Hindsight Bias and other Probabilistic Processing Problems

1. 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 www.EPS-Consulting.com

2. Advice on Trial Strategy • What do we know? • Statistical Verdict Studies • Surveys • Mock Jury Experiments • What can we extrapolate from what we know? • Related Studies • Experience with Similar Cases • What do we need to study? • Run our own survey, focus group or mock trial www.EPS-Consulting.com

3. 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 www.EPS-Consulting.com

4. 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.” www.EPS-Consulting.com

5. Beware! Jurors HATE cost-benefit analysis!!! www.EPS-Consulting.com

6. Juror Reaction to Cost-Benefit AnalysisViscusi Punitive Damages study, 2001 Faulty car electrical system Judge awarded $800k per victim in compensatory damages www.EPS-Consulting.com

7. 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 www.EPS-Consulting.com

8. 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? www.EPS-Consulting.com

9. months 90% months Gestation Time for a Hippopotamus www.EPS-Consulting.com

10. miles 90% miles Distance between Seattle and Rio de Janeiro www.EPS-Consulting.com

11. players 90% players Number of Major League Baseball Players earning more than $2 million this season www.EPS-Consulting.com

12. months 90% months Gestation Time for a Hippopotamus 8 months www.EPS-Consulting.com

13. Distance between Seattle and Rio de Janeiro miles 90% 5987 miles miles www.EPS-Consulting.com

14. Number of Major League Baseball Players earning more than $2 million this season players 277 players = 32% 90% players www.EPS-Consulting.com

15. Overconfidence in Estimates • People tend to be overconfident in their own estimates. • People also generally believe that the world is more predictable and controllable than it really is. • This results in an attitude of “Well, if I had been in charge, something like this never would have happened.” • So, how do you counteract this type of attitude? www.EPS-Consulting.com

16. 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. www.EPS-Consulting.com

17. 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. www.EPS-Consulting.com

18. 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. www.EPS-Consulting.com

19. 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+. www.EPS-Consulting.com

20. Was the patient likely to be HIV positive?Before her test In 2004, approximately 1.1 millionAmericans 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. www.EPS-Consulting.com

21. 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 www.EPS-Consulting.com

22. Each square represents 100 women But 50 will test positive even though they’re not 10,000 white women 100 Only 6 are HIV+ Think Visually!- Jurors do - www.EPS-Consulting.com

23. 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.” www.EPS-Consulting.com