Tag: Peter Thiel

Power Laws: How Nonlinear Relationships Amplify Results

“The greatest shortcoming of the human race is our inability to understand the exponential function.”

— Albert Allen Bartlett

Defining A Power Law

Consider a person who begins weightlifting for the first time.

During their initial sessions, they can lift only a small amount of weight. But as they invest more time, they find that for each training session, their strength increases a surprising amount.

For a while, they make huge improvements. Eventually, however, their progress slows down. At first, they could increase their strength by as much as 10% per session; now it takes months to improve by even 1%. Perhaps they resort to taking performance-enhancing drugs or training more often. Their motivation is sapped and they find themselves getting injured, without any real change in the amount of weight they can lift.

Now, let’s imagine that our frustrated weightlifter decides to take up running instead. Something similar happens. While the first few runs are incredibly difficult, the person’s endurance increases rapidly with the passing of each week, until it levels off and diminishing returns set in again.

Both of these situations are examples of power laws — a relationship between two things in which a change in one thing can lead to a large change in the other, regardless of the initial quantities. In both of our examples, a small investment of time in the beginning of the endeavor leads to a large increase in performance.

Power laws are interesting because they reveal surprising correlations between disparate factors. As a mental model, power laws are versatile, with numerous applications in different fields of knowledge.

If parts of this post look intimidating to non-mathematicians, bear with us. Understanding the math behind power laws is worthwhile in order to grasp their many applications. Invest a little time in reading this and reap the value — which is in itself an example of a power law!

A power law is often represented by an equation with an exponent:


Each letter represents a number. Y is a function (the result); X is the variable (the thing you can change); B is the order of scaling (the exponent); and M is a constant (unchanging).

If M is equal to 1, the equation is then Y=X^B. If B=2, the equation becomes Y=X^2 (Y=X squared). If X is 1, Y is also 1. But if X=2, then Y=4; if X=3, then Y=9, and so on. A small change in the value of X leads to a proportionally large change in the value of Y.

B=1 is known as the linear scaling law.

To double a cake recipe, you need twice as much flour. To drive twice as far will take twice as long. (Unless you have kids, in which case you need to factor in bathroom breaks that seemingly have little to do with distance.) Linear relationships, in which twice-as-big requires twice-as-much, are simple and intuitive.

Nonlinear relationships are more complicated. In these cases, you don’t need twice as much of the original value to get twice the increase in some measurable characteristic. For example, an animal that’s twice our size requires only about 75% more food than we do. This means that on a per-unit-of-size basis, larger animals are more energy efficient than smaller ones. As animals get bigger, the energy required to support each unit decreases.

One of the characteristics of a complex system is that the behavior of the system differs from the simple addition of its parts. This characteristic is called emergent behavior. “In many instances,” write Geoffrey West in Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies, “the whole seems to take on a life of its own, almost dissociated from the specific characteristics of its individual building blocks.”

This collective outcome, in which a system manifests significantly different characteristics from those resulting from simply adding up all of the contributions of its individual constituent parts, is called an emergent behavior.

When we set out to understand a complex system, our intuition tells us to break it down into its component pieces. But that’s linear thinking, and it explains why so much of our thinking about complexity falls short. Small changes in a complex system can cause sudden and large changes. Small changes cause cascades among the connected parts, like knocking over the first domino in a long row.

Let’s return to the example of our hypothetical weightlifter-turned-runner. As they put in more time on the road, constraints will naturally arise on their progress.

Recall our exponential equation: Y=MX^B. Try applying it to the runner. (We’re going to simplify running, but stick with it.)

Y is the distance the runner can run before becoming exhausted. That’s what we’re trying to calculate. M, the constant, represents their running ability: some combination of their natural endowment and their training history. (Think of it this way: Olympic champion Usain Bolt has a high M; film director Woody Allen has a low M.)

That leaves us with the final term: X^B. The variable X represents the thing we have control over: in this case, our training mileage. If B, the exponent, is between 0 and 1, then the relationship between X and Y— between training mileage and endurance — becomes progressively less proportional. All it takes is plugging in a few numbers to see the effect.

Let’s set M to 1 for the sake of simplicity. If B=0.5 and X=4, then Y=2. Four miles on the road gives the athlete the ability to run two miles at a clip.

Increase X to 16, and Y increases only to 4. The runner has to put in four times the road mileage to merely double their running endurance.

Here’s the kicker: With both running and weightlifting, as we increase X, we’re likely to see the exponent, B, decline! Quadrupling our training mileage from 16 to 64 miles is unlikely to double our endurance again. It might take a 10x increase in mileage to do that. Eventually, the ratio of training mileage to endurance will become nearly infinite.

We know this state, of course, as diminishing returns: the point where more input yields progressively less output. Not only is the relationship between training mileage and endurance not linear to begin with, but it also gets less linear as we increase our training.

And what about negative exponents?

It gets even more interesting. If B=−0.5 and X=4, then Y=0.5. Four miles on the road gets us a half-mile of endurance. If X is increased to 16, Y declines to 0.25. More training, less endurance! This is akin to someone putting in way too much mileage, way too soon: the training is less than useful as injuries pile up.

With negative numbers, the more X increases, the more Y shrinks. This relationship is known as an inverse power law. B=−2, for example, is known as the inverse square law and is an important equation in physics.

The relationship between gravity and distance follows an inverse power law. G is the gravitational constant; it’s the constant in Newton's law of gravitation, relating gravity to the masses and separation of particles, equal to:

6.67 × 10−11 N m2 kg−2

Any force radiating from a single point — including heat, light intensity, and magnetic and electrical forces — follows the inverse square law. At 1m away from a fire, 4 times as much heat is felt as at 2m, and so on.

Higher Order Power Laws

When B is a positive integer (a whole number larger than zero), there are names for the power laws.

When B is equal to 1, we have a linear relationship, as we discussed above. This is also known as a first-order power law.

Things really get interesting after that.

When B is 2, we have a second-order power law. A great example of this is kinetic energy. Kinetic energy = 1/2 mv^2

When B is 3, we have a third-order power law. An example of this is the power converted from wind into rotational energy.

