"The Uncertain Science" argues that sociology has not freed itself from the influence of philosophy, and specifically from the search for certainty. This "foundationalism" which is characteristic of Western thought has influenced both the method adopted by sociologists, and their research practices. The authors criticize sociology for its formalism, arguing that this blunts the radicalism of its project. To regain the radical and critical edge implicit in sociology, it is necessary to adopt a comparative and historical approach which (...) interprets social science as part of societal learning. In the first part of the book the authors trace formalism to central positions in Western philosophy and examine its impact on historiography, evolutionary social thought and positivist sociology. In the second part they examine the tensions between formalism and social theory in the work of Levi Strauss and Habermas. In part three they compare modernization theory to more recent descussions of "modernity" and "postmodernity", and show the elements of continuity between these apparently contrary positions. This book should be of interest to undergraduates in sociology and philosophy. (shrink)

Scientific uncertainty puzzles many people. The puzzlement arises when scientists have more than one answer, and disagree among themselves. This book helps people find their way through this maze of scientific contradiction and uncertainty. By acquainting them with the ways that uncertainty arises in science, how scientists accommodate and make use of uncertainty, and how they reach conclusions in the face of uncertainty, the book enables readers to confidently evaluate uncertainty from their own perspectives, in terms of their own (...) experiences. (shrink)

In the late 1970s, the U.S. Congress was debating a number of different proposals to provide monetary compensation to residents of Utah and Nevada who had been exposed to radioactive fallout from government nuclear weapons testing in the 1950s. Yet scientists and government officials expressed concern that such a program would end up compensating many people for cancers that were not caused by the fallout. Thus, after much debate, Congress directed the National Institutes of Health to produce a set of (...) statistical tables—the radioepidemiologic tables—to target compensation awards to “deserving” individuals. Advocates of the tables, notably Senator Orrin Hatch, argued that reliance on scientific data would provide compensation decisions with predictability and evenhandedness. Yet in the end, the effort to employ the tables failed. The substantial scientific uncertainties in the tables and in their application to individual claims failed to deliver the authority they promised. Additionally, the goal of fairness and objectivity could not be convincingly met because of persistent controversy and mistrust surrounding the government’s role in the study of health effects of low‐level radiation. (shrink)

Reviews the book, The uncertain sciences by Bruce Mazlish . In this very wide-ranging book, Mazlish examines the achievements, failings, and possibilities of the human sciences—understood broadly to include history, anthropology, political science, psychology, sociology, economics and other related disciplines. 2012 APA, all rights reserved).

One of the world's premiere cancer researchers reveals an urgent philosophy on the little-known principles that govern medicine--and how understanding these principles can empower everyone.

What is science? How is scientific knowledge affected by the society that produces it? Does scientific knowledge directly correspond to reality? Can we draw a line between science and pseudo-science? Will it ever be possible for computers to undertake scientific investigation independently? Is there such a thing as feminist science? In this book the author addresses questions such as these using a technique of 'cognitive play', which creates and explores new links between the ideas and results (...) of contemporary history, philosophy, and sociology of science. New ideas and approaches are applied to a wide range of case studies, many of them from controversial and contested science. This book will be of interest to historians and sociologists of science, to anyone interested in science studies, and to educated general readers with an interest in the history, philosophy, and social context of science. (shrink)

Recent work in science and technological studies has provided a clearer understanding of the way in which science functions in society and the interconnectedness among different strands of science, policy, economy and environment. It is well acknowledged that a different way of thinking is required in order to address problems facing the global community, particularly in relation to issues of risk and uncertainty, which affect humanity as a whole. However, approaches to education in science tend to (...) perpetuate an outmoded way of thinking that is incommensurable with preparing individuals for participation and decision-making in an uncertain, complex world. Drawing on experiences of interdisciplinary dialogue and practice in a higher education context, this book illustrates how reformulating the agenda in science and technology can have a revolutionary impact on learning and teaching in the classroom at all levels. This exceptional study will interest scholars in Education, Science, Technology, and Society, and those looking to further deliberative democracy and civic participation in their students. (shrink)

