This study examines the concept of “description” and its theoretical foundations. The literature about it is surprisingly limited, and its usage is vague, sometimes even conflicting. Description should be considered in relation to other processes, such as representation, data capturing, and categorizing, which raises the question about what it means to describe something. Description is often used for any type of predication but may better be limited to predications based on observations. Research aims to establish criteria for making optimal descriptions; (...) however, the problems involved in describing something have seldom been addressed. Specific ideals are often followed without examine their fruitfulness. This study provides evidence that description cannot be a neutral, objective activity; rather, it is a theory-laden and interest-based activity. In information science, description occurs in processes such as document description, descriptive metadata assignment, and information resource description. In this field, description has equally been used in conflicting ways that mostly do not evince a recognition of the value- and theory-laden nature of descriptions. It is argued that descriptive activities in information science should always be based on consciously explicit considerations of the goals that descriptions are meant to serve. (shrink)

This paper analyses the relations between philosophy of information (PI), library and information science (LIS) and social epistemology (SE). In the first section, it is argued that there is a natural relation between philosophy and LIS but that SE cannot provide a satisfactory foundation for LIS. SE should rather be seen as sharing with LIS a common ground, represented by the study of information, to be investigated by a new discipline, PI. In the second section, the (...) nature of PI is outlined as the philosophical area that studies the conceptual nature of information, its dynamics and problems. In the third section, LIS is defined as a form of applied PI. The hypothesis supported is that PI should replace SE as the philosophical discipline that can best provide the conceptual foundation for LIS. In the conclusion, it is suggested that the 'identity' crisis undergone by LIS has been the natural outcome of a justified but precocious search for a philosophical counterpart that has emerged only recently: namely, PI. The development of LIS should not rely on some borrowed, pre-packaged theory. As applied PI, LIS can fruitfully contribute to the growth of basic theoretical research in PI itself and thus provide its own foundation. (shrink)

Expert knowledge regularly informs personal and civic-decision making. To decide which experts to trust, lay publics —including policymakers and experts from other domains—use different epistemic and non-epistemic cues. Epistemic cues such as honesty, like when experts are forthcoming about conflicts of interest, are a popular way of understanding how people evaluate and decide which experts to trust. However, many other epistemic cues, like the evidence supporting information from experts, are inaccessible to lay publics. Therefore, lay publics simultaneously use second-order (...) social cues in their environment to inform decisions to trust. These second-order social cues, or ‘social indicators of trust’, prevent lay publics from having to trust blindly. Social indicators of trust therefore inform lay publics’ epistemic vigilance, or constant low level-monitoring of testimony from experts. This special issue examines the nature, acquisition and application of social indicators of trust for scientific experts and institutions. It also raises questions about the types of trust asked of lay publics and challenges traditional normative assumptions about the relationship between science and lay publics through study of attitudes, values, and experiences. The issue descriptively re-examines the structure of institutions, their role and methods for ferrying information, as well as how social indicators operate in times of crisis. In this collection of works, we bridge history, science, philosophy of science, science and technology studies, science communication and social epistemology, to broaden the discourse on trust in experts and more accurately reflect the imperfect yet indispensable endeavour that trusting is. (shrink)

The main objective of this dissertation is to philosophically assess how the use of informational concepts in the field of classical thermostatistical physics has historically evolved from the late 1940s to the present day. I will first analyze in depth the main notions that form the conceptual basis on which 'informational physics' historically unfolded, encompassing (i) different entropy, probability and information notions, (ii) their multiple interpretative variations, and (iii) the formal, numerical and semantic-interpretative relationships among them. In the following, (...) I will assess the history of informational thermophysics during the second half of the twentieth century. Firstly, I analyse the intellectual factors that gave rise to this current in the late forties (i.e., popularization of Shannon's theory, interest in a naturalized epistemology of science, etc.), then study its consolidation in the Brillouinian and Jaynesian programs, and finally claim how Carnap (1977) and his disciples tried to criticize this tendency within the scientific community. Then, I evaluate how informational physics became a predominant intellectual current in the scientific community in the nineties, made possible by the convergence of Jaynesianism and Brillouinism in proposals such as that of Tribus and McIrvine (1971) or Bekenstein (1973) and the application of algorithmic information theory into the thermophysical domain. As a sign of its radicality at this historical stage, I explore the main proposals to include information as part of our physical reality, such as Wheeler’s (1990), Stonier’s (1990) or Landauer’s (1991), detailing the main philosophical arguments (e.g., Timpson, 2013; Lombardi et al. 2016a) against those inflationary attitudes towards information. Following this historical assessment, I systematically analyze whether the descriptive exploitation of informational concepts has historically contributed to providing us with knowledge of thermophysical reality via (i) explaining thermal processes such as equilibrium approximation, (ii) advantageously predicting thermal phenomena, or (iii) enabling understanding of thermal property such as thermodynamic entropy. I argue that these epistemic shortcomings would make it impossible to draw ontological conclusions in a justified way about the physical nature of information. In conclusion, I will argue that the historical exploitation of informational concepts has not contributed significantly to the epistemic progress of thermophysics. This would lead to characterize informational proposals as 'degenerate science' (à la Lakatos 1978a) regarding classical thermostatistical physics or as theoretically underdeveloped regarding the study of the cognitive dynamics of scientists in this physical domain. (shrink)

