Summary - Key Takeaways

We are great at filtering out randomness and making past events look less random. We create narratives around events, to make them more understandable but simplify too much. Like attributing success to hard work, which is necessary, but not the direct and only cause.

We are great at recognizing patterns, even in data that is truly random.

While the book might sound pessimistic, it does not say that everything is random, just that many things are more random than we intuitively think.

It is a great book to learn more about our flawed ways of thinking and to realize more of our biases.

Notes from the book:

Strangely, I gave considerably more thought to some sections of this book after the publication than I had before, particularly in two separate areas: (a) the mechanisms by which our brain sees the world as less, far less, random that it actually is, and (b) the “fat tails,” that wild brand of uncertainty that causes large deviations (rare events explain more and more of the world we live in, but at the same time remain as counterintuitive to us as they were to our ancestors).

Past events will always look less random than they were (it is called the hindsight bias). I would listen to someone’s discussion of his own past realizing that much of what he was saying was just backfit explanations concocted ex post by his deluded mind (Page 9)

In addition, while we may have some understanding of the probabilities in the hard sciences, particularly in physics, we don’t have much of a clue in the social “sciences” like economics, in spite of the fanfares of experts. (Page 11)

Note: Outside of the sciences there exists mostly chaos or at least complex systems

The idea here was that “it is more random than we think” rather than “it is all random.” (Page 12)

risk-conscious hard work and discipline can lead someone to achieve a comfortable life with a very high probability. Beyond that, it is all randomness: either by taking enormous (and unconscious) risks, or by being extraordinarily lucky. Mild success can be explainable by skills and labor. Wild success is attributable to variance (Page 12)

Let me make it clear here: Of course chance favors the prepared! Hard work, showing up on time, wearing a clean (preferably white) shirt, using deodorant, and some such conventional things contribute to success-they are certainly necessary but may be insufficient as they do not cause success. The same applies to the conventional values of persistence, doggedness and perseverance: necessary, very necessary. One needs to go out and buy a lottery ticket in order to win. Does it mean that the work involved in the trip to the store caused the winning? Of course skills count, but they do count less in highly random environments than they do in dentistry (Page 13)

The author notices variations from the general population in a few traits like tenacity and hard work: another confusion of the necessary and the causal. That all millionaires were persistent, hardworking people does not make persistent hard workers become millionaires: Plenty of unsuccessful entrepreneurs were persistent, hardworking people. In a textbook case of naive empiricism, the author also looked for traits these millionaires had in common and figured out that they shared a taste for risk taking. Clearly risk taking is necessary for large success— but it is also necessary for failure. Had the author done the same study on bankrupt citizens he would certainly have found a predilection for risk taking. (Page 14)

I am not saying that Warren Buffett is not skilled; only that a large population of random investors will almost necessarily produce someone with his track records just by luck (Page 15)

the economist proudly detects “regularities” and “anomalies” in data that are plain random (Page 21)

Note: We are too good at noticing patterns in randomness

performance in any given field (war, politics, medicine, investments) by the results, but by the costs of the alternative (i.e., if history played out in a different way). Such substitute courses of events are called alternative histories. Clearly, the quality of a decision cannot be solely judged based on its outcome, but such a point seems to be voiced only by people who fail (those who succeed attribute their success to the quality of their decision (Page 22)

to value distilled thought over newer thinking. […] For an idea to have survived so long across so many cycles is indicative of its relative fitness. Noise, at least some noise, was filtered out. (Page 59)

Note: That is why classical literature seems better than modern literature

for an n times increase in the sample size, we increase our knowledge by the square root of n. Suppose I am drawing from an urn containing red and black balls. My confidence level about the relative proportion of red and black balls after 20 drawings is not twice the one I have after 10 drawings; it is merely multiplied by the square root of 2 (that is, 1.41).

Where statistics becomes complicated, and fails us, is when we have distributions that are not symmetric, like the urn above. If there is a very small probability of finding a red ball in an urn dominated by black ones, then our knowledge about the absence of red balls will increase very slowly-more slowly than at the expected square root of n rate. (Page 112)

Note: We can barely learn something new about very rare events and cannot infer them from the past

I have just completed a thorough statistical examination of the life of President Bush. For fifty-eight years, close to 21,000 observations, he did not die once. I can hence pronounce him as immortal, with a high degree of statistical significance. (Page 120)

Note: Perfect example of the problem of induction. We do the same with markets. „The market has never dine this before“

There are only two types of theories:

Theories that are known to be wrong, as they were tested and adequately rejected (he calls them falsified).