While complexity science is gaining interest among educational theorists, its constructs do not speak to educational responsibility or related core issues in education of power and ethics. Yet certain themes of complexity, as taken up in educational theory, can help unsettle the more controlling and problematic discourses of educational responsibility such as the potential to limit learning and subjectivity or to prescribe social justice. The purpose of this article is to critically examine complexity science against notions of responsibility (...) in terms of implications for education. First, themes of complexity science prominent in contemporary educational writing are explained. Then dilemmas of responsibility in complexity are explored, such as what forms and meanings responsibility can have in a ‘complexified’ perspective of education, how care for others is mobilised, and how desire can be understood. Analyses of ethical action grounded in complexity science are then examined, as well as theories of the ethical subject and participatory responsibility that are congruent with certain tenets of a complexity ontology. Finally, the possibility of an educational vision of responsibility animated by complexity theories is considered, drawing from related writings of Bai, Biesta, Derrida, Levinas and Varela. (shrink)

Coping with uncertainty is a necessary part of ordinary life and is crucial to an understanding of how the mind works. For example, it is a vital element in developing artificial intelligence that will not be undermined by its own rigidities. There have been many approaches to the problem of uncertain inference, ranging from probability to inductive logic to nonmonotonic logic. Thisbook seeks to provide a clear exposition of these approaches within a unified framework. The principal market for the (...) book will be students and professionals in philosophy, computer science, and AI. Among the special features of the book are a chapter on evidential probability, which has not received a basic exposition before; chapters on nonmonotonic reasoning and theory replacement, matters rarely addressed in standard philosophical texts; and chapters on Mill's methods and statistical inference that cover material sorely lacking in the usual treatments of AI and computer science. (shrink)

Reasoning under uncertainty, that is, making judgements with only partial knowledge, is a major theme in artificial intelligence. Professor Paris provides here an introduction to the mathematical foundations of the subject. It is suited for readers with some knowledge of undergraduate mathematics but is otherwise self-contained, collecting together the key results on the subject, and formalising within a unified framework the main contemporary approaches and assumptions. The author has concentrated on giving clear mathematical formulations, analyses, justifications and consequences of the (...) main theories about uncertain reasoning, so the book can serve as a textbook for beginners or as a starting point for further basic research into the subject. It will be welcomed by graduate students and research workers in logic, philosophy, and computer science as a textbook for beginners, a starting point for further basic research into the subject, and not least, an account of how mathematics and artificial intelligence can complement and enrich each other. (shrink)

Human cognition requires coping with a complex and uncertain world. This suggests that dealing with uncertainty may be the central challenge for human reasoning. In Bayesian Rationality we argue that probability theory, the calculus of uncertainty, is the right framework in which to understand everyday reasoning. We also argue that probability theory explains behavior, even on experimental tasks that have been designed to probe people's logical reasoning abilities. Most commentators agree on the centrality of uncertainty; some suggest that there (...) is a residual role for logic in understanding reasoning; and others put forward alternative formalisms for uncertain reasoning, or raise specific technical, methodological, or empirical challenges. In responding to these points, we aim to clarify the scope and limits of probability and logic in cognitive science; explore the meaning of the explanation of cognition; and re-evaluate the empirical case for Bayesian rationality. (shrink)

People can be uncertain in their moral judgments. Philosophers have argued that such uncertainty can either refer to the underlying empirical facts (empirical uncertainty) or to the normative evaluation of these facts itself (normative uncertainty). Psychological investigations of this distinction, however, are rare. In this paper, we combined factor-analytical and experimental approaches to show that empirical and normative uncertainty describe two related but different psychological states. In Study 1, we asked N = 265 participants to describe a case of (...) moral uncertainty and to rate different aspects of their uncertainty about this case. Across this wide range of moral scenarios, our items loaded onto three reliable factors: lack of information, unclear consequences, and normative uncertainty. In Study 2, we confirmed this factor structure using predefined stimulus material. N = 402 participants each rated eight scenarios that systematically varied in their degree of uncertainty regarding the consequences of the described actions and in the value conflict that was inherent to them. The empirical uncertainty factors were mainly affected by the introduction of uncertainty regarding consequences, and the normative uncertainty factor was mainly affected by the introduction of value conflict. Our studies provide evidence that the distinction between empirical and normative uncertainty accurately describes a psychological reality. We discuss the relevance of our findings for research on moral judgments and decision-making, and folk metaethics. (shrink)

