Rounding Up the Usual Suspects: A Logical and Legal Analysis of DNA Trawling Cases
David H. Kaye
Penn State Law
September 17, 2008
North Carolina Law Review, Vol. 87, No. 2, 2009
Courts are beginning to confront a problem that has divided the scientific community - whether identifying a defendant by fishing through a database of DNA types to find a match to a crime-scene sample reduces the significance of a match. For years, the problem seemed academic. Now that the U.S. has more than five million DNA profiles from convicted offenders and suspects in a national, computer-searchable database, the question has assumed more urgency. Increasingly, individuals are being charged with crimes as a result of a match between their recorded profile and the DNA from a victim or scene of a crime. Arguing that there is no generally accepted scientific opinion on how the probative value of a match from a database trawl should be quantified, some of these defendants have moved to exclude the DNA evidence. Trial courts have ruled both ways. Appellate courts in California and the District of Columbia have rebuffed these challenges, reasoning that the general-acceptance standard for scientific evidence does not apply in this situation. Furthermore, they have held that even though the defendant was not selected randomly, the jury can be given the usual probability that a randomly selected individual will match a crime-scene sample. This Article criticizes the reasoning (but not the outcome) in these opinions. It argues that the attempts to avoid directly confronting the debate among scientists and statisticians rob the opinions of any persuasive value. Elaborating on earlier statistical analyses of the database-trawl question, it presents a more satisfactory rationale for admitting the unadjusted random-match probability.
Number of Pages in PDF File: 95
Keywords: evidence, probative value, DNA, database, cold hits, probability, ascertainment bias, multiple hypothesis testing, data mining, Bayes' rule, presumption of innocenceAccepted Paper Series
Date posted: May 24, 2008 ; Last revised: September 22, 2008
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