Nassim Nicholas Taleb
Academic libertarian: someone
(like myself) who considers that knowledge is subjected to strict rules, but not institutional authority
as the interests of organized knowledge is self-perpetuation, not necessarily
truth (as with governments). Some
academic circles can suffer from an acute expert problem (q.v.) producing cosmetic but fake knowledge,
particularly in narrative disciplines (q.v.), an can be a main source of Black Swans.
Apelles-style strategy: a strategy of seeking positive gains by collecting positive accidents
by maximizing exposure to Ògood Black SwansÓ.
Barbell Strategy:
method that consists in taking both a defensive attitude and an excessively
aggressive one at the same time, by protecting assets from all sources of
uncertainty while allocating a small portion for high-risk strategies.
Bildungsphilister:
a philistine with cosmetic,
non-genuine culture, prone to be an imitator –Nietzsche meant the
dogma-prone newspaper reader and opera lover with cosmetic exposure to culture
and shallow depth. I extend it to the buzzword-using researcher in
non-experimental fields, who lacks in imagination, curiosity, erudition and
culture and is closely-centered on his ideas, on his ÒdisciplineÓ, not
questioning the cultural map around him. This prevents him from seeing the
conflicts between his ideas and the texture of the world.
Black Swan ethical problem: owing to the nonrepeatable aspect of the Black
Swan, there is an asymmetry between the rewards of those who prevent compared
to those who cure.
Black-Swan blindness:
underestimation of the role of the Black Swan, and occasional
overestimation of some specific one.
Confirmation error –or Platonic confirmation: you look for instances that confirm your beliefs, your construction (or
model) –and find them.
Empty suit problem (or Òexpert problemÓ): some members of professions have no differential
abilities from the rest of the population, but, for some reason, and against
their empirical record, are believed to be experts: clinical psychologists,
academic economists, risk ÒexpertsÓ, statisticians, political analysts, financial ÒexpertsÓ, military
analysts, CEOs. etc. They dress up their expertise in beautiful language,
jargon, mathematics, and often wear expensive suits.
Epilogism: a theory
free method of looking at history with minimal generalization and with consciousness of the side
effect of making causal claims. The idea is not to go too much outside the
observations, minimize claims about the unseen.
Epistemic arrogance:
take a measure of the difference between what someone actually knows and how
much he thinks he knows. An excess
will imply arrogance, a deficit humility. An epistemocrat is someone of
epistemic humility, one who holds his own knowledge in greatest suspicion.
Epistemic opacity:
randomness is the result of incomplete information at some level. It is
functionally indistinguishable from ÒtrueÓ or ÒphysicalÓ randomness.
Extremistan: province where the total can be conceivably
impacted by a single observation.
Fallacy of silent evidence: looking at history, we do not see the full story, only the rosier
parts of the process.
Fooled by Randomness: general
confusion between luck and determinism, leading to a variety of superstitions,
with practical consequences such as the belief that earnings in some profession are generated by skills
when there is a significant component of luck in them.
Future blindness:
our natural inability to take into account the properties of the future
–like autism which prevents one from taking into account the existence of
the minds of others.
LockeÕs madman: someone
who makes impeccable and rigorous reasoning from faulty premises
–Samuelson, Robert Merton the minor,Gerard Debreu --thus
producing phony models of uncertainty that make us vulnerable to Black Swans.
Lottery ticket fallacy:
the naive analogy equating an investment in collecting positive Black Swans to
the accumulation of lottery ticket. Lottery tickets are not scalable.
Ludic fallacy (or
uncertainty of the nerd): Manifestation of the
Platonic fallacy in the study of uncertainty; basing studies of chance on the
narrow world of games and dice. APlatonic randomness has an additional layer of uncertainty concerning the rules of the game of real life. The Bell curve
(Gaussian) or GIF, great intellectual
fraud, is the application of the
ludic fallacy to randomness.
Mandelbrotian Gray Swan. Black Swans that we can somewhat take into account –earthquakes,
blockbuster books, stock market crashes – except that it is not possible
to completely figure out their properties and produce precise calculations.
Mediocristan: province dominated by the mediocre, with few extreme successes or
failures. No single observation can meaningfully affect the aggregate. The bell
curve is grounded in Mediocristan. There is a qualitative difference between
Gaussians and scalable laws, much like gas and water.
Naive Empiricism
Narrative discipline:
discipline that consists in fitting a convincing and well-sounding story to the
past (history, statistics, political science). Opposed to experimental
discipline (medicine, classical and quantum physics).
Narrative fallacy:
our need to fit a story or pattern to a series of connected or disconnected
facts. The statistical application
is data mining.
Nerd knowledge: the belief that what cannot be Platonized and
studied does not exist at all, or is not worth considering. There even exists a
form of skepticism practiced by the nerd.
Platonic fold: The
place where our Platonic representation enters in contact with reality and you
can see the side effects of models.
Platonicity: the
focus on those pure, well-defined, and
easily discernible objects like triangles, or more social notions, like
friendship or love – at the cost of ignoring those objects of seemingly
messier and less tractable
structures.
Probability distribution: the model used to calculate the odds of different events, how
they are ÒdistributedÓ. When we
say that an event is distributed according the Òbell curveÓ I mean that the
Gaussian bell curve (after C.F. Gauss, on whom later) can help provide
probabilities of various occurrences.
Problem of induction:
The logical-philosophical extension of the Black Swan Problem.
Randomness as incomplete information: Is
random, simply what I cannot guess because my knowledge about the causes is incomplete, not necessarily because the
process has truly unpredictable properties.
Retrospective distortion: Examining past events with- out adjusting for the forward passage of
time. It leads to the illusion of
posterior predictability.
Reverse Engineering Problem: It is easier to predict how an ince cube would melt into a puddle
than, looking at a puddle, to guess the shape of the ice cube that may have
caused it. This makes narrative disciplines and accounts (such as histories)
suspicious.
Round-trip fallacy:
the confusion of absence of evidence of Black Swans (or something else) for evidence of absence of Black Swans
(or something else). It affects statisticians and other people who have lost
part of their reasoning by solving too many equations.
Scandal of prediction:
the poor prediction record in some forecasting entities (particularly narrative
disciplines) mixed with verbose commentary and lack of awareness of their own
dire past record.
Scorn of the abstract:
Favoring contextualized thinking over more abstract, though more relevant,
matters. ÒThe death of one child is a tragedy; the death of a million is a
statistic.Ó
Statistical regress argument ( or problem of the
circularity of statistics): we need data to discover a probability distribution. How do we know if we have enough data? From the
probability distribution. If it is a Gaussian, then a few points will
suffice. How do we know it is a Gaussian? From the data. So we need the data
to tell us what the probability
distribution to assume, and a probability distribution to tell us how much data
we need. This causes a severe regress argument –which is somewhat
shamelessly circumvented by resorting to the Gaussian and its kin.
Problem
of small probability.
Uncertainty of the deluded: People who tunnel on sources of uncertainty by
producing precise sources like the great uncertainty principle or similar, less
consequential, matters to real life, worrying about subatomic particles while
forgetting that we canÕt predict tomorrowÕs crises.