Composed of scientific and technical experts and lay members, thousands of research ethics committees—Institutional Review Boards in the United States—must identify and assess the potential risks to human research subjects, and balance those risks against the potential benefits of the research. IRBs handle risk and its uncertainty by adopting a version of the precautionary principle. To assess scientific merit, IRBs use a tacit ``sanguinity principle,'' which treats uncertainty as inevitable, even desirable, in scientific progress. In balancing human subjects risks and (...) scientific benefits, IRBs use uncertainty as a boundary-ordering device that allows the mediation of the science and ethics aspects of their decisions. One effect is the entangling of methodological and ethical review. Some have suggested these should be more clearly separated, but decisions by research ethics committees depend in part on the negotiating space created by incommensurable approaches to uncertainty. (shrink)

Probabilistic models have started to replace classical logic as the standard reference paradigm in human deductive reasoning. Mental probability logic emphasizes general principles where human reasoning deviates from classical logic, but agrees with a probabilistic approach (like nonmonotonicity or the conditional event interpretation of conditionals). -/- This contribution consists of two parts. In the first part we discuss general features of reasoning systems including consequence relations, how uncertainty may enter argument forms, probability intervals, and probabilistic informativeness. These concepts are of (...) central importance for the psychological task analysis. In the second part we report new experimental data on the paradoxes of the material conditional, the probabilistic modus ponens, the complement task, and data on the probabilistic truth table task. The results of the experiments provide evidence for the hypothesis that people represent indicative conditionals by conditional probability assertions. (shrink)

It is often said that clinical research and the practice of medicine are fraught with uncertainties. But what do we mean by uncertainty? Where does uncertainty come from? How do we measure uncertainty? Is there a single theory of uncertainty that applies across all scientific domains, including the science and practice of medicine? To answer these questions, we first review the existing theories of uncertainties. We then attempt to bring the enormous literature to bear from other disciplines to address (...) the issue of uncertainty in clinical research and medical practice. Our main and overarching goal is to review and classify uncertainties in clinical medicine. (shrink)

Alors que le temps présent paraît marqué par une incertitude forte, voire croissante, comment (re)trouver des prises sur ce qui est en devenir et qui pourrait composer le futur? Cette contribution propose de montrer que la science-fiction offre un matériau qui a aussi une pertinence et qui peut être travaillé pour être incorporé dans un processus de production de connaissance. Les textes de science-fiction peuvent en effet être pris à la fois comme un réservoir d’expériences de pensée et (...) comme des formes de problématisations (au sens de Michel Foucault). En s’appuyant sur un corpus de textes francophones et anglophones orientés vers un futur plus ou moins proche et généralement considérés comme porteurs de positions engagées (fiction spéculative, anticipation sociale, cyberpunk et postcyberpunk, biopunk, etc.), une première base de démonstration précisera d’abord l’appréhension réflexive qui peut être faite de la science-fiction au-delà de la forme culturelle et de son expression littéraire. Une seconde avancera ensuite une série de propositions méthodologiques pour saisir l’objet et pouvoir traduire cet imaginaire en prises expérimentales sur le futur. (shrink)

The certainties which once underpinned Christian belief have crumbled in a world where science sets the standard for what is true. A rational case for belief must therefore be constructed out of uncertainties. Probability theory provides the tools for measuring and combining uncertainties and is thus the key to progress. This book examines four much debated topics where the logic of uncertain inference can be brought to bear. These are: miracles, the paranormal, God's existence, and the Bible. Given (...) the great diversity of evidence, it is not surprising that opposite conclusions have been drawn by supposedly rational people. An assessment of the state of argument from a probabilistic perspective is overdue. In this book Professor Bartholomew examines and refutes some of the more extravagent claims, evaluates the weight of some of the quantitive evidence, and provides an answer to the fundamental question: is it rational to be a Christian? (shrink)

