The Handbook Philosophy of Technology and Engineering Sciences addresses numerous issues in the emerging field of the philosophy of those sciences that are involved in the technological process of designing, developing and making of new technical artifacts and systems. These issues include the nature of design, of technological knowledge, and of technical artifacts, as well as the toolbox of engineers. Most of these have thus far not been analyzed in general philosophy of science, which has traditionally but inadequately regarded technology (...) as mere applied science and focused on physics, biology, mathematics and the social sciences.. First comprehensive philosophical handbook on technology and the engineering sciences. Unparalleled in scope including explorative articles. In depth discussion of technical artifacts and their ontology. Provides extensive analysis of the nature of engineering design. Focuses in detail on the role of models in technology. (shrink)

Da Costa and French explore the consequences of adopting a 'pragmatic' notion of truth in the philosophy of science. Their framework sheds new light on issues to do with belief, theory acceptance, and the realism-antirealism debate, as well as the nature of scientific models and their heuristic development.

Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton (1990, Mimesis as make-believe: on the foundations of the (...) representational arts. Harvard University Press, Cambridge/MA) has the resources to answer these questions. I introduce this account, outline the answers that it offers, and develop a general picture of scientific modelling based on it. (shrink)

Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton (1990, Mimesis as make-believe: on the foundations of the (...) representational arts. Harvard University Press, Cambridge/MA) has the resources to answer these questions. I introduce this account, outline the answers that it offers, and develop a general picture of scientific modelling based on it. (shrink)

Discussions of representation in science tend to draw on examples from art. However, such examples need to be handled with care given a) the differences between works of art and scientific theories and b) the accommodation of these examples within certain philosophies of art. I shall examine the claim that isomorphism is neither necessary nor sufficient for representation and I shall argue that there exist accounts of representation in both art and science involving isomorphism which accommodate the apparent counterexamples and, (...) moreover, allow us to understand how “impossible” artistic objects and inconsistent scientific theories can be said to represent. (shrink)

Recent discussions of the nature of representation in science have tended to import pre-established decompositions from analyses of representation in the arts, language, cognition and so forth. Which of these analyses one favours will depend on how one conceives of theories in the first place. If one thinks of them in terms of an axiomatised set of logico-linguistic statements, then one might be naturally drawn to accounts of linguistic representation in which notions of denotation, for example, feature prominently. If, on (...) the other hand, one conceives of theories in non-linguistic terms, as in the model-theoretic approach, then one might look to analyses of representation in the arts where notions of resemblance tend to be brought to the fore. Thus van Fraassen, for example, has imported such an analysis into his discussion of representation in science and argued that an appropriate account of resemblance can be given in terms of the set-theoretic relation of isomorphism. This has been strongly criticised by Suarez, who argues that just as isomorphism cannot capture representation in art, so it is inappropriate in the scientific context as well. Similarly Hughes draws on Goodman`s rejection of resemblance in art in favour of denotation and, rather confusingly perhaps, favours the latter whilst also maintaining the model-theoretic view of theories. In this paper, I shall examine the debate in terms of four claims: 1. Isomorphism is not sufficient for representation; 2. Isomorphism is not necessary for representation; 3. Models represent but theories do not; 4. Models denote and do not resemble. Each of these claims will be questioned and I will conclude by suggesting that, through appropriate modifications, a form of isomorphism can serve to underpin representation in both the arts and science. (shrink)

John Searle's Speech Acts (1969) and Expression and Meaning (1979) developed a highly original and influential approach to the study of language. But behind both works lay the assumption that the philosophy of language is in the end a branch of the philosophy of the mind: speech acts are forms of human action and represent just one example of the mind's capacity to relate the human organism to the world. The present book is concerned with these biologically fundamental capacities, and, (...) though third in the sequence, in effect it provides the philosophical foundations for the other two. Intentionality is taken to be the crucial mental phenomenon, and its analysis involves wide-ranging discussions of perception, action, causation, meaning, and reference. In all these areas John Searle has original and stimulating views. He ends with a resolution of the 'mind-body' problem. (shrink)

In this paper, I develop Mauricio Suárez’s distinction between denotation, epistemic representation, and faithful epistemic representation. I then outline an interpretational account of epistemic representation, according to which a vehicle represents a target for a certain user if and only if the user adopts an interpretation of the vehicle in terms of the target, which would allow them to perform valid (but not necessarily sound) surrogative inferences from the model to the system. The main difference between the interpretational conception I (...) defend here and Suárez’s inferential conception is that the interpretational account is a substantial account—interpretation is not just a “symptom” of representation; it is what makes something an epistemic representation of a something else. (shrink)

