attacking non-bayesian reasoning
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Attacking Non-Bayesian Reasoning. William Thompson UC Irvine February 15, 2014. Do Jurors Give More of Less Weight Than They Should to Forensic Science?. Importance to the law of evidence Claims of Underweighting - PowerPoint PPT PresentationTRANSCRIPT
Attacking Non-Bayesian Reasoning
William Thompson UC Irvine
February 15, 2014
Do Jurors Give More of Less Weight Than They Should to Forensic Science?
• Importance to the law of evidence• Claims of Underweighting– Finkelstein & Fairley (1970) , citing Edwards (1968);
Slovic & Lichtenstein (1971)• Claims of Overweighting– Tribe (1971)
• Jury Simulation Studies– E.g., Schklar & Diamond (1999); Nance & Morris,
(2002; 2005)
Figure 1: Log Scale for Estimating Chances Defendant is Guilty
___Certain to be guilty___About 9,999,999 chances in 10 million that he is guilty___About 999,999 chances in 1 million that he is guilty___About 99,999 chances in 100,000 that he is guilty___About 9,999 chances in 10,000 that he is guilty___About 999 chances in 1,000 that he is guilty___About 99 chances in 100 that he is guilty___About 9 chances in 10 that he is guilty___One chance in 2 (fifty-fifty chance) that he is guilty___About 1 chance in 10 that he is guilty___About 1 chance in 100 that he is guilty___About 1 chance in 1,000 that he is guilty___About 1 chance in 10,000 that he is guilty___About 1 chance in 100,000 that he is guilty___About 1 chance in 1 million that he is guilty___About 1 chance in 10 million that he is guilty___Impossible that he is guilty
What are the chances that an innocent man in a case like this would, just by coincidence, happen to match the DNA left by another man at the crime scene?– 1 in 10– 1 in 100– 1 in 1000– 1 in 10,000– 1 in 100,000– 1 in 1 million– 1 in 1 billion– Zero chances--impossible
Guilty (G) Not Guilty(NG)
Framed (F) FUP FUP
Not Framed
(NF)
1-FUP 1-FUP
Match (M) No Match(NM)
Match Reported
(R)
1 FRP
Not Reported
0 1-FRP
Framed (F) Not Framed (NF)
G NG G NG
Match (M) 1 1 1 RMPNo Match
(NM)0 0 0 1-RMP
Figure 5: Bayesian Network Model for Evaluating the Probative Value of the Forensic Evidence Based on Individual Perceptions of the RMP, FRP and FUP
A DNA Match Between Perpetrator and Suspect: Is the suspect guilty?
The DNA Expert Says:
The prosecutor says:
But the defense lawyer says:
So what are the chances he’s guilty?
How many of the matching people are plausible suspects?
We don’t really know…