We should now be able to come to some general conclusions about the main lines of Cuvier's development as a naturalist after his departure from Normandy. We have seen that Cuvier arrived in Paris aware of the importance of physiology in classification, yet without a fully worked out idea of how such an approach could organize a whole natural order. He was freshly receptive to the ideas of the new physiology developed by Xavier Bichat.Cuvier arrived in a Paris also torn (...) by many overlapping debates on the nature of classification, and in particular that between the natural and artificial systems. The very validity of the enterprise of classification was questioned in many quarters. Cuvier's achievement on his entry into the Parisian world of science was not simply to establish himself as a highly competent anatomist: far more important, he also began to use ideas from many different specialties to change completely the notion of what was involved in natural history.124 At the same time that he himself swung away from the guiding image of the field naturalist as the ideal of the specialty, he took ideas from the new physiology to answer questions about the order of the animal world, and from comparative anatomy to resurrect extinct creation — and to come to conclusions from that creation about the history of the forms of life and the manner of their succession. He showed himself able to alter the relationships between natural history and many other fields of study in a way that implied, rightly or wrongly, his own complete mastery over such a movement. Partly he was able to do this because the ideas he borrowed were not themselves logically articulated and thus could be easily adapted and refocused for many different specific purposes. The value of the heuristic possibilities inherent in the idea of life, for example, far outweighed its inability to generate full systems of classification. Cuvier also consistently refused to consider in science matters relating to the first causes of events. Freed from the consideration of first-order phenomena, he was able to use second-order explanations across a far wider field of applicability. Personal doubts about the validity of a theology that had used science in order to bolster its own claims were combined here with the strong influence of the Kantian critique of the limits of human reason.125Cuvier's characteristic mode of procedure was that of intellectual appropriation and a bold capacity for altering the relationships between different fields of knowledge, rather than, with the exception of taxonomy, the technique of expanding their subject matter. His claims to originality came, first, from this reappropriation and reorientation and, second, from the sheer scope of his work, which aimed at nothing less than the cataloging and classification of all animate objects.126 They rested also on his acute use of his assertion of a certain relationship with the past of his subject. Very often he would present this history in such a way as to obscure his own intellectual genealogy, and often too he would give differing accounts of the priority of use of an idea in order to distract attention from the questionable exactitude of his own claims to originality. Cuvier came to Paris at precisely the time when society and institutions were most profitably malleable for a newcomer; it was also a time when many scientific disciplines had reached a stage advanced in terms of their factual content, yet relatively inadequate in conceptual organization. They were ripe for takeover by large-scale organizing ideas such as the animal economy and the subordination of characteristics. Paleontology is a particularly good example of a specialty in this particular form of underdevelopment in 1795.Cuvier paid a high price for his initial success. His electic applications of large-scale organizing ideas tended to mean that little of his own work had complete coherence at all levels. Ideas, as we have seen, that proved capable of providing a complete reform of the larger groups of the animal kingdom were incapable of producing its detailed working-out in the taxonomy of smaller groups, which had to be supplied from observed analogical correlations. Further, his physiological approach to classification involved the breakdown of strict correspondence between organs and functions, which left the way open for workers such as Geoffroy St. Hilaire gradually to tilt the balance away from the study of the correlations of hierarchies of functions, and toward morphology as the basis of the order of nature. Cuvier's brilliant appropriations from physiology from the beginning, therefore, contained the seeds of conflict with Geoffroy.Cuvier's eclectic approach made it very nearly impossible for him to present a clear idea of the ways in which the life sciences could be said to be lawful. In spite of his efforts to assimilate them to the position of the physical sciences in this respect, he was forced in the end to accord only an ambiguous status as “laws” to observational correlations. From this area of failure came much of the attempt to give his own two laws — the correlation of parts and the subordination of characteristics — predictive qualities, particularly in relation to paleontological research.It is not surprising that Cuvier's title as the “legislator” of natural history should represent more a claim than a reality. How, then, was he able to emerge as the leading French naturalist of his day? First of all must be adduced the sheer scale of his undertakings. Then comes his expertise as a practical anatomist, and the range of different topics toward which he turned his interest. His collaborators cannot be given credit for his output nor, as we have seen, for slavish adherence to his ideas. Cuvier was able to successfully claim to have dominated the underdeveloped specialties, such as paleontology, and turned them into a major heuristic input into both geology and comparative anatomy; but in other fields, such as physiology, he appropriated concepts and encouraged research but made little impact on the field himself. His attempts in 1812 to head off, or neutralize and absorb the growth of morphological studies landed him in a dangerously rigid position, which despite his encouragement of the new physiological research under the Restoration made further elaboration of his own conceptual underpinnings almost impossible.Cuvier's authority in the scientific world would in any case have been great because of his substantive achievement in taxonomy, but the rest of his work had enough ambiguities and dislocations for it to need the support of his political and social power. Cuvier's detractors seized on a vital fragment of the truth when they accused him of finding the political dimension all-important: it obscured the disjunctions in his theories and at the same time gave him the authority to make new claims for the status of the observational sciences - and for their relations of power with their surrounding specialties. Cuvier's science both thrived on and was halted by the power games of intellectual appropriation, manipulation of the past to confirm the present, and continual claims for hegemony. (shrink)

