by Nassim Nicholas Taleb, Random House, April 17, 2007, 978-1400063512
Nassim Nicholas Taleb makes us face that our statistics are out of
whack with our observations. Taleb is a "hyper-skeptic" along with
other skeptics such as Popper, Poincare, and Mandelbrot. His thesis
is that our statistical techniques are based on induction and
therefore part of the problem. Gaussian distributions do not exist in
our natural world. Buffet & Gates are not an anomolies, they must be
part of the distribution. Mandelbrot taught us about power laws, and
we ignored him except for the pretty pictures of fractals that are so
Taleb wants us to look for counterfactuals: data that disaffirms our
hypothesis. Instead, we all look for confirmation: BMW drivers read
BMW ads. We need to think about how we think about our data. It's
all too easy to pat ourselves on the back when we find a correlation
after throwing out a few outliers -- that really don't matter, do
they? Just the opposite: The outliers are Black Swans which effect
change. Try a lot of things and keep what works is about the
outliers, not the average of all the things. We have to expose
ourselves to as many Black Swans with possible positive outcomes, and
avoid as many Black Swans with possible negative outcomes.
[p xxi] So I disagree with the followers of Marx and those of Adam
Smith: the reason free markets work is because they allow people to be
lucky, thanks to aggressive trial and error, not by giving rewards or
"incentives" for skill. The strategy is, then, to tinker as much as
possible and try to collect as many Black Swan opportunities as you
[p xxi] We do not spontaneously learn that
we don't learn that we don't learn.
The problem lies in the structure of our minds: we
don't learn rules, just facts, and only facts. Metarules (such as the
rule that we have a tendency to not learn rules) we don't seem to be
good at getting. We scorn the abstract; we scorn it with passion.
[p xxvii] There is a contradiction; this book is a story, and I
prefer to use stories and vignettes to illustrate our gullibility
about stories and our preference for the dangerous compression of
narratives. You need a story to displace a story. Metaphors and
stories are far more potent (alas) than ideas; they are also easier to
remember and more fun to read. If I have to go after what I call the
narrative disciplines, my best tool is a narrative.
Ideas come and go, stories stay.
[p30] Some people naively believe that the process of unfairness
started with the gramophone, according to the logic that I just
presented. I disagree. I am convinced that the process started much,
much earlier, with our DNA, which stores information about our selves
and allows us to repeat our performance without our being there by
spreading our genes down the generations. Evolution is scalable: the
DNA that wins (whether by luck or survival advantage) will reproduce
itself, like a bestselling book or a successful record, and become
pervasive. Other DNA will vanish. Just consider the difference between
us humans (excluding financial economists and businessmen) and other
living beings on our planet.
[p30] In the arts-say the cinema-things are far more vicious. What we
call "talent" generally comes from success, rather than its
opposite. A great deal of empiricism has been done on the subject,
most notably by Art De [p31] Vany, an insightful and original thinker
who singlemindedly studied wild uncertainty in the movies. He showed
that, sadly, much of what we ascribe to skills is an after-the-fact
attribution. The movie makes the actor, he claims--and a large dose of
nonlinear luck makes the movie.
The success of movies depends severely on contagions. Such contagions
do not just apply to the movies: they seem to affect a wide range of
cultural products. It is hard for us to accept that people do not fall
in love with works of art only for their own sake, but also in order
to feel that they belong to a community. By imitating, we get closer
to others--that is, other imitators. It fights solitude.
[p32] In the utopian province of Mediocristan, particular events don't
contribute much individually-only collectively. I can state the
supreme law of Mediocristan as follows:
When your sample is large, no single instance will significantly
change the aggregate or the total.
The largest observation will remain impressive, but eventually
insignificant, to the sum.
[p33] Try it also with academic citations (the mention of one academic
by another academic in a formal publication), media references,
income, company size, and so on. Let us call these social matters, as
they are manmade, as opposed to physical ones, like the size of
In Extremistan, inequalities are such that one single observation can
disproportionately impact the aggregate, or the total.
So while weight, height, and calorie consumption are from
Mediocristan, wealth is not. Almost all social matters are from
Extremistan. Another way to say it is that social quantities are
informational, not physical: you cannot touch them. Money in a bank
account is something important, but certainly not physical. As
such it can take any value without necessitating the expenditure of
energy. It is just a number!
[p43] So it took just one summer to figure out that this was a
sucker's business and that all their earnings came from a very risky
game. All that while the bankers led everyone, especially themselves,
into believing that they were "conservative." They are not
conservative; just phenomenally skilled at self-deception by burying
tbe possibility of a large, devastating loss under the rug.
