A formal approach to qualifying and quantifying the 'goodness' of forensic identification decisions. (4th August 2018)

• Record Type: Journal Article
• Authors: Biedermann, Alex; Bozza, Silvia; Taroni, Franco; Garbolino, Paolo
• Is Part Of: Law, probability & risk. Volume 17:Number 4(2018)
• Page Start: 295
• Page End: 310
• Publication Date: 2018-08-04
• Subjects: forensic individualization -- decision analysis -- decision theory -- minimax -- decision-theoretic criterion; Proximate cause (Law) -- Periodicals; Risk -- Periodicals; Law -- Mathematical models -- Periodicals; Law -- Methodology -- Periodicals; Probabilities -- Periodicals; Risk assessment -- Periodicals; Law -- Mathematical models; Law -- Methodology; Probabilities; Proximate cause (Law); Risk; Risk assessment; Periodicals; 340.1
• DOI: 10.1093/lpr/mgy016
• Languages: English
• ISSNs: 1470-8396

Abstract

Abstract: In this article, we review and analyse common understandings of the degree to which forensic inference of source—also called identification or individualization—can be approached with statistics and is referred to, increasingly often, as a decision. We also consider this topic from the strongly empirical perspective of PCAST (2016 ) in its recent review of forensic science practice. We will point out why and how these views of forensic identification as a decision, and empirical approaches to it (namely experiments by multiple experts under controlled conditions), provide only descriptive measures of expert performance and of general scientific validity regarding particular forensic branches (e.g. fingermark examination). Although relevant to help assess whether the identification practice of a given forensic field can be trusted, these empirical accounts do not address the separate question of what ought to be a sensible, or 'good' in some sense, (identification-)decision to make in a particular case. The latter question, as we will argue, requires additional considerations, such as decision-making goals. We will point out that a formal approach to qualifying and quantifying the relative merit of competing forensic decisions can be considered within an extended view of statistics in which data analysis and inference are a necessary but not sufficient preliminary.