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Mental Models

The Tyranny of the Accident

Taleb contrasts domains where many ordinary observations determine the total with domains where a few extreme observations can dominate it. He calls them Mediocristan and Extremistan. The distinction affects how much past experience can tell us about future outcomes. It is a rough framework: an extreme event need not be an unpredictable Black Swan.

THE IDEA

The Tyranny of the Accident

Another way to rephrase the general distinction is as follows: Mediocristan is where we must endure the tyranny of the collective, the routine, the obvious, and the predicted; Extremistan is where we are subjected to the tyranny of the singular, the accidental, the unseen, and the unpredicted. As hard as you try, you will never lose a lot of weight in a single day; you need the collective effect of many days, weeks, even months. Likewise, if you work as a dentist, you will never get rich in a single day—but you can do very well over thirty years of motivated, diligent, disciplined, and regular attendance to teeth-drilling sessions. If you are subject to Extremistan-based speculation, however, you can gain or lose your fortune in a single minute.

Table 1 summarizes the differences between the two dynamics; confusing the left column with the right one can lead to dire (or extremely lucky) consequences.

TABLE 1
Mediocristan Extremistan
Nonscalable Scalable
Mild or type 1 randomness Wild (even superwild) or type 2 randomness
The most typical member is mediocre The most “typical” is either giant or dwarf, i.e., there is no typical member
Winners get a small segment of the total pie Winner-take-almost-all effects
Example: audience of an opera singer before the gramophone Today’s audience for an artist
More likely to be found in our ancestral environment More likely to be found in our modern environment
Impervious to the Black Swan Vulnerable to the Black Swan
Subject to gravity There are no physical constraints on what a number can be
Corresponds (generally) to physical quantities, i.e., height Corresponds to numbers, say, wealth
As close to utopian equality as reality can spontaneously deliver Dominated by extreme winner-take-all inequality
Total is not determined by a single instance or observation Total will be determined by a small number of extreme events
When you observe for a while you can get to know what’s going on It takes a long time to know what’s going on
Tyranny of the collective Tyranny of the accidental
Easy to predict from what you see and extend to what you do not see Hard to predict from past information
History crawls History makes jumps
Events are distributed * according to the “bell curve” (the GIF) or its variations The distribution is either Mandelbrotian “gray” Swans (tractable scientifically) or totally intractable Black Swans

* What I call “probability distribution” here is the model used to calculate the odds of different events, how they are distributed. When I say that an event is distributed according to the “bell curve,” I mean that the Gaussian bell curve (after C. F. Gauss; more on him later) can help provide probabilities of various occurrences.

This framework, showing that Extremistan is where most of the Black Swan action is, is only a rough approximation—please do not Platonify it; don’t simplify it beyond what’s necessary.

Extremistan does not always imply Black Swans. Some events can be rare and consequential, but somewhat predictable, particularly to those who are prepared for them and have the tools to understand them (instead of listening to statisticians, economists, and charlatans of the bell-curve variety). They are near–Black Swans. They are somewhat tractable scientifically—knowing about their incidence should lower your surprise; these events are rare but expected. I call this special case of “gray” swans Mandelbrotian randomness. This category encompasses the randomness that produces phenomena commonly known by terms such as scalable, scale-invariant, power laws, Pareto-Zipf laws, Yule’s law, Paretian-stable processes, Levy-stable, and fractal laws, and we will leave them aside for now since they will be covered in some depth in Part Three. They are scalable, according to the logic of this chapter, but you can know a little more about how they scale since they share much with the laws of nature.

You can still experience severe Black Swans in Mediocristan, though not easily. How? You may forget that something is random, think that it is deterministic, then have a surprise. Or you can tunnel and miss on a source of uncertainty, whether mild or wild, owing to lack of imagination—most Black Swans result from this “tunneling” disease, which I will discuss in Chapter 9.*

This “literary” overview offers a rough way to distinguish the two domains. The distinction matters for knowledge: how much can the observations we have made tell us about outcomes we have not seen?

* To those readers who Googled Yevgenia Krasnova, I am sorry to say that she is (officially) a fictional character.

* I emphasize possible because the chance of these occurrences is typically in the order of one in several trillion trillion, as close to impossible as it gets.

* It is worth mentioning here that one of the mistakes people make in the interpretation of the Black Swan idea is that they believe that Black Swans are more frequent than in our imagination. Not quite the point. Black Swans are more consequential, not necessarily more frequent. There are actually fewer remote events, but they are more and more extreme in their impact, which confuses people, as they tend to write them off more easily.

Chapter Four

ONE THOUSAND AND ONE DAYS, OR HOW NOT TO BE A SUCKER

Surprise, surprise—Sophisticated methods for learning from the future—Sextus was always ahead—The main idea is not to be a sucker—Let us move to Mediocristan, if we can find it

Figure from the source book

Which brings us to the Black Swan problem in its original form.