[p5] Now, there are other themes arising from our blindness to the Black Swan:
a. We focus on preselected segments of the seen and generalize from it
to the unseen: the error of confirmation.
b. We fool ourselves with stories that cater to our Platonic thirst
for distinct patterns: the narrative fallacy.
c. We behave as if the Black Swan does not exist: human nature is not
programmed for Black Swans.
d. What we see is not necessarily all that is there. History hides
Black Swans from us and gives us a mistaken idea about the odds of
these events: this is the distortion of silent evidence.
e. We "tunnel": that is, we focus on a few well-defined sources of
uncertainty, on too specific a list of Black Swans (at the expense of
the others that do not easily come to mind).
[p54] For another illustration of the way we can be ludicrously
domainspecific in daily life, go to the luxury Reebok Sports Club in
New York City, and look at the number of people who, after riding the
escalator for a couple of floors, head directly to the StairMasters.
This domain specificity of our inferences and reactions works both
ways: some problems we can understand in their applications but not in
textbooks; others we are better at capturing in the textbook than in
the practical application. People can manage to effortlessly solve a
problem in a social situation but struggle when it is presented as an
abstract logical problem. We tend to use different mental
machinery-so-called modulesin different situations: our brain lacks a
central all-purpose computer that starts with logical rules and
applies them equally to all possible situations.
[p58] But it remains the case that you know what is wrong with a lot
more confidence than you know what is right. All pieces of information
are not equal in importance.
Popper introduced the mechanism of conjectures and refutations, which
works as follows: you formulate a (bold) conjecture and you start
looking for the observation that would prove you wrong. This is the
alternative to our search for confirmatory instances. If you think the
task is easy, you will be disappointed_few humans have a natural
ability to do this. I confess that I am not one of them; it does not
come naturally to me.
Counting to Three
Cognitive scientists have studied our natural tendency to look only
for corroboration; they call this vulnerability to the corroboration
error the confirmation bias. There are some experiments showing
that people focus only on the books read in Umberto Eco's library. You
can test a given rule either directly, by looking at instances where
it works, or indirectly, by focusing on where it does not work. As we
saw earlier, disconfirming instances are far more powerful in
establishing truth. Yet we tend to not be aware of this property.
[p69] We, members of the human variety of primates, have a hunger for
rules because we need to reduce the dimension of matters so they can
get into our heads. Or, rather, sadly, so we can squeeze them into our
heads. The more random information is, the greater the dimensionality,
and thus the more difficult to summarize. The more you summarize, the
more order it. you put in, the less randomness. Hence the same
condition that makes us simplify pushes us to think that the world is
less random than it actually is.
And the Black Swan is what we leave out of simplification.
[p73] How can you get rid of such a persistent throb? Don't try to
willingly avoid thinking about it: this will almost surely backfire. A
more appropriate solution is to make the event appear more
unavoidable. Hey, it was bound to take place and it seems futile to
agonize over it. How can you do so? Well,
with a narrative.
Patients who spend fifteen minutes every day writing an
account of their daily troubles feel indeed better about what has
befallen them. You feel less guilty for not having avoided certain
events; you feel less responsible for it. Things appear as if they
were bound to happen.
If you work in a randomness-laden profession, as we see, you are
likely to suffer burnout effects from that constant second-guessing of
your past actions in terms of what played out subsequently. Keeping a
diary is the least you can do in these circumstances.
[p89] These nonlinear relationships are ubiquitous in life. Linear
relationships are truly the exception; we only focus on them in
classrooms and textbooks because they are easier to
understand. Yesterday afternoon I tried to take a fresh look around me
to catalog what I could see during my day that was linear. I could not
find anything, no more. than someone hunting for squares or triangles
could find them in the rain forest-or, as we will see in Part Three,
any more than someone looking for bell-shape randomness finding it in
[p90] It is my great hope someday to see science and decision makers
rediscover what the ancients have always known, namely that our
highest currency is respect.
Even economically, the individual Black Swan hunters are not the ones
who make the bucks. The researcher Thomas Astebro has shown that
returns on independent inventions (you take the cemetery into account)
are far lower than those on venture capital. Some blindness to the
odds or an obsession with their own positive Black Swan is necessary
for entrepreneurs to function. The venture capitalist is the one who
gets the shekels. The economist William Baumol calls this "a touch of
madness." This may indeed apply to all concentrated businesses: when
you look at the empirical record, you not only see that venture
capitalists do better than entrepreneurs, but publishers do better
than writers, dealers do better than artists, and science does better
than scientists (about 50 percent of scientific and scholarly papers,
costing months, sometimes years, of effort, are never truly read). The
person involved in such gambles is paid in a currency other than
material success: hope.
