I have fond memories of this author – one of my favourites among the books I’ve read. I was hooked by his style of skeptical empiricism when I was introduced to his first book – ‘Fooled by Randomness’ – by serendipity. The author will be glad that it is through a series of black swan event that lead me to his first book, and consequently, to his second book.
Long time ago, my gf went to US for a conference on a paper she submitted. Man, in these conferences, there are people literally giving out books for free (to be fair, they did try to sell during the first few days of the conference, but towards the last day, book hell went loose). My gf, a typical free-must-grab Singaporean, grabbed a few of the books, regardless of race, language or religion (ok, I exaggerate). Among the horde of books, one of them is Nassim Nicolas Taleb’s ’Fooled by randomness’.
Talk about Black swan events (these are incalculable, low probabilistic and highly consequential events), my introduction to the author’s first book must fall squarely into such category. The author’s style is very refreshing, a logical salad mixed with lots of stories woven with facts, creating a potent mix of philosophical brouhaha.
Black swans are named as such because of this story. Imagine all throughout your life, you only saw swans which are white. Based on historical past, you can ‘extrapolate’ your data by induction that all swans are white. This is all jolly well and good until one day you saw your first black swan. This event totally tears away your hypothesis that all swans are white and is something that the past data can never predict. The probability of meeting a black swan is not calculable, though based on the past data it has a very low probability (which explains why you didn’t see one earlier) and has serious consequences. Here, ‘absence of evidence’ is misconstrued as ‘evidence of absence’.
Are we similarly fooled by such logic errors? I can think of a few:
1. From analyzing a company’s past earnings for say 10 years, I come to the conclusion that the earnings are stable and growing steadily. I treat the absence of evidence of ‘poor earning years’ as the evidence of absence of ‘poor earning years’, leading to my skewed over-bullishness of the company.
2. A man, having lived till a ripe age of 100 years old, declares that from his 100 years of non-dying, he is an immortal and thus will carry on living for a few 100 years more. He made a mistake of thinking that ‘no evidence of death’ is the same as the ‘evidence of no death’.
These are exaggerated examples to illustrate the points, but it blows my mind to think in this way.
‘The Black Swan’ carries with this style of writing, perhaps more brilliantly so. The new book talks about how we systemically and biologically ignore black swan events. In fact, he argued that the world is governed mainly by black swan events, not by regular and inconsequential events that are predictable. He goes as far as to say that what we do not know is far more important than what we know. Among the most important things I carried away from reading the book, is this notion of ‘silent evidence’ – how we are blinded by things that are not found in the sample size, hence we discounted them to the extent of skewing our perception of things.
Below is an example to illustrate this point:
Consider the world’s richest people – all of them exhibit traits of risk-taking, go-getter mindset, determined etc etc. Thus,
Rich people have a certain characteristics.
I have these characteristics.
Therefore, I’ll be a rich person.
This is logically flawed. Having a set of characteristics exhibited by rich people does not necessarily mean I’ll be a rich person. There are many examples of people with these characteristics but are not necessarily rich. Hence, these people who had these set of characteristics could be there based on pure luck.
I think these ideas ties in very much with the idea of causality. Correlation does not necessarily imply causality, though causality implies correlation. For example, almost 99.9% of cancer patients drink water (high correlation) but it does not mean that drinking water will cause cancer (no causality). We are often tricked into believing such logic errors, which tend to exacerbate the consequences of black swan events.
------------
The review is split into two parts because the books is exceedingly thick and I had to write down my thoughts halfway before it gets diluted and lost in transition.
This had to be the most the most relevant book I’ve read in my life. It’s like I’ve been born blind, then after a corrective surgery, I see the world as it is now but had been elusive to me before. I can never look at the world again because the book had permanently changed me. Don’t go out and grab the book because I said so…my experiences lead me to different perspectives when I read the book, which will be vastly different from another reader.
The second half of the books talks about more technical stuff. I confess I do not really understand the whole of it in the first reading. Perhaps, like Intelligent investor, the true gist of it will only be realized after subsequent readings. The author highlights the fallacy of treating everyday occurrences to fit the bell-curve (the Standard normal or Gaussian distribution). This fallacy is so rampant that it permeates most of the ‘scientific’ methods regarding a range of socio-economic disciplines like economics, sociology and finance. I’ve never believed in the Modern Portfolio Theory (MPT) and efficient market hypothesis (EMT), so this didn’t struck me hard enough to feel defensive about his ideas.
I guess the author wants us to follow a bottom-up approach rather than a top-down approach in everything. A bottom-up approach means using real, empirical data to look at the world. A top-down approach means learning ‘scientific’ theories and principles, then fitting data that follows them and ignoring or downplaying data that do not.
A simple example would be a stereotypical Western trained doctor who abhor using traditional chinese methods like acupuncture or herbs, judging it unscientific (though it’s very empirically based) because of top-down approach.
Am I also blinded by my own theoretical framework?
The author suggests a few ways to deal with the uncertain world:
1. Make a distinction between positive black swans and negative black swans. Black swans events can benefit or cripple. Once identified, expose yourself maximally from positive black swans, and limit exposure to negative ones
2. Invest in preparedness, not in prediction
3. Seize any opportunity, even those that looks like opportunity. This is the same as exposing one to positive black swans. Work hard, not in grunt work, but in maximizing one’s exposure to opportunities.
4. When caught between unknown probabilities of choices presented to you, focus on the (known) consequences of each choice and not on the probabilities. It’s also known as Pascal’s Wager.
