Literally Fooled by Randomness

A review of the book by Nassim Nicholas Taleb

Fooled by Randomness by Nassim Taleb begins a greek story that recalls an encounter where a king, Croesus, is interacting with a Greek legislator, Solon. Croesus at the time was loaded rich 🤑💵💰, but despite Croesus’ wealth, the legislator Solon wasn’t impressed. That annoyed him and prompted him to ask whether Solon knows anyone alive who is happier than him: whether he was “to be considered the happiest man of all”. To that, Solon replied:

The observation of the numerous misfortunes that attend all conditions forbids us to grow insolent upon our present enjoyments, or to admire a man’s happiness that may yet, in course of time, suffer change. For the uncertain future has yet to come, with all variety of future; and him only to whom the divinity has [guaranteed] continued happiness until the end we may call happy.

Why I bring this up first and why the book probably brings this up as well is because it relates heavily to the idea of randomness. Randomness means that anything can happen, and in the way it’s phrased, you can’t know whether one lived a great, happy life until they die because who is to say that how their life ends in the moment of their death isn’t a direct result of what they did in the past? And who is to say that their current life state isn’t this way only because they are lucky? As I was reading this book, I found so many places where randomness influences life in ways that we often try to explain in hindsight but when viewed from the standpoint of randomness, it’s just luck.

Photo by Naser Tamimi on Unsplash

Randomness

Google’s definition of randomness is “the quality or state of lacking a pattern or principle of organization; unpredictability”, but it goes deeper than that. A friend asked me recently, “where do you think randomness comes from?” I speculate that randomness is really a limit of the human mind. When you get down to it, we are often capable of explaining deep concepts down to the molecular or even atomic level, but we always reach a point where things don’t make sense. For instance, the concept of Quantum Entanglement is something that baffles most people the first time they hear it. An even simpler example: no one can really explain why a particular coin toss lands heads or tail at a particular time. To me, it seems as though when we get to a level where we’re incapable of explaining some outcomes (i.e., when our human mind reaches its limits), everything looks “random”—every possibility happen with a defined percentage/probability in such a way that we’re unable to predict which possibility will happen.

Randomness in a One’s Professional Life

One of the earliest thing Nassim Taleb says is, “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.” Taleb is getting at the idea that luck plays a huge role in anyone’s success, and when someone explains why they are successful, they often ignore this important factor. The Veritasium youtube Channel video “Is Success Luck or Hard Work?” explains how professional hockey players might attribute their success to hard work, coaches, parents, etc, when studies show that they are up to 4 times more likely to be selected into the top tier leagues when they are born early in the year—which happens by chance as no one chooses when they’re born. This is not to say that the hard work that you do doesn’t play a role in how successful you are: as the Youtube video and Nassim Taleb reassures, “Of course chance favors the prepared”. Instead, the point is to realize that there is more luck involved than you think.

In addition, being successful at certain professions involve much more luck than others. In the book, Taleb often compares financial traders with dentists. When there’s something wrong with one’s teeth, dentists aren’t making a bet in how to fix it: they are indeed fixing the issue because they understand what is wrong because they’ve spent years in medical school studying this stuff. Once in a while, doctors make a mistake, and in other areas, machines may even outperform doctors at certain tasks (in this study, doctors had an 88.9% success of identifying benign skin cancer when a neural-network enabled machine was more successful at 95%). However, these are nothing compared to traders since for them, there’s a lot more luck involved. The following article states that “90 per cent of traders fail to make money when trading the stock market”. That’s because the stock market is very random (more on this in the investing section), so succeeding in it involves a lot of luck. Imagine that if in the study above, doctors had only a 10% accuracy at identified skin cancer. How crazy would that be? We trust doctors because they are overwhelmingly successful at what they do.

With that said, what can you take away from the randomness present in professional life? Here are my suggestions.

(1) Randomness is there and be aware of it. Don’t get cocky thinking you’re amazing. You certainly may be, but you’re also lucky!

(2) If you’re trying to pick a career, keep in mind that some professions have more randomness in them than others. All things equal, you’re more likely to fail in professions that have more randomness, so you will have to work harder on average.

(3) Be aware of the randomness in your profession and use it to your advantage. One quote from the book says, “the statistic that 90% of all option positions lost money is meaningless, (i.e., the frequency) if we do not take into account how much money is made on average during the remaining 10%”. In this way, betting often on something that makes a lot of money when it succeeds (despite it failing 9 out of 10 times) can be profitable.

Randomness in Investing

Why we have to talk about investing separately from the professional life is because (1) investing is something that a lot of people do, often passively, and (2) there’s a lot of misconceptions about investing that many—often investing “gurus”—spread or believe, and a lot of it has to deal with the fact that they ignore randomness. Let me first start with a quote from John Stuart Mill (taken from the book): “No amount of observations of white swans can allow the inference that all swans are white, but the observation of a single black swan is sufficient to refute that conclusion.” Intuitively, most people would read that, understand it, and accept it. The book, however, dives deeper. It gives another example to drive the point forward. Imagine someone saying following statement:

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.

How absurd (and funny 😄)! Figuratively speaking, maybe that makes the idea of the absence of black swans much more clear, but let me tell you the clearest example of this that we often hear in the stock market—something I’m guilty of having said before (literally in an article I wrote recently).

The market has never gone down in any 20 year period.