[p91] Making $1 million in one year, but nothing in the preceding
nine, does not bring the same pleasure as having the total evenly
distributed over the same period, that is, $100,000 every year for ten
years in a row. The same applies to the inverse order-making a bundle
the first year, then nothing for the remaining period. Somehow, your
pleasure system will be saturated rather quickly, and it will not
carry forward the hedonic balance like a sum on a tax return. As a
matter of fact, your happiness depends far more on the number of
instances of positive feelings, what psychologists call ,"positive
affect," than on their intensity when they hit. In other words, good
news is good news first; how good matters rather little. So to have a
pleasant life you should spread these small "affects" across time as
evenly as possible. Plenty of mildly good news is preferable to one
single lump of great news.
[p116] Once again, I am not dismissing the idea of risk taking, having
been involved in it myself. I am only critical of the encouragement of
uninformed risk taking. The iiberpsychologist Danny Kahneman has given
us evidence that we generally take risks not out of bravado but out of
ignorance and blindness to probability! The next few chapters will
show in more depth how we tend to dismiss outliers and adverse
outcomes when projecting the future. But I insist on the following:
that we got here by accident does not mean that we should continue
to take the same risks. We are mature enough a race to realize
this point, enjoy our blessings, and try to preserve, by becoming more
conservative, what we got by luck. We have been playing Russian
roulette; now let's stop and get a real job.
[p118] Once when I returned to Lebanon during the war, at the age of
eighteen, I felt episodes of extraordinary fatigue and cold chills in
spite of the summer heat. It was typhoid fever. Had it not been for
the discovery of antibiotics, only a few decades earlier, I would not
be here today. I was also later "cured" of another severe disease that
would have left me for dead, thanks to a treatment that depends on
another recent medical technology. As a human being alive here in the
age of the Internet, capable of writing and reaching an audience, I
have also benefited from society's luck and the remarkable absence of
recent large-scale war. In addition, I am the result of the rise of
the human race, itself an accidental event.
My being here is a consequential low-probability occurrence, and I
tend to forget it.
[p120] My biggest problem with the educational system lies precisely
in that it forces students to squeeze explanations out of subject
matters and shames them for withholding judgment, for uttering the "I
don't know." Why did the Cold War end? Why did the Persians lose the
battle of Salamis? Why did Hannibal get his behind kicked? Why did
Casanova bounce back from hardship? In each of these examples, we are
taking a condition, survival, and looking for the explanations,
instead of flipping the argument on its head and stating that
conditional on such survival, one cannot read that
much into the
process, and should learn instead to invoke some measure of randomness
(randomness is what we don't know; to invoke randomness is to plead
ignorance). It is not just your college professor who gives
you bad habits. I showed in Chapter 6 how newspapers need to stuff
their texts with causal links to make you enjoy the narratives. But
have the integrity to deliver your "because" very sparingly; try to
limit it to situations where the "because" is derived from
experiments, not backward-looking history.
Note here that I am not saying causes do not exist; do not use this
argument to avoid trying to learn from history. All I am saying is
that it is not so simple; be suspicious of the "because" and
handle it with careparticularly in situations where you suspect silent
[p129] In a beautiful treatise now vanished from our consciousness,
Dissertation on the Search for Truth, published in 1673, the
polemist Simon Foucher exposed our psychological predilection for
certainties. He teaches us the art of doubting, how to position
ourselves between doubting and believing. He writes: "One needs to
exit doubt in order to produce science-but few people heed the
importance of not exiting from it prematurely .... It is a fact that
one usually exits doubt without realizing it." He warns us further:
"We are dogma-prone from our mother's wombs."
By the confirmation error discussed in Chapter 5, we use the example
of games, which probability theory was successful at tracking, and
claim that this is a general case. Furthermore, just as we tend to
underestimate the role of luck in life in general, we tend to
overestimate it in games of chance.
[p132] Alas, we are not manufactured, in our current edition of the
human race, to understand abstract matters-;we need
context. Randomness and uncertainty are abstractions. We respect what
has happened, ignoring what could have happened. In other words, we
are naturally shallow and superficial-and we do not know it. This is
not a psychological problem; it comes from the main property of
information. The dark side of the moon is harder to see; beaming light
on it costs energy. In the same way, beaming light on the unseen is
costly in both computational and mental effort.
