Not All Identification Conclusions are Equal: Quantifying the Strength of Fingerprint Decisions

In the pattern comparison disciplines, forensic practitioners evaluate two impressions with respect to the same-source and different-sources propositions. The results are communicated using a pre-determined conclusion scale, and in the friction ridge discipline Identification is typically the highest category on the scale. Although error rates have been measured in most disciplines, there are no widespread quantitative approaches and therefore most conclusions rely on subjective human evaluations. The current work uses decisions provided by fingerprint examiners to produce a quantitative likelihood ratio measure that characterizes the strength of the support for the two propositions. We use an ordered probit model to summarize the distribution of responses of examiners who participated in error rate and validation studies. We then aggregate the data for all image pairs in a database to construct a set of likelihood ratios based on the ratio of the two strength-of-support values. We find that these values are modest relative to values typically produced by DNA analysis or implied by current fingerprint articulation language. The technique can be applied to any pattern comparison discipline for which error-rate data is available, and therefore can be used to appropriately weigh the evidence from different disciplines.