Sven Ove Hansson

The relatively new discipline of risk analysis promises to provide objective guidance in some of the most controversial issues in modern high‐technology societies. Four conditions are discussed that must be satisfied for this promise to be fulfilled. Since none of these conditions is satisfied, risk analysis does not keep its promise. In its attempts to reduce genuinely political issues to technocratic calculations, it neglects many of the factors that should influence decisions on risk acceptance. A list of tentative guidelines is given for numerical decision support that encourages democratic decision‐making instead of trying to evade it.

Primitive dyadic (two-place) probability functions have been proposed both as representations of conditional probability and as tools for modelling iterated probability revision. However, the usefulness of dyadic probability functions for these purposes is limited by the problems involved in updating with propositions whose prior probability is zero. These limitations are investigated and specified. They turn out to be more serious for the use of dyadic probability functions to represent probability revision than for their use as representations of conditional probability.

Karl Popper introduced a metaphor of demarcation for identification of claims that should not be classified as scientific. This metaphor still dominates the philosophical discussion on pseudoscience. We show that it has hampered the discussion in several ways, most importantly by blocking the insight that determining whether some particular claim is pseudoscientific usually requires specialized scientific expertise. We conclude that it would be better to give up this metaphor and leave room for the two tasks of defining pseudoscience (a task for philosophers) and diagnosing potential cases of pseudoscience (a task for experts in the respective areas of science).

The meaning of the phrase “equal opportunity” is investigated with a combination of historical text studies and philosophical analysis. In the late nineteenth century, this phrase obtained a specialized meaning that cannot be derived from the meanings of its constituent words. The “equality” of equal opportunity refers to equality among people belonging to different groups, and the “opportunities” mostly concern access to desirable activities and resources that are important for a person’s career and chances in life. Contrary to many other social goals, the ideal of equal opportunity does not have a well-defined endpoint, that is, we cannot describe a plausible social state in which equal opportunity is perfectly satisfied. But in spite of this, equal opportunity has sufficient directional precision to tell us in which direction to go. Strivings for equal opportunity form an essential component of strivings for social justice. A major reason for this is that equal opportunities are incompatible with discrimination, i.e., worse treatment of people because they belong to certain groups. Discrimination is a particularly dangerous form of inequality, since each act of discrimination contributes to perpetuating a pattern that can persist for generations. Working for equal opportunity is an efficient way to counteract discrimination.

Fragen dieser Art werden nicht nur in der Ethik behandelt, sondern auch in einer anderen Disziplin, nämlich in der Entscheidungstheorie. Traditionellerweise wird gelehrt, dass diese zwei Disziplinen verschiedene Aspekte praktischen Handelns untersuchen: Die Ethik befasst sich mit der Suche nach den richtigen Normen und Zielen menschlichen Handelns; in der Entscheidungstheorie werden dagegen die Normen und Ziele als gegebene angesehen, und man untersucht wie sie am besten erreicht warden können. Es ist aber eine offene Frage, ob die ethische und entscheidungstheoretische Fragestellungen, in dieser Weise definiert, überhaupt voneinander trennbar sind.

BackgroundWith the increased use of implanted medical devices follows a large number of explantations. Implants are removed for a wide range of reasons, including manufacturing defects, recovery making the device unnecessary, battery depletion, availability of new and better models, and patients asking for a removal. Explantation gives rise to a wide range of ethical issues, but the discussion of these problems is scattered over many clinical disciplines.MethodsInformation from multiple clinical disciplines was synthesized and analysed in order to provide a comprehensive approach to the ethical issues involved in the explantation of medical implants.ResultsDiscussions and recommendations are offered on pre-implantation information about a possible future explantation, risk–benefit assessments of explantation, elective explantations demanded by the patient, explantation of implants inserted for a clinical trial, patient registers, quality assurance, routines for investigating explanted implants, and demands on manufacturers to prioritize increased service time in battery-driven implants and to market fewer but more thoroughly tested models of implants.ConclusionSpecial emphasis is given to the issue of control or ownership over implants, which underlies many of the ethical problems concerning explantation. It is proposed that just like transplants, implants that fulfil functions normally carried out by biological organs should be counted as supplemented body parts. This means that the patient has a strong and inalienable right to the implant, but upon explantation it loses that status.

Our uncertainty about matters of fact can often be adequately represented by probabilities, but there are also cases in which we, intuitively speaking, know too little even to assign meaningful probabilities. In many of these cases, other formal representations can be used to capture some of the prominent features of our uncertainty. This is a non-technical overview of some of these representations, including probability intervals, belief functions, fuzzy sets, credal sets, weighted credal sets, and second order probabilities.

Preferences and choices have central roles in moral philosophy, economics, and the decision sciences in general. In a formal language we can express and explore the properties of preferences, choices, and their interrelations in a precise way, and uncover connections that are inaccessible without formal tools. In this chapter, the plausibility of different such properties is discussed, and it is shown how close attention to the logical details can help dissolve some apparent paradoxes in informal and semi-formal treatments.

Deontic logic is the logic of normative concepts such as obligation, permission, and prohibition. This non-technical overview of the area has a strong emphasis on the connections between deontic logic and problems discussed in moral philosophy. Major issues treated are the distinction between ought-to-be and ought-to-do, the various meanings of permissive expressions, the logical relations among norms, the paradoxes of deontic logic, and the nature of moral conflicts and moral dilemmas. It is concluded that deontic logic has resources for precise treatment of important issues in moral philosophy, but in order to make full use of these resources, more co-operation between logicians and moral philosophers is needed.

This introduction to formal philosophy has its focus on the basic methodology of formalization: the selection of concepts for formalization, appropriate splittings and merges of concepts to be formalized, the idealization that is necessary prior to formalization, the identification of variables and their domains, and the construction of a formal language. Other topics covered in this chapter are the advantages and pitfalls of formal philosophy, the relationships between formal models and that which they represent, and the use of non-logical models in philosophy.

We encounter the notion of coherence in many branches of philosophy. This overview introduces some basic distinctions that can be used to characterize concepts of coherence. After that, two formal frameworks for the analysis of coherence are introduced. The first of these is based on the logic of support relations. It is used to show that coherentism and foundationalism may be combinable rather than antithetical. The second framework assumes that coherence comes in degrees and that it can be measured in probability-based units. The properties of such measures is discussed, and so are the difficulties in constructing a measure of coherence that satisfies intuitively reasonable constraints.

All formal models of belief change involve choices between different ways to accommodate new information. However, the models differ in their loci of choice, i.e. in what formal entities the choice mechanism is applied to. Four models of belief change with different loci of choice are investigated in terms of how they satisfy a set of important properties of belief contraction and revision. It is concluded that the locus of epistemic choice has a large impact on the properties of the resulting belief change operation.

We can express values in three major ways: in terms of classification (“good”, “bad”, “best”, etc.), comparison (“better”, “at least as good”, “equal in value”), and quantity (numbers are assigned). The interrelations among these three types of value expressions are surveyed, with a particular emphasis on relations of interdefinability. Furthermore, interrelations between value terms and terms expressing norms or choices are explored. Several of these connections have been surprisingly little studied, and further investigations may possibly lead to the discovery of additional connections among the different formal representations of value and value-related concepts.