[p138] Why on earth do we predict so much? Worse, even, and more
interesting: Why don't we talk about our record in predicting? Why
don't we see how we (almost) always miss the big events? I call this
the scandal of prediction.
[p143] When you are employed, hence dependent on other people's
judgment, looking busy can help you claim responsibility for the
results in a random environment. The appearance of busyness reinforces
the perception of causality, of the link between results and one's
role in them. This of course applies even more to the CEOs of large
companies who need to trumpet a link between their "presence" and
"leadership" and the results of the company. I am not aware of any
studies that probe the usefulness of their time being invested in
conversations and the absorption of small-time information-nor have
too many writers had the guts to question how large the CEO's role is
in a corporation's success.
Let us discuss one main effect of information: impediment to knowledge.
[p144] The more information you give someone, the more hypotheses they
will formulate along the way, and the worse off they will be. They see
more random noise and mistake it for information.
The problem is that our ideas are sticky: once we produce a theory, we
are not likely to change our minds-so those who delay developing their
theories are better off. When you develop your opinions on the basis
of weak evidence, you will have difficulty interpreting subsequent
information that contradicts these opinions, even if this new
information is obviously more accurate. Two mechanisms are at play
here: the confirmation bias that we saw in Chapter 5, and belief
perseverance, the tendency not to reverse opinions you already
have. Remember that we treat ideas like possessions, and it will be
hard for us to part with them.
[p149] One elementary empirical test is to compare these star
economists to a hypothetical cabdriver (the equivalent of Mikhail from
Chapter 1): you create a synthetic agent, someone who takes the most
recent number as the best predictor of the next, while assuming that
he does not know anything. Then all you have to do is compare the
error rates of the hotshot economists and your synthetic agent. The
problem is that when you are swayed by stories you forget about the
necessity of such testing.
[p151] Tetlock studied the business of political and economic
"experts." He asked various specialists to judge the likelihood of a
number of political, economic, and military events occurring within a
specified time frame (about five years ahead). The outcomes
represented a total number of around twenty-seven thousand
predictions, involving close to three hundred specialists. Economists
represented about a quarter of his sample. The study revealed that
experts' error rates were clearly many times what they had
estimated. His study exposed an expert problem: there was no
difference in results whether one had a PhD or an undergraduate
degree. Well-published professors had no advantage over
journalists. The only regularity Tetlock found was the negative effect
of reputation on prediction: those who had a big reputation were worse
predictors than those who had none.
[p155] Here again, you see the narrative fallacy at work, except that
in place of journalistic stories you have the more dire situation of
the "scientists" with a Russian accent looking in the rearview mirror,
narrating with equations, and refusing to look ahead because he may
get too dizzy. The econometrician Robert Engel, an otherwise charming
gentleman, invented a very complicated statistical method called GARCH
and got a Nobel for it. No one tested it to see if it has any validity
in real life. Simpler, less sexy methods fare exceedingly better, but
they do not take you to Stockholm. You have an expert problem in
Stockholm, and I will discuss it in Chapter 17.
This unfitness of complicated methods seems to apply to all methods.
[p166] The managers flew across the world in order to meet: Barcelona,
Hong Kong, et cetera. A lot of miles for a lot of verbiage. Needless
to say they were usually sleep-deprived. Being an executive does not
require very developed frontal lobes, but rather a combination of
charisma, a capacity to sustain boredom, and the ability to shallowly
perform on harrying schedules. Add to these tasks the "duty" of
attending opera performances.
The managers sat down to brainstorm during these meetings, about, of
course, the medium-term future-they wanted to have "vision." But then
an event occurred that was not in the previous five-year plan: the
Black Swan of the Russian financial default of 1998 and the
accompanying meltdown of the values of Latin American debt markets. It
had such an effect on the firm that, although the institution had a
sticky employment policy of retaining managers, none of the five was
still employed there a month after the sketch of the 1998 five-year
Yet I am confident that today their replacements are still meeting to
work on the next "five-year plan." We never learn.
[p167] We forget about unpredictability when it is our turn to
predict. This is why people can read this chapter and similar
accounts, agree entirely with them, yet fail to heed their arguments
when thinking about the future.
