Proceedings of the Annual Meeting of the Cognitive Science Society

Witness credibility is important for establishing testimonial value.The story model posits that people construct narratives fromevidence but does not explain how credibility is assessed. Formalapproaches use Bayesian networks (BN) to represent legalevidence. Recent empirical work suggests people might alsoreason using qualitative causal networks. In two studies,participants read a realistic trial transcript and judge guilt andwitness credibility. Study 1 varied testimonial consistency anddefendant character. Guilt and credibility assessments wereaffected by consistency but not prior convictions. Study 2constructed a BN to represent consistency issues. Individualparameter estimates were elicited for the corresponding BN tocompute posterior predictions for guilt and credibility. The BNprovided a good model for overall and individual guilt andcredibility ratings. These results suggest people construct causalmodels of the evidence and consider witness credibility. The BNapproach is a promising direction for future research in legalreasoning.