Power Available = ½ (Air Density)( πr^2)(Windspeed^3)(Power Coefficient)

(There is a natural limit here. Albert Betz concluded in 1919 that wind turbines cannot convert more than 59.3% of the kinetic energy of the wind into mechanical energy. This number is called the Betz Limit and represents the power coefficient above.)[1]

The law of heat radiation is a fourth-order power law. Derived first by the Austrian physicist Josef Stefan in 1879 and separately by Austrian physicist Ludwig Boltzmann, the law works like this: the radiant heat energy emitted from a unit area in one second is equal to the constant of proportionality (the Stefan-Boltzmann constant) times the absolute temperature to the fourth power.[2]

There is only one power law with a variable exponent, and it’s considered to be one of the most powerful forces in the universe. It’s also the most misunderstood. We call it compounding. The formula looks like this:

Future Value = (Present Value)(1+i)^n

where i is the interest rate and n is the number of years.

Unlike in the other equations, the relationship between X and Y is potentially limitless. As long as B is positive, Y will increase as X does.

Non-integer power laws (where B is a fraction, as with our running example above) are also of great use to physicists. Formulas in which B=0.5 are common.

Imagine a car driving at a certain speed. A non-integer power law applies. V is the speed of the car, P is the petrol burnt per second to reach that speed, and A is the air resistance. For the car to go twice as fast, it must use 4 times as much petrol, and to go 3 times as fast, it must use 9 times as much petrol. Air resistance increases as speed increases, and that is why faster cars use such ridiculous amounts of petrol. It might seem logical to think that a car going from 40 miles an hour to 50 miles an hour would use a quarter more fuel. That is incorrect, though, because the relationship between air resistance and speed is itself a power law.

Another instance of a power law is the area of a square. Double the length of two parallel sides and the area quadruples. Do the same for a 3D cube and the area increases by a factor of eight. It doesn’t matter if the length of the square went from 1cm to 2cm, or from 100m to 200m; the area still quadruples. We are all familiar with second-order (or square) power laws. This name comes from squares, since the relationship between length and area reflect the way second-order power laws change a number. Third-order (or cubic) power laws are likewise named due to their relationship to cubes.

Using Power Laws in Our Lives

Now that we’ve gotten through the complicated part, let’s take a look at how power laws crop up in many fields of knowledge. Most careers involve an understanding of them, even if it might not be so obvious.

“What's the most powerful force in the universe? Compound interest. It builds on itself. Over time, a small amount of money becomes a large amount of money. Persistence is similar. A little bit improves performance, which encourages greater persistence which improves persistence even more. And on and on it goes.”

— Daniel H. Pink, The Adventures of Johnny Bunko

The Power Behind Compounding

Compounding is one of our most important mental models and is absolutely vital to understand for investing, personal development, learning, and other crucial areas of life.

In economics, we calculate compound interest by using an equation with these variables: P is the original sum of money. P’ is the resulting sum of money, r is the annual interest rate, n is the compounding frequency, and t is the length of time. Using an equation, we can illustrate the power of compounding.

If a person deposits $1000 in a bank for five years, at a quarterly interest rate of 4%, the equation becomes this:

Future Value = Present Value * ((1 + Quarterly Interest Rate) ^ Number of Quarters)

This formula can be used to calculate how much money will be in the account after five years. The answer is $2,220.20.

Compound interest is a power law because the relationship between the amount of time a sum of money is left in an account and the amount accumulated at the end is non-linear.

In A Random Walk Down Wall Street, Burton Malkiel gives the example of two brothers, William and James. Beginning at age 20 and stopping at age 40, William invests $4,000 per year. Meanwhile, James invests the same amount per year between the ages of 40 and 65. By the time William is 65, he has invested less money than his brother, but has allowed it to compound for 25 years. As a result, when both brothers retire, William has 600% more money than James — a gap of $2 million. One of the smartest financial choices we can make is to start saving as early as possible: by harnessing power laws, we increase the exponent as much as possible.

Compound interest can help us achieve financial freedom and wealth, without the need for a large annual income. Members of the financial independence movement (such as the blogger Mr. Money Mustache) are living examples of how we can apply power laws to our lives.

As far back as the 1800s, Robert G. Ingersoll emphasized the importance of compound interest:

One dollar at compound interest, at twenty-four per cent., for one hundred years, would produce a sum equal to our national debt. Interest eats night and day, and the more it eats the hungrier it grows. The farmer in debt, lying awake at night, can, if he listens, hear it gnaw. If he owes nothing, he can hear his corn grow. Get out of debt as soon as possible. You have supported idle avarice and lazy economy long enough.

Compounding can apply to areas beyond finance — personal development, health, learning, relationships and more. For each area, a small input can lead to a large output, and the results build upon themselves.

Nonlinear Language Learning

When we learn a new language, it’s always a good idea to start by learning the 100 or so most used words.

In all known languages, a small percentage of words make up the majority of usage. This is known as Zipf’s law, after George Kingsley Zipf, who first identified the phenomenon. The most used word in a language may make up as much as 7% of all words used, while the second-most-used word is used half as much, and so on. As few as 135 words can together form half of a language (as used by native speakers).

Why Zipf’s law holds true is unknown, although the concept is logical. Many languages include a large number of specialist terms that are rarely needed (including legal or anatomy terms). A small change in the frequency ranking of a word means a huge change in its usefulness.

Understanding Zipf’s law is a central component of accelerated language learning. Each new word we learn from the most common 100 words will have a huge impact on our ability to communicate. As we learn less-common words, diminishing returns set in. If each word in a language were listed in order of frequency of usage, the further we moved down the list, the less useful a word would be.

Power Laws in Business, Explained by Peter Thiel

Peter Thiel, the founder of PayPal (as well as an early investor in Facebook and Palantir), considers power laws to be a crucial concept for all businesspeople to understand. In his fantastic book, Zero to One, Thiel writes:

Indeed, the single most powerful pattern I have noticed is that successful people find value in unexpected places, and they do this by thinking about business from first principles instead of formulas.


In 1906, economist Vilfredo Pareto discovered what became the “Pareto Principle,” or the 80-20 rule, when he noticed that 20% of the people owned 80% of the land in Italy—a phenomenon that he found just as natural as the fact that 20% of the peapods in his garden produced 80% of the peas. This extraordinarily stark pattern, when a small few radically outstrip all rivals, surrounds us everywhere in the natural and social world. The most destructive earthquakes are many times more powerful than all smaller earthquakes combined. The biggest cities dwarf all mere towns put together. And monopoly businesses capture more value than millions of undifferentiated competitors. Whatever Einstein did or didn’t say, the power law—so named because exponential equations describe severely unequal distributions—is the law of the universe. It defines our surroundings so completely that we usually don’t even see it.

… [I]n venture capital, where investors try to profit from exponential growth in early-stage companies, a few companies attain exponentially greater value than all others. … [W]e don’t live in a normal world; we live under a power law.