Theories that have not yet been known to be wrong, not falsified yet, but are exposed to be proved wrong. (Page 126)

Note: Popper - David Deutsch - Theory of Knowledge

He refused to blindly accept the notion that knowledge can always increase with incremental information which is the foundation of statistical inference. It may in some instances, but we do not know which ones. (Page 127)

The initial sample size matters greatly. If there are five monkeys in the game, I would be rather impressed with the Iliad writer, to the point of suspecting him to be a reincarnation of the ancient poet. If there are a billion to the power one billion monkeys I would be less impressed (Page 136)

Note: A huge sample size, like the amount of investors, will inevitably lead to wins, even if they just randomly operate and yet we try to explain their success in hindsight

A brief summing up at this point: I showed how we tend to mistake one realization among all possible random histories as the most representative one, forgetting that there may be others. In a nutshell, the survivorship bias implies that the highest performing realization will be the most visible. Why? Because the losers do not show up. (Page 146)

Note: Only looking at the existing evidence (winners) means missing most of the relevant data.

I am fitting the rule on the data. This activity is called data snooping. The more I try, the more I am likely, by mere luck, to find a rule that worked on past data. A random series will always present some detectable pattern. I am convinced that there exists a tradable security in the Western world that would be 100% correlated with the changes in temperature in Ulan Bator, Mongolia. (Page 162)

What we are witnessing here is a nonlinear effect resulting from a linear force exerted on an object. A very small additional input, here the grain of sand, caused a disproportionate result, namely the destruction of my starter Tower of Babel. Popular wisdom has integrated many such phenomena, as witnessed by such expressions as “the straw that broke the camel’s back” or “the drop that caused the water to spill.”

Chaos theory concerns itself primarily with functions in which a small input can lead to a disproportionate response. (Page 173)

The dynamics of such fame follow a rotating helix, which may have started at the audition, as the selection could have been caused by some silly detail that fitted the mood of the examiner on that day. Had the examiner not fallen in love the previous day with a person with a similar-sounding last name, then our selected actor from that particular sample history would be serving caffe latte in the intervening sample history. (Page 175)

Note: Randomness in every day life and success. One situation line this leads to a spiral upwards - Winner Takes All

the final outcome is more than frequently the undeserved one. The arrangement of the letters on a typewriter is an example of the success of the least deserving method. For our typewriters have the order of the letters on their keyboard arranged in a nonoptimal manner, as a matter of fact in such a nonoptimal manner as to slow down the typing rather than make the job easy, in order to avoid jamming the ribbons as they were designed for less electronic days. (Page 175)

Note: Same goes for windows. Everybody is using it because everybody else is using it and not because it is the best

This goes against classical economist models, in which results come from a precise reason

the journalist claims to provide an explanation for something that amounts to perfect noise. A move of 1.03 with the Dow at 11,000 constitutes less than a 0.01% move. Such a move does not warrant an explanation. There is nothing there that an honest person can try to explain; there are no reasons to adduce (Page 214)

Note: We love to explain randomness, especially in areas where we cannot check its correctness

For it is harder to act as if one were ignorant than as if one were smart (Page 231)

Note: That is why we tend to establish causal links between (unrelated) events

Most of us know pretty much how we should behave. It is the execution that is the problem, not the absence of knowledge. I am tired of the moralizing slow-thinkers who pound me with platitudes like I should floss daily, eat my regular apple, and visit the gym outside of the New Year’s resolution (Page 232)

Note: How to improve this? Make knowledge less abstract? We are weak creatures, looking for the path of least resistance. We need to train ourselves to enjoy the hard things and improve the system around us to not tempt us

There are those who think that there are easy clear-cut answers and those who don’t think that simplification is possible without severe distortion (his hero: Wittgenstein; his villain: Descartes). I am enamored of the difference as I think that the generator of the Fooled by Randomness problem, the false belief in determinism, is also associated with such reduction of the dimensionality of things. As much as you believe in the “keepitsimplestupid” it is the simplification that is dangerous.

Note: Reduction is only possible in some fields, because simplification can lead to distortion