Hindsight Bias and other
Probabilistic Processing Problems
Presented to the
Costco Wholesale Defense Counsel Conference
August 25, 2006
Edward P. Schwartz
www.EPS-Consulting.com
8/25/2006
www.EPS-Consulting.com
1
Advice on Trial Strategy
1. What do we know?
•
•
•
Statistical Verdict Studies
Surveys
Mock Jury Experiments
2. What can we extrapolate from what we know?
•
•
Related Studies
Experience with Similar Cases
3. What do we need to study?
•
Run our own survey, focus group or mock trial
8/25/2006
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2
Information Aggregation
• Meter Readers (Lopes, 1986, Hogarth and
Einhorn, 1992)
– Algebraic
– Balancing
– Anchoring and Adjustment
• Story Tellers (Pennington and Hastie, 1991)
– Narrative Construction
– Seek Coherence
– More prevalent
8/25/2006
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3
Hindsight Bias
• Jurors tend to treat low a probability event that actually
occurs as much more likely than it is.
– Jurors will believe it to have been more easily anticipated and will
assign greater urgency to guarding against it.
– Jurors often conclude that manufacturers, utilities and doctors should
have anticipated every contingency.
– Jurors can be quick to blame victims who engage in intrinsically risky
behavior, regardless of who might have been negligent
• A second order effect is that the more bizarre the
circumstances, the more jurors tend to believe that it must
have been “somebody’s fault.”
8/25/2006
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4
Beware!
Jurors HATE cost-benefit
analysis!!!
8/25/2006
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Juror Reaction to Cost-Benefit Analysis
Viscusi Punitive Damages study, 2001
Faulty car electrical system
Judge awarded $800k per victim in compensatory
damages
Proportion
favoring punitives
Average punitive
award
C/B Analysis?
Value of life used
None
N/A
0.881
$2.91 million
Yes
Compensatory
award: $800k
0.928
$4.02 million
NHTSA value:
$3 million
0.931
$5.31 million
Cost: $4 million/life
Yes
Cost: $4 million/life
8/25/2006
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Mitigating Hindsight Bias
• One strategy for overcoming hindsight bias is to
argue by analogy to something familiar to jurors.
– Sneezing while driving
– Teenage babysitters
– Skiing without a helmet
• Avoid “zero-risk fallacy” jurors
– Supplemental juror questionnaires
– Safe career choices
• Focus on positive safety policies
8/25/2006
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7
Be prepared!
• Witness Prep
– Employees, experts
– Simulate aggressive cross examination
• Focus Groups
– Which arguments will fly?
– Test exhibits for clarity and comprehension
– Can experts “teach”?
• Surveys
– Who are likely to be the “zero-risk fallacy” jurors?
– Who will be sympathetic to safety concerns of Costco employees?
8/25/2006
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8
Gestation Time for a Hippopotamus
months
90%
months
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9
Distance between Seattle and
Rio de Janeiro
miles
90%
miles
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10
Number of Major League Baseball Players
earning more than $2 million this season
players
90%
players
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Gestation Time for a Hippopotamus
months
8 months
90%
months
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Distance between Seattle and
Rio de Janeiro
miles
5987 miles
90%
miles
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Number of Major League Baseball Players
earning more than $2 million this season
players
277 players
= 32%
90%
players
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Overconfidence in Estimates
1. People tend to be overconfident in their own
estimates.
2. People also generally believe that the world is
more predictable and controllable than it really is.
3. This results in an attitude of “Well, if I had been in
charge, something like this never would have
happened.”
4. So, how do you counteract this type of attitude?
8/25/2006
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15
We’re all human
Just because your house caught on fire doesn’t make it a fire trap.
Just because you had a car accident doesn’t make you a bad driver.
Just because you lost your car keys doesn’t make you irresponsible.
Just because your kid fell down and had to go to the emergency room
doesn’t make you a bad parent.
Just because you missed a deadline at work doesn’t make you a bad
employee.
Just because someone got hurt at Costco doesn’t make it an
unsafe store.
8/25/2006
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Probabilistic Example
30-year-old white woman takes FDA approved home AIDS test.
She tests positive for HIV and immediately calls her doctor.
Her doctor puts her on aggressive anti-HIV drugs (HAART) and orders
follow-up tests.
While waiting for additional test results, the patient has an acute allergic
reaction to her medication.
Anaphylactic shock,
Requires hospitalization,
Lapses into coma,
Loses her job as forest ranger,
Some permanent impairment
The follow-up tests come back negative for HIV.
8/25/2006
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Hypothetical Law Suit
Patient sues her doctor:
Doctor should not have put her on medication until follow-up test results
returned
Doctor should have discussed risks of treatment with her in greater
detail
Doctor defends treatment:
Home test was FDA approved and very accurate
AIDS is very aggressive disease, requiring aggressive treatment
Risks of side effects were very low
No rational patient, even had she been fully informed of all risks, would
have refused prescribed treatment.
8/25/2006
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The Home HIV test
The test is 99.9% effective:
It identifies virtually all HIV positive people. That is,
there are no false negative results.
It correctly identifies 99.5% of HIV negative
people. So, the rate of false positives is 0.5%
The test will incorrectly identify 1 out of every 200
HIV- people as HIV+.
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Was the patient likely to be HIV positive?
Before her test
In 2004, approximately 1.1 million Americans were living with HIV
or AIDS.
About 23% of these, or 253,000 were estimated to be women
AIDS disproportionately affects the African American and Hispanic
communities. Only 19% of women living with HIV/AIDS in 2004
were white.
As such, approximately 50,000 white women (13 and older) were
estimated to be HIV positive in 2004.
This represents approximately 0.06% of this particular population.
As such, approximately 6 white women in 10,000 are HIV positive.
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Was the patient likely to be HIV positive?
After her test
Out of 10,000 white women, number expected to be HIV positive after receiving
positive test results:
6 (expected # HIV+) X 1.0 (prob. Test was right) = 6
Out of 10,000 white women, number expected to be HIV negative after
receiving positive test results:
9,994 (expected # HIV-) X 0.005 (prob. Test was wrong) = 49.97
Probability that patient receiving positive test result is actually HIV+:
Number of HIV+ women receiving positive tests =
6
------------------------------------------------------------------------------ = 0.1076
Number of total positive tests
(6 + 49.75)
The probability that this patient was HIV+ was about 11% !!!!!
8/25/2006
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Think Visually!
- Jurors do Each square
represents
100 women
But 50 will test
positive even though
they’re not
10,000
white
women
100
Only 6 are HIV+
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22
Good teachers make good witnesses
• Think of jurors as interested college
freshmen
•
• Jurors appreciate good teachers:
– Pay closer attention.
– More receptive to message.
– Greater credibility.
• Talking down to jurors can produce
“reactance.”
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