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The Black Swan
Chapter 12 (Human can’t predict) and
Chapter 13 (Go to parties!)
Melanie Swan, Futurist
MS Futures Group
http://www.melanieswan.com
http://futurememes.blogspot.com
BCIG National Institutes of Health
Bethesda MD June 28, 2007
BCIG June 28, 2007
2
 Educational background:
 BA French & Economics, Georgetown University
 MBA Finance & Accounting, Wharton, Univ. of Pennsylvania
 Current course work in Physics & Computer Science
 Professional experience
 Futurist: speaker, researcher, business advisor
 Hedge Fund Manager: Wall Street, proprietary
 Current projects
 OpenBasicResearch.org
 del.icio.us for people
 Issues in running Historical Simulations
 Interests: science fiction, travel
Bio – Melanie Swan
BCIG June 28, 2007
3
 Continued theme of inability
to predict, inability to
comprehend uncertainty
 The Past has a Past:
problems with the past
 We do not learn from the past
 Future blindness and future
autism
 Epistemic arrogance
Ch 12 Summary: Humans can’t predict
BCIG June 28, 2007
4
 History is not facts, but ex-post narrative
 The past is very difficult to predict
 Ice cube melting
 “Butterfly in India” paradigm
 The Iliad: Helenus
 Humans cannot understand uncertainty
 Do not learn from the past
 Cannot understand a future mixed with chance
 Black Swan asymmetry allows confidence in
what is wrong
 “Our problem is not just that we don’t know the
future, we don’t know much of the past either…”
Ch 12: The Past has a Past: problems with the past
BCIG June 28, 2007
5
 Humans are not natural skeptics
 Disbelief requires more energy
 No cognitive science research on
future blindness
 Happiness research:
overestimation of both pleasant
and unpleasant events
 Epistemocracy, epistemic
arrogance, epistemic humility
 Advice: skeptical-empiricism like
Monsieur de Montaigne
Ch 12: Future blindness
Michel de Montaigne
BCIG June 28, 2007
6
 Epistemic arrogance and
corresponding future blindness
 Fooled by reductions
 Especially told by people wearing
neckties
 Flawed tools of inference,
especially from Black Swan-free
Mediocristan
 E.g.; perception that the exceptional
is inconsequential
 Confirmation bias
 Casnova / survivor bias
Ch 12: Why humans can’t predict
BCIG June 28, 2007
7
 Phenomenon: low volatility = high risk
 Action in the face of the Black Swan
 Be fooled in small matters not large
 Benefit from unpredictability
 Embrace trial and error
 Manage exposure to Black Swans
 Be prepared and seize opportunity
 Central theme: Asymmetric outcomes
 Uncertainty: prepare for possible
consequences (knowable) vs. the
probability of occurrence (unknowable)
Ch 13 Summary: Go to parties!
BCIG June 28, 2007
8
 People engage in strategies that
produce low volatility but have
the risk of large loss
 Long-time corporate employee vs.
consultant
 Seemingly stable dictatorship
(Saudi Arabia) vs. democracy
 Bankers, lenders
 Achilles heel of capitalism: the
fittest looking company is the
most exposed for a negative
Black Swan
 Enron, IBM, telecoms, etc.
Ch 13: Phenomenon: low volatility = high risk
BCIG June 28, 2007
9
 Distinguish between positive and negative contingencies
 Act against errors in prediction and risk perception
 Lopsided barbell: increase exposure to positive Black Swans,
decrease exposure to negative Black Swans
 Financial investments: 85-90% in T-bills (safest), 10-15% in as
many as possible options/private equity (riskiest)
Ch 13: Manage your Black Swan exposure
Positive Black Swan Industries Negative Black Swan Industries
 Scientific Research
 Biotech
 Movies
 Publishing
 Venture Capital
 Military
 Catastrophe insurance
 Homeland security
 Banking, lending
BCIG June 28, 2007
10
 Don’t look for the precise and
the local
 Pasteur “Chance favors the
prepared”
 Seize opportunity
 Collect non-lottery tickets (open-
ended payoffs)
 Gain exposure to the envelope
of serendipity: go to parties
 Beware of forecasters
 Public and private sector equally
bad at forecasting - “paid
forecasters are institutionalized
fraud”
Ch 13: Be prepared and seize opportunity
BCIG June 28, 2007
11
 Why humans can’t predict
 Epistemic arrogance
 Fooled by reductions
 Flawed tools of inference from Mediocristan
Ch 12-13 Summary: Don’t predict, go to parties
Mediocristan Extremistan
 Gaussian
 Linear (easier to predict)
 Experts
 Exceptional is inconsequential
 Black Swans
 Non-linear (impossible to predict)
 No experts
 Exception matters
 Central theme of the book: Asymmetric outcomes
 Uncertainty: focus on the consequences (knowable) vs. the
probability of occurrence (unknowable)
 Use preparedness and serendipity to manage Black
Swan exposure
Thank you Melanie Swan, Futurist
MS Futures Group
http://www.melanieswan.com
http://futurememes.blogspot.com

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Black Swan Chapter Summaries: Humans Can't Predict