Take this dramatic example of a serendipitous discovery. Alexander
Fleming was cleaning up his laboratory when he found that penicillium
mold had contaminated one of his old experiments. He thus happened
upon the antibacterial properties of penicillin, the reason many of us
are alive today (including, as I said in Chapter 8, myself, for
typhoid fever is often fatal when untreated). True, Fleming was
looking for "something," but the actual discovery was simply
[p168] As happens so often in discovery, those looking for evidence
did not find it; those not looking for it found it and were hailed as
[p169] Engineers tend to develop tools for the pleasure of developing
tools, not to reduce nature to yield its secrets. It so happens that
some of these tools bring us more knowledge; because of the
silent evidence effect, we forget consider tools that accomplished
nothing but keeping engineers off the streets. Tools lead to unexpected
discoveries, which themselves lead to other unexpected discoveries. But
rarely do our tools seem to work as intended; it is only the engineer's
gusto and love for the building of toys and chines that contribute to
the augmentation of our knowledge. Knowledge does not progress from
tools designed to verify or help theories, but rather the opposite. The
computer was not built to allow us to develop new, visual, geometric
mathematics, but for some other purpose. It happened to allow us to
discover mathematical objects that few cared to look for. Nor was the
computer invented to let you chat with your friends in Siberia, but it
has caused some long-distance relationships to bloom.
As an essayist, I can attest that the Internet has helped me to spread
my ideas by bypassing journalists. But this was not the stated purpose
of its military designer.
[p170] Yet just consider the effects of the laser in the world around
you: compact disks, eyesight corrections, microsurgery, data storage
and retrieval-all unforeseen applications of the technology.
We build toys. Some of those toys change the world.
[p170] "Luck favors the prepared," Pasteur said, and, like all great
discoverers, he knew something about accidental discoveries. The best
way to get maximal exposure is to keep researching. Collect
opportunities--on that, later.
[p172] This point can be generalized to all forms of knowledge. There
is actually a law in statistics called the
law of iterated expectations,
which I outline here in its strong form: if I expect
to expect something at some date in the future, then I already expect
that something at present.
[p172] This incapacity is not trivial. The mere knowledge that
something has been invented often leads to a series of inventions of a
similar nature, even though not a single detail of this invention has
been disseminated--there is no need to find the spies and hang them
publicly. In mathematics, once a proof of an arcane theorem has been
announced, we frequently witness the proliferation of similar proofs
coming out of nowhere, with occasional accusations of leakage and
plagiarism. There may be no plagiarism: the information that the
solution exists is itself a big piece of the solution.
[p178] This multiplicative difficulty leading to the need for greater
and greater precision in assumptions can be illustrated with the
following simple exercise concerning the prediction of the movements
of billiard balls on a table. I use the example as computed by the
mathematician Michael Berry. If you know a set of basic parameters
concerning the ball at rest, can compute the resistance of the table
(quite elementary), and can gauge the strength of the impact, then it
is rather easy to predict what would happen at the first hit. The
second impact becomes more complicated, but possible; you need to be
more careful Clbout your knowledge of the initial states, and more
precision is called for. The problem is that to correctly compute the
ninth impact, you need to take into account the gravitational pull of
someone standing next to the table (modestly, Berry's computations use
a weight of less than 150 pounds). And to compute the fifty-sixth
impact, every single elementary particle of the universe needs to be
present in your assumptions! An electron at the edge of the universe,
separated from us by 10 billion light-years, must figure in the
calculations, since it exerts a meaningful effect on the outcome. Now,
consider the additional burden of having to incorporate predictions
about where these variables will be in the future. Forecasting
the motion of a billiard ball on a pool table requires knowledge of
the dynamics of the entire universe, down to every single atom! We can
easily predict the movements of large objects like planets (though not
too far into the future), but the smaller entities can be difficult to
figure out--and there are so many more of them.
[p178] Poincare proposed that we can only work with qualitative [p179]
matters-some property of systems can be discussed, but not
computed. You can think rigorously, but you cannot use
numbers. Poincare even invented a field for this, analysis in situ,
now part of topology. Prediction and forecasting are a more
complicated business. than is commonly accepted, but it takes someone
who knows mathematics to understand that. To accept it takes both
understanding and courage.
[p185] Alas, it turns out that it was [Paul] Samuelson and most of his
followers who did not know much math, or did not know how to use what
math they knew, how to apply it to reality. They only knew enough math
to be blinded by it.
[p189] We have a natural tendency to listen to the exper, even in
fields where there may be no experts.