The theory of evolution of complex and comprising of human systems and algorithm for its constructing are the synthesis of evolutionary epistemology, philosophical anthropology and concrete scientific empirical basis in modern (transdisciplinary) science. «Trans-disciplinary» in the context is interpreted as a completely new epistemological situation, which is fraught with the initiation of a civilizational crisis. Philosophy and ideology of technogenic civilization is based on the possibility of unambiguous demarcation of public value and descriptive scientific discourses (1), and the object (...) and subject of the cognitive process (2). Both of these attributes are no longer valid. For mass, everyday consciousness and institutional philosophical tradition it is intuitively obvious that having the ability to control the evolutionary process, Homo sapiens came close to the borders of their own biological and cultural identity. The spontaneous coevolutionary process of interaction between the «subject» (rational living organisms) and the «object» (material world), is the teleological trend of the movement towards the complete rationalization of the World as It Is, its merger with the World of Due. The stratification of the global evolutionary process into selective and semantic (teleological) coevolutionary and therefore ontologically inseparable components follows. With the entry of anthropogenic civilization into the stage of the information society, firsty, the post-academic phase of the historical evolution of scientific rationality began, the attributes of which are the specific methodology of scientific knowledge, scientific ethos and ontology. Bioethics as a phenomenon of intellectual culture represents a natural philosophical core of modern post- academic (human-dimensional) science, in which the ethical neutrality of scientific theory principle is inapplicable, and elements of public-axiological and scientific-descriptive discourses are integrated into a single logic construction. As result, hermeneutics precedes epistemology not only methodologically, but also meaningfully, and natural philosophy is regaining the status of the backbone of the theory of evolution – in an explicit form. (shrink)

The formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences. Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain models are sufficient to generate emergent macrostructures of interest. The description of scientific practice implies additional epistemic conceptions of scientific knowledge. Three kinds of knowledge that account for a comprehensive description of the discipline were identified: formal, empirical and intentional knowledge. The use of formal (...) conceptions of computation for describing simulation is refuted; the roles of programming languages according to intentional accounts of computation are identified; and the roles of iconographic programming languages and aesthetic machines in simulation are characterized. The roles that simulation and intentional decision making may be able to play in a participative information society are also discussed. (shrink)

This Editorial summarizes the papers in a Frontiers in Communication Research Topic that looks at science journalism’s mediating role between the production of scientific knowledge and its public uptake. The four papers in the Research Topic consider science communication and journalism from the perspective of philosophy of science and epistemology. Framing the Research Topic is a conceptual analysis of the multiple aims of science communication and an assessment of empirical evidence to date regarding whether these aims (...) are being met. The other papers consider the practices of science journalism, the public reception of science information, and how the process of science is presented in three major mass media outlets. (shrink)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more (...) fact-oriented and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

Recent years have seen a surge in online collaboration between experts and amateurs on scientific research. In this article, we analyse the epistemological implications of these crowdsourced projects, with a focus on Zooniverse, the world’s largest citizen science web portal. We use quantitative methods to evaluate the platform’s success in producing large volumes of observation statements and high impact scientific discoveries relative to more conventional means of data processing. Through empirical evidence, Bayesian reasoning, and conceptual analysis, we show how (...) information and communication technologies enhance the reliability, scalability, and connectivity of crowdsourced e-research, giving online citizen science projects powerful epistemic advantages over more traditional modes of scientific investigation. These results highlight the essential role played by technologically mediated social interaction in contemporary knowledge production. We conclude by calling for an explicitly sociotechnical turn in the philosophy of science that combines insights from statistics and logic to analyse the latest developments in scientific research. (shrink)

