• we humans have the largest cortex, followed by bank executives, dolphins, and our cousins the apes.

• Positive lumpy outcomes, for which we either collect big or get nothing, prevail in numerous occupations, those invested with a sense of mission, such as doggedly pursuing (in a smelly laboratory) the elusive cure for cancer, writing a book that will change the way people view the world (while living hand to mouth), making music,

• If you run a public corporation, things were great for you before you had shareholders, when you and your partners were the sole owners, along with savvy venture capitalists who understood uneven results and the lumpy nature of economic life. But now you have a slow-thinking thirty-year-old security analyst at a downtown Manhattan firm who “judges” your results and reads too much into them. He likes routine rewards, and the last thing you can deliver are routine rewards.

• Many people labor in life under the impression that they are doing something right, yet they may not show solid results for a long time.

• Believe me, it is tough to deal with the social consequences of the appearance of continuous failure. We are social animals; hell is other people.

• 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

• Have you ever wondered why so many of these straight-A students end up going nowhere in life while someone who lagged behind is now getting the shekels, buying the diamonds, and getting his phone calls returned? Or even getting the Nobel Prize in a real discipline (say, medicine)? Some of this may have something to do with luck in outcomes, but there is this sterile and obscurantist quality that is often associated with classroom knowledge that may get in the way of understanding what’s going on in real life. In an IQ test, as well as in any academic setting (including sports), Dr. John would vastly outperform Fat Tony. But Fat Tony would outperform Dr. John in any other possible ecological, real-life situation. In fact, Tony, in spite of his lack of culture, has an enormous curiosity about the texture of reality, and his own erudition—to me, he is more scientific in the literal, though not in the social, sense than Dr. John.

• Two illustrators for a paperback edition of one of my books spontaneously and independently added a die to the cover and below every chapter, throwing me into a state of rage. The editor, familiar with my thinking, warned them to “avoid the ludic fallacy,” as if it were a well-known intellectual violation. Amusingly, they both reacted with an “Ah, sorry, we didn’t know.”

• Meanwhile, what Nietzsche calls bildungsphilisters,fn2 or learned philistines, blue collars of the thinking business, tell you that you are spread out between fields; you reply that these disciplines are artificial and arbitrary, to no avail. Then you tell them that you are a limousine driver, and they leave you alone—you feel better because you do not identify with them, and thus you no longer need to be amputated to fit into the Procrustean bed of the disciplines. Finally, a little push and you see that it was all one single problem.

• If you study Onassis’s life, which I spent part of my early adulthood doing, you would notice an interesting regularity: “work,” in the conventional sense, was not his thing. He did not even bother to have a desk, let alone an office. He was not just a dealmaker, which does not necessitate having an office, but he also ran a shipping empire, which requires day-to-day monitoring. Yet his main tool was a notebook, which contained all the information he needed. Onassis spent his life trying to socialize with the rich and famous, and to pursue (and collect) women. He generally woke up at noon. If he needed legal advice, he would summon his lawyers to some nightclub in Paris at two A.M. He was said to have an irresistible charm, which helped him take advantage of people.

• The Greeks made a distinction between technē and epistēmē. The empirical school of medicine of Menodotus of Nicomedia and Heraclites of Tarentum wanted its practitioners to stay closest to technē (i.e., “craft”), and away from epistēmē (i.e., “knowledge,” “science”).

• 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.

• This unfitness of complicated methods seems to apply to all methods. Another study effectively tested practitioners of something called game theory, in which the most notorious player is John Nash, the schizophrenic mathematician made famous by the film A Beautiful Mind. Sadly, for all the intellectual appeal of these methods and all the media attention, its practitioners are no better at predicting than university students.

• The biotech company seemed to follow implicitly, though not explicitly, Louis Pasteur’s adage about creating luck by sheer exposure. “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.

• Think of a bookworm picking up a new language. He will learn, say, Serbo-Croatian or !Kung by reading a grammar book cover to cover, and memorizing the rules. He will have the impression that some higher grammatical authority set the linguistic regulations so that nonlearned ordinary people could subsequently speak the language. In reality, languages grow organically; grammar is something people without anything more exciting to do in their lives codify into a book. While the scholastic-minded will memorize declensions, the a-Platonic nonnerd will acquire, say, Serbo-Croatian by picking up potential girlfriends in bars on the outskirts of Sarajevo, or talking to cabdrivers, then fitting (if needed) grammatical rules to the knowledge he already possesses.

