Computer simulations are widely used in current scientific practice, as a tool to obtain information about various phenomena. Scientists accordingly rely on the outputs of computer simulations to make statements about the empirical world. In that sense, simulations seem to enable scientists to acquire empirical knowledge. The aim of this paper is to assess whether computer simulations actually allow for the production of empirical knowledge, and how. It provides an epistemological analysis of present-day empirical science, to which the traditional epistemological (...) categories cannot apply in any simple way. Our strategy consists in acknowledging the complexity of scientific practice, and trying to assess its rationality. Hence, while we are careful not to abstract away from the details of scientific practice, our approach is not strictly descriptive: our goal is to state in what conditions empirical science can rely on computer simulations. In order to do so, we need to adopt a renewed epistemological framework, whose categories would enable us to give a finer-grained, and better-fitted analysis of the rationality of scientific practice. (shrink)

Paul Faulkner presents a new theory of testimony - the basis of much of what we know. He addresses the questions of what makes it reasonable to accept a piece of testimony, and what warrants belief formed on that basis. He rejects rival theories and argues that testimonial knowledge and testimonially warranted belief are based on trust.

Whether simulation models provide the right kind of understanding comparable to that of analytic models has been and remains a contentious issue. The assessment of understanding provided by simulations is often hampered by a conflation between the sense of understanding and understanding proper. This paper presents a deflationist conception of understanding and argues for the need to replace appeals to the sense of understanding with explicit criteria of explanatory relevance and for rethinking the proper way of conceptualizing the role of (...) a single human mind in the collective scientific understanding. (shrink)

In this book, which remained unfinished at his death, Husserl attempts to forge a union between phenomenology and existentialism.

Our trust in the word of others is often dismissed as unworthy, because the illusory ideal of "autonomous knowledge" has prevailed in the debate about the nature of knowledge. Yet we are profoundly dependent on others for a vast amount of what any of us claim to know. Coady explores the nature of testimony in order to show how it might be justified as a source of knowledge, and uses the insights that he has developed to challenge certain widespread assumptions (...) in the areas of history, law, mathematics, and psychology. (shrink)

Reasons are given to justify the claim that computer simulations and computational science constitute a distinctively new set of scientific methods and that these methods introduce new issues in the philosophy of science. These issues are both epistemological and methodological in kind.

We address some of the epistemological challenges highlighted by the Critical Data Studies literature by reference to some of the key debates in the philosophy of science concerning computational modeling and simulation. We provide a brief overview of these debates focusing particularly on what Paul Humphreys calls epistemic opacity. We argue that debates in Critical Data Studies and philosophy of science have neglected the problem of error management and error detection. This is an especially important feature of the epistemology of (...) Big Data. In “Error” section we explain the main characteristics of error detection and correction along with the relationship between error and path complexity in software. In this section we provide an overview of conventional statistical methods for error detection and review their limitations when faced with the high degree of conditionality inherent to modern software systems. (shrink)

Computer simulations are an exciting tool that plays important roles in many scientific disciplines. This has attracted the attention of a number of philosophers of science. The main tenor in this literature is that computer simulations not only constitute interesting and powerful new science, but that they also raise a host of new philosophical issues. The protagonists in this debate claim no less than that simulations call into question our philosophical understanding of scientific ontology, the epistemology and semantics of models (...) and theories, and the relation between experimentation and theorising, and submit that simulations demand a fundamentally new philosophy of science in many respects. The aim of this paper is to critically evaluate these claims. Our conclusion will be sober. We argue that these claims are overblown and that simulations, far from demanding a new metaphysics, epistemology, semantics and methodology, raise few if any new philosophical problems. The philosophical problems that do come up in connection with simulations are not specific to simulations and most of them are variants of problems that have been discussed in other contexts before. (shrink)

Computer simulations are an exciting tool that plays important roles in many scientific disciplines. This has attracted the attention of a number of philosophers of science. The main tenor in this literature is that computer simulations not only constitute interesting and powerful new science , but that they also raise a host of new philosophical issues. The protagonists in this debate claim no less than that simulations call into question our philosophical understanding of scientific ontology, the epistemology and semantics of (...) models and theories, and the relation between experimentation and theorising, and submit that simulations demand a fundamentally new philosophy of science in many respects. The aim of this paper is to critically evaluate these claims. Our conclusion will be sober. We argue that these claims are overblown and that simulations, far from demanding a new metaphysics, epistemology, semantics and methodology, raise few if any new philosophical problems. The philosophical problems that do come up in connection with simulations are not specific to simulations and most of them are variants of problems that have been discussed in other contexts before. (shrink)

Epistemic opacity vis a vis human agents has been presented as an essential, ineliminable characteristic of computer simulation models resulting from the characteristics of the human cognitive agent. This paper argues, on the contrary, that such epistemic opacity as does occur in computer simulations is not a consequence of human limitations but of a failure on the part of model developers to adopt good software engineering practice for managing human error and ensuring the software artefact is maintainable. One consequence of (...) such failures is to create a “technical debt” which manifests itself in the so-called novel confirmation holism confronted by complex systems models. The argument from the supposed essential epistemic opacity of computational science to a non-anthropocentric epistemology runs counter to best practice in software engineering and overlooks empirical results of software engineering science. (shrink)

Im vorliegenden Buch geht es um die methodologische und epistemologische Charakterisierung der Computersimulation. Zu diesem Zweck werden Computermodelle vor der Kontrastfolie mathematischer Modelle betrachtet. Eine Strategie der Mathematisierung zielt darauf ab, komplexe Ph nomene in idealisierter Form zu modellieren und so die Komplexit t zu reduzieren. Die Simulation markiert das Ende dieser Strategie: Die Modelle werden nun selbst komplex und erhalten eine partielle Autonomie. Insbesondere der Prozess der Simulationsmodellierung erf hrt gegen ber traditioneller mathematischer Modellierung eine Transformation. Als zentrale Merkmale (...) der Simulationsmodellierung werden anhand typischer Beispiele analysiert: Artifizialit t, Experimentieren, Visualisierung, Plastizit t und epistemische Opazit t. Erst aus der Verkn pfung dieser Merkmale resultiert ein philosophisch neuartiges Bild, das wiederum zum Diskurs um das Verh ltnis von Wissenschaft und Technik beitr gt. (shrink)

Thought experiments and simulation experiments are compared and contrasted with each other. While the former rely on epistemic transparency as a working condition, in the latter complexity of model dynamics leads to epistemic opacity. The difference is elucidated by a discussion of the different kinds of iteration that are at work in both sorts of experiment.