing what she’s supposed to do and doing it. She delivers without any added work from her boss.

John and Jane have the same boss. The amount of effort required to get John to do something is 10 times the amount of effort required to get Jane to do something.


Let’s shift our perspective here.

From John’s point of view, he’s competent and capable, even if he’s not ambitious or highly motivated.

From Jane’s point of view, she’s equally competent and capable and wonders why she’s treated the same as John when she does the same amount of work with way less hassle.

From the boss’s point of view, they’re both valuable employees, but they are not equally valuable. Jane is much more valuable than John. If one of them had to be let go, it’d be John.


Let’s invert the problem a little. Instead of asking what more you can do to add value you can ask what you can remove.

One of the easiest ways to increase your value to an organization is to reduce the friction required to get you to do your job. You don’t need to learn any new skills for this; you just have to shift your perspective to your boss’s point of view and see how hard it is for them to get you to do something. Like nature, which removes mistakes to progress, you can remove things to not only survive but thrive. (This is one of the ways we can apply via negativa, an important mental model.)

Think about it this way. Your boss, like you, has 100 units of energy a day with which to accomplish something. If you both spend 10 units on getting you to do the thing you already know you should be doing, you’re making yourself look bad, despite the amazing quality you deliver. And you’re making your boss look less productive than they really are in the process.

When we think of improving our value to an organization, we often think about the skills we need to develop, the jobs we should take, or the growing responsibility we have. In so doing, we miss the most obvious method of all: reducing friction. Reducing friction means that the same 100 units of energy are going to get you further, which is going to get your boss further, which is going to get the organization further.


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Frozen Accidents: Why the Future Is So Unpredictable

“Each of us human beings, for example, is the product of an enormously long
sequence of accidents,
any of which could have turned out differently.”
— Murray Gell-Mann


What parts of reality are the product of an accident? The physicist Murray Gell-Mann thought the answer was “just about everything.” And to Gell-Mann, understanding this idea was the the key to understanding how complex systems work.

Gell-Mann believed two things caused what we see in the world:

  1. A set of fundamental laws
  2. Random “accidents” — the little blips that could have gone either way, and had they, would have produced a very different kind of world.

Gell-Mann pulled the second part from Francis Crick, co-discoverer of the human genetic code, who argued that the code itself may well have been an “accident” of physical history rather than a uniquely necessary arrangement.

These accidents become “frozen” in time, and have a great effect on all subsequent developments; complex life itself is an example of something that did happen a certain way but probably could have happened other ways — we know this from looking at the physics.

This idea of fundamental laws plus accidents and the non-linear second-order effects they produce became the science of complexity and chaos theory.

Gell-Mann discussed the fascinating idea further in a 1996 essay on Edge:

Each of us human beings, for example, is the product of an enormously long sequence of accidents, any of which could have turned out differently. Think of the fluctuations that produced our galaxy, the accidents that led to the formation of the solar system, including the condensation of dust and gas that produced Earth, the accidents that helped to determine the particular way that life began to evolve on Earth, and the accidents that contributed to the evolution of particular species with particular characteristics, including the special features of the human species. Each of us individuals has genes that result from a long sequence of accidental mutations and chance matings, as well as natural selection.

Now, most single accidents make very little difference to the future, but others may have widespread ramifications, many diverse consequences all traceable to one chance event that could have turned out differently. Those we call frozen accidents.

These “frozen accidents” occur at every nested level of the world: As Gell-Mann points out, they are an outcome in physics (the physical laws we observe may be accidents of history); in biology (our genetic code is largely a byproduct of “advantageous accidents” as discussed by Crick); and in human history, as we’ll discuss. In other words, the phenomenon hits all three buckets of knowledge.

Gell-Mann gives a great example of how this plays out on the human scale:

For instance, Henry VIII became king of England because his older brother Arthur died. From the accident of that death flowed all the coins, all the charters, all the other records, all the history books mentioning Henry VIII; all the different events of his reign, including the manner of separation of the Church of England from the Roman Catholic Church; and of course the whole succession of subsequent monarchs of England and of Great Britain, to say nothing of the antics of Charles and Diana. The accumulation of frozen accidents is what gives the world its effective complexity.

