open mind and the desire to probe the ideas of others. Above all, an erudite
can be dissatisfied with his own knowledge, and such dissatisfaction
is a wonderful shield against Platonicity, the simplifications of the fiveminute
manager, or the philistinism of the overspecialized scholar. Indeed,
scholarship without erudition can lead to disasters.
ONE THOUSAND AND ONE DAYS, OR HOW NOT T O BE A S U C K E R 49
/ Don't Want to Be a Turkey
But promoting philosophical skepticism is not quite the mission of this
book. If awareness of the Black Swan problem can lead us into withdrawal
and extreme skepticism, I take here the exact opposite direction. I
am interested in deeds and true empiricism. So, this book was not written
by a Sufi mystic, or even by a skeptic in the ancient or medieval sense, or
even (we will see) in a philosophical sense, but by a practitioner whose
principal aim is to not be a sucker in things that matter, period.
Hume was radically skeptical in the philosophical cabinet, but abandoned
such ideas when it came to daily life, since he could not handle
them. I am doing here the exact opposite: I am skeptical in matters that
have implications for daily life. In a way, all I care about is making a decision
without being the turkey.
Many middlebrows have asked me over the past twenty years, "How
do you, Taleb, cross the street given your extreme risk consciousness?" or
have stated the more foolish "You are asking us to take no risks." Of
course I am not advocating total risk phobia (we will see that I favor an
aggressive type of risk taking): all I will be showing you in this book is
how to avoid crossing the street blindfolded.
They Want to Live in Mediocristan
I have just presented the Black Swan problem in its historical form: the
central difficulty of generalizing from available information, or of learning
from the past, the known, and the seen. I have also presented the list of
those who, I believe, are the most relevant historical figures.
You can see that it is extremely convenient for us to assume that we
live in Mediocristan. Why? Because it allows you to rule out these Black
Swan surprises! The Black Swan problem either does not exist or is of
small consequence if you live in Mediocristan!
Such an assumption magically drives away the problem of induction,
which since Sextus Empiricus has been plaguing the history of thinking.
The statistician can do away with epistemology.
Wishful thinking! We do not live in Mediocristan, so the Black Swan
needs a different mentality. As we cannot push the problem under the rug,
we will have to dig deeper into it. This is not a terminal difficulty—and we
can even benefit from it.
50 UMBERTO E C O ' S A N T I L I B R A RY
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).
I will discuss each of the points in the next five chapters. Then, in the
conclusion of Part One, I will show how, in effect, they are the same topic.
Chapter Five
CONFIRMATION SHMONFIRMATION!
/ have so much evidence—Can Zoogles be (sometimes) Boogies?—
Corroboration shmorroboration—Popper's idea
As much as it is ingrained in our habits and conventional wisdom, confirmation
can be a dangerous error.
Assume I told you that I had evidence that the football player O. J .
Simpson (who was accused of killing his wife in the 1990s) was not a
criminal. Look, the other day I had breakfast with him and he didn't kill
anybody. I am serious, I did not see him kill a single person. Wouldn't that
confirm his innocence? If I said such a thing you would certainly call a
shrink, an ambulance, or perhaps even the police, since you might think
that I spent too much time in trading rooms or in cafés thinking about this
Black Swan topic, and that my logic may represent such an immediate
danger to society that I myself need to be locked up immediately.
You would have the same reaction if I told you that I took a nap the
other day on the railroad track in New Rochelle, New York, and was not
killed. Hey, look at me, I am alive, I would say, and that is evidence that
lying on train tracks is risk-free. Yet consider the following. Look again at
Figure 1 in Chapter 4; someone who observed the turkey's first thousand
days (but not the shock of the thousand and first) would tell you, and
rightly so, that there is no evidence of the possibility of large events, i.e.,
52 UMBERTO E C O ' S A N T I L I B R A RY
Black Swans. You are likely to confuse that statement, however, particularly
if you do not pay close attention, with the statement that there is
evidence of no possible Black Swans. Even though it is in fact vast, the
logical distance between the two assertions will seem very narrow in your
mind, so that one can be easily substituted for the other. Ten days from
now, if you manage to remember the first statement at all, you will be
likely to retain the second, inaccurate version—that there is proof of no
Black Swans. I call this confusion the round-trip fallacy, since these statements
are not interchangeable.
Such confusion of the two statements partakes of a trivial, very trivial
(but crucial), logical error—but we are not immune to trivial, logical errors,
nor are professors and thinkers particularly immune to them (complicated
equations do not tend to cohabit happily with clarity of mind).
Unless we concentrate very hard, we are likely to unwittingly simplify the
problem because our minds routinely do so without our knowing it.
It is worth a deeper examination here.
Many people confuse the statement "almost all terrorists are Moslems"
with "almost all Moslems are terrorists." Assume that the first statement
is true, that 99 percent of terrorists are Moslems. This would mean that
only about .001 percent of Moslems are terrorists, since there are more
than one billion Moslems and only, say, ten thousand terrorists, one in a
hundred thousand. So the logical mistake makes you (unconsciously)
overestimate the odds of a randomly drawn individual Moslem person
(between the age of, say, fifteen and fifty) being a terrorist by close to fifty
thousand times!
