STEWART BRAND is cofounder and co-chairman of The Long Now Foundation and author of How Buildings Learn, and The Clock of the Long Now.
that, if we used the right distribution, nothing would be a Black
Swan, but the inference about "power laws" is misguided,
and I would like to go a little deeper into the discussion. Also,
a "power law" is another name for what I referred to as
Pareto's distribution in my discussion.
Those who specialise in the statistical properties of large deviations and in their epistemology find it preferable to avoid the casual (and now journalistic) designation "power law" to characterize all manner of fat-tailed processes, particularly those for which we do not have ample sample size. We are experiencing enormous difficulties characterizing those, let alone calibrating them from nonphysical processes. The use of "power laws" for historical events (particularly terrorism) is a gross simplification: history is far more difficult to characterize than a collection of sandpiles; historical knowledge is not verifiable by experiments. As a skeptical empiricist I find it is far preferable to just plead ignorance in these situations and say "I don't know the distribution".
NASSIM TALEB, an essayist and mathematical trader who studies large-impact hard-to-predict rare events ("Black Swans") is the author of Fooled by Randomness.
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