The most important idea here is that the frozen accidents of history have a nonlinear effect on everything that comes after. The complexity we see comes from simple rules and many, many “bounces” that could have gone in any direction. Once they go a certain way, there is no return.

This principle is illustrated wonderfully in the book The Origin of Wealth by Eric Beinhocker. The first example comes from 19th century history:

In the late 1800s, “Buffalo Bill” Cody created a show called Buffalo Bill’s Wild West Show, which toured the United States, putting on exhibitions of gun fighting, horsemanship, and other cowboy skills. One of the show’s most popular acts was a woman named Phoebe Moses, nicknamed Annie Oakley. Annie was reputed to have been able to shoot the head off of a running quail by age twelve, and in Buffalo Bill’s show, she put on a demonstration of marksmanship that included shooting flames off candles, and corks out of bottles. For her grand finale, Annie would announce that she would shoot the end off a lit cigarette held in a man’s mouth, and ask for a brave volunteer from the audience. Since no one was ever courageous enough to come forward, Annie hid her husband, Frank, in the audience. He would “volunteer,” and they would complete the trick together. In 1880, when the Wild West Show was touring Europe, a young crown prince (and later, kaiser), Wilhelm, was in the audience. When the grand finale came, much to Annie’s surprise, the macho crown prince stood up and volunteered. The future German kaiser strode into the ring, placed the cigarette in his mouth, and stood ready. Annie, who had been up late the night before in the local beer garden, was unnerved by this unexpected development. She lined the cigarette up in her sights, squeezed…and hit it right on the target.

Many people have speculated that if at that moment, there had been a slight tremor in Annie’s hand, then World War I might never have happened. If World War I had not happened, 8.5 million soldiers and 13 million civilian lives would have been saved. Furthermore, if Annie’s hand had trembled and World War I had not happened, Hitler would not have risen from the ashes of a defeated Germany, and Lenin would not have overthrown a demoralized Russian government. The entire course of twentieth-century history might have been changed by the merest quiver of a hand at a critical moment. Yet, at the time, there was no way anyone could have known the momentous nature of the event.

This isn’t to say that other big events, many bad, would not have precipitated in the 20th century. Almost certainly there would have been wars and upheavals.

But the actual course of history was in some part determined by small chance event which had no seeming importance when it happened. The impact of Wilhelm being alive rather than dead was totally non-linear. (A small non-event had a massively disproportionate effect on what happened later.)

This is why predicting the future, even with immense computing power, is an impossible task. The chaotic effects of randomness, with small inputs having disproportionate and massive effects, makes prediction a very difficult task. That’s why we must appreciate the role of randomness in the world and seek to protect against it.

Another great illustration from The Origin of Wealth is a famous story in the world of technology:

[In 1980] IBM approached a small company with forty employees in Bellevue, Washington. The company, called Microsoft, was run by a Harvard dropout named bill Gates and his friend Paul Allen. IBM wanted to talk to the small company about creating a version of the programming language BASIC for the new PC. At their meeting, IBM asked Gates for his advice on what operating systems (OS) the new machine should run. Gates suggested that IBM talk to Gary Kildall of Digital Research, whose CP/M operating system had become the standard in the hobbyist world of microcomputers. But Kildall was suspicious of the blue suits from IBM and when IBM tried to meet him, he went hot-air ballooning, leaving his wife and lawyer to talk to the bewildered executives, along with instructions not to sign even a confidentiality agreement. The frustrated IBM executives returned to Gates and asked if he would be interested in the OS project. Despite never having written an OS, Gates said yes. He then turned around and license a product appropriately named Quick and Dirty Operating System, or Q-DOS, from a small company called Seattle Computer Products for $50,000, modified it, and then relicensed it to IBM as PC-DOS. As IBM and Microsoft were going through the final language for the agreement, Gates asked for a small change. He wanted to retain the rights to sell his DOS on non-IBM machines in a version called MS-DOS. Gates was giving the company a good price, and IBM was more interested in PC hardware than software sales, so it agreed. The contract was signed on August 12, 1981. The rest, as they say, is history. Today, Microsoft is a company worth $270 billion while IBM is worth $140 billion.

