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August 3 - November 11, 2018
The payoff of a human venture is, in general, inversely proportional to what it is expected to be.
The strategy for the discoverers and entrepreneurs is to rely less on top-down planning and focus on maximum tinkering and recognizing opportunities when they present themselves. 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 can.
We remember the martyrs who died for a cause that we knew about, never those no less effective in their contribution but whose cause we were never aware of—precisely because they were successful.
naïve empiricism—successions of anecdotes selected to fit a story do not constitute evidence.
Categorizing is necessary for humans, but it becomes pathological when the category is seen as definitive, preventing people from considering the fuzziness of boundaries, let alone revising their categories.
Clearly the drawback of a world economy where the payoff goes to ideas is higher inequality among the idea generators together with a greater role for both opportunity and luck—but I will leave the socioeconomic discussion for Part Three and focus here on knowledge.
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.
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.
the problem is even more general than that; it strikes at the nature of empirical knowledge itself. Something has worked in the past, until—well, it unexpectedly no longer does, and what we have learned from the past turns out to be at best irrelevant or false, at worst viciously misleading.
Mistaking a naïve observation of the past as something definitive or representative of the future is the one and only cause of our inability to understand the Black Swan.
In general, positive Black Swans take time to show their effect while negative ones happen very quickly—it is much easier and much faster to destroy than to build.
the round-trip fallacy, since these statements are not interchangeable.
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 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.
Memory is more of a self-serving dynamic revision machine: you remember the last time you remembered the event and, without realizing it, change the story at every subsequent remembrance. So we pull memories along causative lines, revising them involuntarily and unconsciously. We continuously renarrate past events in the light of what appears to make what we think of as logical sense after these events occur.
The way to avoid the ills of the narrative fallacy is to favor experimentation over storytelling, experience over history, and clinical knowledge over theories.
some business bets in which one wins big but infrequently, yet loses small but frequently, are worth making if others are suckers for them and if you have the personal and intellectual stamina
The term bias also indicates the condition’s potentially quantifiable nature: you may be able to calculate the distortion, and to correct for it by taking into account both the dead and the living, instead of only the living. Silent evidence is what events use to conceal their own randomness, particularly the Black Swan type of randomness.
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.
Experts who tend to be experts: livestock judges, astronomers, test pilots, soil judges, chess masters, physicists, mathematicians (when they deal with mathematical problems, not empirical ones), accountants, grain inspectors, photo interpreters, insurance analysts (dealing with bell curve–style statistics). Experts who tend to be … not experts: stockbrokers, clinical psychologists, psychiatrists, college admissions officers, court judges, councilors, personnel selectors, intelligence analysts (the CIA’s record, in spite of its costs, is pitiful), unless one takes into account some great dose
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We humans are the victims of an asymmetry in the perception of random events. We attribute our successes to our skills, and our failures to external events outside our control, namely to randomness. We feel responsible for the good stuff, but not for the bad. This causes us to think that we are better than others at whatever we do for a living.
The classical model of discovery is as follows: you search for what you know (say, a new way to reach India) and find something you didn’t know was there (America).
you find something you are not looking for and it changes the world, while wondering after its discovery why it “took so long” to arrive at something so obvious.
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 discoverers.
We build toys. Some of those toys change the world.
Popper’s insight concerns the limitations in forecasting historical events and the need to downgrade “soft” areas such as history and social science to a level slightly above aesthetics and entertainment, like butterfly or coin collecting.
Popper’s central argument is that in order to predict historical events you need to predict technological innovation, itself fundamentally unpredictable.
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.
But there is a weaker form of this law of iterated knowledge. It can be phrased as follows: to understand the future to the point of being able to predict it, you need to incorporate elements from this future itself. If you know about the discovery you are about to make in the future, then you have almost made it.
Prediction requires knowing about technologies that will be discovered in the future. But that very knowledge would almost automatically allow us to start developing those technologies right away. Ergo, we do not know what we will know.
Poincaré’s reasoning was simple: as you project into the future you may need an increasing amount of precision about the dynamics of the process that you are modeling, since your error rate grows very rapidly. The problem is that near precision is not possible since the degradation of your forecast compounds abruptly—you would eventually need to figure out the past with infinite precision.
Poincaré showed this in a very simple case, famously known as the “three body problem.” If you have only two planets in a solar-style system, with nothing else affecting their course, then you may be able to indefinitely predict the behavior of these planets, no sweat. But add a third body, say a comet, ever so small, between the planets. Initially the third body will cause no drift, no impact; later, with time, its effects on the two other bodies may become explosive. Small differences in where this tiny body is located will eventually dictate the future of the behemoth planets.
Think of the difficulty in forecasting in terms of branches growing out of a tree; at every fork we have a multiplication of new branches.
Poincaré proposed that we can only work with qualitative matters—some property of systems can be discussed, but not computed. You can think rigorously, but you cannot use numbers. Poincaré even invented a field for this, analysis in situ, now part of topology.
However, if you believe in free will you can’t truly believe in social science and economic projection. You cannot predict how people will act. Except, of course, if there is a trick, and that trick is the cord on which neoclassical economics is suspended. You simply assume that individuals will be rational in the future and thus act predictably.
The idea, as promoted by the philosopher Daniel Dennett, is as follows: What is the most potent use of our brain? It is precisely the ability to project conjectures into the future and play the counterfactual game—“If
Used correctly and in place of more visceral reactions, the ability to project effectively frees us from immediate, first-order natural selection—as opposed to more primitive organisms that were vulnerable to death and only grew by the improvement in the gene pool through the selection of the best. In a way, projecting allows us to cheat evolution: it now takes place in our head, as a series of projections and counterfactual scenarios.
Most of the debate between creationists and evolutionary theorists (of which I do not partake) lies in the following: creationists believe that the world comes from some form of design while evolutionary theorists see the world as a result of random changes by an aimless process. But it is hard to look at a computer or a car and consider them the result of aimless process. Yet they are.
Philosophers since Aristotle have taught us that we are deep-thinking animals, and that we can learn by reasoning. It took a while to discover that we do effectively think, but that we more readily narrate backward in order to give ourselves the illusion of understanding, and give a cover to our past actions.
What you should avoid is unnecessary dependence on large-scale harmful predictions—those and only those. Avoid the big subjects that may hurt your future: be fooled in small matters, not in the large. Do not listen to economic forecasters or to predictors in social science (they are mere entertainers), but do make your own forecast for the picnic. By all means, demand certainty for the next picnic; but avoid government social-security forecasts for the year 2040. Know how to rank beliefs not according to their plausibility but by the harm they may cause.
This same point can be generalized to life: maximize the serendipity around you.
make a distinction between 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.
Don’t look for the precise and the local. Simply, do not be narrow-minded.
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.”
invest in preparedness, not in prediction. Remember that infinite vigilance is just not possible.
Seize any opportunity, or anything that looks like opportunity.
If a big publisher (or a big art dealer or a movie executive or a hotshot banker or a big thinker) suggests an appointment, cancel anything you have planned: you may never see such a window open up again. I am sometimes shocked at how little people realize that these opportunities do not grow on trees. Collect as many free nonlottery tickets (those with open-ended payoffs) as you can, and, once they start paying off, do not discard them. Work hard, not in grunt work, but in chasing such opportunities and maximizing exposure to them.
Beware of precise plans by governments.
Put yourself in situations where favorable consequences are much larger than unfavorable ones.
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.
Our opinions about artistic merit are the result of arbitrary contagion even more than our political ideas are.