I started this book being blind, and I finished this book knowing that I will never view the world the same again.
Long time ago, my gf went to US for a conference on a paper she submitted. Man, in these conferences, there are people literally giving out books for free (to be fair, they did try to sell during the first few days of the conference, but towards the last day, book hell went loose). My gf, a typical free-must-grab Singaporean, grabbed a few of the books, regardless of race, language or religion (ok, I exaggerate). Among the horde of books, one of them is Nassim Nicolas Taleb’s ’Fooled by randomness’.
Talk about Black swan events (these are incalculable, low probabilistic and highly consequential events), my introduction to the author’s first book must fall squarely into such category. The author’s style is very refreshing, a logical salad mixed with lots of stories woven with facts, creating a potent mix of philosophical brouhaha.
Black swans are named as such because of this story. Imagine all throughout your life, you only saw swans which are white. Based on historical past, you can ‘extrapolate’ your data by induction that all swans are white. This is all jolly well and good until one day you saw your first black swan. This event totally tears away your hypothesis that all swans are white and is something that the past data can never predict. The probability of meeting a black swan is not calculable, though based on the past data it has a very low probability (which explains why you didn’t see one earlier) and has serious consequences. Here, ‘absence of evidence’ is misconstrued as ‘evidence of absence’.
Are we similarly fooled by such logic errors? I can think of a few:
1. From analyzing a company’s past earnings for say 10 years, I come to the conclusion that the earnings are stable and growing steadily. I treat the absence of evidence of ‘poor earning years’ as the evidence of absence of ‘poor earning years’, leading to my skewed over-bullishness of the company.
2. A man, having lived till a ripe age of 100 years old, declares that from his 100 years of non-dying, he is an immortal and thus will carry on living for a few 100 years more. He made a mistake of thinking that ‘no evidence of death’ is the same as the ‘evidence of no death’.
These are exaggerated examples to illustrate the points, but it blows my mind to think in this way.
‘The Black Swan’ carries with this style of writing, perhaps more brilliantly so. The new book talks about how we systemically and biologically ignore black swan events. In fact, he argued that the world is governed mainly by black swan events, not by regular and inconsequential events that are predictable. He goes as far as to say that what we do not know is far more important than what we know. Among the most important things I carried away from reading the book, is this notion of ‘silent evidence’ – how we are blinded by things that are not found in the sample size, hence we discounted them to the extent of skewing our perception of things.
Below is an example to illustrate this point:
Consider the world’s richest people – all of them exhibit traits of risk-taking, go-getter mindset, determined etc etc. Thus,
Rich people have a certain characteristics.
I have these characteristics.
Therefore, I’ll be a rich person.
This is logically flawed. Having a set of characteristics exhibited by rich people does not necessarily mean I’ll be a rich person. There are many examples of people with these characteristics but are not necessarily rich. Hence, these people who had these set of characteristics could be there based on pure luck.
I think these ideas ties in very much with the idea of causality. Correlation does not necessarily imply causality, though causality implies correlation. For example, almost 99.9% of cancer patients drink water (high correlation) but it does not mean that drinking water will cause cancer (no causality). We are often tricked into believing such logic errors, which tend to exacerbate the consequences of black swan events.
------------
The review is split into two parts because the books is exceedingly thick and I had to write down my thoughts halfway before it gets diluted and lost in transition.
This had to be the most the most relevant book I’ve read in my life. It’s like I’ve been born blind, then after a corrective surgery, I see the world as it is now but had been elusive to me before. I can never look at the world again because the book had permanently changed me. Don’t go out and grab the book because I said so…my experiences lead me to different perspectives when I read the book, which will be vastly different from another reader.
The second half of the books talks about more technical stuff. I confess I do not really understand the whole of it in the first reading. Perhaps, like Intelligent investor, the true gist of it will only be realized after subsequent readings. The author highlights the fallacy of treating everyday occurrences to fit the bell-curve (the Standard normal or Gaussian distribution). This fallacy is so rampant that it permeates most of the ‘scientific’ methods regarding a range of socio-economic disciplines like economics, sociology and finance. I’ve never believed in the Modern Portfolio Theory (MPT) and efficient market hypothesis (EMT), so this didn’t struck me hard enough to feel defensive about his ideas.
I guess the author wants us to follow a bottom-up approach rather than a top-down approach in everything. A bottom-up approach means using real, empirical data to look at the world. A top-down approach means learning ‘scientific’ theories and principles, then fitting data that follows them and ignoring or downplaying data that do not.
A simple example would be a stereotypical Western trained doctor who abhor using traditional chinese methods like acupuncture or herbs, judging it unscientific (though it’s very empirically based) because of top-down approach.
Am I also blinded by my own theoretical framework?
The author suggests a few ways to deal with the uncertain world:
1. Make a distinction between positive black swans and negative black swans. Black swans events can benefit or cripple. Once identified, expose yourself maximally from positive black swans, and limit exposure to negative ones
2. Invest in preparedness, not in prediction
3. Seize any opportunity, even those that looks like opportunity. This is the same as exposing one to positive black swans. Work hard, not in grunt work, but in maximizing one’s exposure to opportunities.
4. When caught between unknown probabilities of choices presented to you, focus on the (known) consequences of each choice and not on the probabilities. It’s also known as Pascal’s Wager.
I started this book being blind, and I finished this book knowing that I will never view the world the same again.
