When do Fingerprints Exclude?

A new paper by Bradford T. Ulery, R. Austin Hicklin, Maria Antonia Roberts, and JoAnn Buscaglia, titled “Factors associated with latent fingerprint exclusion determinations,” was recently published in FSI.  Until July 7, it can be downloaded for free here.  The authors noted the high rate of erroneous exclusions reported in their prior 2011 Black Box study. This follow-up analysis of the 2011 Black Box study data, together with data from a 2014 “White Box” study, involving 169 and 170 examiners respectively, focusing on exclusion decisions.  They noted that the majority reported that their lab procedures did not differential between prints not of value and prints that could be of value for exclusion.  They found:

Erroneous exclusions were made by at least one examiner on 46% of BB [Black Box study] mated image pairs and 35% of WB [White Box study] mated image pairs; a greater proportion of BB mated pairs were erroneously excluded by at least one examiner than WB pairs because each image pair was presented to more examiners on BB than on WB (mean of 22 examiners per image pair on BB vs. 12 on WB).

They also found that “Examiners usually attributed exclusions to minutia differences regardless of whether their exclusions were erroneous (mated) or not (nonmated).”  And “Even when the exclusion reason was that minutiae differed, examiners marked discrepancies on only 40% of exclusions. Reproducibility of discrepancies was not substantially greater than chance.”

Here is the abstract:

Exclusion is the determination by a latent print examiner that two friction ridge impressions did not originate from the same source. The concept and terminology of exclusion vary among agencies. Much of the literature on latent print examination focuses on individualization, and much less attention has been paid to exclusion. This experimental study assesses the associations between a variety of factors and exclusion determinations. Although erroneous exclusions are more likely to occur on some images
and for some examiners, they were widely distributed among images and examiners. Measurable factors found to be associated with exclusion rates include the quality of the latent, value determinations, analysis minutia count, comparison difficulty, and the presence of cores or deltas.
An understanding of these associations will help explain the circumstances under which errors are more likely to occur and when determinations are less likely to be reproduced by other examiners; the results should also lead to improved effectiveness and efficiency of training and casework quality assurance. This research is intended to assist examiners in improving the examination process and provide information to the broader community regarding the accuracy, reliability, and implications of exclusion decisions.

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