Nassim Taleb, The Black Swan: The Impact of the Highly Improbable (2007) Author Background: devoted student of luck, uncertainty, probablity and knowledge. Professor in Science of Uncertainty at Amherst. Wrote Fooled by Randomness.

Thesis: Experts tend to overestimate what they know and underestimate the uncertainty that is derived from the things they don't know. We can't know what we don't know.

Arguments: - Actively seek viewpoints that contradict your own. Better yet, start from the premise that you are wrong.

- Leader can handle Black Swans, managers cannot - With Black Swans a plan is less important than planning, be agile, prepared to respond. - Emil du Bois-Reymond “We are ignorant and will remain so” while it might seem hard to operate in such an environment, acknowledging that you don't know everything can actually give you a leg up on those people who instead prefer to proceed through life confidently knowing the wrong things. - The power law is much more prevelant than the normal distribution Power Law xx not only can’t we predict what will happen, we are unaware that we are so inept at predicting what will happen

9 the world is not explicable, educated people have the disadvantage of thinking they know enough to make sense of it all

33 technology increases the number of arenas where the outlier is fantastically far out

Beware of the unknown unknown
One important lesson imbedded in these historical analogies is that what we don't know is frequently more important than what we do know (or think we know).

55 avoid definitive, closed beliefs

56 we tend to look for evidence a hypothesis is true, not false

58 you know what is wrong with a lot more confidence than you know what is right, if I don’t see cancer cells in the sample, I can’t say for certain the patient is cancer-free

69 “the same condition [limited cognition] that makes us simplify pushes us to think that the world is less random than it actually is”

74 media, using fact checkers, appears to want to be wrong with infinite precision rather than approximately right (like writers of fables)

140 we overestimate what we know, and the certainty with which we know it

177 sensitive dependence on initial conditions, and the exponential growth in small errors, reveal our inability to predict

182-3 follow empiricism, even if it doesn’t “make sense” – it works!

195 we do not learn from past prediction errors, nor do we remember that we adapt 195

203 be cognizant of these human limitations

203 be prepared for all relevant eventualities

209 beware of govt predictions – civil servants predict without motivation to get to the truth, but to perpetuate their jobs

277 social science theories get traction because they are easy to pass on, not because they are valid

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