The Black Swan: The Impact of the Highly Improbable
by chet ~ March 28th, 2008. Filed under: Boyd's Theories, Business Strategy.A review by Robert D. Brown, III.
On the 1000th day of its life, Bertrand Russell’s turkey felt fat and happy. The next day, Thanksgiving, he was stuffed with bread and eaten to the great satisfaction of the Russell family. Russell’s turkey met a black swan.[1]
A black swan was an idea put forward by the Enlightenment philosopher, David Hume, to represent the unexpected, the stuff you don’t know or don’t know that you don’t know. It was a play on the popular idea in the 17th century that the only color of swan found in nature was white. Hume argued that although no one had ever seen a black swan, their existence was not logically ruled out by their lack of being observed, at least by Europeans, as Europeans would soon find out. In fact, black swans do exist, but they weren’t recorded in natural histories until Europeans (also) discovered Australia. As native Australians already knew, black swans are quite numerous indeed.[2]
Russell’s turkey met a black swan. We’ve all met black swans. Two good friends of mine met a familiar black swan this past Christmas, the one few of us ever anticipate. Both friends had enjoyed decades long careers at a single employer. Suddenly, they were let go, seemingly out of the blue. Sometimes black swans bear teeth.

This beautiful bird is about to wreak havoc on those who fail to
comprehend its predatory ambitions, or it may deliver a golden egg.
But black swans sometimes bear gifts, too. Another friend of mine experienced a virtuous swan just after the new year. He was waiting for his privately held company to go through it’s quarterly valuation and release its updated stock price. If one followed the price history of the company’s stock and believed that past performance indicated future performance, one would reasonable expect an increase of $1 to $5. Imagine his surprise when he opened his email to learn that the company’s stock had jumped $17 per share, and increase of 107%! The value of the ownership he held in the company doubled in one day.
Now both sets of friends face more potential black swans. Will my former example set of friends continue to believe that employment always means stability, or will they take more proactive steps to manage their careers? Will my latter friend be honest enough to understand that his company’s stock price can go back down just as dramatically as it went up?
These surprises are the most general grist for consideration in Nassim Nicholas Taleb’s most recent book, The Black Swan: The Impact of the Highly Improbable, a more thorough and extensive consideration than his previous book, Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets.
Taleb, literary essayist, Dean’s Professor of Uncertainty at the University of Massachusetts, and mathematical options trader, lays out the foundation for his ideas from his experiences in the financial markets. These experiences lead him to discuss three interrelated themes that he ultimately broadens to an understanding of uncertainty in general.
- The Ludic Fallacy: The word ludic comes from the Latin ludus, for “games.” Most of us were taught to think about systems that involve uncertainty and chance using structured, discrete symmetries like those found in games of chance, such as craps, card games, etc. Unfortunately, these analogies don’t frequently hold up into real world situations; but because it’s comfortable and expected to do so, we persist in their use. Use of binomial distributions are often a result of ludic framing, as is its continuous cousin, the bell curve (or Normal Gaussian for those more trained in quantitative analysis). These distributions have appropriate applications, but they do not apply to all cases of uncertainty.
- Mediocristan/Extremistan: Most of us live in Mediocristan, a land not governed so much by mediocrity, but by a persistent belief in the applicability of a characteristic median to all types of uncertainty. When most of us think of uncertainty in some domain, we have been taught to think about that in terms of the bell curve. Taleb demonstrates that many types of uncertainty can be thought of in this way (Class I uncertainty), but not all of them. One characteristic of uncertainties described by a bell curve is that they do not scale, that is, the probability of occurrence of outcomes far from the mean (and median) fall exponentially fast. In this world, no one event outweighs the significance of all the other events. Many physical processes with natural physical constraints are accurately described by such distributions. Black swans can show up here, but they are extremely rare. Unfortunately, most black swans live in Extremistan, the land where uncertainty scales according to a power law (Class II uncertainty), where it is possible for a single event in a domain to outweigh the significance of all the others. Extremistan exists beyond the Platonic fold, where our typical representations of reality fail to apply. The processes that govern such distributions tend to be social, emergent, financial, maybe not entirely physical. This will have an important bearing on seeing the applicability to maneuver conflict.
- Confirmation Bias: Oftentimes we become inebriated with hope, that outcomes will go the way we wish and hope. To convince ourselves that such is the case, we develop narratives from cherry-picked data and information that confirm our bias. Using these narratives as a guide to decision making, we are disabused of our fallacious reasoning in sometimes spectacular ways. Yet we still fail to learn if we are still alive to face the next black swan. “Beware the scalable,” Taleb enjoins.