At any point in that story, business history could have gone a much different way: Kildall could have avoided hot-air ballooning, IBM could have refused Gates’ offer, Microsoft could have not gotten the license for QDOS. Yet this little episode resulted in massive wealth for Gates and a long period of trouble for IBM.

Predicting the outcomes of a complex system must clear a pretty major hurdle: The prediction must be robust to non-linear “accidents” with a chain of unforeseen causation. In some situations this is doable: We can confidently rule out that Microsoft will not go broke in the next 12 months; the chain of events needed to take it under quickly is so low as to be negligible, no matter how you compute it. (Even IBM made it through the above scenario, although not unscathed.)

But as history rolls on and more “accidents” accumulate year by year, a “Fog of the Future” rolls in to obscure our view. In order to operate in such a world, we must learn that predicting is inferior to building systems that don’t require prediction, as Mother Nature does. And if we must predict, must confine our predictions to areas with few variables that lie in our circle of competence, and understand the consequences if we’re wrong.

If this topic is interesting to you, try exploring the rest of the Origin of Wealth, which discusses complexity in the economic realm in great (but readable) detail; also check out the rest of Murray Gell-Mann’s essay on Edge. Gell-Mann also wrote a book on the topic called The Quark and the Jaguar which is worth checking out. The best writer on randomness and robustness in the face of an uncertain future is of course Nassim Taleb, whom we have written about many times.

The Need for Biological Thinking to Solve Complex Problems

“Biological thinking and physics thinking are distinct, and often complementary, approaches to the world, and ones that are appropriate for different kinds of systems.”


How should we think about complexity? Should we use a biological or physics system? The answer, of course, is that it depends. It’s important to have both tools available at your disposal.

These are the questions that Samuel Arbesman explores in his fascinating book Overcomplicated: Technology at the Limits of Comprehension.

[B]iological systems are generally more complicated than those in physics. In physics, the components are often identical—think of a system of nothing but gas particles, for example, or a single monolithic material, like a diamond. Beyond that, the types of interactions can often be uniform throughout an entire system, such as satellites orbiting a planet.

Biology is different and there is something meaningful to be learned from a biological approach to thinking.

In biology, there are a huge number of types of components, such as the diversity of proteins in a cell or the distinct types of tissues within a single creature; when studying, say, the mating behavior of blue whales, marine biologists may have to consider everything from their DNA to the temperature of the oceans. Not only is each component in a biological system distinctive, but it is also a lot harder to disentangle from the whole. For example, you can look at the nucleus of an amoeba and try to understand it on its own, but you generally need the rest of the organism to have a sense of how the nucleus fits into the operation of the amoeba, how it provides the core genetic information involved in the many functions of the entire cell.

Arbesman makes an interesting point here when it comes to how we should look at technology. As the interconnections and complexity of technology increases, it increasingly resembles a biological system rather than a physics one. There is another difference.

[B]iological systems are distinct from many physical systems in that they have a history. Living things evolve over time. While the objects of physics clearly do not emerge from thin air—astrophysicists even talk about the evolution of stars—biological systems are especially subject to evolutionary pressures; in fact, that is one of their defining features. The complicated structures of biology have the forms they do because of these complex historical paths, ones that have been affected by numerous factors over huge amounts of time. And often, because of the complex forms of living things, where any small change can create unexpected effects, the changes that have happened over time have been through tinkering: modifying a system in small ways to adapt to a new environment.

Biological systems are generally hacks that evolved to be good enough for a certain environment. They are far from pretty top-down designed systems. And to accommodate an ever-changing environment they are rarely the most optimal system on a mico-level, preferring to optimize for survival over any one particular attribute. And it’s not the survival of the individual that’s optimized, it’s the survival of the species.