Mathematics plays a central role in much of contemporary science, but philosophers have struggled to understand what this role is or how significant it might be for mathematics and science. In this book Christopher Pincock tackles this perennial question in a new way by asking how mathematics contributes to the success of our best scientific representations. In the first part of the book this question is posed and sharpened using a proposal for how we can determine the content of a (...) scientific representation. Several different sorts of contributions from mathematics are then articulated. Pincock argues that each contribution can be understood as broadly epistemic, so that what mathematics ultimately contributes to science is best connected with our scientific knowledge. In the second part of the book, Pincock critically evaluates alternative approaches to the role of mathematics in science. These include the potential benefits for scientific discovery and scientific explanation. A major focus of this part of the book is the indispensability argument for mathematical platonism. Using the results of part one, Pincock argues that this argument can at best support a weak form of realism about the truth-value of the statements of mathematics. The book concludes with a chapter on pure mathematics and the remaining options for making sense of its interpretation and epistemology. Thoroughly grounded in case studies drawn from scientific practice, this book aims to bring together current debates in both the philosophy of mathematics and the philosophy of science and to demonstrate the philosophical importance of applications of mathematics. (shrink)

Recent work in the philosophy of science has generated an apparent conflict between theories attempting to explicate the nature of scientific representation. On one side, there are what one might call 'informational' views, which emphasize objective relations (such as similarity, isomorphism, and homomorphism) between representations (theories, models, simulations, diagrams, etc.) and their target systems. On the other side, there are what one might call 'functional' views, which emphasize cognitive activities performed in connection with these targets, such as interpretation and inference. (...) The main sources of the impression of conflict here are arguments by some functionalists to the effect that informational theories are flawed: it is suggested that relations typically championed by informational theories are neither necessary nor sufficient for scientific representation, and that any theory excluding functions is inadequate. In this paper I critically examine these arguments, and contend that, as it turns out, informational and functional theories are importantly complementary. (shrink)

Bas C. van Fraassen presents an original exploration of how we represent the world.

An account of scientific representation in terms of partial structures and partial morphisms is further developed. It is argued that the account addresses a variety of difficulties and challenges that have recently been raised against such formal accounts of representation. This allows some useful parallels between representation in science and art to be drawn, particularly with regard to apparently inconsistent representations. These parallels suggest that a unitary account of scientific and artistic representation is possible, and our article can be viewed (...) as laying the groundwork for such an account—although, as we shall acknowledge, significant differences exist between these two forms of representation. (shrink)

In this paper, I take scientific models to be epistemic representations of their target systems. I define an epistemic representation to be a tool for gaining information about its target system and argue that a vehicle’s capacity to provide specific information about its target system—its informativeness—is an essential feature of this kind of representation. I draw an analogy to our ordinary notion of interpretation to show that a user’s aim of faithfully representing the target system is necessary for securing this (...) feature. (shrink)

The aim of this paper is to defend the structural concept of representation, as defined by homomorphisms, against its main objections, namely: logical objections, the objection from misrepresentation, theobjection from failing necessity, and the copy theory objection. The logical objections can be met by reserving the relation ‘to be homomorphic to’ for the explication of potential representation (or, of the representational content). Actual reference objects (‘targets’) of representations are determined by (intentional or causal) representational mechanisms. Appealing to the independence of (...) the dimensions of ‘content’ and ‘target’ also helps to see how the structural concept can cope with misrepresentation. Finally, I argue that homomorphic representations are not necessarily ‘copies’ of their representanda, and thus can convey scientific insight. (shrink)

The paper defends the structural concept of representation, defined by homomorphisms, against the main objections that have been raised against it: Logical objections, the objection from misrepresentation, the objection from failing necessity, and the copy theory objection. Homomorphic representations are not necessarily ‘copies’ of their representanda, and thus can convey scientific insight.

The paper defends the structural concept of representation, defined by homomorphisms, against the main objections that have been raised against it: Logical objections, the objection from misrepresentation, the objection from failing necessity, and the copy theory objection. Homomorphic representations are not necessarily ‘copies’ of their representanda, and thus can convey scientific insight.

