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Fingerprint error rate on close non‐matches
Author(s) -
Koehler Jonathan J.,
Liu Shiquan
Publication year - 2021
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/1556-4029.14580
Subject(s) - fingerprint (computing) , word error rate , replication (statistics) , identification (biology) , statistics , value (mathematics) , computer science , medicine , mathematics , computer security , artificial intelligence , biology , botany
The accuracy of fingerprint identifications is critically important to the administration of criminal justice. Accuracy is challenging when two prints from different sources have many common features and few dissimilar features. Such print pairs, known as close non‐matches (CNMs), are increasingly likely to arise as ever‐growing databases are searched with greater frequency. In this study, 125 fingerprint agencies completed a mandatory proficiency test that included two pairs of CNMs. The false‐positive error rates on the two CNMs were 15.9% (17 out of 107, 95% C.I.: 9.5%, 24.2%) and 28.1% (27 out of 96, 95% C.I.: 19.4%, 38.2%), respectively. These CNM error rates are (a) inconsistent with the popular notion that fingerprint evidence is nearly infallible, and (b) larger than error rates reported in leading fingerprint studies. We conclude that, when the risk of CNMs is high, the probative value of a reported fingerprint identification may be severely diminished due to an elevated false‐positive error risk. We call for additional CNM research, including a replication and expansion of the present study using a representative selection of CNMs from database searches.