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The Black Swan
Book

The Black Swan

The Impact of the Highly Improbable

Random House, 2007 更多详情


Editorial Rating

10

Recommendation

According to critic Harold Bloom, Hamlet’s predicament is not “that he thinks too much” but rather that “he thinks too well,” being ultimately “unable to rest in illusions of any kind.” The same could be said for philosopher, essayist and trader Nassim Nicholas Taleb, who finds something rotten in misguided yet supremely confident investment gurus, traders, hedge fund managers, Wall Street bankers, M.B.A.s, CEOs, Nobel-winning economists and others who claim that they can predict the future and explain the past. Like everyone else, says Taleb, these so-called “experts” fail to appreciate “black swans”: highly consequential but unlikely events that render predictions and standard explanations worse than worthless. Taleb’s style is personal and literary, but his heterodox insights are rigorous (if sometimes jolted by authorial filigree). This combination makes for a thrilling, disturbing, contentious and unforgettable book on chance and randomness. While Taleb offers strong medicine some readers may find too bitter at times, getAbstract prescribes it to anyone who wants a powerful inoculation against gullibility.

Take-Aways

  • “Black swans” are highly consequential but unlikely events that are easily explainable – but only in retrospect.
  • Black swans have shaped the history of technology, science, business and culture.
  • As the world gets more connected, black swans are becoming more consequential.

About the Author

Nassim Nicholas Taleb, a former derivatives trader, is Dean’s Professor in the Sciences of Uncertainty at the University of Massachusetts and teaches at New York University’s Courant Institute of Mathematical Sciences. He also wrote Fooled by Randomness.


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    A. .. 8 years ago
    The experts or "gurues" of the future are unknown today
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    E. Z. 9 years ago
    Need to read the book. A lot of complicated concepts
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    R. J. 1 decade ago
    Appreciated the closing comment on how we are all statistical outliers.