This is supposed to make you feel safe at the idea of doing long term investing. The logical conclusion most people would draw is, “if the market has never gone down in any 20 year period, then I should be safe in investing for the long term because I will at least break even!” Alas, this is a classic example of the black swan problem. Just because we’ve never seen it before doesn’t mean that it will never happen! To that, Taleb says, “if the past, by bringing surprises, did not resemble the past previous to it (what I call the past’s past), then why should our future resemble our current past?”

With that said, what can you take away from the randomness present in investing? Here are my suggestions.

(1) Diversify. This is advice you always hear, but the point of diversifying is that it is a way to lower your risks. If one market goes down, that won’t necessarily mean other markets go down. Yes, there’s a chance that the market will go down for the first time in a 20 year period, no one knows. However, I still think that not investing is worse because in that case the value of your money is guaranteed to go down.

(2) Place guardrails. Full disclosure, this is not something that I am currently doing, but I think it’s important to do (and I plan to do so in the future). A guardrail would be like saying that you’d sell everything in case the value goes down by a given amount. Just keep in mind that that won’t always be the best decision because the market often rallies after it goes down.

Randomness in Decisions Making

People often ruminate on decisions they made in the past when they’ve lead to an outcome that they didn’t like, but when Taleb says that “a mistake is not something to be determined after the fact, but in the light of the information until that point,” that struck me. I asked myself whether this is true and whether I would change the way I live my life if I internalized such a belief?

There’s two distinctions to make. The first one is that there’s a difference between knowingly making a mistake vs. unknowingly making a mistake. If you knowingly make a mistake (like drunk driving), then that’s on you. If you do something when you don’t know it’s a mistake (like when a kid gets burned by touching fire the first time), then the negative outcome of that situation is really there as a lesson for you to learn that that was a mistake. The information is often available (e.g., through warnings from the grown ups), but something about it makes people either not learn it or ignore it. Despite that, both of these cases are still mistakes.

The second distinction is doing an action that leads to a negative outcome but that isn’t a mistake.For example, entering a relationship with someone where both partners are fully invested (with no red flags from either side) but it later down the line turning out bad due to reasons outside their control. For instance, losing the partner over death, something life changing happening to one of them and causing them to not be who the other partner originally fell in love with, or even getting married and then divorcing and having a bad divorce. At this point, the decision to enter this relationship was not a mistake because the negative outcome purely happened by chance. So this take from Taleb, that “a mistake is not something to be determined after the fact, but in the light of the information until that point,” specifically applies to cases like those. Sometimes, this type of bad outcome just happens, and there’s nothing one can do about it but make the right decision now about how they want their future to be.

Past this idea of making mistakes, people think they use logic when they’re making a decision when people actually use “heuristics” to make decisions. Heuristics are sort of like approximation rules that help humans and animals make decisions quickly. For example, the availability bias is the thing that makes you afraid to go on a plane when you have recently heard of a plane crash when in fact it is much safer to be inside an airplane than a car. Unfortunately there are too many heuristics to list here. Fortunately, the book Thinking Fast & Slow is a great place to go if you want to learn about many of them, and in addition I’ve written two articles that touch on the topic:

With that said, what can you take away from the randomness present in decision making? Here are my suggestions.

(1) Be aware of the heuristics you use, and the book Thinking Fast & Slow is a great place to learn about them.

(2) Be more skeptical than you usually are. Fooled by Randomness talks about Karl Popper, who said that there are only two types of theories: (a) those known to be wrong (because they were tested & rejected), and (b) those that will be proven wrong (because “we will never know if all the swans are white”, as Taleb says). To me, that is a good enough reason to be a bit more skeptical of pretty much anything.

Randomness is Everywhere, Now What?

Let me leave you with one final scenario from Fooled by Randomness:

If one puts an infinite number of monkeys in front of (strongly built) typewriters, and lets them clap away, there is a certainty that one of them would come out with an exact version of the Iliad. Upon examination, this may be less interesting a concept than it appears at first: Such probability is ridiculously low. But let us carry the reasoning one step beyond. Now that we have found that hero among monkeys, would any reader invest his life’s savings on a bet that the monkey would write the Odyssey next?

That’s fruit for thoughts! While you think about that, here are some conclusions that I drew directly from the book. Because randomness is everywhere and there’s not much we can do about it, the author roughly (per my own understanding of the text) provides the following advices:

  • Accept that one’s a fool: Taleb says, “my lesson from Soros is to start every meeting at my boutique by convincing everyone that we are a bunch of idiots who know nothing and are mistake-prone, but happen to be endowed with the rare privilege of knowing it”.
  • Live a life of dignity: Taleb says, “No matter how sophisticated our choices, how we are at dominating the odds, randomness will have the last word. We are left only with dignity as a solution—dignity defined as the execution of a protocol of behavior that does not depend on the immediate circumstances. … Grace under pressure, for example. … Try not to play the victim when diagnosed with cancer. … Do not complain. … Th only article Lady Fortuna has no control over is your behavior.

No one escapes randomness. It is happening. It is here. Now you know, and I hope you don’t get fooled. Good luck!

Hey there, you made it this far! I regularly write on medium about book reviews, philosophical topics, life reflections, or any other topics that peek my interest. If you’d like to be notified whenever I publish a new story like this one, you can subscribe here, and I promise you one thing: these articles will make you think. See you soon and thanks for reading ☺️

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