ArgumentScientific uncertainty is fundamental to the management of contemporary global risks. In 2009, the World Health Organization declared the start of the H1N1 Influenza Pandemic. This declaration signified the risk posed by the spread of the H1N1 virus, and in turn precipitated a range of actions by global public health actors. This article analyzes the WHO's public representation of risk and examines the centrality of scientific uncertainty in the case of H1N1. It argues that the WHO's risk narrative reflected the (...) context of scientific uncertainty in which it was working. The WHO argued that it was attempting to remain faithful to the scientific evidence, and the uncertain nature of the threat. However, as a result, the WHO's public risk narrative was neither consistent nor socially robust, leading to the eventual contestation of the WHO's position by other global public health actors, most notably the Council of Europe. This illustrates both the significance of scientific uncertainty in the investigation of risk, and the difficulty for risk managing institutions in effectively acting in the face of this uncertainty. (shrink)

The discovery of induced pluripotent stem (iPS) cells in 2006 was heralded as a major breakthrough in stem cell research. Since then, progress in iPS cell technology has paved the way towards clinical application, particularly cell replacement therapy, which has refueled debate on the ethics of stem cell research. However, much of the discourse has focused on questions of moral status and potentiality, overlooking the ethical issues which are introduced by the clinical testing of iPS cell replacement therapy. First-in-human trials, (...) in particular, raise a number of ethical concerns including informed consent, subject recruitment and harm minimisation as well as the inherent uncertainty and risks which are involved in testing medical procedures on humans for the first time. These issues, while a feature of any human research, become more complex in the case of iPS cell therapy, given the seriousness of the potential risks, the unreliability of available animal models, the vulnerability of the target patient group, and the high stakes of such an intensely public area of science. Our paper will present a detailed case study of iPS cell replacement therapy for Parkinson's disease to highlight these broader ethical and epistemological concerns. If we accept that iPS cell technology is fraught with challenges which go far beyond merely refuting the potentiality of the stem cell line, we conclude that iPS cell research should not replace, but proceed alongside embryonic and adult somatic stem cell research to promote cross-fertilisation of knowledge and better clinical outcomes. (shrink)