The biggest secret in venture capital is that the best investment in a successful fund equals or outperforms the entire rest of the fund combined.

This implies two very strange rules for VCs. First, only invest in companies that have the potential to return the value of the entire fund. … This leads to rule number two: because rule number one is so restrictive, there can’t be any other rules.

…[L]ife is not a portfolio: not for a startup founder, and not for any individual. An entrepreneur cannot “diversify” herself; you cannot run dozens of companies at the same time and then hope that one of them works out well. Less obvious but just as important, an individual cannot diversify his own life by keeping dozens of equally possible careers in ready reserve.

Thiel teaches a class called Startup at Stanford, where he hammers home the value of understanding power laws. In his class, he imparts copious wisdom. From Blake Masters’ notes on Class 7:

Consider a prototypical successful venture fund. A number of investments go to zero over a period of time. Those tend to happen earlier rather than later. The investments that succeed do so on some sort of exponential curve. Sum it over the life of a portfolio and you get a J curve. Early investments fail. You have to pay management fees. But then the exponential growth takes place, at least in theory. Since you start out underwater, the big question is when you make it above the water line. A lot of funds never get there.

To answer that big question you have to ask another: what does the distribution of returns in [a] venture fund look like? The naïve response is just to rank companies from best to worst according to their return in multiple of dollars invested. People tend to group investments into three buckets. The bad companies go to zero. The mediocre ones do maybe 1x, so you don’t lose much or gain much. And then the great companies do maybe 3-10x.

But that model misses the key insight that actual returns are incredibly skewed. The more a VC understands this skew pattern, the better the VC. Bad VCs tend to think the dashed line is flat, i.e. that all companies are created equal, and some just fail, spin wheels, or grow. In reality you get a power law distribution.

Thiel explains how investors can apply the mental model of power laws (more from Masters’ notes on Class 7):

…Given a big power law distribution, you want to be fairly concentrated. … There just aren’t that many businesses that you can have the requisite high degree of conviction about. A better model is to invest in maybe 7 or 8 promising companies from which you think you can get a 10x return. …

Despite being rooted in middle school math, exponential thinking is hard. We live in a world where we normally don’t experience anything exponentially. Our general life experience is pretty linear. We vastly underestimate exponential things.

He also cautions against over-relying on power laws as a strategy (an assertion that should be kept in mind for all mental models). From Masters’ notes:

One shouldn’t be mechanical about this heuristic, or treat it as some immutable investment strategy. But it actually checks out pretty well, so at the very least it compels you to think about power law distribution.

Understanding exponents and power law distributions isn’t just about understanding VC. There are important personal applications too. Many things, such as key life decisions or starting businesses, also result in similar distributions.

Thiel then explains why founders should focus on one key revenue stream, rather than trying to build multiple equal ones:

Even within an individual business, there is probably a sort of power law as to what’s going to drive it. It’s troubling if a startup insists that it’s going to make money in many different ways. The power law distribution on revenues says that one source of revenue will dominate everything else.

For example, if you’re an entrepreneur who opens a coffee shop, you’ll have a lot of ways you can make money. You can sell coffee, cakes, paintings, merchandise, and more. But each of those things will not contribute to your success in an equal way. While there is value in the discovery process, once you’ve found the variable that matters most, you should place more time on that one and less on the others. The importance of finding this variable cannot be overstated.

He also acknowledges that power laws are one of the great secrets of investing success. From Masters’ notes on Class 11:

On one level, the anti-competition, power law, and distribution secrets are all secrets about nature. But they’re also secrets hidden by people. That is crucial to remember. Suppose you’re doing an experiment in a lab. You’re trying to figure out a natural secret. But every night another person comes into the lab and messes with your results. You won’t understand what’s going on if you confine your thinking to the nature side of things. It’s not enough to find an interesting experiment and try to do it. You have to understand the human piece too.

… We know that, per the power law secret, companies are not evenly distributed. The distribution tends to be bimodal; there are some great ones, and then there are a lot of ones that don’t really work at all. But understanding this isn’t enough. There is a big difference between understanding the power law secret in theory and being able to apply it in practice.

The key to all mental models is knowing the facts and being able to use the concept. As George Box said, “all models are false but some are useful.” Once we grasp the basics, the best next step is to start figuring out how to apply it.

The metaphor of an unseen person sabotaging laboratory results is an excellent metaphor for how cognitive biases and shortcuts cloud our judgement.

Natural Power Laws

Anyone who has kept a lot of pets will have noticed the link between an animal’s size and its lifespan. Small animals, like mice and hamsters, tend to live for a year or two. Larger ones, like dogs and cats, can live to 10-20 years, or even older in rare cases. Scaling up even more, some whales can live for 200 years. This comes down to power laws.

Biologists have found clear links between an animal’s size and its metabolism. Kleiber’s law (identified by Max Kleiber) states that an animal’s metabolic rate increases at three-fourths of the power of the animal’s weight (mass). If an average rabbit (2 kg) weighs one hundred times as much as an average mouse (20g), the rabbit’s metabolic rate will be 32 times the mouse’s. In other words, the rabbit’s structure is more efficient. It all comes down to the geometry behind their mass.

Which leads us to another biological power law: Smaller animals require more energy per gram of body weight, meaning that mice eat around half their body weight in dense foods each day. The reason is that, in terms of percentage of mass, larger animals have more structure (bones, etc.) and fewer reserves (fat stores).

Research has illustrated how power laws apply to blood circulation in animals. The end units through which oxygen, water, and nutrients enter cells from the bloodstream are the same size in all animals. Only the number per animal varies. The relationship between the total area of these units and the size of the animal is a third-order power law. The distance blood travels to enter cells and the actual volume of blood are also subject to power laws.

The Law of Diminishing Returns

As we have seen, a small change in one area can lead to a huge change in another. However, past a certain point, diminishing returns set in and more is worse. Working an hour extra per day might mean more gets done, whereas working three extra hours is likely to lead to less getting done due to exhaustion. Going from a sedentary lifestyle to running two days a week may result in greatly improved health, but stepping up to seven days a week will cause injuries. Overzealousness can turn a positive exponent into a negative exponent. For a busy restaurant, hiring an extra chef will mean that more people can be served, but hiring two new chefs might spoil the proverbial broth.

Perhaps the most underappreciated diminishing return, the one we never want to end up on the wrong side of, is the one between money and happiness.

In David and Goliath, Malcolm Gladwell discusses how diminishing returns relate to family incomes. Most people assume that the more money they make, the happier they and their families will be. This is true — up to a point. An income that’s too low to meet basic needs makes people miserable, leading to far more physical and mental health problems. A person who goes from earning $30,000 a year to earning $40,000 is likely to experience a dramatic boost in happiness. However, going from $100,000 to $110,000 leads to a negligible change in well-being.

