Understanding Hindsight Bias and Its Implications in Trial Strategy

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