Many standard philosophical accounts of scientific practice fail to distinguish between modeling and other types of theory construction. This failure is unfortunate because there are important contrasts among the goals, procedures, and representations employed by modelers and other kinds of theorists. We can see some of these differences intuitively when we reflect on the methods of theorists such as Vito Volterra and Linus Pauling on the one hand, and Charles Darwin and Dimitri Mendeleev on the other. Much of Volterra's and (...) Pauling's work involved modeling; much of Darwin's and Mendeleev's did not. In order to capture this distinction, I consider two examples of theory construction in detail: Volterra's treatment of post-WWI fishery dynamics and Mendeleev's construction of the periodic system. I argue that modeling can be distinguished from other forms of theorizing by the procedures modelers use to represent and to study real-world phenomena: indirect representation and analysis. This differentiation between modelers and non-modelers is one component of the larger project of understanding the practice of modeling, its distinctive features, and the strategies of abstraction and idealization it employs. (shrink)

I argue against theories that attempt to reduce scientific representation to similarity or isomorphism. These reductive theories aim to radically naturalize the notion of representation, since they treat scientist's purposes and intentions as non-essential to representation. I distinguish between the means and the constituents of representation, and I argue that similarity and isomorphism are common but not universal means of representation. I then present four other arguments to show that similarity and isomorphism are not the constituents of scientific representation. I (...) finish by looking at the prospects for weakened versions of these theories, and I argue that only those that abandon the aim to radically naturalize scientific representation are likely to be successful. (shrink)

This paper defends the deflationary character of two recent views regarding scientific representation, namely RIG Hughes’ DDI model and the inferential conception. It is first argued that these views’ deflationism is akin to the homonymous position in discussions regarding the nature of truth. There, we are invited to consider the platitudes that the predicate “true” obeys at the level of practice, disregarding any deeper, or more substantive, account of its nature. More generally, for any concept X, a deflationary approach is (...) then defined in opposition to a substantive approach, where a substantive approach to X is an analysis of X in terms of some property P, or relation R, accounting for and explaining the standard use of X. It then becomes possible to characterize a deflationary view of scientific representation in three distinct senses, namely: a “no-theory” view, a “minimalist” view, and a “use-based” view – in line with three standard deflationary responses in the philosophical literature on truth. It is then argued that both the DDI model and the inferential conception may be suitably understood in any of these three different senses. The application of these deflationary ‘hermeneutics’ moreover yields significant improvements on the DDI model, which bring it closer to the inferential conception. It is finally argued that what these approaches have in common – the key to any deflationary account of scientific representation – is the denial that scientific representation may be ultimately reduced to any substantive explanatory property of sources, or targets, or their relations. (shrink)

This paper defends an inferential conception of scientific representation. It approaches the notion of representation in a deflationary spirit, and minimally characterizes the concept as it appears in science by means of two necessary conditions: its essential directionality and its capacity to allow surrogate reasoning and inference. The conception is defended by showing that it successfully meets the objections that make its competitors, such as isomorphism and similarity, untenable. In addition the inferential conception captures the objectivity of the cognitive representations (...) used by science, it sheds light on their truth and completeness, and it explains the source of the analogy between scientific and artistic modes of representation. (shrink)

I address questions about values in model-making in engineering, specifically: Might the role of values be attributable solely to interests involved in specifying and using the model? Selected examples illustrate the surprisingly wide variety of things one must take into account in the model-making itself. The notions of system, and physically similar systems are important and powerful in determining what is relevant to an engineering model. Another example illustrates how an idea to completely re-characterize, or reframe, an engineering problem arose (...) during model-making. I employ a qualitative analogue of the notion of physically similar systems. Historical cases can thus be drawn upon; I illustrate with a comparison between a geoengineering proposal to inject, or spray, sulfate aerosols, and two different historical cases involving the spraying of DDT. The current geoengineering proposal is seen to be like the disastrous and counterproductive case, and unlike the successful case, of the spraying of DDT. I conclude by explaining my view that model-making in science is analogous to moral perception in action, drawing on a view in moral theory that has come to be called moral particularism. (shrink)

In this paper I show how certain requirements must be set on any tenable account of scientific representation, such as the requirement allowing for misrepresentation. I then continue to argue that two leading accounts of scientific representation— the inferential account and the interpretational account—are flawed for they do not satisfy such requirements. Through such criticism, and drawing on an analogy from non-scientific representation, I also sketch the outline of a superior account. In particular, I propose to take epistemic representations to (...) be intentional objects that come with reference, semantic contents and a representational code, and I identify faithful representations as representations that act as guides to ontology. (shrink)

Models as Make-Believe offers a new approach to scientific modelling by looking to an unlikely source of inspiration: the dolls and toy trucks of children's games of make-believe.

