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Accuracy and reliability of forensic latent fingerprint decisions
Open accessAbstract
The interpretation of forensic fingerprint evidence relies on the expertise of latent print examiners. The National Research Council of the National Academies and the legal and forensic sciences communities have called for research to measure the accuracy and reliability of latent print examiners’ decisions, a challenging and complex problem in need of systematic analysis. Our research is focused on the development of empirical approaches to studying this problem. Here, we report on the first large-scale study of the accuracy and reliability of latent print examiners’ decisions, in which 169 latent print examiners each compared approximately 100 pairs of latent and exemplar fingerprints from a pool of 744 pairs. The fingerprints were selected to include a range of attributes and quality encountered in forensic casework, and to be comparable to searches of an automated fingerprint identification system containing more than 58 million subjects. This study evaluated examiners on key decision points in the fingerprint examination process; procedures used operationally include additional safeguards designed to minimize errors. Five examiners made false positive errors for an overall false positive rate of 0.1%. Eighty-five percent of examiners made at least one false negative error for an overall false negative rate of 7.5%. Independent examination of the same comparisons by different participants (analogous to blind verification) was found to detect all false positive errors and the majority of false negative errors in this study. Examiners frequently differed on whether fingerprints were suitable for reaching a conclusion.
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“For the first time in some disciplines, careful studies have attempted to estimate error rates (Ulery et al. 2011).”
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The effect of fingerprint expertise on visual short-term memory
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Summersby, S., Edmond, G., Kemp, R. I., Ballantyne, K. N., & Martire, K. A. (2024) · Forensic Science International · doi:10.1016/j.forsciint.2024.112034 · Cited by 5
Parvathy, J., & Patil, P. G. (2024) · SN Computer Science · doi:10.1007/s42979-024-02885-3 · Cited by 5
Metadata
- Authors
- Ulery, B. T., Hicklin, R. A., Buscaglia, J., & Roberts, M. A.
- Affiliations
- Noblis (US)
- Federal Bureau of Investigation (US)
- Corresponding author
- Buscaglia, JoAnn
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2011-04-25
- Volume
- 108
- Issue
- 19
- Pages
- 7733-7738
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3093498
- OpenAlex
- W2009575609
- Cited by
- 350
- References
- 22
- Citations by year
- 2026: 24 · 2025: 17 · 2024: 29 · 2023: 23 · 2022: 35 · 2021: 31 · 2020: 40 · 2019: 21 · 2018: 16 · 2017: 20 · 2016: 17 · 2015: 23 · 2014: 21 · 2013: 20 · 2012: 10
- FWCI
- 18.13
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Health Sciences › Medicine › Pathology and Forensic Medicine › Forensic Fingerprint Detection Methods
- Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
- Keywords
- forensic evidence reliability, false positives, false negative errors, automated fingerprint identification systems, fingerprint comparison
- MeSH terms
- Dermatoglyphics, Expert Testimony, False Negative Reactions, False Positive Reactions, Humans, Professional Competence, Software, Reproducibility of Results, Observer Variation
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