A CommonKADS Representation for a Knowledge-Based System to Evaluate Eyewitness Identification

Abstract

The Joseph Bell Centre for Forensic Statistics and Legal Reasoning has been set up to examine the correct presentation, interpretation and evaluation of scientific and forensic evidence through the use of technology. The aim of the Centre is to build computer systems for those operating in the legal system so that they can follow best practice whether investigating a crime or presenting evidence in court. The initial approach to developing computational systems is to build small-scale knowledge-based systems in specific domains. This paper presents a CommonKADS approach to designing a small-scale system to evaluate eyewitness evidence. CommonKADS is a Knowledge Acquisition Design System using computer-generated models to represent how tasks are performed, which agents are involved, their expertise and the communication involved in the process of evaluating eyewitness evidence. The knowledge to be modelled for the application has been drawn from sources such as: the police, the prosecution service, lawyers and psychologists. This system will be piloted and evaluated by the Centre with collaborating institutions for ultimate use by law enforcement agencies and prosecution and defence agents.

Keywords: law, expert system, AI, eyewitness, evidence