• Consider again the central planner. As with language, there is no grammatical authority codifying social and economic events; but try to convince a bureaucrat or social scientist that the world might not want to follow his “scientific” equations. In fact, thinkers of the Austrian school, to which Hayek belonged, used the designations tacit or implicit precisely for that part of knowledge that cannot be written down, but that we should avoid repressing. They made the distinction we saw earlier between “know-how” and “know-what”—the latter being more elusive and more prone to nerdification.

• To clarify, Platonic is top-down, formulaic, closed-minded, self-serving, and commoditized; a-Platonic is bottom-up, open-minded, skeptical, and empirical.

• For instance, what is the “optimal” quantity you should allocate to stocks? It involves complicated mathematics and thus raises a barrier to entry by nonmathematically trained scholars. I would not be the first to say that this optimization set back social science by reducing it from the intellectual and reflective discipline that it was becoming to an attempt at an “exact science.” By “exact science,” I mean a second-rate engineering problem for those who want to pretend that they are in the physics department—so-called physics envy. In other words, an intellectual fraud.

• Optimization is a case of sterile modeling that we will discuss further in Chapter 17. It had no practical (or even theoretical) use, and so it became principally a competition for academic positions, a way to make people compete with mathematical muscle. It kept Platonified economists out of the bars, solving equations at night.

• 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 followers.

• As I am writing these lines I am using a Macintosh, by Apple, after years of using Microsoft-based products. The Apple technology is vastly better, yet the inferior software won the day. How? Luck.

• Luck is the grand equalizer, because almost everyone can benefit from it. The socialist governments protected their monsters and, by doing so, killed potential newcomers in the womb.

• I may have something in my genes driving me away from bildungsphilisters.

• He was emphatic: “un homme extraordinaire,” he called Tresser, and could not stop praising him. But when I asked him about a particular famous hotshot, he replied, “He is the prototypical bon élève, a student with good grades, no depth, and no vision.” That hotshot was a Nobel laureate.

• I have just read three “popular science” books that summarize the research in complex systems: Mark Buchanan’s Ubiquity, Philip Ball’s Critical Mass, and Paul Ormerod’s Why Most Things Fail.

• As I have said earlier, the world, epistemologically, is literally a different place to a bottom-up empiricist. We don’t have the luxury of sitting down to read the equation that governs the universe; we just observe data and make an assumption about what the real process might be, and “calibrate” by adjusting our equation in accordance with additional information. As events present themselves to us, we compare what we see to what we expected to see. It is usually a humbling process, particularly for someone aware of the narrative fallacy, to discover that history runs forward, not backward.

• Robert Merton, Jr., and Myron Scholes were founding partners in the large speculative trading firm called Long-Term Capital Management, or LTCM, which I mentioned in Chapter 4. It was a collection of people with top-notch résumés, from the highest ranks of academia. They were considered geniuses. The ideas of portfolio theory inspired their risk management of possible outcomes—thanks to their sophisticated “calculations.” They managed to enlarge the ludic fallacy to industrial proportions.

• The theorems are compatible with other theorems from Modern Portfolio Theory, themselves compatible with still other theorems, building a grand theory of how people consume, save, face uncertainty, spend, and project the future. He assumes that we know the likelihood of events. The beastly word equilibrium is always present. But the whole edifice is like a game that is entirely closed, like Monopoly with all of its rules.

• Now, elegant mathematics has this property: it is perfectly right, not 99 percent so. This property appeals to mechanistic minds who do not want to deal with ambiguities. Unfortunately you have to cheat somewhere to make the world fit perfect mathematics; and you have to fudge your assumptions somewhere.

• The position I suggest should be based both on ignorance and on deference to the wisdom of Mother Nature, since it is older than us, hence wiser than us, and has been proven much smarter than scientists. We do not understand enough about Mother Nature to mess with her—and I do not trust the models used to forecast climate change. Simply, we are facing nonlinearities and magnifications of errors coming from the so-called butterfly effects we saw in Chapter 11, actually discovered by Lorenz using weather-forecasting models.