Gladwell writes:

The scholars who research happiness suggest that more money stops making people happier at a family income of around seventy-five thousand dollars a year. After that, what economists call “diminishing marginal returns” sets in. If your family makes seventy-five thousand and your neighbor makes a hundred thousand, that extra twenty-five thousand a year means that your neighbor can drive a nicer car and go out to eat slightly more often. But it doesn’t make your neighbor happier than you, or better equipped to do the thousands of small and large things that make for being a good parent.

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A Primer on Critical Mass: Identifying Inflection Points

The Basics

Sometimes it can seem as if drastic changes happen at random.

One moment a country is stable; the next, a revolution begins and the government is overthrown. One day a new piece of technology is a novelty; the next, everyone has it and we cannot imagine life without it. Or an idea lingers at the fringes of society before it suddenly becomes mainstream.

As erratic and unpredictable as these occurrences are, there is a logic to them, which can be explained by the concept of critical mass. A collaboration between Thomas Schelling (a game theorist) and Mark Granovetter (a sociologist) led to the concept's being identified in 1971.

Also known as the boiling point, the percolation threshold, the tipping point, and a host of other names, critical mass is the point at which something (an idea, belief, trend, virus, behavior, etc.) is prevalent enough to grow, or sustain, a process, reaction, or technology.

As a mental model, critical mass can help us to understand the world around us by letting us spot changes before they occur, make sense of tumultuous times, and even gain insight into our own behaviors. A firm understanding can also give us an edge in launching products, changing habits, and choosing investments.

In The Decision Book, Mikael Krogerus wrote of technological critical masses:

Why is it that some ideas – including stupid ones – take hold and become trends, while others bloom briefly before withering and disappearing from the public eye?

… Translated into a graph, this development takes the form of a curve typical of the progress of an epidemic. It rises, gradually at first, then reaches the critical point of any newly launched product, when many products fail. The critical point for any innovation is the transition from the early adapters to the sceptics, for at this point there is a ‘chasm'. …

With technological innovations like the iPod or the iPhone, the cycle described above is very short. Interestingly, the early adaptors turn away from the product as soon as the critical masses have accepted it, in search of the next new thing.

In Developmental Evaluation, Michael Quinn Patton wrote:

Complexity theory shows that great changes can emerge from small actions. Change involves a belief in the possible, even the “impossible.” Moreover, social innovators don't follow a linear pathway of change; there are ups and downs, roller-coaster rides along cascades of dynamic interactions, unexpected and unanticipated divergences, tipping points and critical mass momentum shifts. Indeed, things often get worse before they get better as systems change creates resistance to and pushback against the new.

In If Nobody Speaks of Remarkable Things, Jon McGregor writes a beautiful explanation of how the concept of critical mass applies to weather:

He wonders how so much water can resist the pull of so much gravity for the time it takes such pregnant clouds to form, he wonders about the moment the rain begins, the turn from forming to falling, that slight silent pause in the physics of the sky as the critical mass is reached, the hesitation before the first swollen drop hurtles fatly and effortlessly to the ground.

Critical Mass in Physics

In nuclear physics, critical mass is defined as the minimum amount of a fissile material required to create a self-sustaining fission reaction. In simpler terms, it's the amount of reactant necessary for something to happen and to keep happening.

This concept is similar to the mental model of activation energy. The exact critical mass depends on the nuclear properties of a material, its density, its shape, and other factors.

In some nuclear reactions, a reflector made of beryllium is used to speed up the process of reaching critical mass. If the amount of fissile material is inadequate, it is referred to as a subcritical mass. Once the rate of reaction is increasing, the amount of material is referred to as a supercritical mass. This concept has been taken from physics and used in many other disciplines.

Critical Mass in Sociology

In sociology, a critical mass is a term for a group of people who make a drastic change, altering their behavior, opinions or actions.

“When enough people (a critical mass) think about and truly consider the plausibility of a concept, it becomes reality.”

—Joseph Duda

In some societies (e.g., a small Amazonian tribe), just a handful of people can change prevailing views. In larger societies (in particular, those which have a great deal of control over people, such as North Korea), the figure must usually be higher for a change to occur.

The concept of a sociological critical mass was first used in the 1960s by Morton Grodzins, a political science professor at the University of Chicago. Grodzins studied racial segregation — in particular, examining why people seemed to separate themselves by race even when that separation was not enforced by law. His hypothesis was that white families had different levels of tolerance for the number of people of racial minorities in their neighborhoods. Some white families were completely racist; others were not concerned with the race of their neighbors. As increasing numbers of racial minorities moved into neighborhoods, the most racist people would soon leave. Then a tipping point would occur — a critical mass of white people would leave until the area was populated by racial minorities. This phenomenon became known as “white flight.”

Critical Mass in Business

In business, at a macro level, critical mass can be defined as the time when a company becomes self-sustaining and is economically viable. (Please note that there is a difference between being economically viable and being profitable.) Just as a nuclear reaction reaches critical mass when it can sustain itself, so must a business. It is important, too, that a business chooses its methods for growth with care: sometimes adding more staff, locations, equipment, stock, or other assets can be the right choice; at other times, these additions can lead to negative cash flow.

The exact threshold and time to reach critical mass varies widely, depending on the industry, competition, startup costs, products, and other economic factors.

Bob Brinker, host of Money Talk, defines critical mass in business as:

A state of freedom from worry and anxiety about money due to the accumulation of assets which make it possible to live your life as you choose without working if you prefer not to work or just working because you enjoy your work but don't need the income. Plainly stated, the Land of Critical Mass is a place in which individuals enjoy their own personal financial nirvana. Differentiation between earned income and assets is a fundamental lesson to learn when thinking in terms of critical mass. Earned income does not produce critical mass … critical mass is strictly a function of assets.

Independence or “F*** You” Money

Most people work jobs and get paychecks. If you depend on a paycheck, like most of us, this means you are not independent — you are not self-sustaining. Once you have enough money, you can be self-sustaining.

If you were wealthy enough to be free, would you really keep the job you have now? How many of us check our opinions or thoughts before voicing them because we know they won't be acceptable? How many times have you agreed to work on a project that you know is doomed, because you need the paycheck?

“Whose bread I eat: his song I sing.”


