It is often supposed that the spectacular successes of our modern mathematical sciences support a lofty vision of a world completely ordered by one single elegant theory. In this book Nancy Cartwright argues to the contrary. When we draw our image of the world from the way modern science works - as empiricism teaches us we should - we end up with a world where some features are precisely ordered, others are given to rough regularity and still others behave in (...) their own diverse ways. This patchwork makes sense when we realise that laws are very special productions of nature, requiring very special arrangements for their generation. Combining classic and newly written essays on physics and economics, The Dappled World carries important philosophical consequences and offers serious lessons for both the natural and the social sciences. (shrink)

Is science unified or disunified? This collection brings together contributions from prominent scholars in a variety of scientific disciplines to examine this important theoretical question. They examine whether the sciences are, or ever were, unified by a single theoretical view of nature or a methodological foundation and the implications this has for the relationship between scientific disciplines and between science and society.

This fascinating study in the sociology of science explores the way scientists conduct, and draw conclusions from, their experiments. The book is organized around three case studies: replication of the TEA-laser, detecting gravitational rotation, and some experiments in the paranormal. "In his superb book, Collins shows why the quest for certainty is disappointed. He shows that standards of replication are, of course, social, and that there is consequently no outside standard, no Archimedean point beyond society from which we can lever (...) the intellects of our fellows. "- -Donald M. McCloskey, Journal of Economic Psychology "Collins is one of the genuine innovators of the sociology of scientific knowledge.... Changing Order is a rich and entertaining book. "- - Isis "The book gives a vivid sense of the contingent nature of research and is generally a good read. "- -Augustine Brannigan, Nature "This provocative book is a review of [Collins's] work, and an attempt to explain how scientists fit experimental results into pictures of the world.... A promising start for new explorations of our image of science, too often presented as infallibly authoritative. "- -Jon Turney, New Scientist. (shrink)

As computating technologies become ubiquitous and at least partly autonomous, they will have increasing impact on societies, both in the developed and developing worlds. This article outlines a framework for guiding emerging technologies in directions that promise social as well as technical progress. Multiple stakeholders will have to be engaged in dialogues over new technological directions, forming trading zones in which knowledge and resources are exchanged. Such discussions will have to incorporate cultural and individual values.

In this paper we describe in some detail a formal computer model of inferential discourse based on a belief system. The key issue is that a logical model in a computer, based on rational sets, can usefully model a human situation based on irrational sets. The background of this work is explained elsewhere, as is the issue of rational and irrational sets (Billinge and Addis, in: Magnani and Dossena (eds.), Computing, philosophy and cognition, 2004; Stepney et al., Journey: Non-classical philosophy—socially (...) sensitive computing in journeys non-classical computation: A grand challenge for computing research, 2004). The model is based on the Belief System (Addis and Gooding, Proceedings of the AISB’99 Symposium on Scientific Creativity, 1999) and it provides a mechanism for choosing queries based on a range of belief. We explain how it provides a way to update the belief based on query results, thus modelling others’ experience by inference. We also demonstrate that for the same internal experience, different models can be built for different actors. (shrink)

Western philosophers have traditionally concentrated on theory as the means for expressing knowledge about a variety of phenomena. This absorbing book challenges this fundamental notion by showing how objects themselves, specifically scientific instruments, can express knowledge. As he considers numerous intriguing examples, Davis Baird gives us the tools to "read" the material products of science and technology and to understand their place in culture. Making a provocative and original challenge to our conception of knowledge itself, _Thing Knowledge _demands that we (...) take a new look at theories of science and technology, knowledge, progress, and change. Baird considers a wide range of instruments, including Faraday's first electric motor, eighteenth-century mechanical models of the solar system, the cyclotron, various instruments developed by analytical chemists between 1930 and 1960, spectrometers, and more. (shrink)

