A cultural change to enable improved decision-making in forensic science: A six phased approach.

There has been an increased engagement by researchers in understanding the decision-making processes that occur within forensic science. There is a rapidly growing evidence base underpinning our understanding of decision-making and human factors and this body of work is the foundation for achieving truly improved decision-making in forensic science. Such an endeavour is necessary to minimise the misinterpretation of scientific evidence and maximize the effectiveness of crime reconstruction approaches and their application within the criminal justice system. This paper proposes and outlines a novel six phased approach for how a broadening and deepening knowledge of decision-making in forensic science can be articulated and incorporated into the spheres of research, practice, education, and policy making within forensic science specifically, and the criminal justice system more generally. Phases 1 and 2 set out the importance of systematic examination of the decisions which play a role throughout forensic reconstruction and legal processes. Phase 3 focuses on how these decisions can, and should, be studied to understand the underlying mechanisms and contribute to reducing the occurrence of misleading decisions. Phase 4 highlights the ways in which the results and implications of this research should be communicated to the forensic community and wider criminal justice system. Lastly, the way in which the forensic science domain can move forwards in managing the challenges of human decision-making and create and embed a culture of acceptance and transparency in research, practice and education (learning and training) are presented in phases 5 and 6. A consideration of all 6 connected phases offers a pathway for a holistic approach to improving the transparency and reproducibility of decision making within forensic science.

A systematic analysis of misleading evidence in unsafe rulings in England and Wales.

Evidence has the potential to be misleading if its value when expressing beliefs in hypotheses is not fully understood or presented. Although the knowledge base to understand uncertainties is growing, a challenge remains to prioritise research and to continuously assess the magnitude and consequences of misleading evidence in criminal cases. This study used a systematic content analysis to identify misleading evidence, drawing information from case transcripts of rulings argued unsafe by the Court of Appeal of England and Wales. In the 7-year study period, 218 applications were successful on appeal, containing 235 cases of misleading evidence. The majority (76%) of successful appeals were based upon the same materials available in the original trial, rather than the presentation of new relevant information. Witness (39%), forensic (32%), and character evidence (19%) were the most commonly observed evidence types, with the validity of witnesses (26%), probative value of forensic evidence (12%), and relevance of character evidence (10%) being the most prevalent combinations of identified issues. Additionally, the majority (66%) of misleading evidence types relate to their interpretation at activity level. The findings suggest that many of these misleading aspects could have been prevented by providing more transparency in the relationship between evidence and hypotheses. Generally, the results contribute to gaining a more complete picture of the role of misleading evidence in the criminal justice system.

Using Bayesian networks to guide the assessment of new evidence in an appeal case.

When new forensic evidence becomes available after a conviction there is no systematic framework to help lawyers to determine whether it raises sufficient questions about the verdict in order to launch an appeal. This paper presents such a framework driven by a recent case, in which a defendant was convicted primarily on the basis of audio evidence, but where subsequent analysis of the evidence revealed additional sounds that were not considered during the trial. The framework is intended to overcome the gap between what is generally known from scientific analyses and what is hypothesized in a legal setting. It is based on Bayesian networks (BNs) which have the potential to be a structured and understandable way to evaluate the evidence in a specific case context. However, BN methods suffered a setback with regards to the use in court due to the confusing way they have been used in some legal cases in the past. To address this concern, we show the extent to which the reasoning and decisions within the particular case can be made explicit and transparent. The BN approach enables us to clearly define the relevant propositions and evidence, and uses sensitivity analysis to assess the impact of the evidence under different assumptions. The results show that such a framework is suitable to identify information that is currently missing, yet clearly crucial for a valid and complete reasoning process. Furthermore, a method is provided whereby BNs can serve as a guide to not only reason with incomplete evidence in forensic cases, but also identify very specific research questions that should be addressed to extend the evidence base and solve similar issues in the future.