A strawman with machine learning for a brain: A response to Biedermann (2022) the strange persistence of (source) "identification" claims in forensic literature.

We agree wholeheartedly with Biedermann (2022) FSI Synergy article 100222 in its criticism of research publications that treat forensic inference in source attribution as an "identification" or "individualization" task. We disagree, however, with its criticism of the use of machine learning for forensic inference. The argument it makes is a strawman argument.

Consensus on validation of forensic voice comparison.

Since the 1960s, there have been calls for forensic voice comparison to be empirically validated under casework conditions. Since around 2000, there have been an increasing number of researchers and practitioners who conduct forensic-voice-comparison research and casework within the likelihood-ratio framework. In recent years, this community of researchers and practitioners has made substantial progress toward validation under casework conditions becoming a standard part of practice: Procedures for conducting validation have been developed, along with graphics and metrics for representing the results, and an increasing number of papers are being published that include empirical validation of forensic-voice-comparison systems under conditions reflecting casework conditions.

Forensic gait analysis - Morphometric assessment from surveillance footage.

Following the technological rise of surveillance cameras and their subsequent proliferation in public places, the use of information gathered by such means for investigative and evaluative purposes sparked a large interest in the forensic community and within policing scenarios. In particular, it is suggested that analysis of the body, especially the assessment of gait characteristics, can provide useful information to aid the investigation. This paper discusses the influences upon gait to mitigate some of the limitations of surveillance footage, including those due to the varying anatomical differences between individuals.

Forensic image analysis - CCTV distortion and artefacts.

As a result of the worldwide deployment of surveillance cameras, authorities have gained a powerful tool that captures footage of activities of people in public areas. Surveillance cameras allow continuous monitoring of the area and allow footage to be obtained for later use, if a criminal or other act of interest occurs. Following this, a forensic practitioner, or expert witness can be required to analyse the footage of the Person of Interest.

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

In this article, the performance of a score-based likelihood ratio (LR) system for comparisons of fingerprints with fingermarks is studied. The system is based on an automated fingerprint identification system (AFIS) comparison algorithm and focuses on fingerprint comparisons where the fingermarks contain 6-11 minutiae. The hypotheses under consideration are evaluated at the level of the person, not the finger.

Likelihood ratio data to report the validation of a forensic fingerprint evaluation method.

Data to which the authors refer to throughout this article are likelihood ratios (LR) computed from the comparison of 5-12 minutiae fingermarks with fingerprints. These LRs data are used for the validation of a likelihood ratio (LR) method in forensic evidence evaluation. These data present a necessary asset for conducting validation experiments when validating LR methods used in forensic evidence evaluation and set up validation reports.

A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation.

This Guideline proposes a protocol for the validation of forensic evaluation methods at the source level, using the Likelihood Ratio framework as defined within the Bayes' inference model. In the context of the inference of identity of source, the Likelihood Ratio is used to evaluate the strength of the evidence for a trace specimen, e.g.

Sampling variability in forensic likelihood-ratio computation: A simulation study.

Recently, in the forensic biometric community, there is a growing interest to compute a metric called "likelihood-ratio" when a pair of biometric specimens is compared using a biometric recognition system. Generally, a biometric recognition system outputs a score and therefore a likelihood-ratio computation method is used to convert the score to a likelihood-ratio. The likelihood-ratio is the probability of the score given the hypothesis of the prosecution, Hp (the two biometric specimens arose from a same source), divided by the probability of the score given the hypothesis of the defense, Hd (the two biometric specimens arose from different sources).

Measuring coherence of computer-assisted likelihood ratio methods.

Measuring the performance of forensic evaluation methods that compute likelihood ratios (LRs) is relevant for both the development and the validation of such methods. A framework of performance characteristics categorized as primary and secondary is introduced in this study to help achieve such development and validation. Ground-truth labelled fingerprint data is used to assess the performance of an example likelihood ratio method in terms of those performance characteristics.

Introducing a semi-automatic method to simulate large numbers of forensic fingermarks for research on fingerprint identification.

Statistical research on fingerprint identification and the testing of automated fingerprint identification system (AFIS) performances require large numbers of forensic fingermarks. These fingermarks are rarely available. This study presents a semi-automatic method to create simulated fingermarks in large quantities that model minutiae features or images of forensic fingermarks.

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

Recent challenges to fingerprint evidence have brought forward the need for peer-reviewed scientific publications to support the evidential value assessment of fingerprint. This paper proposes some research directions to gather statistical knowledge of the within-source and between-sources variability of configurations of three minutiae on fingermarks and fingerprints. This paper proposes the use of the likelihood ratio (LR) approach to assess the value of fingerprint evidence.