Literature DB >> 35198945

Probabilistic reporting and algorithms in forensic science: Stakeholder perspectives within the American criminal justice system.

H Swofford1, C Champod1.   

Abstract

In recent years, there have been efforts to promote probabilistic reporting and the use of computational algorithms across several forensic science disciplines. Reactions to these efforts have been mixed-some stakeholders argue they promote greater scientific rigor whereas others argue that the opacity of algorithmic tools makes it challenging to meaningfully scrutinize the evidence presented against a defendant resulting from these systems. Consequently, the forensic community has been left with no clear path to navigate these concerns as each proposed approach has countervailing benefits and risks. To explore these issues further and provide a foundation for a path forward, this study draws on semi-structured interviews with fifteen participants to elicit the perspectives of key criminal justice stakeholders, including laboratory managers, prosecutors, defense attorneys, judges, and other academic scholars, on issues related to interpretation and reporting practices and the use of computational algorithms in forensic science within the American legal system.
© 2022 The Authors.

Entities:  

Keywords:  Algorithms; Forensic science; Pattern evidence; Probabilities; Statistics

Year:  2022        PMID: 35198945      PMCID: PMC8850671          DOI: 10.1016/j.fsisyn.2022.100220

Source DB:  PubMed          Journal:  Forensic Sci Int Synerg        ISSN: 2589-871X


  15 in total

1.  Computation of likelihood ratios in fingerprint identification for configurations of three minutiae.

Authors:  Cedric Neumann; Christophe Champod; Roberto Puch-Solis; Nicole Egli; Alexandre Anthonioz; Didier Meuwly; Andie Bromage-Griffiths
Journal:  J Forensic Sci       Date:  2006-11       Impact factor: 1.832

2.  Fingermark evidence evaluation based on automated fingerprint identification system matching scores: the effect of different types of conditioning on likelihood ratios.

Authors:  Ivo Alberink; Arent de Jongh; Crystal Rodriguez
Journal:  J Forensic Sci       Date:  2013-11-01       Impact factor: 1.832

3.  Quantitative assessment of evidential weight for a fingerprint comparison. Part II: a generalisation to take account of the general pattern.

Authors:  Cedric Neumann; Ian W Evett; James E Skerrett; Ismael Mateos-Garcia
Journal:  Forensic Sci Int       Date:  2011-09-01       Impact factor: 2.395

4.  Quantifying the weight of fingerprint evidence through the spatial relationship, directions and types of minutiae observed on fingermarks.

Authors:  Cedric Neumann; Christophe Champod; Mina Yoo; Thibault Genessay; Glenn Langenburg
Journal:  Forensic Sci Int       Date:  2015-01-16       Impact factor: 2.395

5.  Performance Study of a Score-based Likelihood Ratio System for Forensic Fingermark Comparison.

Authors:  Anna Jeannette Leegwater; Didier Meuwly; Marjan Sjerps; Peter Vergeer; Ivo Alberink
Journal:  J Forensic Sci       Date:  2017-02-07       Impact factor: 1.832

6.  Spatial analysis of corresponding fingerprint features from match and close non-match populations.

Authors:  Joshua Abraham; Christophe Champod; Chris Lennard; Claude Roux
Journal:  Forensic Sci Int       Date:  2012-11-13       Impact factor: 2.395

7.  Assessing the clarity of friction ridge impressions.

Authors:  R Austin Hicklin; JoAnn Buscaglia; Maria Antonia Roberts
Journal:  Forensic Sci Int       Date:  2013-01-10       Impact factor: 2.395

8.  A method for the statistical interpretation of friction ridge skin impression evidence: Method development and validation.

Authors:  H J Swofford; A J Koertner; F Zemp; M Ausdemore; A Liu; M J Salyards
Journal:  Forensic Sci Int       Date:  2018-04-03       Impact factor: 2.395

Review 9.  Implementation of algorithms in pattern & impression evidence: A responsible and practical roadmap.

Authors:  H Swofford; C Champod
Journal:  Forensic Sci Int       Date:  2021-02-18       Impact factor: 2.395

10.  Forensic comparison and matching of fingerprints: using quantitative image measures for estimating error rates through understanding and predicting difficulty.

Authors:  Philip J Kellman; Jennifer L Mnookin; Gennady Erlikhman; Patrick Garrigan; Tandra Ghose; Everett Mettler; David Charlton; Itiel E Dror
Journal:  PLoS One       Date:  2014-05-02       Impact factor: 3.240

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  3 in total

1.  The opacity myth: A response to Swofford & Champod (2022).

Authors:  Geoffrey Stewart Morrison; Nabanita Basu; Ewald Enzinger; Philip Weber
Journal:  Forensic Sci Int Synerg       Date:  2022-06-19

Review 2.  Advancing a paradigm shift in evaluation of forensic evidence: The rise of forensic data science.

Authors:  Geoffrey Stewart Morrison
Journal:  Forensic Sci Int Synerg       Date:  2022-05-18

3.  Machine learning algorithms in forensic science: A response to Morrison et al. (2022).

Authors:  H Swofford; C Champod
Journal:  Forensic Sci Int Synerg       Date:  2022-08-05
  3 in total

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