The notion of scientific representation plays a central role in current debates on modeling in the sciences. One or maybe the major epistemic virtue of successful models is their capacity to adequately represent specific phenomena or target systems. According to similarity views of scientific representation, models should be similar to their corresponding targets in order to represent them. In this paper, Suárez’s arguments against similarity views of representation will be scrutinized. The upshot is that the intuition that scientific representation involves (...) similarity is not refuted by the arguments. The arguments do not make the case for the strong claim that similarity between vehicles and targets is neither necessary nor sufficient for scientific representation. Especially, one claim that a similarity view wants to uphold, still, is the following thesis: only if a vehicle is similar to a target in relevant respects and to a specific degree of similarity then the vehicle is a scientific representation of that target. (shrink)

Many people assume that the claims of scientists are objective truths. But historians, sociologists, and philosophers of science have long argued that scientific claims reflect the particular historical, cultural, and social context in which those claims were made. The nature of scientific knowledge is not absolute because it is influenced by the practice and perspective of human agents. Scientific Perspectivism argues that the acts of observing and theorizing are both perspectival, and this nature makes scientific knowledge contingent, as Thomas Kuhn (...) theorized forty years ago. Using the example of color vision in humans to illustrate how his theory of “perspectivism” works, Ronald N. Giere argues that colors do not actually exist in objects; rather, color is the result of an interaction between aspects of the world and the human visual system. Giere extends this argument into a general interpretation of human perception and, more controversially, to scientific observation, conjecturing that the output of scientific instruments is perspectival. Furthermore, complex scientific principles—such as Maxwell’s equations describing the behavior of both the electric and magnetic fields—make no claims about the world, but models based on those principles can be used to make claims about specific aspects of the world. Offering a solution to the most contentious debate in the philosophy of science over the past thirty years, Scientific Perspectivism will be of interest to anyone involved in the study of science. (shrink)

This is a welcome reprint of a book that continues to grow in importance.

It is now part and parcel of the official philosophical wisdom that models are essential to the acquisition and organisation of scientific knowledge. It is also generally accepted that most models represent their target systems in one way or another. But what does it mean for a model to represent its target system? I begin by introducing three conundrums that a theory of scientific representation has to come to terms with and then address the question of whether the semantic view (...) of theories, which is the currently most widely accepted account of theories and models, provides us with adequate answers to these questions. After having argued in some detail that it does not, I conclude by pointing out in what direction a tenable account of scientific representation might be sought. (shrink)

Taking scientific practice as its starting point, this book charts the complex territory of models used in science. It examines what scientific models are and what their function is. Reliance on models is pervasive in science, and scientists often need to construct models in order to explain or predict anything of interest at all. The diversity of kinds of models one finds in science – ranging from toy models and scale models to theoretical and mathematical models – has attracted attention (...) not only from scientists, but also from philosophers, sociologists, and historians of science. This has given rise to a wide variety of case studies that look at the different uses to which models have been put in specific scientific contexts. By exploring current debates on the use and building of models via cutting-edge examples drawn from physics and biology, the book provides broad insight into the methodology of modelling in the natural sciences. It pairs specific arguments with introductory material relating to the ontology and the function of models, and provides some historical context to the debates as well as a sketch of general positions in the philosophy of scientific models in the process. (shrink)

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

The aim of this paper is to defend the structural concept of representation, as defined by homomorphisms, against its main objections, namely: logical objections, the objection from misrepresentation, theobjection from failing necessity, and the copy theory objection. The logical objections can be met by reserving the relation.

During the last two centuries, the way economic science is done has changed radically: it has become a social science based on mathematical models in place of words. This book describes and analyses that change - both historically and philosophically - using a series of case studies to illuminate the nature and the implications of these changes. It is not a technical book; it is written for the intelligent person who wants to understand how economics works from the inside out. (...) This book will be of interest to economists and science studies scholars. But it also aims at a wider readership in the public intellectual sphere, building on the current interest in all things economic and on the recent failure of the so-called economic model, which has shaped our beliefs and the world we live in. (shrink)