• Case 1: You give the patient a dose of cyanide, hemlock, or some poisonous substance, assuming they are equally harmful—and assuming, for the case of this experiment, the absence of super-additivity (that is, no synergetic effects). Case 2: You give the patient a tenth of a dose of each of ten such substances, for the same total amount of poison. Clearly we can see that Case 2, by spreading the poison ingested across substances, is at the worst equally harmful (if all the poisonous substances act in the same way), and at the best close to harmless to the patient.

• The best way to illustrate such redundancy is with an aspect of the life story of the colorful philosopher of science Paul Feyerabend. Feyerabend was permanently impotent from a war injury, yet he married four times, and was a womanizer to the point of leaving a trail of devastated boyfriends and husbands whose partners he snatched, and an equally long one of broken hearts, including those of many of his students (in his day, certain privileges were allowed to professors, particularly flamboyant professors of philosophy). This was a particular achievement given his impotence. So there were other parts of the body that came to satisfy whatever it was that made women attached to him. Mother Nature initially created the mouth to eat, perhaps to breathe, perhaps for some other function linked to the existence of the tongue. Then new functions emerged that were most probably not part of the initial plan. Some people use the mouth and tongue to kiss, or to do something more involved to which Feyerabend allegedly had recourse.

• For Aristotle, an object had a clear purpose set by its designer. An eye was there to see, a nose to smell. This is a rationalistic argument, another manifestation of what I call Platonicity. Yet anything that has a secondary use, and one you did not pay for, will present an extra opportunity should a heretofore unknown application emerge or a new environment appear. The organism with the largest number of secondary uses is the one that will gain the most from environmental randomness and epistemic opacity!

• So when you have a lot of functional redundancies, randomness helps on balance, but under one condition—that you can benefit from the randomness more than you can be hurt by it (an argument I call more technically convexity to uncertainty). This is certainly the case with many engineering applications, in which tools emerge from other tools.

• I have given more complicated names to this idea, in addition to convexity, like optionality—since you have the option of taking the freebie from randomness—but this is still work in progress for me. The progress coming from the second type of randomness is what I call tinkering, or bricolage, the subject of my next book.

• Mixing vocabulary has been very common in history. Let me take the idea of chance again. At some point in history the same Latin word, felix (from felicitas) was used to designate both someone lucky and someone happy. (The conflation of happiness and luck was explainable in an antique context: the goddess Felicitas represented both.) The English word luck comes from the Germanic Glück, happiness. An ancient would have seen the distinction between the two concepts as a waste, since all lucky people seem happy (not thinking that one could be happy without being lucky). But in a modern context we need to extricate luck from happiness—utility from probability—in order to perform any psychological analysis of decision making.

• One useful trick, I discovered, is to avoid listening to the question of the interviewer, and answer with whatever I have been thinking about recently. Remarkably, neither the interviewers nor the public notices the absence of correlation between question and answer.

• Organisms need, to use the metaphor of Marcus Aurelius, to turn obstacles into fuel—just as fire does.

• long, very long, slow, meditative (or conversational) walks in a stimulating urban setting, but with occasional (and random) very short sprints, during which I made myself angry imagining I was chasing the bankster Robert Rubin with a big stick, trying to catch him and bring him to human justice. I went to weight-lifting facilities in a random way for a completely stochastic workout—typically in hotels, when I was on the road.

• Saying the maps we had were better than having no maps. (People who do not have experience in cartography, risk “experts,” or worse, employees of the Federal Reserve Bank of the United States.) This is the strangest of errors. I know few people who would board a plane heading for La Guardia airport in New York City with a pilot who was using a map of Atlanta’s airport “because there is nothing else.” People with a functioning brain would rather drive, take the train, or stay home. Yet once they get involved in economics, they all prefer professionally to use in Extremistan the measures made for Mediocristan, on the ground that “we have nothing else.”

• Emre Soyer and Robin Hogarth subsequently took the point and tested it in the use of an abhorrent field called econometrics (a field that, if any scientific scrutiny was applied to it, would not exist)—again, most researchers don’t understand the tools they are using. Now that the book’s reception is off my chest, let us move into more analytical territory.

• I have spent considerable time away from the weight-lifting room repeating that a Black Swan for the turkey is not a Black Swan for the butcher.