The Evolutionary Synthesis is often seen as a unification process in evolutionary biology, one which provided this research area with a solid common theoretical foundation. As such, neo-Darwinism is believed to constitute from this time onward a single, coherent, and unified movement offering research guidelines for investigations. While this may be true if evolutionary biology is solely understood as centred around evolutionary mechanisms, an entirely different picture emerges once other aspects of the founding neo-Darwinists’ views are taken into consideration, aspects (...) potentially relevant to the elaboration of an evolutionary worldview: the tree of life, the ontological distinctions of the main cosmic entities , the inherent properties of self-organizing matter, evolutionary ethics, and so on. Profound tensions and inconsistencies are immediately revealed in the neo-Darwinian movement once this broader perspective is adopted. This pluralism is such that it is possible to identify at least three distinct and quasi-incommensurable epistemological/metaphysical frameworks as providing a proper foundation for neo-Darwinism. The analysis of the views of Theodosius Dobzhansky, Bernhard Rensch, and Ernst Mayr will illustrate this untenable pluralism, one which requires us to conceive of the neo-Darwinian research agenda as being conducted in more than one research programme or research tradition at the same time. (shrink)

Imagine you are faced with a quantum mechanical device which will display either H or T when it is operated. You know that the single-case probability, or chance, of H is 0.8, and the chance of T is 0.2.

Conditionals are basic for human reasoning. In our paper, we present two experiments, which for the first time systematically compare how people reason about indicative conditionals (Experiment 1) and counterfactual conditionals (Experiment 2) in causal and non-causal task settings (N = 80). The main result of both experiments is that conditional probability is the dominant response pattern and thus a key ingredient for modeling causal, indicative, and counterfactual conditionals. In the paper, we will give an overview of the main experimental (...) results and discuss their relevance for understanding how people reason about conditionals. (shrink)

Oaksford & Chater (O&C) begin in the halfway Bayesian house of assuming that minor premises in conditional inferences are certain. We demonstrate that this assumption is a serious limitation. They additionally suggest that appealing to Jeffrey's rule could make their approach more general. We present evidence that this rule is not limited enough to account for actual probability judgements.

Review of M. Giaquinto, The Search for Certainty: A Philosophical Account of Foundations of Mathematics (Osford, 2002).

. This paper follows the journey of two small fluid units throughout the nineteenth century in Anglo-American medicine and pharmacy, explaining how the non-uniform “drop” survived while the standardized minim became obsolete. I emphasize two roles these units needed to fulfill: that of a physical measuring device, and that of a rhetorical communication device. First, I discuss the challenges unique to measuring small amounts of fluid, outlining how the modern medicine dropper developed out of an effort to resolve problems with (...) the “minimometer,” which measured minims. Second, I explain how drops, utilized in “the open drop method” of administering general anesthesia, effectively communicated a gradual process and epistemically valuable heuristic to the audience of practitioners, whose attention to individual medical outcomes was important for verifying the proper dosage. The standardized minim was never able to achieve success as the drop’s intended replacement; the non-uniform drop better served the relevant epistemic goals within the practical contexts for which these units were designed. The surprising historical trajectory of drops should cause us to question the common equivocation of “standardization” with “progress” in the history and philosophy of measurement. This study also exemplifies how examining non-standard measurement practices can be instructive for better understanding the role and function of standardization within epistemology of measurement. (shrink)

Bayesian accounts are currently popular in the field of inductive reasoning. This commentary briefly reviews the limitations of one such account, the Rational Model (Anderson 1991b), in explaining how inferences are made about objects whose category membership is uncertain. These shortcomings are symptomatic of what Jones & Love (J&L) refer to as Bayesian approaches.

Two important assumptions of behavioral momentum theory are contradicted by existing data. Resistance to change is not due simply to the Pavlovian contingency between a discriminative stimulus and the rate of reinforcement in its presence, because variations in the response-reinforcer contingency, independent of the stimulus-reinforcer contingency, produce differential resistance to change. Resistance to change is also not clearly related to measures of preference, in that several experiments show the two measures to dissociate.