In recent years, the growing academic field called “Data Science” has made many promises. On closer inspection, relatively few of these promises have come to fruition. A critique of Data Science from the phenomenological tradition can take many forms. This paper addresses the promise of “participation” in Data Science, taking inspiration from Paul Majkut’s 2000 work in Glimpse, “Empathy’s Impostor: Interactivity and Intersubjectivity,” and some insights from Heidegger’s "The Question Concerning Technology." The description of Data Science (...) provided in the scholarly literature includes “the study of the generalizable extraction of knowledge from data” (Dhar 2013, 64), “data stewardship and data sharing…access to data at higher volumes and more quickly, and the potential for replication and augmentation of existing research” (Hartter et al., 2013, 1), and “personal information, health status, daily activities and shopping preferences that are recorded and used to give us instant feedback and recommendations based on previous online behavior.” (Shin 2013) United States universities have begun to offer graduate programs in “data science”, anticipating the growth of this field for marketing, national security, and health industries. These universities include New York University, Columbia University, Stanford, Northwestern, and Syracuse. (shrink)

Many current problems surrounding science revolve around the complex epistemological framework that shapes a new vision of knowledge about reality. The traditional epistemological positions are characterized by the explanation of nature by means of concatenated facts; that is, as bricks attached to each other giving shape to the edifice of science. A conception of this nature showed that the idea of certainty was nothing more than a mere illusion, opening the way, on the contrary, to the idea of (...) the uncertainty of knowledge based on the descriptions of quantum physics, also a product of the non-reductionist conception of reality, thus criticizing the specular representation. This article addresses the main problems surrounding the critical conceptions that the emerging epistemology reveals about knowledge, pointing towards a much more complex vision of reality. (shrink)

There have been several calls from LIS researchers for practical or applied research not to ignore the epistemological assumptions underlying the systems and artifacts they design lest they showcase only the dominant theory at a given time. Others have also deplored the "epistemological promiscuity" or "eclecticism" of the field, its incessant borrowing of theories and models from elsewhere and the fact that the field has largely neglected the contributions that philosophy and epistemology could have made in its research. This problem (...) raises that of the boundaries of LIS and is all the more troublesome because boundaries between epistemological theories are fuzzy. Indeed, some epistemological theories share the same basic assumptions or are historically derived from one another. Gathering a wide array of acknowledged theorists in philosophy of science and epistemology, this panel aims to examine how research work in the LIS field can clearly articulate the epistemological assumptions underlying that research and under what constraints this can be achieved. The topic is of prime importance to Information studies as a whole and to ASIST as the scientific flag bearer of information scientists worldwide. (shrink)

We’ll sketch the debate on testimony in social epistemology by reference to the contemporary debate on reductionism/anti-reductionism, communitarian epistemology and inferentialism. Testimony is a fundamental source of knowledge we share and it is worthy to be considered in the ambit of a dialogical perspective, which requires a description of a formal structure which entails deontic statuses and deontic attitudes. In particular, we’ll argue for a social reformulation of the “space of reasons”, which establishes a fruitful relationship with the epistemological view (...) of Wilfrid Sellars. (shrink)

Marine ecosystems are under increasing pressure from human activity, yet successful management relies on knowledge. The evidence-based policy (EBP) approach has been promoted on the grounds that it provides greater transparency and consistency by relying on ‘high quality’ information. However, EBP also creates epistemic responsibilities. Decision-making where limited or no empirical evidence exists, such as is often the case in marine systems, creates epistemic obligations for new information acquisition. We argue that philosophical approaches can inform the science-policy (...) interface. Using marine biosecurity examples, we specifically examine the epistemic challenges in the acquisition and acceptance of evidence to inform policy, discussing epistemic due care and biases in consideration of evidence. (shrink)

