The Black Swan is the second book in former options trader Nassim Nicholas Taleb’s five-volume series on uncertainty. This book analyzes so-called “Black Swans”—extremely unpredictable events that have massive impacts on human society.
The Black Swan is named after a classic error of induction wherein an observer assumes that because all the swans he’s seen are white, all swans must be white. Black Swans have three salient features:
Taleb’s thesis, however, is that Black Swans, by their very nature, are always unpredictable—they are the “unknown unknowns” for which even our most comprehensive models can’t account. The fall of the Berlin Wall, the 1987 stock market crash, the creation of the Internet, 9/11, the 2008 financial crisis—all are Black Swans.
Once Taleb introduces the concept of the Black Swan, he delves into human society and psychology, analyzing why modern civilization invites wild randomness and why humans can neither accept nor control that randomness.
To explain how and why Black Swans occur, Taleb coins two categories to describe the measurable facets of existence: Extremistan and Mediocristan.
In Mediocristan, randomness is highly constrained, and deviations from the average are minor. Physical characteristics such as height and weight are from Mediocristan: They have upper and lower bounds, their distribution is a bell curve, and even the tallest or lightest human being isn’t much taller or lighter than the average. In Mediocristan, prediction is possible.
In Extremistan, however, randomness is wild, and deviations from the average can be, well, extreme. Most social, man-made aspects of human society—the economy, the stock market, politics—hail from Extremistan: They have no known upper or lower bounds, their behavior can’t be graphed on a bell curve, and individual events or phenomena—i.e., Black Swans—can have exponential impacts on averages.
Imagine you put ten people in a room. Even if one of those people is Shaquille O’Neal, the average height in the room is likely to be pretty close to the human average (Mediocristan). If one of those people is Jeff Bezos, however, suddenly the wealth average changes drastically (Extremistan).
Taleb has very little patience for “experts”—academics, thought leaders, corporate executives, politicians, and the like. Throughout the book, Taleb illustrates how and why “experts” are almost always wrong and have little more ability to predict the future than the average person.
There are two reasons “experts” make bad predictions:
1) Human Nature
Because of various habits innate to our species—our penchant for telling stories, our belief in cause and effect, our tendency to “cluster” around specific ideas (confirmation bias) and “tunnel” into specific disciplines or methods (specialization)—we tend to miss or minimize randomness’s effect on our lives. Experts are no less guilty of this blindspot than your average person.
2) Flawed Methods
Because experts both (1) “tunnel” into the norms of their particular discipline and (2) base their predictive models exclusively on past events, their predictions are inevitably susceptible to the extremely random and unforeseen.
Consider, for example, a financial analyst predicting the price of a barrel of oil in ten years. This analyst may build a model using the gold standards of her field: past and current oil prices, car manufacturers’ projections, projected oil-field yields, and a host of other factors, computed using the techniques of regression analysis. The problem is that this model is innately narrow. It can’t account for the truly random—a natural disaster that disrupts a key producer, or a war that increases demand exponentially.
Taleb draws a key distinction between experts in Extremistan...
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In his April 2007 review of The Black Swan in the New York Times, Gregg Easterbrook, riffing on the author’s skepticism about forecasts of any kind, noted, “At the beginning of 2006, the Wall Street Journal forecast a bad year for stocks; the Dow Jones Industrial Average rose 16% that year. (Disturbingly, the Journal has forecast a good year for 2007.)” Mere months later, the world economy would be in a tailspin—and Nassim Nicholas Taleb, who in The Black Swan warned that the global financial system was vulnerable to collapse, would be treated as a seer.
The Black Swan covers a broad range of topics and is organized in a somewhat...
For millennia, it was universally accepted that all swans were white. In fact, this truth was so incontrovertible that logicians would often use it to illustrate the process of deductive reasoning. That classic deduction went like this:
But in 1697, Willem de Vlamingh, a Dutch explorer, discovered black swans while on a rescue mission in Australia—and, in an instant, a universal, incontrovertible truth was shown to be anything but.
After Vlamingh’s discovery, philosophers used the term “black swan” to describe a seeming logical impossibility that could very well end up being possible.
Taleb, however, offers a new spin on the term. He uses it to describe specific historical events with specific impacts. These events have three salient features:
Some examples of Black Swan events include World Wars I and...
One reason that Black Swans are so profoundly disruptive is that they occur in the “scalable” parts of our lives—where physical limits don’t apply and effects tend toward incredible extremes. When a particular thing—an income, an audience for a particular product—is “scalable,” it can grow exponentially without any additional expenditure of effort.
“Massage therapist,” for example, is a “nonscalable” profession. There is an upper limit on how many clients you can see—there’s only so much time in a day, and therapists’ bodies fatigue—and thus there’s only so much income you can expect from that profession.
“Quantitative trader,” however, is a “scalable” profession. It takes no additional energy or time to purchase 5,000 shares of a stock than 50, and your income isn’t limited by physical constraints.
Artists, too, are in a scalable profession (at least in the age of digital reproduction). For instance, a singer doesn’t need to perform her hit song each time someone wants to hear it. She performs it once for the record, and that performance can be disseminated widely.
The problem with scalability is that it creates vast inequalities. Let’s look at the singer example...
Picture a turkey cared for by humans. It has been fed every day for its entire life by the same humans, and so it has come to believe the world works in a certain, predictable, and advantageous way. And it does...until the day before Thanksgiving.
Made famous by British philosopher Bertrand Russell (though, in his telling, the unlucky bird was a chicken), this story illustrates the problem with inductive reasoning (the derivation of general rules from specific instances). With certain phenomena—marketing strategy, stock prices, record sales—a pattern in the past is no guarantee of a pattern in the future.
