Aristotle, in his Rhetoric, postulated that envy is something you are more likely to encounter in your own kin: lower classes are more likely to experience envy toward their cousins or the middle class than toward the very rich. And the expression Nobody is a prophet in his own land, making envy a geographical thing (mistakenly thought to originate with Jesus), originates from that passage in the Rhetoric. Aristotle himself was building on Hesiod: cobbler envies cobbler, carpenter envies carpenter. Later, Jean de La Bruyère wrote that jealousy is to be found within the same art, talent, and condition.*10
So I doubt Piketty bothered to ask blue-collar Frenchmen what they want, as Michelle Lamont did (as we saw earlier in the chapter). I am certain that they would ask for better beer, a new dishwasher, or faster trains for their commute, not to bring down some rich businessman invisible to them. But, again, people can frame questions and portray enrichment as theft, as was done before the French Revolution, in which case the blue-collar class would ask, once again, for heads to roll.*11
INEQUALITY, WEALTH, AND VERTICAL SOCIALIZATION
If intellectuals are overly worried about inequality, it is because they tend to view themselves in hierarchical terms, and thus think that others do too. Furthermore, as if by pathology, discussions in “competitive” universities are all about hierarchy. Most people in the real world don’t obsess over it.*12
In the more rural past, envy was rather controlled; wealthy people were not as exposed to other persons of their class. They didn’t have the pressure to keep up with other wealthy persons and compete with them. The wealthy stayed within their region, surrounded by people who depended on them, say a lord on his property. Except for the occasional season in the cities, their social life was quite vertical. Their children played with the children of the servants.
It was in mercantile urban environments that socializing within social classes took place. And, over time, with industrialization, the rich started moving to cities or suburbs surrounded by other people of similar—but not completely similar—condition. Hence they needed to keep up with each other, racing on a treadmill.
For a rich person isolated from vertical socializing with the poor, the poor become something entirely theoretical, a textbook reference. As I mentioned in the past chapter, I have yet to see a bien pensant Cambridge don hanging out with Pakistani cab drivers or lifting weights with cockney speakers. The intelligentsia therefore feels entitled to deal with the poor as a construct; one they created. Thus they become convinced that they know what is best for them.
EMPATHY AND HOMOPHILY
Recall the scaling problem, the idea that people’s ethical rules are not universal; they vary according to whether someone is “Swiss,” that is, an outsider or not.
The same applies to empathy (the reverse of envy). You can see that people feel more for those of their class. Traditionally, the upper class engaged in rescuing those from ruined families by making them “stewards” or dames de compagnie. Such in-group protection has a self-insurance attribute—something that can only work for a limited number of people and can’t be universalized: you take care of my progeny if they are ruined; I will take care of yours.
DATA, SHMATA
Another lesson from Piketty’s ambitious volume: it was loaded with charts and tables. There is a lesson here: what we learn from professionals in the real world is that data is not necessarily rigor. One reason I—as a probability professional—left data out of The Black Swan (except for illustrative purposes) is that it seems to me that people flood their stories with numbers and graphs in the absence of solid or logical arguments. Further, people mistake empiricism for a flood of data. Just a little bit of significant data is needed when one is right, particularly when it is disconfirmatory empiricism, or counterexamples: only one data point (a single extreme deviation) is sufficient to show that Black Swans exist.
Traders, when they make profits, have short communications; when they lose they drown you in details, theories, and charts.
Probability, statistics, and data science are principally logic fed by observations—and absence of observations. For many environments, the relevant data points are those in the extremes; these are rare by definition, and it suffices to focus on those few but big to get an idea of the story. If you want to show that a person has more than, say $10 million, all you need is to show the $50 million in his brokerage account, not, in addition, list every piece of furniture in his house, including the $500 painting in his study and the silver spoons in the pantry. So I’ve discovered, with experience, that when you buy a thick book with tons of graphs and tables used to prove a point, you should be suspicious. It means something didn’t distill right! But for the general public and those untrained in statistics, such tables appear convincing—another way to substitute the true with the complicated.
For instance, the science journalist Steven Pinker played that trick with his book The Better Angels of Our Nature, which claims a decline of violence in modern human history, and attributes this to modern institutions. My collaborator Pasquale Cirillo and I, when we put his “data” under scrutiny, found out that either he didn’t understand his own numbers (actually, he didn’t), or he had a story in mind and kept adding charts, not realizing that statistics isn’t about data but distillation, rigor, and avoiding being fooled by randomness—but no matter, the general public and his state-worshipping IYI colleagues found it impressive (for a while).
ETHICS OF CIVIL SERVICE
Let us finish this discussion with an unfairness that is worse than inequality: the sore sight of back office, non-risk-takers getting rich from public service.