• The psychologist Simon Baron-Cohen has produced much research distinguishing between polar extremes in people’s temperament with respect to two faculties: ability to systematize, and ability to empathize and understand others. According to his research, purely systematizing persons suffer from a lack of theory of mind; they are drawn to engineering and similar occupations (and when they fail, to, say, mathematical economics); empathizing minds are drawn to more social (or literary) professions. Fat Tony, of course, would fall in the more social category. Males are overrepresented in the systematizing category; females dominate the other extreme.

• I discovered (but by then I was not even surprised) that no researcher has tested whether large deviations in economics can be predicted from past large deviations—whether large deviations have predecessors, that is. This is one of the elementary tests missing in the field, as elementary as checking whether a patient is breathing or whether a lightbulb is screwed in, but characteristically nobody seems to have tried to do it. It does not take a lot of introspection to figure out that big events don’t have big parents: the Great War did not have a predecessor; the crash of 1987, in which the market went down close to 23 percent in a single day, could not have been guessed from its worst predecessor, a one-day loss of around 10 percent—and this applies to almost all such events, of course. My results were that regular events can predict regular events, but that extreme events, perhaps because they are more acute when people are unprepared, are almost never predicted from narrow reliance on the past.

• These constraints of consistency in decision making are obvious: you cannot bet there is a 60 percent chance of snow tomorrow and a 50 percent chance that there will be no snow. The agent needs to avoid violating something called the Dutch book constraint: that is, you cannot express your probabilities inconsistently by engaging in a series of bets that lock in a certain loss, for example, by acting as if the probabilities of separable contingencies can add up to more than 100 percent. There is another difference

• It means that there is no such thing as a long run for such systems, called “nonergodic” systems—as opposed to the “ergodic” ones. In an ergodic system, the probabilities of what may happen in the long run are not impacted by events that may take place, say, next year. Someone playing roulette in the casino can become very rich, but, if he keeps playing, given that the house has an advantage, he will eventually go bust. Someone rather unskilled will eventually fail. So ergodic systems are invariant, on average, to paths, taken in the intermediate term—what researchers call absence of path dependency. A nonergodic system has no real long-term properties—it is prone to path dependency.

• By focusing on the True/False distinction, epistemology remained, with very few exceptions, prisoner of an inconsequential, and highly incomplete, 2-D framework. The third missing dimension is, of course, the consequence of the True, and the severity of the False, the expectation. In other words, the payoff from decisions, the impact and magnitude of the result of such a decision. Sometimes one may be wrong and the mistake may turn out to be inconsequential. Or one may be right, say, on such a subject as the sex of angels, and it may turn out to be of no use beyond intellectual stamp collecting.

• Seneca was the great teacher and practitioner of Stoicism, who transformed Greek-Phoenician Stoicism from metaphysical and theoretical discourse into a practical and moral program of living, a way to reach the summum bonum, an untranslatable expression depicting a life of supreme moral qualities, as perceived by the Romans. But, even apart from this unreachable aim, he has practical advice, perhaps the only advice I can see transfer from words to practice. Seneca is the one who (with some help from Cicero) taught Montaigne that to philosophize is to learn how to die. Seneca is the one who taught Nietzsche the amor fati, “love fate,” which prompted Nietzsche to just shrug and ignore adversity, mistreatment by his critics, and his disease, to the point of being bored by them.

• Seneca’s credibility as a moral philosopher (to me) came from the fact that, unlike other philosophers, he did not denigrate the value of wealth, ownership, and property because he was poor. Seneca was said to be one of the wealthiest men of his day. He just made himself ready to lose everything every day. Every day. Although his detractors claim that in real life he was not the Stoic sage he claimed to be, mainly on account of his habit of seducing married women (with non-Stoic husbands), he came quite close to it. A powerful man, he just had many detractors—and, if he fell short of his Stoic ideal, he came much closer to it than his contemporaries.

• In Seneca’s Epistle IX, Stilbo’s country was captured by Demetrius, called the Sacker of Cities. Stilbo’s children and his wife were killed. Stilbo was asked what his losses were. Nihil perditi, I have lost nothing, he answered. Omnia mea mecum sunt! My goods are all with me. The man had reached the Stoic self-sufficiency, the robustness to adverse events, called apatheia in Stoic jargon. In other words, nothing that might be taken from him did he consider to be a good.