The Black Swan: The Impact of the Highly Improbable, by Nassim Nicholas Taleb, is none of those things. First, it's an intellectually challenging book, so it's not for everyone (particularly economists, social scientists and government planners, who would benefit from reading it, but take quite a beating from Mr. Taleb here). Second, the tone is engaging, but certainly not cheerleading, and ranges from dryly academic in spots (e.g. discursions on competing schools of philosophy) to positively engrossing (e.g. first-hand accounts of the Lebanese civil war). Finally, the author's advice, while highly practical, deals with nothing as mundane as B2B lead generation or podcasting, and will require considerable thought on the part of the reader to properly and constructively apply.
The "black swan" of the title comes from the fact that for centuries, scientists and pretty much everyone else believed that all swans were white. The first sighting of a black swan thus completely upset the established conventional wisdom. A "black swan" in the context of Taleb's book is a completely unexpected event that has a large impact. The terrorist attack of 9-11 was a black swan, as was the stock market crash of October 1987. Black swan events can be positive as well, such as the end of the cold war.
To give you some sense of the book, here are just three of the author's numerous intriguing observations and anecdotes:
1. Know when to apply the bell curve—and when not to. If you gather a thousand people in a stadium, and measure their weight (or height, or IQ, or any other natural measure), you can plot that on a bell curve, and be highly confident that one additional observation wouldn't have any significant effect on your statistics (i.e. you won't a human anywhere who is 900 feet tall and weighs 50,000 pounds).
The bell curve does not, however, apply in the man-made realm. Measure the financial net worth of those same thousand people, and then add a 1,001st person—Bill Gates. What does that do to the shape of the curve, and the average value? Human-world attributes don't follow the bell curve: stock market valuations, book sales by author, the income distribution for actors, singers and professional athletes, stock valuations within a specific industry, etc. Prediction errors are frequently caused by applying bell curve thinking to non-bell curve phenomena.
2. Predictions are always wrong. Before reading this book, I believed that economic forecasts were generally more reliable than weather forecasts (particularly living here in Minnesota, it's difficult to imagine anyone making a living being wrong more often than our weather forecasters). Yet weather patterns, despite their intrinsic variability, still follow physical laws. The entire "science" of economics rests on a faulty premise—that people will always act rationally to maximize value. That is, cloud formations and wind patterns have no free will, but people do. Throw in one large irrational economic act, or a hundred small ones, and economic forecasts become dreadfully wrong. Yet research also shows that while economic forecasts rarely cluster around the true values (e.g. next year's GDP growth rate or prime interest rate), predicted values do usually cluster around each other. Which is to say, economists seem to be more afraid of being significantly different from one another than they are of being significantly wrong.
As an example of this, Taleb writes about the experience of a large Las Vegas casino. The casino went to great length and expense to protect itself from gambling losses or unusual "lucky streaks." Yet these risks were both modest and quantifiable. The six largest financial losses in the casino's history had nothing to do, directly, with gambling at all. Among these were the loss of an irreplaceable performer to a tiger mauling; the kidnapping for ransom of the owner's daughter; and a large fine after it was discovered that a casino employee had inexplicably failed the winnings of high-rollers to the federal government for tax purposes.
3. Recognize the limitations of classroom knowledge in the real world, or, the importance of street smarts. An engineer and a real estate speculator were both posed the classic question, "If I am flipping a perfectly fair coin, and it comes up heads 99 times in a row, what are the odds of it coming up tails on the 100th flip?" The engineer answers: 50%. That's the correct answer, the one we all learned in school, right? The speculator, however, though he knows the "right" answer just as well as the engineer, pegs the odds at no more than 1%. Why? Because, given that heads have come up 99 times in a row, he questions the assertion that this is indeed a "fair coin." To use the tired but applicable phrase, he "thinks outside the box" by questioning the basic premise of the question. This relates to the weakness of economic forecasts which rely on the assumption of "human rationality" as well.
Three interesting facts from the book that you may or may not have known:
1. "The best predictor of the success of a movie is mild rain in large cities on the release date." Light rain makes outdoor activities unpleasant, but doesn't keep people from going out altogether. This increases the probability of a big opening weekend and subsequent buzz for the film.
2. Alexander Fleming accidentally discovered the antibacterial properties of penicillin when one of his old experiments became contaminated.
3. Charles Townes, inventor of the laser, was initially teased by colleagues about the irrelevance of his discovery.
And finally, three lessons from the book:
1. Be humble about your knowledge. Taleb writes about author Umberto Eco's "antilibrary," a collection of 30,000+ unread books. Eco keeps this library to remind himself of how much there is that he doesn't know, which helps him maintain humility. It's okay to say "I don't know" when that is indeed the right answer. It helps one avoid making (inevitably wrong) predictions.
2. Follow the 85/15 rule. Focus 85% of your endeavors (professional time, your stock portfolio, etc.) on low-risk ventures. These are investments with a high probability of yielding small returns, and extremely low probability of loss. They are unexciting, but keep you from starving in the dark.
Invest the other 15% in black swan-seeking, high-risk opportunities. These carry a low probability of a very high payout. While there is high risk of loss (but remember, this is only 15%—and the investments should be spread out to avoid overexposure to any single opportunity), these are exciting and hold the potential to let you do far more than keep the lights on and food in the refrigerator.
3. Be skeptical and empirical. In other words, be like the real estate speculator. Question assumptions, dubious reasoning and even "facts." Believe what you can verify through observation and experimentation, mindful of the limits of your knowledge and aware of the possibility of black swans.
Taleb simply thinks at a higher level than many other writers. This book isn't for everyone—but if you are up to the intellectual challenge, reading The Black Swan: The Impact of the Highly Improbable will be highly rewarding.
Other reviews of this book: Platformonics blog, BusinessWeek
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