Hindsight Bias and other Probabilistic Processing Problems

8/25/2006 www.EPS-Consulting.com 1

Hindsight Bias and other

Probabilistic Processing Problems

Presented to the

Costco Wholesale Defense Counsel Conference

August 25, 2006

Edward P. Schwartzwww.EPS-Consulting.com


Advice on Trial Strategy1. 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


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


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.”


Jurors HATE cost-benefit analysis!!!

Beware!


Juror Reaction to Cost-Benefit AnalysisViscusi Punitive Damages study, 2001

Faulty car electrical system

Judge awarded $800k per victim in compensatory damages

C/B Analysis? Value of life usedProportion

favoring punitivesAverage punitive

award

None N/A 0.881 $2.91 million

Yes Cost: $4 million/life

Compensatory

award: $800k0.928 $4.02 million

YesCost: $4 million/life

NHTSA value:

$3 million0.931 $5.31 million


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


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?


Gestation Time for a Hippopotamus

90%

months

months


Distance between Seattle and Rio de Janeiro

90%

miles

miles


Number of Major League Baseball Players earning more than $2 million this season

90%

players

players


Gestation Time for a Hippopotamus

90%

months

months

8 months


Distance between Seattle and Rio de Janeiro

90%

miles

miles

5987 miles


Number of Major League Baseball Players earning more than $2 million this season

90%

players

players

277 players

= 32%


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?


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.


Probabilistic Example30-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.


Hypothetical Law SuitPatient 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.


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+.


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.


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 ------------------------------------------------------------------ ------------- Number of total positive tests (6 + 49.75)

The probability that this patient was HIV+ was about 11% !!!!!

= 0.1076


Think Visually!- Jurors do -

10,000 white

women

Each square represents 100 women

But 50 will test positive even though

they’re not

100

Only 6 are HIV+


Good teachers make good witnesses

• Think of jurors as interested college freshmen•

– Pay closer attention. – More receptive to message.– Greater credibility.

• Talking down to jurors can produce “reactance.”

• Jurors appreciate good teachers:

Documents

Hindsight Bias and other Probabilistic Processing Problems