What Jurors Hear When DNA Experts Testify: Results From Controlled Experiments Jonathan J. Koehler McCombs School of Bu

1. What Jurors Hear When DNA Experts Testify: Results From Controlled Experiments Jonathan J. Koehler McCombs School of Business The University of Texas at Austin koehler@mail.utexas.edu Forensic Bioinformatics5th Annual Conference Dayton, OH August 13, 2006

2. What is a Controlled Experiment? A scientific method for testing hypothesized causal relationships between independent and dependent variables Randomly assign subjects to groups Manipulate independent variables Measure dependent variables Advantage: Control Disadvantage: Artificial

3. Who Are the Subjects in Jury Experiments? Students “Real” jurors

4. Does Type of Subject Matter? “[T]he overwhelming majority of studies that have directly compared different mock juror samples have failed to find consistent differences…[There is] strong evidence that factors at trial affect students and nonstudents in the same way.” (Bornstein, 1999, p. 80)

5. What Kind of Materials are Used in Jury Experiments? Simple Written Materials (1 page case summaries) Detailed Written Materials (opening arguments, witness statements, closing arguments, judicial instructions, deliberation) Detailed Video Materials (videotaped trials based on actual cases, deliberation)

6. Does Type of Experimental Materials Matter? “Studies that have directly compared presentation media [e.g., written summaries, transcripts, audiotape, videotape] – for either a whole trial or a portion of testimony – fail to offer consistent findings. . . . [R]esearch on the trial medium tends not to find many differences.” (Bornstein, 1999, p. 82 & 84)

7. Conclusion The results of controlled studies (i.e., experiments) with mock jurors can provide insight into how real jurors think and respond at trial.

8. Theory The weight that people attach to statistical evidence is influenced by whether or not they can easily imagine examples of the event in question.

9. Lottery Example There are different ways to describe the chance of winning the daily three-digit New York Lottery Numbers game: 1. One in every 1,000 tickets out of the 500,000 tickets that are sold each day will win. 2. There is a 0.1% chance that your ticket will win.

10. Statistical Information Can Be “Formed” in Different Ways Frequency Form: 1 in 1,000 Probability Form: 0.1% Odds Form: 1:999

11. Statistical Information Can be “Targeted” in Different Ways Multiple Target (examples: yes) Single Target (examples: no) “0.1% of the 500,000 tickets sold each day will win” [multiple] “There is a 0.1% chance that your ticket will win” [single]

12. What is the Relevance of Statistical Forms and Targets for DNA Evidence? Statistical Form and Target influence whether jurors find it easy or hard to imagine examples of others who might match. Easy to imagine examples of other matches? Yes No

13. Experiment #1:Clinton – Lewinsky(RMP = .001) Two Groups 1. Probability Form + Single Target “The probability that Mr. Clinton would match the semen stain if he were not its source is 0.1%” 2. Frequency Form + Multiple Target “1 in 1,000 people in Washington D.C. who are not the source would also match the semen stain”

14. How Likely is Clinton the Source of the DNA on Monica’s Dress?

15. Proportion of Jurors Who are at Least 99% Certain that Clinton is the Source

16. Experiment #2:Murder Facts Hardware store owner shot and killed during robbery Killer wore a mask Killer bled at crime scene Several neighborhood residents gave blood samples One suspect matched partial PCR DNA profile (RMP = 1 in 100,000) No corroborating evidence

17. Variables Independent Variables Form (probability, frequency) Target (single, multiple) Reference Class Size (small, large) Dependent Variables Evidence Strength Probability of Source Probability of Guilt Verdict

21. Does RMP Size Matter? RMP & Reference Class Size affect whether examples of coincidental matches will be easy or hard to imagine. RMP Reference Class Size Examples? 1 in 1,000 5,000,000 Yes 1 in 1,000,000 5,000,000 Yes 1 in 1,000,000,000 5,000,000 No Implication: The way RMP is presented matters less as RMP becomes very small.

22. Form X RMP Frequency

23. Target X RMP Frequency

24. Experiment #3:Pseudo-Exemplar Expert: My tests cannot rule out [the suspect] as a possible source of the recovered genetic material. Approximately [X] out of [Y] people share this DNA profile, and the suspect is one of those people. RMP = 1 in 100,000 A. 0.1 out of 10,000 people B. 1 out of 100,000 people C. 2 out of 200,000 people RMP = 1 in 1,000 A. 0.1 out of 100 people B. 1 out of 1,000 people C. 2 out of 2,000 people

28. DNA Evidence in Odds Form DNA evidence can be presented in odds form as the ratio of 2 conditional probabilities, when a few assumptions are made. This is the Likelihood Ratio (LR) The LR is a term that appears in a mathematical formula called Bayes Theorem.

30. Do People Understand LRs? 77% of people verbally confuse LRs with Posterior Odds Ratios (Wolfe, 1995) Most people reason more accurately with frequencies than with conditional probabilities (Cosmides & Tooby, 1996) Some people equate P(H|D) with P(H&D) (Gigerenzer & Hoffrage, 1995) or with P(D|H) (Thompson, 1989)

31. LR Confusion in Court Experts Make Errors When Explaining the meaning of a LR LR = 14,961 [State of Texas v. Griffith, 1996] Expert: “Given this evidence, it is 14,961 times more likely that the defendant is the father than a random man.”

32. LR Confusion in Court (continued) Proper Statement (LR): "It is 14,941 times more likely that we would see this evidence if the defendant were the father than if the defendant were not the father.“ Improper Statement (Posterior Odds): “Given this evidence, it is 14,941 times more likely that the defendant is that father than that the defendant is not the father.“ Is it reasonable to expect that jurors will understand that these two statements are different?

33. Experiment #4:Freq. vs. LR vs. Posterior Odds Ratio Three Groups 1. Frequency: Approximately 1 person out of every 1000 would yield a DNA match with the semen and the defendant is one such person. 2. LR: It is approximately 1000 times more likely we would see this DNA match if the defendant is the source of the semen than if the defendant is not the source of the semen." 3. Posterior Odds Ratio: Given that we see this DNA match, it is approximately 1000 times more likely that the defendant is the source of the semen than that he is not the source of the semen.

34. Results Jurors are more persuaded by a LR than by a frequency Jurors respond to a LR just as they respond to a posterior odds ratio. Conclusion: Jurors think that a likelihood is a posterior.

35. Error Rates Do jurors understand how to integrate error rates with RMPs?

36. Experiment #5:Error Rates False Positive Error Rate = .02 (also used .001) RMP = 1 in 1,000,000,000 Three Groups 1. Error rate only 2. RMP only 3. Error Rate + RMP (separately)

39. Summary The way DNA RMPs are presented matter Easy to think of examples: Good for Defense Hard to think of examples: Good for Prosecution LRs are misunderstood DNA error rates are often ignored When not ignored, jurors are not sure how to incorporate them.

40. Related Research Schklar & Diamond (1999) Jurors usually underweight DNA evidence Jurors overweight DNA evidence when given separate estimates for the RMP and error rate - overweighting persists with aggregation instruction Nance & Morris (2005) Aggregation instruction for RMP + error rate has no effect LR approach yields higher conviction rate