Full title: The Black Swan: The Impact of the Highly Improbable
Hardcover: 400 pages
Publisher: Random House; 1 edition (April 17, 2007)
Author: Nassim Nicholas Taleb
Possible audio reference: Thom Yorke's beautiful song Black Swan
You may have heard of this book as the anti-Secret, that is; the reasonable person's answer to the dopey message "Think good, and good comes!" of Rhonda Byrne's The Secret as made famous by Oprah's Book Club in early 2007. Instead, Taleb's message might be, "Shit happens. Seriously. Don't be a sucker."
It is not an easy read. Taleb is at least as megalomaniacal, hyper-opinionated, and rambling as the least favorite professor in your memory. The book really could have used a few more passes through an aggressive editor with an eye towards clarity, but as it is, to have slogged through it is something of a red badge of erudition. Still, I kind of wish he had discussed the subject with Steven Pinker and let him write it.
What follows is a summary of his arguments in as clear a way as I can make it.
Systems can be understood to be one of two types. (Despite the fact that he is discussing systems, he clouds the issue by describing these two systems using a very geopolitical metaphor, i.e. as if they were places, as follows.)
The first system/place is Mediocristan. Such systems are largely stable, having few variables and little interdependencies amongst its variables. Its participants' successes are determined by their individual advantages, and variables change with mathematical progression. Uncertainty in this domain entails "known unknowns," and people can become useful experts in these fields. Some examples are livestock judging, astronomers, test pilots, soil judges, chess masters, accountants, photo interpreters.
The second system/place is Extremistan. Such systems are chaotic, having many variables and/or high degrees of interdependence. Its participants' success are determined by cumulative advantage, and variables change in geometric and/or exponential progression. Uncertainty in these domains often entails "unknown unknowns." Anyone called an "expert" in this field is largely a good bullshitter, and little better at prediction in these domains than computer models based on single-point, just-prior performance. Some examples include stockbrokers, clinical psychologists, psychiatry, college admissions officers, court judges, and personnel selectors.
Humans are good at working with Mediocristan systems. Extremistan, on the other hand, confounds us. The difficulty arises from several psychological factors.
- The confirmation bias: People seek largely to confirm what they know, i.e. to confirm their model, rather than refute it. (which is related to…)
- The problem of silent evidence: Even when looking at the facts, what must be taken into account are the facts that never were but might have been.
- The narrative fallacy: People prefer stories over data, even if the story version is misleading or wrong. This is because stories are easier to store and recall. (Which is related to…)
- Attraction to platonic simplicity: People prefer the reduced, and simple when reality is rarely so.
- The ludic fallacy: People mistake the (predictable, constrained) model for the real thing, and very often base plans in the world as if it was a simple model.
The most serious effect of our ineptitude with Extremistan is our inability to make predictions in these systems. In such cases, we are subject to being completely caught unawares by factors outside of our expectations and models. He calls such surprises "Black Swans," referencing an old assertion that "All swans are white." The negative Black Swans are what originally caught his attention and what he spends most of his time on in the book, but there are positive Black Swans, such as sudden, phenomenal success in book publishing.
To combat this effect, his general advice is to adopt a pervasive empirical skepticism. He acknowledges that it takes more mental effort, and sometimes more actual effort, but it is necessary to deal with Extremistan.
He also suggests a few other, more practical things we can do.
- Learn to distinguish between Extremistan and Mediocristan.
- Learn not to demand certainty.
- Feel free to predict and accept predictions for small Extremistan things, like the weather.
- Avoid predicting and accepting expert predictions for large Extremistan things, like the stock market.
- Be generally prepared for all possibilities. (One of my main beefs with Taleb is on this point. He does not answer the nagging question, "With limited resources to commit to preparation, 'For what should we prepare?'", since this takes us headfirst right back to the problem.)
- Minimize your exposure to negative Black Swans, where the worst case scenarios can destroy everything. An example is to invest a large portion of your portfolio (he presumes we all have them) in ultra-safe Treasury bills, and risk the rest on much riskier things. Then if the riskier things go pear shaped, you're not left destitute.
- Maximize your exposure to positive White Swans, where the best case scenarios can improve everything. This means expose yourself to opportunity. (A respected teacher of mine used to advise, "Lay traps for miracles.") Go to parties, live in big cities, attend lectures and talk during the coffee break.
- Carpe diem like nobody's business, seizing everything that even vaguely smells like an opportunity.
The end of the book is an in-depth criticism of the flaws and presumptions of the bell curve, but it is mostly mathematic in nature, and inaccessible to your poor reviewer.
All in all these are good, eye-opening points he makes, once you make it through and write and rewrite what it is you think you heard. I think he's right that domains like Extremistan exist, and his advice on dealing with them makes sense. If you're up for the grind and would like to know more details, grab the book and give it a try. If you do, my only remaining advice is to skip chapter 1, which he spends expounding on his personal background and why that makes him so super, duper special.
This review is dedicated to the klump, for bearing with my unusually long borrowing.