In his book The Black Swan, Nassim Taleb describes “f*** you” money, which, “in spite of its coarseness, means that it allows you to act like a Victorian gentleman, free from slavery”:

It is a psychological buffer: the capital is not so large as to make you spoiled-rich, but large enough to give you the freedom to choose a new occupation without excessive consideration of the financial rewards. It shields you from prostituting your mind and frees you from outside authority — any outside authority. … Note that the designation f*** you corresponds to the exhilarating ability to pronounce that compact phrase before hanging up the phone.

Critical Mass in Psychology

Psychologists have known for a long time that groups of people behave differently than individuals.

Sometimes when we are in a group, we tend to be less inhibited, more rebellious, and more confident. This effect is known as mob behaviour. (An interesting detail is that mob psychology is one of the few branches of psychology which does not concern individuals.) As a general rule, the larger the crowd, the less responsibility people have for their behaviour. (This is also why individuals and not groups should make decisions.)

“[Groups of people] can be considered to possess agential capabilities: to think, judge, decide, act, reform; to conceptualize self and others as well as self's actions and interactions; and to reflect.”

—Burns and Engdahl

Gustav Le Bon is one psychologist who looked at the formation of critical masses of people necessary to spark change. According to Le Bon, this formation creates a collective unconsciousness, making people “a grain of sand amid other grains of sand which the wind stirs up at will.”

He identified three key processes which create a critical mass of people: anonymity, contagion, and suggestibility. When all three are present, a group loses their sense of self-restraint and behaves in a manner he considered to be more primitive than usual. The strongest members (often those who first convinced others to adopt their ideas) have power over others.

Examples of Critical Mass


Viral media include forms of content (such as text, images, and videos) which are passed amongst people and often modified along the way. We are all familiar with how memes, videos and jokes spread on social media. The term “virality” comes from the similarity to how viruses propagate.

“We are all susceptible to the pull of viral ideas. Like mass hysteria. Or a tune that gets into your head that you keep on humming all day until you spread it to someone else. Jokes. Urban legends. Crackpot religions. No matter how smart we get, there is always this deep irrational part that makes us potential hosts for self-replicating information.”

—Neal Stephenson, Snow Crash

In The Selfish Gene, Richard Dawkins compared memes to human genes. While the term “meme” is now, for the most part, used to describe content that is shared on social media, Dawkins described religion and other cultural objects as memes.

The difference between viral and mainstream media is that the former is more interactive and is shaped by the people who consume it. Gatekeeping and censorship are also less prevalent. Viral content often reflects dominant values and interests, such as kindness (for example, the dancing-man video) and humor. The importance of this form of media is apparent when it is used to negatively impact corporations or powerful individuals (such as the recent United Airlines and Pepsi fiascoes.)

Once a critical mass of people share and comment on a piece of content online, it reaches viral status. Its popularity then grows exponentially before it fades away a short time later.


The concept of critical mass is crucial when it comes to the adoption of new technology. Every piece of technology which is now (or once was) a ubiquitous part of our lives was once new and novel.

Most forms of technology become more useful as more people adopt them. There is no point in having a telephone if it cannot be used to call other people. There is no point in having an email account if it cannot be used to email other people.

The value of networked technology increases as the size of the network itself does. Eventually, the number of users reaches critical mass, and not owning that particular technology becomes a hindrance. Useful technology tends to lead the first adopters to persuade those around them to try it, too. As a general rule, the more a new technology depends upon a network of users, the faster it will reach critical mass. This situation creates a positive feedback loop.

In Zero to One, Peter Thiel describes how PayPal achieved the critical mass of users needed for it to be useful:

For PayPal to work, we needed to attract a critical mass of at least a million users. Advertising was too ineffective to justify the cost. Prospective deals with big banks kept falling through. So we decided to pay people to sign up.

We gave new customers $10 for joining, and we gave them $10 more every time they referred a friend. This got us hundreds of thousands of new customers and an exponential growth rate.

Another illustration of the importance of critical mass for technology (and the unique benefits of crowdfunding) comes from Chris LoPresti:

A friend of mine raised a lot of money to launch a mobile app; however, his app was trounced by one from another company that had raised a tenth of what he had, but had done so through 1,000 angels on Kickstarter. Those thousand angels became the customers and evangelists that provided the all-important critical mass early on. Any future project I do, I’ll do through Kickstarter, even if I don’t need the money.

Urban Legends

Urban legends are an omnipresent part of society, a modern evolution of traditional folklore. They tend to involve references to deep human fears and popular culture. Whereas traditional folklore was often full of fantastical elements, modern urban legends are usually a twist on reality. They are intended to be believed and passed on. Sociologists refer to them as “contemporary legends.” Some can survive for decades, being modified as time goes by and spreading to different areas and groups. Researchers who study urban legends have noted that many do have vague roots in actual events, and are just more sensationalized than the reality.

One classic urban legend is “The Hook.” This story has two key elements: a young couple parked in a secluded area and a killer with a hook for a hand. The radio in their car announces a serial killer on the loose, often escaped from a nearby institution, with a hook for a hand. In most versions, the couple panics and drives off, only to later find a hook hanging from the car door handle. In others, the man leaves the car while the woman listens to the radio bulletin. She keeps hearing a thumping sound on the roof of the car. When she exits to investigate, the killer is sitting on the roof, holding the man’s severed head. The origins of this story are unknown, although it first emerged in the 1950s in America. By 1960, it began to appear in publications.

Urban legends are an example of how a critical mass of people must be reached before an idea can spread. While the exact origins are rarely clear, it is assumed that it begins with a single person who misunderstands a news story or invents one and passes it on to others, perhaps at a party.

Many urban legends have a cautionary element, so they may first be told in an attempt to protect someone. “The Hook” has been interpreted as a warning to teenagers engaging in promiscuous behaviour. When this story is looked at by Freudian folklorists, the implications seem obvious. It could even have been told by parents to their children.

This cautionary element is clear in one of the first printed versions of “The Hook” in 1960:

If you are interested in teenagers, you will print this story. I do not know whether it's true or not, but it does not matter because it served its purpose for me… I do not think I will ever park to make out as long as I live. I hope this does the same for other kids.

Once a critical mass of people know an urban legend, the rate at which it spreads grows exponentially. The internet now enables urban legends (and everything else) to pass between people faster. Although a legend might also be disproved faster, that's a complicated mess. For now, as Lefty says in Donnie Brasco, “Forget about it.”

The more people who believe a story, the more believable it seems. This effect is exacerbated when media outlets or local police fall for the legends and issue warnings. Urban legends often then appear in popular culture (for example, “The Hook” inspired a Supernatural episode) and become part of our modern culture. The majority of people stop believing them, yet the stories linger in different forms.