When, on leaving office, Barack Obama accepted a sum of more than $40 million to write his memoirs, many people were outraged. His supporters, statists who were defending him, on the other hand, were critical of the rich entrepreneurs hired by the subsequent administration. Money is greed, for them—but those who did not earn the money via commerce were illogically exempt. I had a rough time explaining that having rich people in a public office is very different from having public people become rich—again, it is the dynamics, the sequence, that matters.
Rich people in public office have shown some evidence of lack of total incompetence—success may come from randomness, of course, but we at least have a hint of some skill in the real world, some evidence that the person has dealt with reality. This is of course conditional on the person having had skin in the game—and it is better if the person felt a blowup, has experienced at least once the loss of part of his or her fortune and the angst associated with it.
As usual, there is a mix of the ethical and the effective here.
It is downright unethical to use public office for enrichment.
A good rule for society is to oblige those who start in public office to pledge never subsequently to earn from the private sector more than a set amount; the rest should go to the taxpayer. This will ensure sincerity in, literally, “service”—where employees are supposedly underpaid because of their emotional reward from serving society. It would prove that they are not in the public sector as an investment strategy: you do not become a Jesuit priest because it may help you get hired by Goldman Sachs later, after your eventual defrocking—given the erudition and the masterly control of casuistry generally associated with the Society of Jesus.
Currently, most civil servants tend to stay in civil service—except for those in delicate areas that industry controls: the agro-alimentary segment, finance, aerospace, anything related to Saudi Arabia…
A civil servant can make rules that are friendly to an industry such as banking—and then go off to J.P. Morgan and recoup a multiple of the difference between his or her current salary and the market rate. (Regulators, you may recall, have an incentive to make rules as complex as possible so their expertise can later be hired at a higher price.)
So there is an implicit
bribe in civil service: you act as a servant to an industry, say, Monsanto, and they take care of you later on. They do not do it out of a sense of honor: simply, it is necessary to keep the system going and encourage the next guy to play by these rules. The IYI-cum-cronyist former Treasury Secretary Tim Geithner—with whom I share the Calabrese barber of the Prologue—was overtly rewarded by the industry he helped bail out. He helped bankers get bailouts, let them pay themselves from the largest bonus pool in history after the crisis, in 2010 (that is, using taxpayer money), and then got a multimillion-dollar job at a financial institution as his reward for good behavior.
NEXT
There is a vicious domain-dependence of expertise: the electrician, dentist, scholar of Portuguese irregular verbs, assistant colonoscopist, London cabby, and algebraic geometer are experts (plus or minus some local variations), while the journalist, State Department bureaucrat, clinical psychologist, management theorist, publishing executive, and macroeconomist are not. This allows us to answer the questions: Who is the real expert? Who decides who is and who is not an expert? Where is the meta-expert?
Time is the expert. Or, rather, the temperamental and ruthless Lindy, as we see in the next chapter.
*1 It came to my notice that in countries with high rent-seeking, wealth is seen as something zero-sum: you take from Peter to give to Paul. On the other hand, in places with low rent-seeking (say the United States before the Obama administration), wealth is seen as a positive-sum game, benefiting everybody.
*2 Complex regulations allow former government employees to find jobs helping firms navigate the regulations they themselves created.
*3 Thirty-nine percent of Americans will spend a year in the top 5 percent of the income distribution, 56 percent will find themselves in the top 10 percent, and 73 percent will spend a year in the top 20 percent.
*4 Or, more mathematically: Dynamic equality assumes Markov chain with no absorbing states.
*5 A technical comment (for nitpickers): what we can call here imperfect ergodicity means that each one of us has long-term, ergodic probabilities that have some variation among individuals: your probability of ending in the one percent may be higher than mine; nevertheless no state will have a probability of 0 for me, and no state will have a transition probability of 1 for you.
*6 Another comment for nitpickers. Rawls’s veil, discussed in Fooled by Randomness, assumes that a fair society is the one which you would select if there were some type of a lottery. Here we go further and discuss a dynamic structure, in other words, how such a society would move, as it obviously will not be static.
*7 This section is technical and can be skipped by those who aren’t particularly impressed with economists.
*8 The type of distributions—called fat tails—associated with it made the analyses more delicate, far more delicate, and it had become my mathematical specialty. In Mediocristan, changes over time are the result of the collective contributions of the center, the middle. In Extremistan these changes come from the tails. Sorry if you don’t like it, but that is purely mathematical.