The scandalous malpractice, as Taleb shouts, is that the rules that apply to Mediocristan are too often misappropriated to understand and manage systems that don’t obey such laws, often at the expense of lives and immense fortunes. The most pointed cases involve applications of options and modern portfolio theory in which billions of dollars of investors’ fortunes are lost by the malpractice of Nobel “intellectuals” who should know better (anyone remember the tragedy of the Amaranth fund or the trading company Long-Term Capital Management?); the poignant disaster of the unsinkable Titanic; the current woes of Bear Stearns and the sub-prime lending industry; and, in Taleb’s case, the decade and a half long civil war in his centuries-long peaceful Lebanon, a war that he and all too many others sadly believed would end soon after it started.
How does understanding the black swan inform our understanding of maneuver conflict? Consider the martial arts version of the Ludic Fallacy offered by Mark Spitznagel.
Organized competitive fighting trains the athlete to focus on the game and, in order not to dissipate his concentration, to ignore the possibility of what is not specifically allowed by the rules, such as kicks to the groin, a surprise knife, et cetera. So those who win the gold medal might be precisely those who will be most vulnerable in real life. (Black Swan, pg. 127)
John Boyd leads us to understand that conflict is often a non-cooperative contest for limited resources by novelty generating agents. Novelty is the black swan of conflict. When we become convinced that our side will win on the basis of strength or numbers, when we believe that the other side will follow our rules of engagement, we will be exposed to cruel novelty. This is precisely what Chet Richards describes as a disease of orientation called fixation: “…attachments to appearances, conclusions, institutional positions, dogmas, ideologies — pretty much anything that keeps the people inside the organization from recognizing that the world is changing or being changed by competitors.”
How do we escape the tyranny of the black swan? We have to learn to do at least two things. First, we have to learn how to really learn, always looking for disconfirming evidence to the self-justifying narratives we generate from the first cousins of confirmation & my-side bias, availability bias, and anchoring that keep us from considering a wide range of possible outcomes, their appropriate degrees of likelihood, and their consequences. We have to learn that images in the mirror tell us scant little about the road ahead. To do this, next, we have to learn how to properly discern systems governed by the laws of Mediocristan from those governed by the laws of Extremistan, and act accordingly.
Nassim Nicholas Taleb delivers what may be the only book on epistemology that I would describe as both a blustery and a rollicking good read. If only all the other text books in philosophy of knowledge I read in school had been so fun. If only all the others had been so honest. In that sense, Taleb’s book is its own black swan.
[1] The reader should almost immediately recognize that Bertrand Russell was English and did not observe Thanksgiving. In fact, as Russell himself tells this story, he uses a chicken as the example of the doomed bird. Taleb acknowledges this, but adapts the story to an American audience. [back]
[2] I am reminded of an event in my 9th grade year in which my algebra teacher convinced a sizable portion of our class that the state of Nevada did not exist, that it was a ruse invented by the US Air Force to deter investigation into super secret military programs. His “proof” was a simple question: “Have you ever seen a car tag from Nevada?” For kids in rural mid-Georgia, his scam was based on a rather safe bet that Nevadans rarely drove to our sleepy little town. [back]
March 28th, 2008 at 4:31 pm
Impressive comments, extremely welcome. It seems a synthesis of
the material from Eliot Cohen, John Gooch and Manuel de Landa. I
will read it. Thanks!
March 29th, 2008 at 9:37 am
Given the rising influx of childhood cancer survivors and other individuals with unusual medical backgrounds into society, there is a growing number of people for whom life itself has always been a black swan.
Their direct experience is a resource that should be tapped.
Also, you talk at length about Gaussian distributions and what not. The appropriate language for black swan talk should be poetry - not statistics.
March 29th, 2008 at 11:35 am
Taleb talks a bit about two species of black swans. Those that are truly black represent that which you don’t know that you don’t know. They cannot be represented by much more than speculative prose and and poetry, if you even know to do so. The second species is really a gray swan, that which you know about but don’t think about because of biases or lack of expertise, the stuff that you know you don’t know. These swans can be discussed using the statistics of power laws and fractal laws. They are not Gaussian, but Mandelbrotian, after the mathematician, Benoit Mandelbrot, who expanded and explored fractal math. Taleb claims he is getting traction using this latter approach to explore gray swans.
March 29th, 2008 at 6:21 pm
I enjoyed your review, and I have a couple of questions:
1) I’m still ruminating on your equation of novelty in armed conflict with the truly black swan. Do you happen to have any historical military anecdotes handy that you believe depict grey swans?
2) Can you think of a way to include black swans in simulation models? Built-in unexpected events are anathema to software engineering, so my lazy first answer would be to just write a bad model and something will go wrong (speaking here of a logical error not a functional error). I’ve been tinkering with agent-based models a lot recently, and have been trying to imagine ways to investigate the black swan from the bottom-up.