Everyone has an idea of utopia. For many it means equality, universal
justice, freedom from oppression, freedom from work (for some it may
be the more modest, though no more attainable, society with commuter
trains free of lawyers on cell phones). To me utopia is an
epistemocracy, a society in which anyone of rank is an epistemocrat,
and where epistemocrats manage to be elected. It would be a society
governed from the basis of the awareness of ignorance, not knowledge.
Alas, one cannot assert authority by accepting one's own fallibility.
Simply, people need to be blinded by knowledge-we are made to follow
leaders who can gather people together because the advantages of being
in groups trump the disadvantages of being alone. It has been more
profitable for us to bind together in the wrong direction than to be
alone in the right one. Those who have followed the assertive idiot
rather than the introspective wise person have passed us some of their
genes. This is apparent from a social pathology: psychopaths rally
[p202] Where I beg to differ with the great man [Bertrand Russell] is
that I do not believe in the track record of advice-giving
"philosophy" in helping us deal with the problem; nor do I believe
that virtues can be easily taught; nor do I urge people to
strain in order to avoid making a judgment. Why? Because we have to
deal with humans as humans. We cannot teach people to withhold
judgment; judgments are embedded in the way we view objects. I do not
see a "tree"; I see a pleasant or an ugly tree. It is not possible
without great, paralyzing effort to strip these small values we attach
to matters. Likewise, it is not possible to hold a situation in one's
head without some element of bias.
[p203] Know how to rank beliefs not according to their plausibility
but by the harm they may cause.
The bottom line: be prepared! Narrow-minded prediction has an
analgesic or therapeutic effect. Be aware of the numbing effect of
magic numbers. Be prepared for all relevant eventualities.
THE IDEA OF POSITIVE ACCIDENT
Recall the empirics, those members of the Greek school of empirical
medicine. They considered that you should be open-minded in your
medical diagnoses to let luck play a role.
[p204] In Japanese culture, which is ill-adapted to randomness and
badly equipped to understand that bad performance can come from bad
luck, losses can severely tarnish someone's reputation. People hate
volatility, thus engage in strategies exposed to blowups, leading to
occasional suicides after a big loss.
Furthermore, this trade-off between volatility and risk can show up in
[p205] careers that give the appearance of being stable, like jobs at
IBM until the 1990s. When laid off, the employee faces a total void:
he is no longer fit for anything else. The same holds for those in
protected industries. On the other hand, consultants can have volatile
earnings as their clients' earnings go up and down, but face a lower
risk of starvation, since their skills match demand-fluetuat nec
mergitur (fluctuates but doesn't sink).
[p205] [footnote] Make sure that you have plenty of these small bets;
avoid being blinded by the vividness of one single Black Swan. Have as
many of these small bets as you can conceivably have. Even venture
capital firms fall for the narrative fallacy with a few stories that
"make sense" to them; they do not have as many bets as they should. If
venture capital firms are profitable, it is not because of the stories
they have in their heads, but because they are exposed to unplanned
[p206] Here are the (modest) tricks. But note that the more modest
they are, the more effective they will be.
a. First, make adistinctionbetween positive contingencies
and negative ones. Learn to distinguish between those human
undertakings, in which the lack of predictability can be (or has
been) extremely beneficial and those where the failure to understand
the future caused harm. There are both positive and negative Black
[p208] b. Don't look for the precise and the local. Simply, do
not be narrowminded. The great discoverer Pasteur, who came up with
the notion that chance favors the prepared, understood that you do not
look for something particular every morning but work hard to let
contingency enter your working life. As Yogi Berra, another great
thinker, said, "You got to be very careful if you don't know where
you're going, because you might not get there."
[p208] Remember that infinite vigilance is just not possible.
c. Seize any opportunity, or anything that looks like
opportunity. They are rare, much rarer than you think. Remember
that positive Black Swans have a necessary first step: you need to be
exposed to them. Many people do not realize that they are getting a
lucky break in life when they get it. If a big publisher (or a big art
dealer or a movie executive or a hotshot banker or a big thinker)
suggests [p209] an appointment, cancel anything you have planned: you may
never see such a window open up again.
[p209] d. Beware of precise plans by governments. As discussed
in Chapter 10, let governments predict (it makes officials feel better
about themselves and justifies their existence) but do not set much
store by what they say. Remember that the interest of these civil
servants is to survive and self-perpetuate--not to get to the
truth. It does not mean that governments are useless, only that you
need to keep a vigilant eye on their side effects.