  • 1. The Black Swan Chapter 12 (Human can’t predict) and Chapter 13 (Go to parties!) Melanie Swan, Futurist MS Futures Group http://www.melanieswan.com http://futurememes.blogspot.com BCIG National Institutes of Health Bethesda MD June 28, 2007
  • 2. BCIG June 28, 2007 2  Educational background:  BA French & Economics, Georgetown University  MBA Finance & Accounting, Wharton, Univ. of Pennsylvania  Current course work in Physics & Computer Science  Professional experience  Futurist: speaker, researcher, business advisor  Hedge Fund Manager: Wall Street, proprietary  Current projects  OpenBasicResearch.org  del.icio.us for people  Issues in running Historical Simulations  Interests: science fiction, travel Bio – Melanie Swan
  • 3. BCIG June 28, 2007 3  Continued theme of inability to predict, inability to comprehend uncertainty  The Past has a Past: problems with the past  We do not learn from the past  Future blindness and future autism  Epistemic arrogance Ch 12 Summary: Humans can’t predict
  • 4. BCIG June 28, 2007 4  History is not facts, but ex-post narrative  The past is very difficult to predict  Ice cube melting  “Butterfly in India” paradigm  The Iliad: Helenus  Humans cannot understand uncertainty  Do not learn from the past  Cannot understand a future mixed with chance  Black Swan asymmetry allows confidence in what is wrong  “Our problem is not just that we don’t know the future, we don’t know much of the past either…” Ch 12: The Past has a Past: problems with the past
  • 5. BCIG June 28, 2007 5  Humans are not natural skeptics  Disbelief requires more energy  No cognitive science research on future blindness  Happiness research: overestimation of both pleasant and unpleasant events  Epistemocracy, epistemic arrogance, epistemic humility  Advice: skeptical-empiricism like Monsieur de Montaigne Ch 12: Future blindness Michel de Montaigne
  • 6. BCIG June 28, 2007 6  Epistemic arrogance and corresponding future blindness  Fooled by reductions  Especially told by people wearing neckties  Flawed tools of inference, especially from Black Swan-free Mediocristan  E.g.; perception that the exceptional is inconsequential  Confirmation bias  Casnova / survivor bias Ch 12: Why humans can’t predict
  • 7. BCIG June 28, 2007 7  Phenomenon: low volatility = high risk  Action in the face of the Black Swan  Be fooled in small matters not large  Benefit from unpredictability  Embrace trial and error  Manage exposure to Black Swans  Be prepared and seize opportunity  Central theme: Asymmetric outcomes  Uncertainty: prepare for possible consequences (knowable) vs. the probability of occurrence (unknowable) Ch 13 Summary: Go to parties!
  • 8. BCIG June 28, 2007 8  People engage in strategies that produce low volatility but have the risk of large loss  Long-time corporate employee vs. consultant  Seemingly stable dictatorship (Saudi Arabia) vs. democracy  Bankers, lenders  Achilles heel of capitalism: the fittest looking company is the most exposed for a negative Black Swan  Enron, IBM, telecoms, etc. Ch 13: Phenomenon: low volatility = high risk
  • 9. BCIG June 28, 2007 9  Distinguish between positive and negative contingencies  Act against errors in prediction and risk perception  Lopsided barbell: increase exposure to positive Black Swans, decrease exposure to negative Black Swans  Financial investments: 85-90% in T-bills (safest), 10-15% in as many as possible options/private equity (riskiest) Ch 13: Manage your Black Swan exposure Positive Black Swan Industries Negative Black Swan Industries  Scientific Research  Biotech  Movies  Publishing  Venture Capital  Military  Catastrophe insurance  Homeland security  Banking, lending
  • 10. BCIG June 28, 2007 10  Don’t look for the precise and the local  Pasteur “Chance favors the prepared”  Seize opportunity  Collect non-lottery tickets (open- ended payoffs)  Gain exposure to the envelope of serendipity: go to parties  Beware of forecasters  Public and private sector equally bad at forecasting - “paid forecasters are institutionalized fraud” Ch 13: Be prepared and seize opportunity
  • 11. BCIG June 28, 2007 11  Why humans can’t predict  Epistemic arrogance  Fooled by reductions  Flawed tools of inference from Mediocristan Ch 12-13 Summary: Don’t predict, go to parties Mediocristan Extremistan  Gaussian  Linear (easier to predict)  Experts  Exceptional is inconsequential  Black Swans  Non-linear (impossible to predict)  No experts  Exception matters  Central theme of the book: Asymmetric outcomes  Uncertainty: focus on the consequences (knowable) vs. the probability of occurrence (unknowable)  Use preparedness and serendipity to manage Black Swan exposure
  • 12. Thank you Melanie Swan, Futurist MS Futures Group http://www.melanieswan.com http://futurememes.blogspot.com