In this paper we want to examine how the mutual understanding of speakers is reached during a conversation through collaborative processes, and what role is played by abductive inference (in the Peircean sense) in these processes. We do this by bringing together contributions coming from a variety of disciplines, such as logic, philosophy of language and psychology. When speakers are engaged in a conversation, they refer to a supposed common ground: every participant ascribes to the others some knowledge, belief, opinion (...) etc. on which to rely in order to reach mutual understanding. As the conversation unfolds, this common ground is continually corrected and reshaped by the interchanges. An abductive reasoning takes place, in a collaborative setting, in order to build new possible theories about the common ground. In reconstructing this process through the use of a working example, we argue that the integration of a collaborative perspective within the Peircean theory of abduction can help to solve some of the drawbacks that the critics of the latter have outlined, for example its permissivity and non generativity. (shrink)

We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, (...) such as the influence of bias and prejudice. The scheme of inferential calculations invokes a Peircian concept of ‘belief’ as the propensity to choose a particular course of action. (shrink)

We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, (...) such as the influence of bias and prejudice. The scheme of inferential calculations invokes a Peircian concept of ‘belief’ as the propensity to choose a particular course of action. (shrink)

The anthropological approach is the central focus of this study. Laboratories are looked upon with the innocent eye of the traveller in exotic lands, and the societies found in these places are observed with the objective yet compassionate eye of the visitor from a quite other cultural milieu. There are many surprises that await us if we enter a laboratory in this frame of mind... This study is a realistic enterprise, an attempt to truly represent the social order of life (...) in laboratories and institutes of research, just as they are. By bringing the philosophical issues to the surface as matters not of prejudgement but as matters of concern, Karin Knorr-Cetina has developed the first really positive challenge to the philosophy of science since the days of paradigms and internal definitions of meanings. (shrink)

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

From the perspective of cognitive science, it is illuminating to think of much contemporary scientific research as taking place in distributed cognitive systems. This is particularly true of large-scale experimental and observational systems such as the Hubble Telescope. Clark, Hutchins, Knorr-Cetina, and Latour insist or imply such a move requires expanding our notions of knowledge, mind, and even consciousness. Whether this is correct seems to me not a straightforward factual question. Rather, the issue seems to be how best to develop (...) a theoretical understanding of such systems appropriate to the study of science and technology. I argue that there is no need to attribute to such systems as a whole any form of cognitive agency. We can well understand the importance of such systems while restricting agency to the human components. The implication is that we think of these large-scale distributed cognitive systems not so much as unified wholes, but as hybrid systems including both physical artifacts and ordinary humans. (shrink)

... the topic of 'meaning' is the one topic discussed in philosophy in which there is literally nothing but 'theory' - literally nothing that can be labelled or even ridiculed as the 'common sense view'. Putnam, 'The Meaning of Meaning' This book explores some truths behind the truism that experimentation is a hallmark of scientific activity. Scientists' descriptions of nature result from two sorts of encounter: they interact with each other and with nature. Philosophy of science has, by and large, (...) failed to give an account of either sort of interaction. Philosophers typically imagine that scientists observe, theorize and experiment in order to produce general knowledge of natural laws, knowledge which can be applied to generate new theories and technologies. This view bifurcates the scientist's world into an empirical world of pre-articulate experience and know how and another world of talk, thought and argument. Most received philosophies of science focus so exclusively on the literary world of representations that they cannot begin to address the philosophical problems arising from the interaction of these worlds: empirical access as a source of knowledge, meaning and reference, and of course, realism. This has placed the epistemological burden entirely on the predictive role of experiment because, it is argued, testing predictions is all that could show that scientists' theorizing is constrained by nature. Here a purely literary approach contributes to its own demise. The epistemological significance of experiment turns out to be a theoretical matter: cruciality depends on argument, not experiment. (shrink)

This paper presents a study of the generation, manipulation and use of visual representations in different episodes of scientific discovery. The study identifies a common set of transformations of visual representations underlying the distinctive methods and imagery of different scientific fields. The existence of common features behind the diversity of visual representations suggests a common dynamical structure for visual thinking, showing how visual representations facilitate cognitive processes such as pattern-matching and visual inference through the use of tools, technologies and other (...) cultural resources. This dynamical model suggests a way of theorizing the interaction of cognitive, socio-cultural and technological aspects of science without losing sight of the essential contribution each makes to the processes of discovery. Whereas scientific work is often construed epistemically, as having the aim of improving the fit between theories and phenomena or culturally given notions of what counts as reality, this study shows that scientists use transformations to modify visual representations in ways that achieve other kinds of match: between a representation and the cognitive demands of a task or between an emerging representation and the social need to communicate and negotiate new meanings in a context of culturally embedded conventions. By showing how images connect each of the overlapping contexts of scientific work the proposed model negotiates the sometimes contested boundary between cognitive and social aspects of science. (shrink)