[p210] e. "There are some people who, if they don't already know, you
can't tell 'em," as the great philosopher of uncertainty Yogi Berra
once said. Do not waste your time trying to fight forecasters, stock
analysts, economists, and social scientists, except to play pranks on
them. They are considerably easy to make fun of, and many get angry
quite readily. It is ineffective to moan about unpredictability:
people will continue to predict foolishly, especially if they are paid
for it, and you cannot put an end to institutionalized frauds., If you
ever do have to heed a forecast, keep in mind that its accuracy
degrades rapidly as you extend it through time.
[p210] The Great Asymmetry
All these recommendations have one point in common: asymmetry. Put
yourself in situations where favorable consequences are much larger
than unfavorable ones.
Indeed, the notion of asymmetric outcomes as the central idea of this
book: I will never get to know the unknown since, by definition, it is
unknown. However, I can always guess how it might affect me, and I
should base my decisions around that.
[p211] We can have a clear idea of the consequences of an event, even
if we do not know how likely it is to occur. I don't know the odds of
an earthquake, but I can imagine how San Francisco might be affected
by one. This idea that in order to make a decision you need to focus
on the consequences (which you can know) rather than the probability
(which you can't know) is the central idea of uncertainty. Much of my
life is based on it.
[p211] The next chapter shows why I am optimistic that the academy is
losing its power and ability to put knowledge in straitjackets and
that more out-of-the-box knowledge will be generated Wiki-style.
[p220] What people call "memes," ideas that spread and that compete
with one another using people as carriers, are not truly like
genes. Ideas spread because, alas, they have for carriers self-serving
agents who are interested in them, and interested in distorting them
in the replication process. You do not make a cake for the sake of
merely replicating a recipe-you try to make your own cake, using ideas
from others to improve it. We humans are not photocopiers.
[p225] In sum, the long tail is a by-product of Extremistan that makes
it somewhat less unfair: the world is made no less unfair for the
little guy, but it now becomes extremely unfair for the big
man. Nobody is truly established. The little guy is very subversive.
[p227] REVERSALS AWAY FROM EXTREMISTAN
There is, inevitably, a mounting tension between our society, full of
concentration, and our classical idea of aurea mediocritas, the golden
mean, so it is conceivable that efforts may be made to reverse such
concentration. We live in a society of one person, one vote, where
progressive taxes have been enacted precisely to weaken the
winners. Indeed, the rules of society can be easily rewritten by those
at the bottom of the pyramid to prevent concentration from hurting
them. But it does not require voting to do soreligion could soften the
problem. Consider that before Christianity, in many societies the
powerful had many wives, thus preventing those at the bottom from
accessing wombs, a condition that is not too different from the
reproductive exclusivity of alpha males in many species. But
Christianity reversed this, thanks to the one man-one woman
rule. Later, Islam came to limit the number of wives to four. Judaism,
which had been polygenic, became monogamous in the Middle Ages. One
can say that such a strategy has been successful-the institution of
tightly monogamous marriage (with no official concubine, as in the
Greco-Roman days), even when practiced the "French way," provides
social stability since there is no pool of angry, sexually deprived
men at the bottom fomenting a revolution just so they can have the
chance to mate.
But I find the emphasis on economic inequality, at the expense of
other types of inequality, extremely bothersome. Fairness is not
exclusively an economic matter; it becomes less and less so when we
are satisfying our basic material needs. It is pecking order that
matters! The superstars will always be there. The Soviets may have
flattened the economic structure, but they encouraged their own brand
of iibermensch. What is poorly understood, or denied (owing to its
unsettling implications), is the absence of a role for the average in
intellectual production. The disproportionate share of the very few in
intellectual influence is even more unsettling than the unequal
distribution of wealth-unsettling because, unlike the income gap, no
social policy can eliminate it. Communism could conceal or compress
income discrepancies, but it could not eliminate the superstar system
in intellectual life.
[p228] Winners kill their peers as those in a steep social gradient
live shorter lives, regardless of their economic condition.
I do not know how to remedy this (except through religious
beliefs). Is insurance against your peers' demoralizing success
possible? Should the Nobel Prize be banned? Granted the Nobel medal in
economics has not been good for society or knowledge, but even those
rewarded for real contributions in medicine and physics too rapidly
displace others from our consciousness, and steal longevity away from
them. Extremistan is here to stay, so we have to live with it, and
find the tricks that make it more palatable.
[p228] I had time to kill at the airport and it was a great
opportunity for me to buy dark European chocolate, especially since I
have managed to successfully convince myself that airport calories
[p232] [footnote] One of the most misunderstood aspects of a Gaussian
is its fragility and vulnerability in the estimation of tail
events. The odds of a 4 sigma move are twice that of a 4.15 sigma. The
odds of a 20 sigma are a trillion times higher than those of a 21
sigma! It means that a small measurement error of the sigma will lead
to a massive under-estimation of the probability. We can be a trillion
times wrong about some events.