*9 If the process is fat-tailed (Extremistan), then wealth is generated at the top, which means increases in wealth lead to increases of measured inequality. Within populations, wealth creation is a series of small probability bets. So it is natural that the pool of wealth (measured in years of spending, as Piketty does) increases with wealth. Consider one hundred people in a 80/20 world: the additional wealth should come from one person, with the remaining bottom fifty contributing nothing. It is not a zero-sum gain: eliminate that person, and there will be almost no wealth increases. In fact the rest are already benefiting from the contribution of the minority.
*10 La Bruyère: L’émulation et la jalousie ne se rencontrent guère que dans les personnes du même art, de même talent et de même condition.
*11 What happened with the U.K. Parliament expenses scandal: MPs were giving themselves TVs and dishwashers, which the public could easily imagine, and revolted against. One MP said, “It’s not like I took one million in bonds.” The public understands TVs, not bonds.
*12 There is a technical argument that, if one looks at the issue dynamically, not statically, a wealth tax favors the salaryperson over the entrepreneur.
She is the one and only expert—Don’t eat their cheesecake—Meta-experts judged by meta-meta-experts—Prostitutes, nonprostitutes, and amateurs
Lindy is a deli in New York, now a tourist trap, that proudly claims to be famous for its cheesecake, but in fact has been known for fifty or so years by physicists and mathematicians thanks to the heuristic that developed there. Actors who hung out there gossiping about other actors discovered that Broadway shows that lasted for, say, one hundred days, had a future life expectancy of a hundred more. For those that lasted two hundred days, two hundred more. The heuristic became known as the Lindy effect.
Let me warn the reader: while the Lindy effect is one of the most useful, robust, and universal heuristics I know, Lindy’s cheesecake is…much less distinguished. Odds are the deli will not survive, by the Lindy effect.
There had been a bevy of mathematical models that sort of fit the story, though not really, until a) yours truly figured out that the Lindy effect can be best understood using the theory of fragility and antifragility, and b) the mathematician Iddo Eliazar formalized its probabilistic structure. Actually the theory of fragility directly leads to the Lindy effect. Simply, my collaborators and I managed to define fragility as sensitivity to disorder: the porcelain owl sitting in front of me on the writing desk, as I am writing these lines, wants tranquility. It dislikes shocks, disorder, variations, earthquakes, mishandling by dust-phobic cleaning service operators, travel in a suitcase transiting through Terminal 5 in Heathrow, and shelling by Saudi Barbaria–sponsored Islamist militias. Clearly, it has no upside from random events and, more generally, disorder. (More technically, being fragile, it necessarily has a nonlinear reaction to stressors: up until its breaking point, shocks of larger intensity affect it disproportionally more than smaller ones).
Now, crucially, time is equivalent to disorder, and resistance to the ravages of time, that is, what we gloriously call survival, is the ability to handle disorder.
That which is fragile has an asymmetric response to volatility and other stressors, that is, will experience more harm than benefit from it.
In probability, volatility and time are the same. The idea of fragility helped put some rigor around the notion that the only effective judge of things is time—by things we mean ideas, people, intellectual productions, car models, scientific theories, books, etc. You can’t fool Lindy: books of the type written by the current hotshot Op-Ed writer at The New York Times may get some hype at publication time, manufactured or spontaneous, but their five-year survival rate is generally less than that of pancreatic cancer.
WHO IS THE “REAL” EXPERT?
Effectively Lindy answers the age-old meta-questions: Who will judge the expert? Who will guard the guard? (Quis custodiet ipsos custodes?) Who will judge the judges? Well, survival will.
For time operates through skin in the game. Things that have survived are hinting to us ex post that they have some robustness—conditional on their being exposed to harm. For without skin in the game, via exposure to reality, the mechanism of fragility is disrupted: things may survive for no reason for a while, at some scale, then ultimately collapse, causing a lot of collateral harm.
A few more details (for those interested in the intricacies, the Lindy effect has been covered at length in Antifragile). There are two ways things handle time. First, there is aging and perishability: things die because they have a biological clock, what we call senescence. Second, there is hazard, the rate of accidents. What we witness in physical life is the combination of the two: when you are old and fragile, you don’t handle accidents very well. These accidents don’t have to be external, like falling fro
m a ladder or being attacked by a bear; they can also be internal, from random malfunctioning of your organs or circulation. On the other hand, animals that don’t really age, say turtles and crocodiles, seem to have a remaining life expectancy that stays constant for a long time. If a twenty-year-old crocodile has forty more years to live (owing to the perils of the habitat), a forty-year-old one will also have about forty years to live.
Let us use as shorthand “Lindy proof,” “is Lindy,” or “Lindy compatible” (one can substitute for another) to show something that seems to belong to the class of things that have proven to have the following property:
That which is “Lindy” is what ages in reverse, i.e., its life expectancy lengthens with time, conditional on survival.
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