Technologies can appear robust until they are confronted with some minor disturbance, causing a catastrophe. The same thing can happen to living things. For example, humans can adapt incredibly well to a large array of environments, but a tiny change in a person’s genome can cause dwarfism, and two copies of that mutation invariably cause death. We are of a different scale and material from a particle accelerator or a computer network, and yet these systems have profound similarities in their complexity and fragility.

Biological thinking, with a focus on details and diversity, is a necessary tool to deal with complexity.

The way biologists, particularly field biologists, study the massively complex diversity of organisms, taking into account their evolutionary trajectories, is therefore particularly appropriate for understanding our technologies. Field biologists often act as naturalists— collecting, recording, and cataloging what they find around them—but even more than that, when confronted with an enormously complex ecosystem, they don’t immediately try to understand it all in its totality. Instead, they recognize that they can study only a tiny part of such a system at a time, even if imperfectly. They’ll look at the interactions of a handful of species, for example, rather than examine the complete web of species within a single region. Field biologists are supremely aware of the assumptions they are making, and know they are looking at only a sliver of the complexity around them at any one moment.


When we’re dealing with different interacting levels of a system, seemingly minor details can rise to the top and become important to the system as a whole. We need “Field biologists” to catalog and study details and portions of our complex systems, including their failures and bugs. This kind of biological thinking not only leads to new insights, but might also be the primary way forward in a world of increasingly interconnected and incomprehensible technologies.

Waiting and observing isn’t enough.

Biologists will often be proactive, and inject the unexpected into a system to see how it reacts. For example, when biologists are trying to grow a specific type of bacteria, such as a variant that might produce a particular chemical, they will resort to a process known as mutagenesis. Mutagenesis is what it sounds like: actively trying to generate mutations, for example by irradiating the organisms or exposing them to toxic chemicals.

When systems are too complex for human understanding, often we need to insert randomness to discover the tolerances and limits of the system. One plus one doesn’t always equal two when you’re dealing with non-linear systems. For biologists, tinkering is the way to go.

As Stewart Brand noted about legacy systems, “Teasing a new function out of a legacy system is not done by command but by conducting a series of cautious experiments that with luck might converge toward the desired outcome.”

When Physics and Biology Meet

This doesn’t mean we should abandon the physics approach, searching for underlying regularities in complexity. The two systems complement one another rather than compete.

Arbesman recommends asking the following questions:

When attempting to understand a complex system, we must determine the proper resolution, or level of detail, at which to look at it. How fine-grained a level of detail are we focusing on? Do we focus on the individual enzyme molecules in a cell of a large organism, or do we focus on the organs and blood vessels? Do we focus on the binary signals winding their way through circuitry, or do we examine the overall shape and function of a computer program? At a larger scale, do we look at the general properties of a computer network, and ignore the individual machines and decisions that make up this structure?

When we need to abstract away a lot of the details we lean on physics thinking more. Think about it from an organizational perspective. The new employee at the lowest level is focused on the specific details of their job whereas the executive is focused on systems, strategy, culture, and flow — how things interact and reinforce one another. The details of the new employee’s job are lost on them.

We can’t use one system, whether biological or physics, exclusively. That’s a sure way to fragile thinking. Rather, we need to combine them.

In Cryptonomicon, a novel by Neal Stephenson, he makes exactly this point talking about the structure of the pantheon of Greek gods:

And yet there is something about the motley asymmetry of this pantheon that makes it more credible. Like the Periodic Table of the Elements or the family tree of the elementary particles, or just about any anatomical structure that you might pull up out of a cadaver, it has enough of a pattern to give our minds something to work on and yet an irregularity that indicates some kind of organic provenance—you have a sun god and a moon goddess, for example, which is all clean and symmetrical, and yet over here is Hera, who has no role whatsoever except to be a literal bitch goddess, and then there is Dionysus who isn’t even fully a god—he’s half human—but gets to be in the Pantheon anyway and sit on Olympus with the Gods, as if you went to the Supreme Court and found Bozo the Clown planted among the justices.

There is a balance and we need to find it.