[p237] I've had plenty of cups of coffee in my life (it's my principal
[p245] This explains why empirical psychology and its insights on
human nature, which I presented in the earlier parts of this book, are
robust to the mistake of using the bell curve; they are also lucky,
since most of their variables allow for the application of
conventional Gaussian statistics. When measuring how many people in a
sample have a bias, or make a mistake, these studies generally elicit
a yeslno type of result. No single observation, by itself, can disrupt
their overall findings.
[p250] Those Comforting Assumptions
Note the central assumptions we made in the coin-flip game that led to
the proto-Gaussian, or mild randomness.
First central assumption: the flips are independent of one
another. The conin no memory. The fact that you got heads or tails on
the previous flip does not change the odds of your getting heads or
tails on the next one. You do not become a "better" coin flipper over
time. If you introduce memory, or skills in flipping, the entire
Gaussian business becomes shaky.
[p251] Second central assumption: no "wild" jump. The step size in the
bu~lding block of the basic random walk is always known, namely one
step. There is no uncertainty as to the size of the step. We did not
encounter situations in which the move varied wildly.
Remember that if either of these two central assumptions is not met,
your moves (or coin tosses) will not cumulatively lead to the bell
curve. Depending on what happens, they can lead to the wild
Mandelbrotian-style scale-invariant randomness.
[p252] I sometimes get a little emotional because I've spent a large
part of my life thinking about this problem. Since I started thinking
about it, and conducting a variety of thought experiments as I have
above, I have not for the life of me been able to find anyone around
me in the business and statistical world who was intellectually
consistent in that he both accepted the Black Swan and rejected the
Gaussian and Gaussian tools. Many people accepted my Black Swan idea
but could not take it to its logical conclusion, which is that you
cannot use one single measure for randomness called standard deviation
(and call it "risk"); you cannot expect a simple answer to
characterize uncertainty. To go the extra step requires courage,
commitment, an ability to connect the dots, a desire to understand
randomness fully. It also means not accepting other people's wisdom as
gospel. Then I started finding physicists who had rejected the
Gaussian tools but fell for another sin: gullibility about precise
predictive models, mostly elaborations around the preferential
attachment of Chapter 14another form of Pia tonicity. I could not find
anyone with depth and scientific technique who looked at the world of
randomness and understood its nature, who looked at calculations as an
aid, not a principal aim. It took me close to a decade and a half to
find that thinker, the man who made many swans gray: Mandelbrot-the
great Benoit Mandelbrot.
[p268] [N]early everyone who works with data but doesn't make
decisions on the basis of these data tends to be guilty of the same
sin, a variation of the narrative fallacy. In the absence of a
feedback process you look at models and think that they confirm
reality. [...] As a matter of fact, complexity theory should make us
more suspicious of scientific claims of precise models of reality. It
does not make all the swans white; that is predictable: it makes them
gray, and only gray.
[p269] I thought that finance and economics were just a place where one
learned from various empirical phenomena and filled up one's bank
account with f*you cash before leaving for bigger and better
things. Mandelbrot's answer was, "Data, a gold mine of data."
Indeed, everyone forgets that he started in economics before moving on
to physics and the geometry of nature. Working with such abundant data
humbles us; it provides the intuition of the following error:
traveling the road between representation and reality in the wrong
[p284] I care about the premises more than the theories, and I want to
minimize reliance on theories, stay light on my feet, and reduce my
surprises. I want to be broadly right rather than precisely
wrong. Elegance in the theories is often indicative of Platonicity and
weakness--it invites you to seek elegance for elegance's sake. A theory
is like medicine (or government): often useless, sometimes necessary,
always self-serving, and on occasion lethal. So it needs to be used
with care, moderation, and close adult supervision.
[p290] I hope I've sufficiently drilled home the notion that, as a
practitioner, my thinking is rooted in the belief that you cannot go
from books to problems, but the reverse, from problems to books. This
approach incapacitates much of that career-building verbiage.
[p297] It is more difficult to be a loser in a game you set up yourself.
In Black Swan terms, this means that you are exposed to the improbable
only if you let it control you. You always control what you do; so
make this your end.
 Stop looking a gift horse in the mouth--remeber that you are a
Black Swan. And thank you for reading my book