The reader might see in this round-trip fallacy the unfairness of
stereotypes—minorities in urban areas in the United States have suffered
from the same confusion: even if most criminals come from their ethnic
subgroup, most of their ethnic subgroup are not criminals, but they still
suffer from discrimination by people who should know better.
"I never meant to say that the Conservatives are generally stupid. I
meant to say that stupid people are generally Conservative," John Stuart
Mill once complained. This problem is chronic: if you tell people that the
key to success is not always skills, they think that you are telling them that
it is never skills, always luck.
Our inferential machinery, that which we use in daily life, is not made
for a complicated environment in which a statement changes markedly
when its wording is slightly modified. Consider that in a primitive environment
there is no consequential difference between the statements most
CONFIRMATION SHMONFIRMATION! 53
killers are wild animals and most wild animals are killers. There is an
error here, but it is almost inconsequential. Our statistical intuitions have
not evolved for a habitat in which these subtleties can make a big difference.
Zoogles Are Not All Boogies
All zoogles are boogies. You saw a boogie. Is it a zoogle? Not necessarily,
since not all boogies are zoogles; adolescents who make a mistake in answering
this kind of question on their SAT test might not make it to college.
Yet another person can get very high scores on the SATs and still feel
a chill of fear when someone from the wrong side of town steps into the
elevator. This inability to automatically transfer knowledge and sophistication
from one situation to another, or from theory to practice, is a quite
disturbing attribute of human nature.
Let us call it the domain specificity of our reactions. By domain-specific
I mean that our reactions, our mode of thinking, our intuitions, depend on
the context in which the matter is presented, what evolutionary psychologists
call the "domain" of the object or the event. The classroom is a domain;
real life is another. We react to a piece of information not on its
logical merit, but on the basis of which framework surrounds it, and how
it registers with our social-emotional system. Logical problems approached
one way in the classroom might be treated differently in daily
life. Indeed they are treated differently in daily life.
Knowledge, even when it is exact, does not often lead to appropriate
actions because we tend to forget what we know, or forget how to process
it properly if we do not pay attention, even when we are experts. Statisticians,
it has been shown, tend to leave their brains in the classroom and
engage in the most trivial inferential errors once they are let out on the
streets. In 1971, the psychologists Danny Kahneman and Amos Tversky
plied professors of statistics with statistical questions not phrased as statistical
questions. One was similar to the following (changing the example
for clarity): Assume that you live in a town with two hospitals—one large,
the other small. On a given day 60 percent of those born in one of the two
hospitals are boys. Which hospital is it likely to be? Many statisticians
made the equivalent of the mistake (during a casual conversation) of
choosing the larger hospital, when in fact the very basis of statistics is that
large samples are more stable and should fluctuate less from the long-term
average—here, 50 percent for each of the sexes—than smaller samples.
54 UMBERTO E C O ' S A N T I L I B R A RY
These statisticians would have flunked their own exams. During my days
as a quant I counted hundreds of such severe inferential mistakes made by
statisticians who forgot that they were statisticians.
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 modules—
in different situations: our brain lacks a central all-purpose computer
that starts with logical rules and applies them equally to all possible situations.
And as I've said, we can commit a logical mistake in reality but not in
the classroom. This asymmetry is best visible in cancer detection. Take
doctors examining a patient for signs of cancer; tests are typically done on
patients who want to know if they are cured or if there is "recurrence." (In
fact, recurrence is a misnomer; it simply means that the treatment did not
kill all the cancerous cells and that these undetected malignant cells have
started to multiply out of control.) It is not feasible, in the present state of
technology, to examine every single one of the patient's cells to see if all of
them are nonmalignant, so the doctor takes a sample by scanning the body
with as much precision as possible. Then she makes an assumption about
what she did not see. I was once taken aback when a doctor told me after
a routine cancer checkup, "Stop worrying, we have evidence of cure."
"Why?" I asked. "There is evidence of no cancer" was the reply. "How do
you know?" I asked. He replied, "The scan is negative." Yet he went
around calling himself doctor!
An acronym used in the medical literature is NED, which stands for
No Evidence of Disease. There is no such thing as END, Evidence of No
Disease. Yet my experience discussing this matter with plenty of doctors,
even those who publish papers on their results, is that many slip into the
round-trip fallacy during conversation.
Doctors in the midst of the scientific arrogance of the 1960s looked
down at mothers' milk as something primitive, as if it could be replicated
by their laboratories—not realizing that mothers' milk might include useCONFIRMATION
SHMONFIRMATION! 55
fui components that could have eluded their scientific understanding—a
simple confusion of absence of evidence of the benefits of mothers' milk
with evidence of absence of the benefits (another case of Platonicity as "it
did not make sense" to breast-feed when we could simply use bottles).
Many people paid the price for this na?ve inference: those who were not
breast-fed as infants turned out to be at an increased risk of a collection of
health problems, including a higher likelihood of developing certain types
of cancer—there had to be in mothers' milk some necessary nutrients that
still elude us. Furthermore, benefits to mothers who breast-feed were also
neglected, such as a reduction in the risk of breast cancer.
Likewise with tonsils: the removal of tonsils may lead to a higher incidence
of throat cancer, but for decades doctors never suspected that this