Changes in Governments and Revolutions

“There are moments when masses establish contact with their nation's spirit. These are the moments of providence. Masses then see their nation in its entire history, and feel its moments of glory, as well as those of defeat. Then they can clearly feel turbulent events in the future. That contact with the immortal and collective nation's spirit is feverish and trembling. When that happens, people cry. It is probably some kind of national mystery, which some criticize, because they do not know what it represents, and others struggle to define it, because they have never felt it.”
―Corneliu Zelea Codreanu, For My Legionaries


From a distance, it can seem shocking when the people of a country revolt and overthrow dominant powers in a short time.

What is it that makes this sudden change happen? The answer is the formation of a critical mass of people necessary to move marginal ideas to a majority consensus. Pyotr Kropotkin wrote:

Finally, our studies of the preparatory stages of all revolutions bring us to the conclusion that not a single revolution has originated in parliaments or in any other representative assembly. All began with the people. And no revolution has appeared in full armor — born, like Minerva out of the head of Jupiter, in a day. They all had their periods of incubation during which the masses were very slowly becoming imbued with the revolutionary spirit, grew bolder, commenced to hope, and step by step emerged from their former indifference and resignation. And the awakening of the revolutionary spirit always took place in such a manner that at first, single individuals, deeply moved by the existing state of things, protested against it, one by one. Many perished, “uselessly,” the armchair critic would say. But the indifference of society was shaken by these progenitors. The dullest and most narrow-minded people were compelled to reflect, “Why should men, young, sincere, and full of strength, sacrifice their lives in this way?” It was impossible to remain indifferent; it was necessary to take a stand, for, or against: thought was awakening. Then, little by little, small groups came to be imbued with the same spirit of revolt; they also rebelled — sometimes in the hope of local success — in strikes or in small revolts against some official whom they disliked, or in order to get food for their hungry children, but frequently also without any hope of success: simply because the conditions grew unbearable. Not one, or two, or tens, but hundreds of similar revolts have preceded and must precede every revolution.

When an oppressive regime is in power, a change is inevitable. However, it is almost impossible to predict when that change will occur. Often, a large number of people want change and yet fear the consequences or lack the information necessary to join forces. When single individuals act upon their feelings, they are likely to be punished without having any real impact. Only when a critical mass of people’s desire for change overwhelms their fear can a revolution occur. Other people are encouraged by the first group, and the idea spreads rapidly.

One example occurred in China in 1989. While the desire for change was almost universal, the consequences felt too dire. When a handful of students protested for reform in Beijing, authorities did not punish them. We have all seen the classic image of a lone student, shopping bags in hand, standing in front of a procession of tanks and halting them. Those few students who protested were the critical mass. Demonstrations erupted in more than 300 towns all over the country as people found the confidence to act.

Malcolm Gladwell on Tipping Points

An influential text on the topic of critical mass is Malcolm Gladwell’s The Tipping Point. Published in 2000, the book describes a tipping point as “the moment of critical mass, the threshold, the boiling point.” He notes that “Ideas and products and messages and behaviors spread just like viruses do” and cites such examples as the sudden popularity of Hush Puppies and the steep drop in crime in New York after 1990. Gladwell writes that although the world “may seem like an immovable, implacable place,” it isn't. “With the slightest push — in just the right place — it can be tipped.”

Referring to the 80/20 rule (also known as Pareto’s principle), Gladwell explains how it takes a tiny number of people to kickstart the tipping point in any sort of epidemic:

Economists often talk about the 80/20 Principle, which is the idea that in any situation roughly 80 percent of the “work” will be done by 20 percent of the participants. In most societies, 20 percent of criminals commit 80 percent of crimes. Twenty percent of motorists cause 80 percent of all accidents. Twenty percent of beer drinkers drink 80 percent of all beer. When it comes to epidemics, though, this disproportionality becomes even more extreme: a tiny percentage of people do the majority of the work.

Rising crime rates are also the result of a critical mass of people who see unlawful behavior as justified, acceptable, or necessary. It takes only a small number of people who commit crimes for a place to seem dangerous and chaotic. Gladwell explains how minor transgressions lead to more serious problems:

[T]he Broken Windows theory … was the brainchild of the criminologist James Q. Wilson and George Kelling. Wilson and Kelling argued that crime is the inevitable result of disorder. If a window is broken and left unrepaired, people walking by will conclude that no one cares and no one is in charge. Soon, more windows will be broken, and the sense of anarchy will spread from the building to the street it faces, sending a signal that anything goes. In a city, relatively minor problems like graffiti, public disorder, and aggressive panhandling, they write, are all the equivalent of broken windows, invitations to more serious crimes…

According to Gladwell’s research, there are three main factors in the creation of a critical mass of people necessary to induce a sudden change.

The first of these is the Law of the Few. Gladwell states that certain categories of people are instrumental in the creation of tipping points. These categories are:

  • Connectors: We all know connectors. These are highly gregarious, sociable people with large groups of friends. Connectors are those who introduce us to other people, instigate gatherings, and are the fulcrums of social groups. Gladwell defines connectors as those with networks of over one hundred people. An example of a cinematic connector is Kevin Bacon. There is a trivia game known as “Six Degrees of Kevin Bacon,” in which players aim to connect any actor/actress to him within a chain of six films. Gladwell writes that connectors have “some combination of curiosity, self-confidence, sociability, and energy.”
  • Mavens: Again, we all know a maven. This is the person we call to ask what brand of speakers we should buy, or which Chinese restaurant in New York is the best, or how to cope after a rough breakup. Gladwell defines mavens as “people we rely upon to connect us with new information.” These people help create a critical mass due to their habit of sharing information, passing knowledge on through word of mouth.
  • Salesmen: Whom would you call for advice about negotiating a raise, a house price, or an insurance payout? That person who just came to mind is probably what Gladwell calls a salesman. These are charismatic, slightly manipulative people who can persuade others to accept what they say.

The second factor cited by Gladwell is the “stickiness factor.” This is what makes a change significant and memorable. Heroin is sticky because it is physiologically addictive. Twitter is sticky because we want to keep returning to see what is being said about and to us. Game of Thrones is sticky because viewers are drawn in by the narrative and want to know what happens next. Once something reaches a critical mass, stickiness can be considered to be the rate of decline. The more sticky something is, the slower its decline. Cat videos aren't very sticky, so even the viral ones thankfully fade into the night quickly.

Finally, the third factor is the specific context; the circumstances, time, and place must be right for an epidemic to occur. Understanding how a tipping point works can help to clarify the concept of critical mass.

