Liar, Liar, Jury's the Trier? The Future of Neuroscience-Based Credibility Assessment and the Court
John B. Meixner
Northwestern University - School of Law; Northwestern University - Department of Psychology
May 30, 2011
Northwestern University Law Review, Vol. 106, No. 3, 2012
Neuroscience-based credibility-assessment tests have recently become increasingly mainstream, purportedly able to determine whether an individual is lying to a certain set of questions (the Control Question Test) or whether an individual recognizes information that only a liable person would recognize (the Concealed Information Test). Courts have hesitated to admit these tests as evidence for two primary reasons. First, following the general standard that credibility assessment is a matter solely for the trier of fact, courts exclude the evidence because it impinges on the province of the jury. Second, because these methods have not been rigorously tested in realistic scenarios, courts rule that they do not meet the Daubert criteria for admissibility of expert testimony. This Comment argues that while neuroscience-based credibility-assessment methods should not currently be admissible under the Daubert standard, they may become admissible with more research, and the courts should avoid creating precedent that would preclude their admissibility once reliability issues are addressed. Specifically, credibility assessment should not be left entirely to the trier of fact because social science evidence indicates that laypeople are poor at making credibility-assessment judgments based on behavioral cues. Additionally, even if courts continue to rule that evidence assessing whether a witness is telling the truth invades the province of the jury, this should not preclude neuroscience-based credibility assessment that merely shows that an individual recognizes something related to the issue at hand.
Number of Pages in PDF File: 38
Keywords: Evidence, Scientific Evidence, Concealed Information Test, Control Question Test, Psychology, Social Science, Lie Detection, Daubert
Date posted: June 10, 2011 ; Last revised: November 20, 2012
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