Isabelle Peschard

What is risk? How do we assess risk? What are the ethical implications of risk? The concept of risk is important – sometimes even crucial – for many philosophical domains, from philosophy of science and technology to ethics and sustainability. Philosophy and Science of Risk is a clear, wide-ranging introduction to this urgent and fast-growing subject. It covers the following key topics: • The philosophical and historical background to understanding and interpreting risk • The meaning of risk and how it differs from closely related concepts, such as uncertainty or dangers • The social construction of risk • Risk perception and risk as an object of scientific study • The measurement of risk, its probability and severity • Risk and scientific modeling • Risk, value judgments, and expertise • Risk management, including cost-benefit analysis and the precautionary approach • Risk communication, including deliberative models • Ethics of risk, including duties toward nonhuman animals and future generations • Risk and sustainability • Decision-making under risk Including helpful additional features such as text boxes, chapter summaries, review, and discussion questions, Philosophy and Science of Risk: An Introduction is an ideal textbook for students of the philosophy of risk. It is also suitable for students studying the conceptual questions surrounding risk in related subjects, such as sociology, psychology, economics, politics, geography, sustainability, and environmental studies.

Experimental modeling is the construction of theoretical models hand in hand with experimental activity. As explained in Section 1, experimental modeling starts with claims about phenomena that use abstract concepts, concepts whose conditions of realization are not yet specified; and it ends with a concrete model of the phenomenon, a model that can be tested against data. This paper argues that this process from abstract concepts to concrete models involves judgments of relevance, which are irreducibly normative. In Section 2, we show, on the basis of several case studies, how these judgments contribute to the determination of the conditions of realization of the abstract concepts and, at the same time, of the quantities that characterize the phenomenon under study. Then, in Section 3, we compare this view on modeling with other approaches that also have acknowledged the role of relevance judgments in science. To conclude, in Section 4, we discuss the possibility of a plurality of relevance judgments and introduce a distinction between locally and generally relevant factors

This paper aims 1) to introduce the notion of theoretical story as a resource and source of constraint for the construction and assessment of models of phenomena; 2) to show the relevance of this notion for a better understanding of the role and nature of values in scientific activity. The reflection on the role of values and value judgments in scientific activity should be attentive, I will argue, to the distinction between models and the theoretical story that guides and constrains their construction. The aim of scientific activity is to develop understanding of phenomena, and something that serves this aim and contributes to the development of understanding has a cognitive value. Cognitive values are the features that something that plays a role in scientific activity should have so that it can serve its aim. I will focus my attention on the features of the theoretical story and of the models.

It is sometimes said that simulation can serve as epistemic substitute for experimentation. Such a claim might be suggested by the fast-spreading use of computer simulation to investigate phenomena not accessible to experimentation. But what does that mean? The paper starts with a clarification of the terms of the issue and then focuses on two powerful arguments for the view that simulation and experimentation are ‘epistemically on a par’. One is based on the claim that, in experimentation, no less than in simulation, it is not the system under study that is manipulated but a system that ‘stands-in’ for it. The other one highlights the pervasive use of models in experimentation. It will be argued that these arguments, as compelling as they might seem, are each based on a mistaken interpretation of experimentation and that, far from simulation and experimentation being epistemically on a par, they do not have the same epistemic function, do not produce the same kind of epistemic results.

Participation of the Public in Science: Towards a New Kind of Scientific Practice Participation of the public in science has been the object of an increasing number of social and political philosophical studies, but there is still hardly any epistemological study of the topic. While it has been objected that involvement of the public is a threat to the integrity of science, the apparent indifference of philosophers of science seems to testify to its lack of relevance to conceptions of scientific activity. I argue both that it is not a threat to science and that it is relevant to philosophy of science by showing that it constitutes a new kind of epistemic practice. Two main objections to the idea that the involvement of non-scientists, with their situated perspective and contextual values, can form an epistemic practice will be addressed: the first bears on the epistemic potentialities of the cooperation between scientist and non-scientists; the second on the possibility that this cooperation takes the form of a practice.

The relation between models and the world is mediated by experimental procedures generating data that are used as evidence to evaluate the model. Data can serve as empirical evidence, for or against, only if they result from reliable experimental procedures. The aim of this article is to discuss the role of relevance judgments in the evaluation of reliability and to clarify the conditions under which reliability can be a strictly empirical matter. It is argued that reliability is a strictly empirical issue only in the restricted case in which the claim under test/investigation is about a data-generating procedure.

This paper aims 1) to introduce the notion of theoretical story as a resource and source of constraint for the construction and assessment of models of phenomena; 2) to show the relevance of this notion for a better understanding of the role and nature of values in scientific activity. The reflection on the role of values and value judgments in scientific activity should be attentive, I will argue, to the distinction between models and the theoretical story that guides and constrains their construction. The aim of scientific activity is to develop understanding of phenomena, and something that serves this aim and contributes to the development of understanding has a cognitive value. Cognitive values are the features that something that plays a role in scientific activity should have so that it can serve its aim. I will focus my attention on the features of the theoretical story and of the models.

It is sometimes said that simulation can serve as epistemic substitute for experimentation. Such a claim might be suggested by the fast-spreading use of computer simulation to investigate phenomena not accessible to experimentation (in astrophysics, ecology, economics, climatology, etc.). But what does that mean? The paper starts with a clarification of the terms of the issue and then focuses on two powerful arguments for the view that simulation and experimentation are ‘epistemically on a par’. One is based on the claim that, in experimentation, no less than in simulation, it is not the system under study that is manipulated but a system that ‘stands-in’ for it. The other one highlights the pervasive use of models in experimentation. It will be argued that these arguments, as compelling as they might seem, are each based on a mistaken interpretation of experimentation and that, far from simulation and experimentation being epistemically on a par, they do not have the same epistemic function, do not produce the same kind of epistemic results.

Experimental activity is traditionally identified with testing the empirical implications or numerical simulations of models against data. In critical reaction to the ‘tribunal view’ on experiments, this essay will show the constructive contribution of experimental activity to the processes of modeling and simulating. Based on the analysis of a case in fluid mechanics, it will focus specifically on two aspects. The first is the controversial specification of the conditions in which the data are to be obtained. The second is conceptual clarification, with a redefinition of concepts central to the understanding of the phenomenon and the conditions of its occurrence.

In the philosophy of science, identity over time emerges as a central concern both as an ontological category in the interpretation of physical theories, and as an epistemological problem concerning the conditions of possibility of knowledge. In Reichenbach and subsequent writers on the problem of indistinguishable quantum particles we see the return of a contrast between Leibniz and Aquinas on the subject of individuation. The possibility of rejecting the principle of the identity of indiscernibles has certain logical difficulties, leading us inexorably from ontology into epistemology. For the epistemological problem we attend to the differences that emerged between the (neo-)Kantian and logical empiricist traditions, also saliently displayed in Reichenbach's writings. After examining the contrast between Kant's and Leibniz's conceptions of empirical knowledge, specifically with respect to the irreducibility of spatiotemporal determinations, we explore an application of a neo-Kantian view to the same problem of indistinguishable quantum particles.

The reduction of the concept of heat to that of molecular kinetic energy is recurrently presented as lending analogical support to the project of reduction of phenomenal concepts to physical concepts. The claimed analogy draws on the way the use of the concept of heat is attached to the experience in first person of a certain sensation. The reduction of this concept seems to prove the possibility to reduce discourse involving phenomenal concepts to a scientific description of neural activity. But is this analogy really justified? We will show that if there is an analogy, far from speaking for a reduction of phenomenal concepts, it rather stresses the necessity to integrate phenomenal reports in the scientific study of experience.