The 10% Rule

One big question is: what percentage of a population is necessary to create a critical mass?

According to researchers at Rensselaer Polytechnic Institute, the answer is a mere 10%. Computational analysis was used to establish where the shift from minority to majority lies. According to director of research Boleslaw Szymanski:

When the number of committed opinion holders is below 10 percent, there is no visible progress in the spread of ideas. It would literally take the amount of time comparable to the age of the universe for this size group to reach the majority. Once that number grows above 10 percent, the idea spreads like flame.

The research has shown that the 10% can comprise literally anyone in a given society. What matters is that those people are set in their beliefs and do not respond to pressure to change them. Instead, they pass their ideas on to others. (I'd argue that the percentage is lower. Much lower. See Dictatorship of the Minority.)

As an example, Szymanski cites the sudden revolutions in countries such as Egypt and Tunisia: “In those countries, dictators who were in power for decades were suddenly overthrown in just a few weeks.”

According to another researcher:

In general, people do not like to have an unpopular opinion and are always seeking to try locally to come to a consensus … As agents of change start to convince more and more people, the situation begins to change. People begin to question their own views at first and then completely adopt the new view to spread it even further. If the true believers just influenced their neighbors, that wouldn’t change anything within the larger system, as we saw with percentages less than 10.

The potential use of this knowledge is tremendous. Now that we know how many people are necessary to form a critical mass, this information can be manipulated — for good or evil. The choice is yours.

Peter Thiel on the End of Hubris and the Lessons from the Internet Bubble of the Late 90s

Madness is rare in individuals—but in groups, parties, nations and ages it is the rule.

The best interview question — what important truth do very few people agree with you on?— is tough to answer. Just think about it for a second.

In his book Zero to One, Peter Thiel argues that it might be easier to start with what everyone seems to agree on and go until you disagree.

If you can identify a delusional popular belief, you can find what lies hidden behind it: the contrarian truth.

Consider the proposition that companies should make money for their shareholders and not lose it. This seems self-evident, but it wasn't so obvious to many in the late 90s. Remember back then? No loss was too big. (In my interview with Sanjay Bakshi he suggested that to some extent this still exists today.)

Making money? That was old school. In the late 1990s it was all about the new economy. Eyeballs first, profits later.

Conventional beliefs only ever come to appear arbitrary and wrong in retrospect; whenever one collapses, we call the old belief a bubble. But the distortions caused by bubbles don’t disappear when they pop. The internet craze of the ’90s was the biggest bubble since the crash of 1929, and the lessons learned afterward define and distort almost all thinking about technology today. The first step to thinking clearly is to question what we think we know about the past.

Peter Thiel:The first step to thinking clearly is to question what we think we know about the past

There's really no need to rehash the 1990s in this article. You can google it. Or you can read the summary in chapter two of Zero to One.

Where things get interesting, at least in the thinking context, are the lessons we drew from the late 90s. Thiel says the following were lessons most commonly learned:

The entrepreneurs who stuck with Silicon Valley learned four big lessons from the dot-com crash that still guide business thinking today:

1. Make incremental advances. Grand visions inflated the bubble, so they should not be indulged. Anyone who claims to be able to do something great is suspect, and anyone who wants to change the world should be more humble. Small, incremental steps are the only safe path forward.

2. Stay lean and flexible. All companies must be “lean,” which is code for “unplanned.” You should not know what your business will do; planning is arrogant and inflexible. Instead you should try things out, “iterate,” and treat entrepreneurship as agnostic experimentation.

3. Improve on the competition. Don’t try to create a new market prematurely. The only way to know you have a real business is to start with an already existing customer, so you should build your company by improving on recognizable products already offered by successful competitors.

4. Focus on product, not sales. If your product requires advertising or salespeople to sell it, it’s not good enough: technology is primarily about product development, not distribution. Bubble-era advertising was obviously wasteful, so the only sustainable growth is viral growth.

These lessons, Thiel argues, are now dogma in the startup world. Ignore them at your peril and risk near certain failure. In fact, many private companies I've worked with have adopted the same view. Governments too are attempting to replicate these ‘facts' — they have become conventional wisdom.

And yet … the opposites are probably just as true if not more correct.

1. It is better to risk boldness than triviality.
2. A bad plan is better than no plan.
3. Competitive markets destroy profits.
4. Sales matters just as much as product.

Such is the world of messy social science — hard and fast rules are difficult to come by, and frequently, good ideas lose value as they gain popularity. (This is the “everyone on their tip-toes at a parade” idea.) Just as importantly, what starts as a good hand tends to be overplayed by man-with-a-hammer types.

And so the lessons which have been culled from the tech crash are not necessarily wrong, they are just context-dependent. It is hard to generalize with them.

Peter Thiel Think For Yourself

According to Thiel, we must learn to use our brains as well as our emotions:

We still need new technology, and we may even need some 1999-style hubris and exuberance to get it. To build the next generation of companies, we must abandon the dogmas created after the crash. That doesn’t mean the opposite ideas are automatically true: you can’t escape the madness of crowds by dogmatically rejecting them. Instead ask yourself: how much of what you know about business is shaped by mistaken reactions to past mistakes? The most contrarian thing of all is not to oppose the crowd but to think for yourself.

In a nutshell, when everyone learns the same lessons, applying them to the point of religious devotion, there can be opportunity in the opposite. If everyone is thinking the same thing, no one is really thinking.

As Alfred Sloan, the heroic former CEO of General Motors, once put it:

Alfred Sloan

The Single Best Interview Question You Can Ask

In Peter Thiel's book, Zero to One: Notes on Startups, or How to Build the Future — more of an exercise in thinking about the questions you must ask to move from zero to one — there is a great section on the single best interview question you can ask someone.

Whenever Peter Thiel interviews someone he likes to ask the following question: “What important truth do very few people agree with you on?

This question sounds easy because it’s straightforward. Actually, it’s very hard to answer. It’s intellectually difficult because the knowledge that everyone is taught in school is by definition agreed upon. And it’s psychologically difficult because anyone trying to answer must say something she knows to be unpopular. Brilliant thinking is rare, but courage is in even shorter supply than genius.

The most common answers, according to Thiel, are “Our educational system is broken and urgently needs to be fixed.” “America is exceptional.” “There is no God.”

These are bad answers.

The first and the second statements might be true, but many people already agree with them. The third statement simply takes one side in a familiar debate. A good answer takes the following form: “Most people believe in x, but the truth is the opposite of x.”


