The Utility of Expanded Conclusion Scales During Latent Print Examinations

Abstract

During fingerprint comparisons, a latent print examiner visually compares two impressions to determine whether or not they originated from the same source. They consider the amount of perceived detail in agreement or disagreement and accumulate evidence toward same source and different sources propositions. This evidence is then mapped to one of three conclusions: Identification, Inconclusive, or Exclusion. A limitation of this 3‐conclusion scale is it can lose information when translating the conclusion from the internal strength‐of‐evidence value to one of only three possible conclusions. An alternative scale with two additional values, support for different sources and support for common sources, has been proposed by the Friction Ridge Subcommittee of OSAC. The expanded scale could lead to more investigative leads but could produce complex trade‐offs in both correct and erroneous identifications. The aim of the present study was to determine the consequences of a shift to expanded conclusion scales in latent print comparisons. Latent print examiners each completed 60 comparisons using one of the two scales, and the resulting data were modeled using signal detection theory to measure whether the expanded scale changed the threshold for an “Identification” conclusion. When using the expanded scale, examiners became more risk‐averse when making “Identification” decisions and tended to transition both the weaker Identification and stronger Inconclusive responses to the “Support for Common Source” statement. The results demonstrate the utility of an expanded conclusion scale and also provide guidance for the adoption of these or similar scales.

Are forensic scientists too risk averse?

“…Some agencies such as the Houston Forensic Science Center already allow for this for some comparisons. One caveat with this approach is that while investigative leads may end up being helpful, additional categories may also make examiners even more risk averse [31]. Each of these policy changes should be made with the support of empirical studies that demonstrate how best to communicate the strength of evidence in a particular case to an eventual consumer such as a detective, prosecutor, or defense attorney.…”

“…Some agencies such as the Houston Forensic Science Center already allow for this for some comparisons. One caveat with this approach is that while investigative leads may end up being helpful, additional categories may also make examiners even more risk averse [31].…”

Planning, design and logistics of a decision analysis study: The FBI/Ames study involving forensic firearms examiners

“…Use of three levels of inconclusive (section 2.10 ) may lead examiners to choose inconclusive A or C [ 131 ] rather than commit to identification or elimination, reducing statistical power of estimated error rate. This tendency was recently demonstrated when latent fingerprint examiners used a similar 5-point scale rather than the prevalent 3-point scale [ 128 ]. Examiners working in an agency that permits only a single level of inconclusive may apply three levels inconsistently.…”

“…A draft OSAC document further elaborates the Range [ 125 ]. The utility and import of the Range, its relation to gradations of conclusions used in other forensic disciplines, and whether inconclusive conclusions should figure into calculation of error rate, or be used to offer a presumptive link to investigators have long been a matter of discussion in various OSAC committees and elsewhere [ 29 , 34 , 92 , 106 , 110 , 113 , [126] , [127] , [128] , [129] , [130] ]. Some go so far as to opine that an inconclusive decision that could, if expressed differently, provide exclusionary power, is as consequential as a false identification [129, p. 198].…”

Validating strength‐of‐support conclusion scales for fingerprint, footwear, and toolmark impressions

“…The response proportions presented in Table 9 through Table 12 can be summarized using extensions to Signal Detection Theory. As in Carter, Vogelsang [8], we fit the response distributions with a model that assumes that the result of each comparison produces a unidimensional value on an internal evidence axis, which is then mapped to a categorical statement using a set of decision criteria. The distribution of nonmated and mated pairs along this evidence axis is summarized using Gaussian distributions, and separate decision criteria are fit to each scale.…”