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

Abstract

Over the years, scientific and legal scholars have called for the implementation of algorithms (e.g., statistical methods) in forensic science to provide an empirical foundation to experts’ subjective conclusions. Despite the proliferation of numerous approaches, the practitioner community has been reluctant to apply them operationally. Reactions have ranged from passive skepticism to outright opposition, often in favor of traditional experience and expertise as a sufficient basis for conclusions. In this paper, we explore why practitioners are generally in opposition to algorithmic interventions and how their concerns might be overcome. We accomplish this by considering issues concerning human—algorithm interactions in both real world domains and laboratory studies as well as issues concerning the litigation of algorithms in the American legal system. Taking into account those issues, we propose a strategy for approaching the implementation of algorithms, and the different ways algorithms can be implemented, in a responsible and practical manner.

Keywords

• Forensic science
• Pattern evidence
• Algorithms
• Statistics
• Models
• Automation