In Taleb’s words, the turkey was a sucker—it had full faith that the events of the past accurately indicated the future. Instead, it was hit with a Black Swan, an event that completely upends the pattern of the past. (It’s worth noting that the problem of inductive reasoning is the problem of Black Swans: Black Swans are possible because we lend too much weight to past experience.)
Another example of faulty inductive reasoning, this time from the world of finance, concerns the hedge fund Amaranth (ironically named after a flower that’s “immortal”), which incurred...
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Explore what it means to be an “empirical skeptic.”
Write down something that happened to you recently, good or bad, that was out of the ordinary.
With the rapid advance of technology—computer chips, cellular networks, the Internet—it stands to reason that our predictive capabilities too are advancing. But consider how few of these groundbreaking advances in technology were themselves predicted. For example, no one predicted the Internet, and it was more or less ignored when it was created.
(Shortform note: It’s unclear how Taleb defines “predicted.” Plenty of science-fiction writers and cultural commentators anticipated recent technologies like the Internet and augmented and virtual reality.)
It is an inconvenient truth that humans’ predictive capabilities are extremely limited; we are continuously faced with catastrophic or revolutionary events that arrive completely unexpectedly and for which we have no plan. Yet, nevertheless, we maintain that the future is knowable and that we can adequately prepare for it. Taleb calls this tendency the scandal of prediction.
The reason we overestimate our ability to predict is that we’re overconfident in our knowledge.
A classic illustration of the fact comes from a study conducted by a pair of Harvard researchers. In the study, the researchers asked...
Think like Taleb about prediction and the limits of your ability to predict things.
Write down a prediction you recently made, whether it was about a baseball game, the economy, an election, or other event.
Epistemic arrogance, the pretensions of “experts,” our ever-increasing access to information—all belie an incontrovertible fact: In many, perhaps even most, areas of our lives, prediction is simply impossible.
Take discoveries, for example. At any given moment, there are scores of scientists, scholars, researchers, and inventors around the world working diligently to better our lives and increase our knowledge. But what often goes unremarked is that the discoveries with the profoundest impact on our lives are inadvertent—random—rather than the reward for careful and painstaking work.
The discovery of [restricted term] is a case in point. Biologist Alexander Fleming left a stack of cultures sitting out in his laboratory while he went on vacation, and when he returned, a bacteria-killing mold had formed on one of the cultures. Voila!—the world’s first antibiotic.
The same goes for the discovery of the cosmic microwave background, the omnipresent radiation in space that provides a key piece of evidence for the Big Bang. No researcher had any idea it existed until two radio astronomers noticed a hiss in their listening devices. How unexpected was their...
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Through the limitations of inductive reasoning as illustrated by the turkey anecdote, as well as the distortions of the narrative fallacy and silent evidence, we’ve seen how problematic the past is vis-à-vis prediction. But because of these phenomena and others, the past itself is as unknowable as the future.
One of the major obstacles that prevents us from knowing the past with certainty is the impossibility of reverse engineering causes for events. That is, there’s no way to determine the precise cause of an event when we work backward in time from the event itself.
An example should help illustrate.
Think of an ice cube sitting on a table. Imagine the shape of the puddle that ice cube will make as it melts.
Now think of a puddle on the table and try to imagine how that puddle got there.
The second thought experiment is much harder than the first. With the right physics know-how and ample time, one could model exactly what kind of puddle will result from the melting ice cube (based on the cube’s shape, the environmental conditions, etc.). In contrast, it’s nearly impossible to reverse engineer a...
If we are surrounded by randomness and unpredictability, if our well-being is radically uncertain, what—besides despair—are our options?
It bears repeating that humans’ ability to predict in the short-term is unique among animal species and quite possibly the reason we’ve survived and thrived as long as we have. To predict is human.
So, when it comes to low-stakes, everyday predictions—about the weather, say, or the outcome of a baseball game—there’s no harm in indulging our natural penchant for prediction: If we’re wrong, the repercussions are minimal. It’s when we make large-scale predictions and incur real risk on their basis that we get into trouble.
Although the most memorable Black Swans are typically the negatively disruptive ones, Black Swans can also be serendipitous. (Shortform note: Love at first sight is undoubtedly a Black Swan.)
Taleb advocates (1) sociability and (2) proactiveness when presented with an opportunity as strategies for opening ourselves up to positive Black Swans. Sociability puts us in the company of others who may be in a...
A barbell strategy devotes the majority of resources to safe options, and a minority to highly risky options that can pay off big. How can you integrate this into your life?
Write down a goal you’ve recently set for yourself, whether in your personal or professional life.
Think about how you can use randomness to your advantage.
Write down an area of your life where you think you could use improvement and why.
Although one needs only an intuitive sense of phenomena like wealth and market returns to understand that they don’t adhere to the same rules as phenomena like height and weight, throughout the book Taleb provides a robust theoretical and statistical scaffolding for his claims about the differences between Mediocristan and Extremistan.
Because these discussions tend toward the technical and aren’t essential for understanding Black Swans and their role in our lives, we at Shortform have decided to summarize them as an appendix.
As exemplified by figures like Beyoncé and Jeff Bezos, social and economic advantages accrue highly unequally in Extremistan.
One reason for this disparity is the “superstar effect.” Coined by economist Sherwin Rosen to describe the unequal distributions of income and prestige in Extremistan sectors like stand-up comedy, classical music, and research scholarship, the “superstar effect” operates when marginal differences in talent yield massive rewards.
The superstar effect, it’s vital to note, is meritocratic—that is, those with the most talent, even if they’re only slightly more talented than their competitors, get...
Reflect on your takeaways from Taleb’s book.
Which of Taleb’s concepts or examples did you find most surprising and why?