Imagine someone of authority and rank, operating in a place where rank matters—say, a government agency or a large corporation. He could be a verbose political commentator on Fox News stuck in front of you at the health club (impossible to avoid looking at the screen), the chairman of a company discussing the “bright future ahead,” a Platonic medical doctor who has categorically ruled out the utility of mother’s milk (because he did not see anything special in it), or a Harvard Business School professor who does not laugh at your jokes. He takes what he knows a little too seriously.

Say that a prankster surprises him one day by surreptitiously sliding a thin feather up his nose during a moment of relaxation. How would his dignified pompousness fare after the surprise? Contrast his authoritative demeanor with the shock of being hit by something totally unexpected that he does not understand. For a brief moment, before he regains his bearings, you will see disarray in his face.

I confess having developed an incorrigible taste for this kind of prank during my first sleepaway summer camp. Introduced into the nostril of a sleeping camper, a feather would induce sudden panic. I spent part of my childhood practicing variations on the prank: in place of a thin feather you can roll the corner of a tissue to make it long and narrow. I got some practice on my younger brother. An equally effective prank would be to drop an ice cube down someone’s collar when he expects it least, say during an official dinner. I had to stop these pranks as I got deeper into adulthood, of course, but I am often involuntarily hit with such an image when bored out of my wits in meetings with serious-looking businesspersons (dark suits and standardized minds) theorizing, explaining things, or talking about random events with plenty of “because” in their conversation. I zoom in on one of them and imagine the ice cube sliding down his back—it would be less fashionable, though certainly more spectacular, if you put a living mouse there, particularly if the person is ticklish and is wearing a tie, which would block the rodent’s normal route of exit.*

Pranks can be compassionate. I remember in my early trading days, at age twenty-five or so, when money was starting to become easy. I would take taxis, and if the driver spoke skeletal English and looked particularly depressed, I’d give him a $100 bill as a tip, just to give him a little jolt and get a kick out of his surprise. I’d watch him unfold the bill and look at it with some degree of consternation ($1 million certainly would have been better but it was not within my means). It was also a simple hedonic experiment: it felt elevating to make someone’s day with the trifle of $100. I eventually stopped; we all become stingy and calculating when our wealth grows and we start taking money seriously.

I don’t need much help from fate to get larger-scale entertainment: reality provides such forced revisions of beliefs at quite a high frequency. Many are quite spectacular. In fact, the entire knowledge-seeking enterprise is based on taking conventional wisdom and accepted scientific beliefs and shattering them into pieces with new counterintuitive evidence, whether at a micro scale (every scientific discovery is an attempt to produce a micro–Black Swan) or at a larger one (as with Poincaré’s and Einstein’s relativity). Scientists may be in the business of laughing at their predecessors, but owing to an array of human mental dispositions, few realize that someone will laugh at their beliefs in the (disappointingly near) future. In this case, my readers and I are laughing at the present state of social knowledge. These big guns do not see the inevitable overhaul of their work coming, which means that you can usually count on them to be in for a surprise.

When to use it

  • When analyzing a portfolio, ask whether a few extreme losses could dominate the result. Diversification or the label of a familiar asset class does not, by itself, establish Mediocristan behavior.

  • Compare earnings tied to hours of work with scalable earnings from a recording, product or business. Keep that income comparison separate from the other risks a career may involve.

  • In disaster planning, examine severe outcomes that average conditions may conceal. Distinguish a rare event that can be anticipated from one that lies outside the working model.

FROM THEORY TO EVERYDAY LIFE

In practice

01

Weight loss vs Dentist income

Taleb contrasts ordinary weight change and income earned through repeated dental work with a speculator’s gains and losses. In the former examples, many small contributions accumulate over time; in the latter, a single event can dominate the result.

02

Opera singer audience before and after gramophone

Before the gramophone, an opera singer's audience was limited by physical venue size (Mediocristan). Today, an artist can reach millions instantly (Extremistan), leading to winner-take-all inequality.

03

Prank with a feather

Taleb imagines a pompous authority figure startled by a feather. The prank provides a comic contrast between confident composure and an unexpected shock; surprise alone does not make an event a consequential Black Swan.

✳

A MOMENT TO REFLECT

Put it to work.

  1. In which domain (Mediocristan or Extremistan) does your daily work or main source of income lie? How does that affect your risk management?

  2. Can you identify a Black Swan event in your personal or professional life that had an outsized impact? What made it unpredictable?

  3. How might the 'tunneling disease'—focusing on one source of uncertainty while ignoring others—lead to surprises in your decision-making?

Connected ideas

Another lens can bring the same problem into focus.

Often confused with

CONTINUE THE CONVERSATION

Source texts

  • The Black Swan The Impact of the Highly Improbable With a new section On Robustness and Fragility (Nassim Nicholas Taleb)
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