The paper discusses this year’s Nobel Prize in physics for experiments of entanglement “establishing the violation of Bell inequalities and pioneering quantum information science” in a much wider, including philosophical context legitimizing by the authority of the Nobel Prize a new scientific area out of “classical” quantum mechanics relevant to Pauli’s “particle” paradigm of energy conservation and thus to the Standard model obeying it. One justifies the eventual future theory of quantum gravitation as belonging to the newly established (...) quantum information science. Entanglement, involving non-Hermitian operators for its rigorous description, non-unitarity as well as nonlocal and superluminal physical signals “spookily” (by Einstein’s flowery epithet) synchronizing and transferring some nonzero action at a distance, can be considered to be quantum gravity so that its local counterpart to be Einstein’s gravitation according to general relativity therefore pioneering an alternative pathway to quantum gravitation different from the “secondary quantization” of the Standard model. So, the experiments of entanglement once they have been awarded by the Nobel Prize launch particularly the relevant theory of quantum gravitation grounded on “quantum information science” thus granted to be nonclassical quantum mechanics in the shared framework of the generalized quantum mechanics obeying rather quantum-information conservation than only energy conservation. The concept of “dark phase” of the universe naturally linked to the very well confirmed “dark matter” and “dark energy” and opposed to its “light phase” inherent to classical quantum mechanics and the Standard model obeys quantum-information conservation, after which reversible causality or the mutual transformation of energy and information are valid. The mythical Big Bang after which energy conservation holds universally is to be replaced by an omnipresent and omnitemporal medium of decoherence of the dark and nonlocal phase into the light and local phase. The former is only an integral image of the latter and borrowed in fact rather from religion than from science. Physical, methodological and proper philosophical conclusions follow from that paradigm shift heralded by this year’s Nobel Prize in physics. For example, the scientific theory of thinking should originate from the dark phase of the universe, as well: probably only approximately modeled by neural networks physically belonging to the light phase thoroughly. A few crucial philosophical sequences follow from the break of Pauli’s paradigm: (1) the establishment of the “dark” phase of the universe as opposed to its “light” phase, only to which the Cartesian dichotomy of “body” and “mind” is valid; (2) quantum information conservation as relevant to the dark phase, furthermore generalizing energy conservation as to its light phase, productively allowing for physical entities to appear “ex nihilo”, i.e., from the dark phase, in which energy and time are yet inseparable from each other; (3) reversible causality as inherent to the dark phase; (4) the interpretation of gravitation only mathematically: as an interpretation of the incompleteness of finiteness to infinity, for example, following the Gödel dichotomy (“either contradiction or incompleteness”) about the relation of arithmetic to set theory; (5) the restriction of the concept of hierarchy only to the light phase; (6) the commensurability of both physical extremes of a quantum and the universe as a whole in the dark phase obeying quantum information conservation and akin to Nicholas of Cusa’s philosophical and theological worldview. (shrink)

This paper challenges the first Gettier counterexample to the tripartite account of knowledge. Noting that 'the man who will get the job' is a description and invoking Donnellan's distinction between their 'referential' and 'attributive' uses, I argue that Smith does not actually believe that the man who will get the job has ten coins in his pocket. Smith's ignorance about who will get the job shows that the belief cannot be understood referentially, his ignorance of the coins in his pocket (...) shows that it cannot be understood attributively. An explanation for why Smith appeared to have justified true belief is given by distinguishing between 'belief' and 'belief in truth'. Smith believes the sentence 'the man who will get the job has ten coins in his pocket' to be true (he mistakenly believes that Jones will get the job, of whom he knows that he has ten coins in his pocket) (hence his 'belief'), the sentence is true (hence 'truth'), and he has sufficient reason to assent to it (hence his 'justification'). But he does not believe the proposition expressed. Hence he does not know it either. (shrink)

This article addresses an open problem in the area of cognitive systems and architectures: namely the problem of handling (in terms of processing and reasoning capabilities) complex knowledge structures that can be at least plausibly comparable, both in terms of size and of typology of the encoded information, to the knowledge that humans process daily for executing everyday activities. Handling a huge amount of knowledge, and selectively retrieve it according to the needs emerging in different situational scenarios, is an (...) important aspect of human intelligence. For this task, in fact, humans adopt a wide range of heuristics (Gigerenzer & Todd) due to their “bounded rationality” (Simon, 1957). In this perspective, one of the requirements that should be considered for the design, the realization and the evaluation of intelligent cognitively-inspired systems should be rep- resented by their ability of heuristically identify and retrieve, from the general knowledge stored in their artificial Long Term Memory (LTM), that one which is synthetically and contextually relevant. This requirement, however, is often neglected. Currently, artificial cognitive systems and architectures are not able, de facto, to deal with complex knowledge structures that can be even slightly comparable to the knowledge heuris- tically managed by humans. In this paper I will argue that this is not only a technological problem but also an epistemological one and I will briefly sketch a proposal for a possible solution. (shrink)

