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A recent report by the US President's Council of Advisors on Science and Technology (PCAST), (2016) has made a number of recommendations for the future development of forensic science. Whereas we all agree that there is much need for change, we find that the PCAST report recommendations are founded on serious misunderstandings. We explain the traditional forensic paradigms of match and identification and the more recent foundation of the logical approach to evidence evaluation. This forms the groundwork for exposing many sources of confusion in the PCAST report. We explain how the notion of treating the scientist as a black box and the assignment of evidential weight through error rates is overly restrictive and misconceived. Our own view sees inferential logic, the development of calibrated knowledge and understanding of scientists as the core of the advance of the profession.

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The value of forensic results crucially depends on the propositions and the information under which they are evaluated. For example, if a full single DNA profile for a contemporary marker system matching the profile of Mr A is assessed, given the propositions that the DNA came from Mr A and given it came from an unknown person, the strength of evidence can be overwhelming (e.g., in the order of a billion). In contrast, if we assess the same result given that the DNA came from Mr A and given it came from his twin brother (i.e., a person with the same DNA profile), the strength of evidence will be 1, and therefore neutral, unhelpful and irrelevant(1) to the case at hand. While this understanding is probably uncontroversial and obvious to most, if not all practitioners dealing with DNA evidence, the practical precept of not specifying an alternative source with the same characteristics as the one considered under the first proposition may be much less clear in other circumstances. During discussions with colleagues and trainees, cases have come to our attention where forensic scientists have difficulty with the formulation of propositions. It is particularly common to observe that results (e.g., observations) are included in the propositions, whereas-as argued throughout this note-they should not be. A typical example could be a case where a shoe-mark with a logo and the general pattern characteristics of a Nike Air Jordan shoe is found at the scene of a crime. A Nike Air Jordan shoe is then seized at Mr A's house and control prints of this shoe compared to the mark. The results (e.g., a trace with this general pattern and acquired characteristics corresponding to the sole of Mr A's shoe) are then evaluated given the propositions 'The mark was left by Mr A's Nike Air Jordan shoe-sole' and 'The mark was left by an unknown Nike Air Jordan shoe'. As a consequence, the footwear examiner will not evaluate part of the observations (i.e., the mark presents the general pattern of a Nike Air Jordan) whereas they can be highly informative. Such examples can be found in all forensic disciplines. In this article, we present a few such examples and discuss aspects that will help forensic scientists with the formulation of propositions. In particular, we emphasise on the usefulness of notation to distinguish results that forensic scientists should evaluate from case information that the Court will evaluate.

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This paper reports on the purpose, design, methodology and target audience of E-learning courses in forensic interpretation offered by the authors since 2010, including practical experiences made throughout the implementation period of this project. This initiative was motivated by the fact that reporting results of forensic examinations in a logically correct and scientifically rigorous way is a daily challenge for any forensic practitioner. Indeed, interpretation of raw data and communication of findings in both written and oral statements are topics where knowledge and applied skills are needed. Although most forensic scientists hold educational records in traditional sciences, only few actually followed full courses that focussed on interpretation issues. Such courses should include foundational principles and methodology - including elements of forensic statistics - for the evaluation of forensic data in a way that is tailored to meet the needs of the criminal justice system. In order to help bridge this gap, the authors' initiative seeks to offer educational opportunities that allow practitioners to acquire knowledge and competence in the current approaches to the evaluation and interpretation of forensic findings. These cover, among other aspects, probabilistic reasoning (including Bayesian networks and other methods of forensic statistics, tools and software), case pre-assessment, skills in the oral and written communication of uncertainty, and the development of independence and self-confidence to solve practical inference problems. E-learning was chosen as a general format because it helps to form a trans-institutional online-community of practitioners from varying forensic disciplines and workfield experience such as reporting officers, (chief) scientists, forensic coordinators, but also lawyers who all can interact directly from their personal workplaces without consideration of distances, travel expenses or time schedules. In the authors' experience, the proposed learning initiative supports participants in developing their expertise and skills in forensic interpretation, but also offers an opportunity for the associated institutions and the forensic community to reinforce the development of a harmonized view with regard to interpretation across forensic disciplines, laboratories and judicial systems.

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We consider the problem of drawing inferences within a legal framework when a person is a suspect for two separate offences. Although we are primarily concerned with scientific evidence the issue inevitably arises as to how that evidence interacts with other, non-scientific evidence. We show that, in this particular context, the evidence can be conveniently classified into three categories that concern, respectively: the first crime only; the second crime only; and evidence that relates to similarities between the two crimes. Two case examples are considered and we consider DNA, fibres and eyewitness evidence. These are viewed from the perspective of a prosecutor who has to decide whether or not to charge a suspect with one or both crimes. Graphical sensivity analyses are presented which have features that are not intuitively obvious.

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The questions that are asked of forensic scientists during the course of a criminal investigation, and during subsequent court proceedings, are of varied form. This paper attempts to place these questions into broad generic types and explores the difference in the inferential process that a scientist may employ when forming opinions that help answer these questions. From this model, a working definition of different roles and attributes for forensic scientists is described which may offer greater clarity for both practitioners and users of forensic science.

