Explaining and trusting expert evidence: What is a ‘sufficiently reliable scientific basis’?

Through a series of judicial decisions and Practice Directions, the English courts have developed a rule that expert evidence must have ‘a sufficiently reliable scientific basis to be admitted’. There is a dearth of case-law as to what degree of reliability is ‘sufficient’. This article argues that the test should be interpreted as analogous to one developed in the law of hearsay: expert evidence (scientific or otherwise) must be ‘potentially safely reliable’ in the context of the evidence as a whole. The implications of this test will vary according to the relationship between the expert evidence and the other evidence in the case. The article identifies three main patterns into which this relationship falls. Whether the jury relies upon the evidence will depend upon what they regard as the best explanation of the evidence and how far they trust the expert. Whether their reliance is safe (as a basis for conviction) depends on whether they could rationally rule out explanations consistent with innocence, and whether the degree to which they take the expert’s evidence on trust is consistent with prosecution’s burden of proving the essential elements of its case, including the reliability of any scientific techniques on which it relies

Expert testimony, law and epistemic authority

© Society for Applied Philosophy, 2016 This article discusses the concept of epistemic authority in the context of English law relating to expert testimony. It distinguishes between two conceptions of epistemic authority (and epistemic deference), one strong and one weak, and argues that only the weak conception is appropriate in a legal context, or in any other setting where reliance on experts can be publicly justified. It critically examines Linda Zagzebski's defence of a stronger conception of epistemic authority and questions whether epistemic authority is as closely analogous to practical authority as she maintains. Zagzebski elucidates a kind of deference that courts generally, and rightly, try to avoid. Her concept of ‘first person reasons’, however, does capture an important aspect of the deliberations of conscientious legal actors

Meaning postulates and deference

Fodor (1998) argues that most lexical concepts have no internal structure. He rejects what he calls Inferential Role Semantics (IRS), the view that primitive concepts are constituted by their inferential relations, on the grounds that this violates the compositionality constraint and leads to an unacceptable form of holism. In rejecting IRS, Fodor must also reject meaning postulates. I argue, contra Fodor, that meaning postulates must be retained, but that when suitably constrained they are not susceptible to his arguments against IRS. This has important implications for the view that certain of our concepts are deferential. A consequence of the arguments I present is that deference is relegated to a relatively minor role in what Sperber (1997) refers to as reflective concepts; deference has no important role to play in the vast majority of our intuitive concepts

Unpacking capabilities underlying design (thinking) process

Engineering graduates must know how to frame and solve non-routine problems. While design classes explicitly teach problem framing and solving, it is lacking throughout much of the rest of the engineering curriculum and is often relegated to capstone classes at the end of the students’ educational experience. This paper explores problem framing and solving through the lens of experiential learning theory. It captures core problem framing and solving approaches from critical, design and systems thinking and concludes with a table of learning outcomes that might be drawn upon in designing an engineering curriculum that more fully develops the problem framing and solving capabilities of its students

The effect of multiple knowledge sources on learning and teaching

Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel

'Not Quite Right': Helping Students to Make Better Arguments

This paper looks at the need for a better understanding of the impediments to critical thinking in relation to graduate student work. The paper argues that a distinction is needed between two vectors that influence student writing: (1) the word-level–sentence-level vector; and (2) the grammar–inferencing vector. It is suggested that much of the work being done to assist students is only done on the first vector. This paper suggests a combination of explicit use of deductive syllogistic inferences and computer-aided argument mapping is needed. A methodology is suggested for tackling assignments that require students to ‘make an argument’. It is argued that what lecturers understand tacitly, now needs to be made a focus of deliberate educational practices

Inferring Acceptance and Rejection in Dialogue by Default Rules of Inference

This paper discusses the processes by which conversants in a dialogue can infer whether their assertions and proposals have been accepted or rejected by their conversational partners. It expands on previous work by showing that logical consistency is a necessary indicator of acceptance, but that it is not sufficient, and that logical inconsistency is sufficient as an indicator of rejection, but it is not necessary. I show how conversants can use information structure and prosody as well as logical reasoning in distinguishing between acceptances and logically consistent rejections, and relate this work to previous work on implicature and default reasoning by introducing three new classes of rejection: {\sc implicature rejections}, {\sc epistemic rejections} and {\sc deliberation rejections}. I show how these rejections are inferred as a result of default inferences, which, by other analyses, would have been blocked by the context. In order to account for these facts, I propose a model of the common ground that allows these default inferences to go through, and show how the model, originally proposed to account for the various forms of acceptance, can also model all types of rejection.Comment: 37 pages, uses fullpage, lingmacros, name