Philosophers have long tried to understand scientific change in terms of a dynamics of revision within ‘theoretical frameworks,’ ‘disciplinary matrices,’ ‘scientific paradigms’ or ‘conceptual schemes.’ No-one, however, has made clear precisely how one might model such a conceptual scheme, nor what form change dynamics within such a structure could be expected to take. In this paper we take some first steps in applying network theory to the issue, modeling conceptual schemes as simple networks and the dynamics of change as cascades (...) on those networks. The results allow a new understanding of two traditional approaches—Popper and Kuhn—as well as introducing the intriguing prospect of viewing scientific change using the metaphor of selforganizing criticality. (shrink)

The first aim of this paper is to elucidate Russell’s construction of spatial points, which is to be <br>considered as a paradigmatic case of the "logical constructions" that played a central role in his epistemology and theory of science. Comparing it with parallel endeavours carried out by Carnap and Stone it is argued that Russell’s construction is best understood as a structural representation. It is shown that Russell’s and Carnap’s representational constructions may be considered as incomplete and sketchy harbingers (...) of Stone’s representation theorems. The representational program inaugurated by Stone’s theorems was one of the success stories of 20th century’s mathematics. This suggests that representational constructions à la Stone could also be important for epistemology and philosophy of science. More specifically it is argued that the issues proposed by Russellian definite descriptions, logical constructions, and structural representations still have a place on the agenda of contemporary epistemology and philosophy of science. Finally, the representational interpretation of Russell’s logical constructivism is used to shed some new light on the recently vigorously discussed topic of his structural realism. (shrink)

This paper reviews current debates in social epistemology about the relations ‎between ‎knowledge ‎and consensus. These relations are philosophically interesting on their ‎own, but ‎also have ‎practical consequences, as consensus takes an increasingly significant ‎role in ‎informing public ‎decision making. The paper addresses the following questions. ‎When is a ‎consensus attributable to an epistemic community? Under what conditions may ‎we ‎legitimately infer that a consensual view is knowledge-based or otherwise ‎epistemically ‎justified? Should consensus be the aim of scientific inquiry, and (...) if so, what ‎kind of ‎consensus? How should dissent be handled? It is argued that a legitimate inference ‎that a ‎theory is correct from the fact that there is a scientific consensus on it requires taking ‎into ‎consideration both cognitive properties of the theory as well as social properties of ‎the ‎consensus. The last section of the paper reviews computational models of ‎consensus ‎formation.‎. (shrink)

For two reasons, physics occupies a preeminent position among the sciences. On the one hand, due to its recognized position as a fundamental science, and on the other hand, due to the characteristic of its obvious certainty of knowledge. For both reasons it is regarded as the paradigm of scientificity par excellence. With its focus on the issue of epistemic certainty, philosophy of science follows in the footsteps of classical epistemology, and this is also the basis of its (...) 'judicial' pretension vis-à-vis physics. Whereas physics is in a strong competitive relationship to philosophy and epistemology with respect to its position as a fundamental science - even on the subject of cognition, as the pretension of 'reductionism' shows. It is the thematic focus on epistemic certainty itself, however, that becomes the root of a profound epistemological misunderstanding of physics. The reason for this is twofold: first, the idea of epistemic certainty as a criterion of 'demarcation' between physics and metaphysics obscures the view of the much deeper heuristic differences between the two kinds of knowledge. The second, related, reason is that epistemology does not ask the question of the reason for the epistemic certainty of physics; instead, it sets itself the task of 'legitimating' physical knowledge, and this, crucially, with reference to the interpretation of the process of cognition. Thus, as a matter of course, all epistemological assumptions about this process – including the common descriptive understanding of knowledge and its ontological premises – flow into the interpretation of physics as a science. Consequently, this undertaking is not only doubtful from the ground up, because it presupposes for its meaningfulness nothing less than certainty of knowledge concerning (the interpretation of) the process of knowledge, thereby relying on mere convictions; moreover, by projecting the descriptive, 'metaphysical' concept of knowledge onto physics, it leads to unsolvable epistemological problems and corresponding resignative conclusions concerning the claim of knowledge of physics. In other words, epistemology itself builds, due to its basic assumptions, a major obstacle for an adequate understanding of physics. Physics' cross-object, deconstructive approach to knowledge implies a completely different, non-descriptive understanding of its concepts, with consequences that extend far beyond itself due to its status as a basic science. (shrink)