Smith et al. present a model that they suggest may clarify aspects of the phylogenetic distribution of metacognition, based on observation of what they call uncertainty monitoring. Although they suggest that their model is supported by data collected using monkeys and dolphins, their interpretation that nonhuman animal behaviors parallel thought processes in humans may be unwarranted. The model presented by Smith et al. is inconsistent with current theories and empirical findings on the comparative aspects of metacognition. We present three oversights (...) of the model and extend our critique to include a brief discussion of animal self-awareness, as well as current neuropsychological perspectives on metacognitive processing in humans. (shrink)

Bayesian epistemology postulates a probabilistic analysis of many sorts of ordinary and scientific reasoning. Huber ([2005]) has provided a novel criticism of Bayesianism, whose core argument involves a challenging issue: confirmation by uncertain evidence. In this paper, we argue that under a properly defined Bayesian account of confirmation by uncertain evidence, Huber's criticism fails. By contrast, our discussion will highlight what we take as some new and appealing features of Bayesian confirmation theory. 1. Introduction2. Uncertain Evidence and (...) Bayesian Confirmation3. Bayesian Confirmation by Uncertain Evidence: Test Cases and Basic Principles. (shrink)

Between the fourth and the recent fifth IPCC report, science as well as policy making have made great advances in dealing with uncertainties in global climate models. However, the uncertainties public decision making has to deal with go well beyond what is currently addressed by policy makers and climatologists alike. It is shown in this paper that within an anthropocentric framework, a whole hierarchy of models from various scientific disciplines is needed for political decisions as regards climate change. Via (...) what is sometimes referred to as ‘uncertainty cascade’ in the technical literature, the uncertainties of various models accumulate in the input to political decision making. This paper aims to chart the uncertainties in the multi-disciplinary enterprise of current climate modeling in broad strokes. It is shown that the uncertainty cascade makes it impossible to quantify uncertainties in the form of probability estimates. Moreover the paper highlights how global climate models fail to provide probability estimates. A better treatment of the uncertainties of climate predictions on the political level would require an overhaul of the current IPCC practice that separates the various scientific fields in various working groups. (shrink)

(No abstract is available for this citation).

Information security governance has become an elusive goal and a murky concept. This paper problematizes both information security governance and the broader concept of governance. What does it mean to govern information security, or for that matter, anything? Why have information technologies proven difficult to govern? And what assurances can governance provide for the billions of people who rely on information technologies every day? Drawing together several distinct bodies of literature—including multiple strands of governance theory, actor–network theory, and scholarship on (...) sociotechnical regimes—this paper conceptualizes networked action on a spectrum from uncertain governance to governing uncertainty. I advance a twofold argument. First, I argue that networks can better govern uncertainty as they become more able not only to enroll actors in a collective agenda, but also to cut ties with those who seek to undermine that agenda. And second, I argue that the dominant conception of information security governance, which emphasizes governing uncertainty through risk management, in practice devolves to uncertain governance. This is largely because information technologies have evolved toward greater connectedness—and with it, greater vulnerability—creating a regime of insecurity. This evolution is illustrated using the history of the US government’s efforts to govern information security. (shrink)

It has recently been argued that a non-Bayesian probabilistic version of inference to the best explanation (IBE*) has a number of advantages over Bayesian conditionalization (Douven [2013]; Douven and Wenmackers [2017]). We investigate how IBE* could be generalized to uncertain evidential situations and formulate a novel updating rule IBE**. We then inspect how it performs in comparison to its Bayesian counterpart, Jeffrey conditionalization (JC), in a number of simulations where two agents, each updating by IBE** and JC, respectively, try (...) to detect the bias of a coin while they are only partially certain what side the coin landed on. We show that IBE** more often prescribes high probability to the actual bias than JC. We also show that this happens considerably faster, that IBE** passes higher thresholds for high probability, and that it in general leads to more accurate probability distributions than JC. (shrink)

An agent often has a number of hypotheses, and must choose among them based on observations, or outcomes of experiments. Each of these observations can be viewed as providing evidence for or against various hypotheses. All the attempts to formalize this intuition up to now have assumed that associated with each hypothesis h there is a likelihood function μ h , which is a probability measure that intuitively describes how likely each observation is, conditional on h being the correct hypothesis. (...) We consider an extension of this framework where there is uncertainty as to which of a number of likelihood functions is appropriate, and discuss how one formal approach to defining evidence, which views evidence as a function from priors to posteriors, can be generalized to accommodate this uncertainty. (shrink)