What does this contrarian question have to do with the future? In the most minimal sense, the future is simply the set of all moments yet to come.

We hope for progress when we think about the future. To Thiel, that progress takes place in two ways.

Horizontal or extensive progress means copying things that work— going from 1 to n. Horizontal progress is easy to imagine because we already know what it looks like. Vertical or intensive progress means doing new things— going from 0 to 1. Vertical progress is harder to imagine because it requires doing something nobody else has ever done. If you take one typewriter and build 100, you have made horizontal progress. If you have a typewriter and build a word processor, you have made vertical progress.

best interview question peter thiel

At the macro level, the single word for horizontal progress is globalization— taking things that work somewhere and making them work everywhere. … The single word for vertical, 0 to 1 progress, is technology. … Because globalization and technology are different modes of progress, it’s possible to have both, either, or neither at the same time.

Peter Thiel
Here is Thiel's answer to his own question:

My own answer to the contrarian question is that most people think the future of the world will be defined by globalization, but the truth is that technology matters more. Without technological change, if China doubles its energy production over the next two decades, it will also double its air pollution. If every one of India’s hundreds of millions of households were to live the way Americans already do— using only today’s tools— the result would be environmentally catastrophic. Spreading old ways to create wealth around the world will result in devastation, not riches. In a world of scarce resources, globalization without new technology is unsustainable.

Peter Thiel: Zero To One

Peter Thiel's book, Zero to One: Notes on Startups, or How to Build the Future, is about building companies that create new things. But more than that, there is a lot of wisdom in this book.


We look to models of success — be they companies, prescriptions, or people and we attempt to blindly copy them without understanding the role of skill versus luck, the ecosystem in which they thrive, or why they work.

We want the shortcut. We want someone to give us the map without understanding the terrain.

I can't tell you the number of times I've seen companies attempt to solve innovation — as if it were a mathematical formula — with a version of Dragon's Den or 20% innovation time.

It doesn't work.

Zero to One

Every moment happens only once.

The next Bill Gates will not build an operating system. The next Larry Page or Sergey Brin won’t make a search engine. And the next Mark Zuckerberg won’t create a social network. If you are copying these guys, you aren’t learning from them.

So why do we copy?

[I]t’s easier to copy a model than to make something new. Doing what we already know how to do takes the world from 1 to n, adding more of something familiar. But every time we create something new, we go from 0 to 1. The act of creation is singular, as is the moment of creation, and the result is something fresh and strange.

We are unique. We are the only animals that build by creating something new.

Other animals are instinctively driven to build things like dams or honeycombs, but we are the only ones that can invent new things and better ways of making them. Humans don’t decide what to build by making choices from some cosmic catalog of options given in advance; instead, by creating new technologies, we rewrite the plan of the world. These are the kind of elementary truths we teach to second graders, but they are easy to forget in a world where so much of what we do is repeat what has been done before.

We are all searching for the elusive formula — the things that if only we'd do them we'd become successful. This is why we flock to the bookstore to learn about how Google innovates only to find that blindly applying the same prescription results in no more success than taking a polar bear and putting it in the desert. There simply is no formula for success. Giving up that notion might be the most helpful thing you can do today.

The paradox of teaching entrepreneurship is that such a formula necessarily cannot exist; because every innovation is new and unique, no authority can prescribe in concrete terms how to be innovative. Indeed, the single most powerful pattern I have noticed is that successful people find value in unexpected places, and they do this by thinking about business from first principles instead of formulas.

In his wonderful book of Fragments, Heraclitus writes: “No man ever steps in the same river twice, for it’s not the same river and he’s not the same man.”

If every moment happens only once, where does this leave us? These are the questions we must explore.

Zero to One: Notes on Startups, or How to Build the Future is worth reading in its entirety.

Peter Thiel Recommends 7 Reads

Eccentric billionaire Peter Thiel's book Zero To One should be required reading for Farnam Street readers. Like The Hard Thing About Hard Things, it's nice to see another business leader come out and write about life in the trenches in their own voice. I pointed out eight lessons that I took away, although there are many more hidden in the book.

In 2012 the Wall Street Journal asked him which books he enjoyed most in 2012, he responded with the following three suggestions:

100 Plus, Sonia Arrison

.. was first published in 2011, but its message is evergreen: how scientists are directly attacking the problem of aging and death and why we should fight for life instead of accepting decay as inevitable. The goal of longer life doesn't just mean more years at the margin; it means a healthier old age. There is nothing to fear but our own complacency.

Bloodlands, Timothy Snyder

… He tells how the Nazis and the Soviets drove each other to ever more murderous atrocities as they fought to dominate Eastern Europe in the 1930s and '40s. Even as he calculates the death toll painstakingly, Mr. Snyder reminds us that the most important number is one: Each victim was an individual whose life cannot be reduced to the violence that cut it short.

Resurrection From the Underground, René Girard

… the great French thinker René Girard's classic study of Fyodor Dostoevsky …. There is no better way to think about human irrationality than to read Dostoevsky, and there is no better reader of Dostoevsky than Mr. Girard. For a fresh application of Mr. Girard's insights into power politics, that great international theater of irrationality, try Jean-Michel Oughourlian's “Psychopolitics,” a brief, freewheeling 2012 work by one of Mr. Girard's closest collaborators.

Of course those were only his favorite books that year. So what then influenced his thinking overall? Luckily he answered this question in a reddit AMA. Prefacing his response with “I like the genre of past books written about the future,” he went on to list four books:

New Atlantis by Francis Bacon
Bacon writes of a utopian land called Bensalem where people live better lives because of science. Bacon “focuses on the duty of the state toward science, and his projections for state-sponsored research anticipate many advances in medicine and surgery, meteorology, and machinery.” Keep in mind this was written in 1627.

The American Challenge by Jean-Jacques Servan-Schreiber
A book that foresaw the information age. Here is a powerful quote from the book: “The signs and instruments of power are no longer armed legions or raw materials or capital… The wealth we seek does not lie in the earth or in numbers of men or in machines, but in the human spirit. And particularly in the ability of men to think and to create.”

The Great Illusion A Study of the Relation of Military Power to National Advantage
I'd never heard of this book before now, but as one Amazon reviewer summed it up: “(this is) a tightly reasoned and broadly historical perspective challenging the reigning view that man's nature is inherently evil and that evil nature must dictate human relations.”

The Diamond Age: Or, a Young Lady's Illustrated Primer
I started reading this once and was mesmerized by Stephenson's imaginative future world. If you like artificial intelligence and nanotechnology, this is the book for you.