Morrison, Geoffrey Stewart (2022). Advancing a paradigm shift in evaluation of forensic evidence: The rise of forensic data science. Forensic Science International: Synergy, 5 ,
Abstract
Widespread practice across the majority of branches of forensic science uses analytical methods based on human perception, and interpretive methods based on subjective judgement. These methods are non-transparent and are susceptible to cognitive bias, interpretation is often logically flawed, and forensic-evaluation systems are often not empirically validated. I describe a paradigm shift in which existing methods are replaced by methods based on relevant data, quantitative measurements, and statistical models; methods that are transparent and reproducible, are intrinsically resistant to cognitive bias, use the logically correct framework for interpretation of evidence (the likelihood-ratio framework), and are empirically validated under casework conditions.
Publication DOI: | https://doi.org/10.1016/j.fsisyn.2022.100270 |
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Divisions: | College of Engineering & Physical Sciences College of Business and Social Sciences > Aston Institute for Forensic Linguistics Aston University (General) |
Additional Information: | © 2022 The Author. Published by Elsevier B.V. This is an open access article under the CC BY license 4.0 Funding: This research was supported by Research England's Expanding Excellence in England Fund as part of funding for the Aston Institute for Forensic Linguistics 2019–2023. |
Uncontrolled Keywords: | Forensic data science,Forensic science,Likelihood ratio,Paradigm shift,Validation,Pathology and Forensic Medicine,Law |
Publication ISSN: | 2589-871X |
Last Modified: | 02 Dec 2024 08:40 |
Date Deposited: | 06 Jun 2022 10:42 |
Full Text Link: | |
Related URLs: |
https://www.sci ... 0559?via%3Dihub
(Publisher URL) http://www.scop ... tnerID=8YFLogxK (Scopus URL) |
PURE Output Type: | Review article |
Published Date: | 2022-05 |
Published Online Date: | 2022-05-18 |
Accepted Date: | 2022-05-16 |
Authors: |
Morrison, Geoffrey Stewart
(
0000-0001-8608-8207)
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