March 30th, 2008 at 3:37 pm
Military examples abound. Check into how Henry V set up the Battle of Agincourt, or how Confederate Gen Robert E. Lee beat Union Maj Gen Joseph Hooker at the Battle of Chancellorsville, or how 300 Spartans and 1000 other Greeks held off tens of thousands of King Xerxes’s Persian forces at the Battle of Thermopylae (the pass was eventually lost by the Greeks, but the Persians experienced hugely disproportionate losses). Chet Richards recent book, Certain to Win, describes the German Blitzkrieg exceptionally well. In each of these cases, the losers (or near losers in the Persians case) did not conceive that they could lose, and they based their belief on a trust in numbers or a goofy sense of genetic superiority. In my mind, these examples are gray swans because the occurred within the realm of possible mental conception (the losers could have thought beforehand about how they could lose). The failure occurred because of “my side” bias or the confirmation bias. Can you think of how black/gray swans show up in business?
You’re latter question is a bit more difficult. Quantitative simulation is what I do (in part) professionally, so I would say that modeling unexpected events is not really anathema at all. In fact, it’s necessary to get deep insight into the effects of uncertainty. Of course there are limits to what can be simulated, and trying to build models that incorporate every uncertainty are a waste of time because they become just as complex the system one seeks to understand. This is why I teach in my classes on modeling that [1] one should develop the requisite model only and [2] that models are not so much for forecasting what will occur (with self-deceiving false precision) as much as providing a platform for asking questions about the consequences of what can occur (with mostly right accuracy). The effect of both of these requirements is that we avoid analysis paralysis and we avoid putting too much faith in a model as opposed to asking good, honest questions. One way to capture the effects of gray swans in modeling and simulation is to incorporate non-normal distributions such as lognormal, pareto, and power law or fractal distributions (I use a distribution for modeling expert assessments that works as a trade-off between these two extremes). These are skewed distributions with fat tails. If you visit my blog at http://thales.blogspot.com, follow the links to my contact information in About Me. There you will find my email address, and we can correspond more offline about this if you prefer. I’d like to learn more about your agent based simulations, too.
One last closing comment…I would absolutely avoid writing bad models. To avoid being “long in the tooth” here, let me simply say that I can’t think of any value in writing such a thing except to point out what bad models looks like.
March 31st, 2008 at 2:32 pm
To A Mouse, On Turning Her Up In Her Nest With The Plough
by Robert Burns
1785
Wee, sleekit, cow’rin, tim’rous beastie,
O, what a panic’s in thy breastie!
Thou need na start awa sae hasty,
Wi’ bickering brattle!
I wad be laith to rin an’ chase thee,
Wi’ murd’ring pattle!
I’m truly sorry man’s dominion,
Has broken nature’s social union,
An’ justifies that ill opinion,
Which makes thee startle
At me, thy poor, earth-born companion,
An’ fellow-mortal!
I doubt na, whiles, but thou may thieve;
What then? poor beastie, thou maun live!
A daimen icker in a thrave
‘S a sma’ request;
I’ll get a blessin wi’ the lave,
An’ never miss’t!
Thy wee bit housie, too, in ruin!
It’s silly wa’s the win’s are strewin!
An’ naething, now, to big a new ane,
O’ foggage green!
An’ bleak December’s winds ensuin,
Baith snell an’ keen!
Thou saw the fields laid bare an’ waste,
An’ weary winter comin fast,
An’ cozie here, beneath the blast,
Thou thought to dwell-
Till crash! the cruel coulter past
Out thro’ thy cell.
That wee bit heap o’ leaves an’ stibble,
Has cost thee mony a weary nibble!
Now thou’s turn’d out, for a’ thy trouble,
But house or hald,
To thole the winter’s sleety dribble,
An’ cranreuch cauld!
But, Mousie, thou art no thy lane,
In proving foresight may be vain;
The best-laid schemes o’ mice an ‘men
Gang aft agley,
An’lea’e us nought but grief an’ pain,
For promis’d joy!
Still thou art blest, compar’d wi’ me
The present only toucheth thee:
But, Och! I backward cast my e’e.
On prospects drear!
An’ forward, tho’ I canna see,
I guess an’ fear!
April 2nd, 2008 at 4:38 pm
Thanks for the great review on this book.
I read it about 6 months ago. It’s a tough read in many ways, and although I sensed that the concepts were related to Boyd, I didn’t make all the connections.
This helps a bunch - I think I’ll re-read this book again - it’s clear there are more ideas and connections to be made than what I saw upon first reading.
Thanks-
April 2nd, 2008 at 4:56 pm
TJ –
Thanks! Rob did a nice job on what I agree is a difficult and often misunderstood topic.
Zenpundit also liked it.