The introduction of the notion of family resemblance represented a major shift in Wittgenstein’s thoughts on the meaning of words, moving away from a belief that words were well defined, to a view that words denoted less well defined categories of meaning. This paper presents the use of the notion of family resemblance in the area of machine learning as an example of the benefits that can accrue from adopting the kind of paradigm shift taken by Wittgenstein. The paper presents (...) a model capable of learning exemplars using the principle of family resemblance and adopting Bayesian networks for a representation of exemplars. An empirical evaluation is presented on three data sets and shows promising results that suggest that previous assumptions about the way we categories need reopening. (shrink)

This study of cognitive processes and scientific research begins with an autobiographical account of a research program that was designed to simulate scientific thinking. It explores such questions as: How do mental models, representations, expectations, and presumptions affect the creation of scientific knowledge? What is the effect of confirmation or disconfirmation on the process of experimentation and the direction of research? How does a scientist decide whether a model or theory is correct? The first-person narrative allows readers to follow the (...) research step by step and to work through the issues as the author grapples with them. The book also discusses important historical examples in which these issues have loomed large, among them the "great Devonian controversy," the etheric force controversy, and Kepler's theory of planetary motion. One fascinating chapter compares the cognitive styles of Bell and Edison and develops a cognitive framework that can be used to compare the creative processes of scientists and inventors. (shrink)

This ambitious book by one of the most original and provocative thinkers in science studies offers a sophisticated new understanding of the nature of scientific, mathematical, and engineering practice and the production of scientific knowledge. Andrew Pickering offers a new approach to the unpredictable nature of change in science, taking into account the extraordinary number of factors—social, technological, conceptual, and natural—that interact to affect the creation of scientific knowledge. In his view, machines, instruments, facts, theories, conceptual and mathematical structures, disciplined (...) practices, and human beings are in constantly shifting relationships with one another—"mangled" together in unforeseeable ways that are shaped by the contingencies of culture, time, and place. Situating material as well as human agency in their larger cultural context, Pickering uses case studies to show how this picture of the open, changeable nature of science advances a richer understanding of scientific work both past and present. Pickering examines in detail the building of the bubble chamber in particle physics, the search for the quark, the construction of the quarternion system in mathematics, and the introduction of computer-controlled machine tools in industry. He uses these examples to address the most basic elements of scientific practice—the development of experimental apparatus, the production of facts, the development of theory, and the interrelation of machines and social organization. (shrink)

I outline a pragmatic view of scientists' use of observation which draws attention to non-discursive, instrumental and social contexts of observation, in order to explain scientists' agreement about the appearance and significance of new phenomena. I argue that: observation is embedded in a network of activities, techniques, and interests; that experimentalists make construals of new phenomena which enable them communicate exploratory techniques and their outcomes, and that empirical enquiry consists of communicative, exploratory and predictive strategies whose interdependence ensures that, notwithstanding (...) the constructedness of representations and the empirical underdetermination of theories, observations contain information about the natural world. (shrink)

Syntactic and structural models specify relationships between their constituents but cannot show what outcomes their interaction would produce over time in the world. Simulation consists in iterating the states of a model, so as to produce behaviour over a period of simulated time. Iteration enables us to trace the implications and outcomes of inference rules and other assumptions implemented in the models that make up a theory. We apply this method to experiments which we treat as models of the particular (...) aspects of reality they are designed to investigate. Scientific experiments are constantly designed and re-designed in the context of implementation and use. They mediate between theoretical understanding and the practicalities of engaging with the empirical and social world. In order to model experiments we need to identify and represent features that all experiments have in common. We treat these features as parameters of a general model of experiment so that by varying these parameters different types of experiment can be modelled. (shrink)