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Previous papers in Science & Justice have described the work of the Case Assessment and Interpretation (CAI) project that has been running for several years within the Forensic Science Service (FSS). The principles of the CAI model, which have developed through casework, are the foundation of a balanced, robust and logical approach to interpretation. The question arises frequently as to what is the most appropriate database that should be available to assist in assigning a value to a given probability. In this paper we present a set of guidelines in the form of flowcharts and explore them within the context of a range of case examples.

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The use of earmarks as evidence in criminal trials appears to be expanding, but there is something of a dearth of peer-reviewed scientific publications to support the pursuit. This paper is a critical review of the current literature in which we emphasize the weaknesses of the present state of knowledge. Some research directions are proposed to gather statistical knowledge of the within-source and between-source variability of earmarks and earprints. Its ultimate goal is to be able to assess likelihood ratios in relation to this type of evidence.

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We report the use of DNA profiles from six STR loci for inferring the ethnic origin of a crime stain and discuss how such inference may be used as intelligence information to reduce the expected number of interviews to resolve a case. To enable this work, databases have been created for five British ethnic groups (Caucasians, Afro-Caribbeans, Indian sub-continentals, Southeast Asians and Middle Easterners) that together comprise 99.7% of the UK population.

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A new ten-locus STR (short tandem repeat) profiling system was recently introduced into casework by the Forensic Science Service (FSS) and statistical analyses are described here based on data collected using this new system for the three major racial groups of the UK: Caucasian. Afro-Caribbean and Asian (of Indo-Pakistani descent). Allele distributions are compared and the FSS position with regard to routine significance testing of DNA frequency databases is discussed. An investigation of match probability calculations is carried out and the consequent analyses are shown to provide support for proposed changes in how the FSS reports DNA results when very small match probabilities are involved.

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The Forensic Science Service (FSS) has devoted appreciable effort to developing the application of the principles of evidence interpretation. Much of the work has been reported in previous papers in this journal, in particular those that develop a model for Case Assessment and Interpretation (CAI). The principles of interpretation are restated and the implications for structure and content of statements are described.

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Interpretation of the weight of scientific evidence depends upon the framing of at least two competing propositions to weigh against each other. It is the stage of framing propositions that is the most difficult aspect of evidence interpretation. The logical structure for case assessment and interpretation has been described by the authors in three previous papers [Cook R, et al. A model for case assessment and interpretation. Science & Justice 1998; 38: 151-156. Cook R, et al. A hierarchy of propositions: deciding which level to address in casework. Science & Justice 1998; 38: 231-239. Cook R, et al. Case pre-assessment and review in a two-way transfer case. Science & Justice 1999; 39: 103-111]. This paper considers the framing of propositions in greater detail, in particular the intermediate stage of exploring less formal explanations. All of the discussion is based on experiences encountered in workshops with caseworking forensic scientists.

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The authors describe a new approach to decision-making in an operational forensic science organization based on a model, embodying the principles of Bayesian inference, which has been developed through workshops run within the Forensic Science Service for forensic science practitioners. Issues which arise from the idea of pre-assessment of cases are explored by means of a case example.

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When evaluating DNA evidence, the necessary calculations are often carried out using databases drawn from broad populations; for example, the Forensic Science Service (FSS) maintains genetic databases for the 3 major racial groups of England and Wales--Caucasian, Afro-Caribbean and Asian (from the Indian subcontinent). The resulting figures may be challenged in court on the premise that they are not based on data from the population of most relevance in the particular case under consideration. One important factor might be the location of the crime. Since the recent establishment of a National DNA Intelligence Database, data have been made available from a wide range of geographical regions in England and Wales. This paper gives details of analyses conducted to measure the differentiation between white caucasian populations from these regions and from other areas of the UK and abroad using a Bayesian approach.

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The interpretation of mixtures of DNA in the forensic context presents particular challenges. The only logical means available for dealing with them is through Bayesian inference, which leads to the formulation, in most cases, of a likelihood ratio which weighs the evidence in favour of two competing hypotheses. However, situations can arise in which additional hypotheses are proposed and the authors discuss one such situation--that where the number of contributors to the mixture is in dispute. A way of dealing with the problem is presented.

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A recent case is described where the evidence of bloodstaining on a knife suggested that it was a mixture from the two victims. Interpretation of the evidence in this problem necessitated the formulation of several sets of multiple hypotheses which were analyzed by means of a tree diagram. The problem was then greatly simplified to one of comparing the two alternative hypotheses of most interest. It was found that results were robust to variation in the expert's judgment regarding the possibility that a mixture of blood was present on the knife.

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This paper establishes a logical framework for taking account of peak areas when interpreting mixed DNA STR profiles. The principles apply wherever such data are available but they are illustrated here by means of data which have been collected from made up mixtures of known concentrations analyzed at short tandem repeat loci. The data have led to some modeling assumptions which are used for numerical examples. In actual casework the proportions of the various components will not be known and there is a discussion of whether they should be allowed for by integrating over a prior distribution. This is a conceptual paper, rather than a prescription for casework, and the scope for further work is outlined.

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Data have been collected from 602 Caucasians, 190 Afro-Caribbeans and 257 Asians of Indo/Pakistani descent who have been profiled using a new six locus short tandem repeat (STR) multiplex. The data have been analysed by conventional significance testing methods: the exact test, homozygosity, and conventional goodness of fit to Hardy-Weinberg proportions. Frequency tables are given and the expected performance in British forensic casework is discussed.

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