In recent years, “Information Ethics” (IE) has come to mean different things to different researchers working in a variety of disciplines, including computer ethics, business ethics, medical ethics, computer science, the philosophy of information, social epistemology and library and information science. Using an ontocentric approach, this paper seeks to define the parameters of IE and thereby increase our understanding of the moral challenges associated with Information Communication Technologies.

Academic social networks and social media have revolutionised the way individuals gather information and express themselves, particularly in academia, science, and research. Through the lens of academics, this study aims to investigate the epistemological and psychosocial aspects of these knowledge sources. The epistemological attitude model presented a framework to delve into and reflect upon the existence of knowledge sources, comprising subjective, interactional, and knowledge dimensions. One hundred and twenty-six university academics participated in this study, including lecturers and researchers (...) from different higher education institutions in Latvia. The study employed two methods: the Epistemological Attitudes towards Sources of Knowledge Questionnaire and the Epistemological Attitudes towards Sources of Knowledge Semantic Questionnaire. The data analysis involved several procedures, including exploratory and confirmatory factor analysis, correlation analysis, and test statistics. By implementing these methods, the study gained valuable insights into the sources of knowledge, examining them from two perspectives. The first perspective brought attention to the differences in academics’ appraisals by discussing their understanding, approach, use, and valuations of these sources. By scrutinising the constructs of meanings, the second perspective sheds light on the anticipated knowledge which is deemed ideal, the concrete knowledge that is both social and objective, and the subjectively valuable nature of academic social networks and social media. The findings underscore the specialised knowledge and qualities that academics rely on for producing knowledge. In terms of epistemology, methodology, social science, and education, the study holds theoretical and practical implications, especially in comprehending knowledge and its sources. (shrink)

In this paper we discuss the new Tweety puzzle. The original Tweety puzzle was addressed by approaches in non-monotonic logic, which aim to adequately represent the Tweety case, namely that Tweety is a penguin and, thus, an exceptional bird, which cannot fly, although in general birds can fly. The new Tweety puzzle is intended as a challenge for probabilistic theories of epistemic states. In the first part of the paper we argue against monistic Bayesians, who assume that epistemic states can (...) at any given time be adequately described by a single subjective probability function. We show that monistic Bayesians cannot provide an adequate solution to the new Tweety puzzle, because this requires one to refer to a frequency-based probability function. We conclude that monistic Bayesianism cannot be a fully adequate theory of epistemic states. In the second part we describe an empirical study, which provides support for the thesis that monistic Bayesianism is also inadequate as a descriptive theory of cognitive states. In the final part of the paper we criticize Bayesian approaches in cognitive science, insofar as their monistic tendency cannot adequately address the new Tweety puzzle. We, further, argue against monistic Bayesianism in cognitive science by means of a case study. In this case study we show that Oaksford and Chater’s (2007, 2008) model of conditional inference—contrary to the authors’ theoretical position—has to refer also to a frequency-based probability function. (shrink)

We show how an epistemology informed by cognitive science promises to shed light on an ancient problem in the philosophy of mathematics: the problem of exactness. The problem of exactness arises because geometrical knowledge is thought to concern perfect geometrical forms, whereas the embodiment of such forms in the natural world may be imperfect. There thus arises an apparent mismatch between mathematical concepts and physical reality. We propose that the problem can be solved by emphasizing the ways in which (...) the brain can transform and organize its perceptual intake. It is not necessary for a geometrical form to be perfectly instantiated in order for perception of such a form to be the basis of a geometrical concept. (shrink)

A principle, according to which any scientific theory can be mathematized, is investigated. Social science, liberal arts, history, and philosophy are meant first of all. That kind of theory is presupposed to be a consistent text, which can be exhaustedly represented by a certain mathematical structure constructively. In thus used, the term “theory” includes all hypotheses as yet unconfirmed as already rejected. The investigation of the sketch of a possible proof of the principle demonstrates that it should be accepted (...) rather a metamathematical axiom about the relation of mathematics and reality. The main statement is formulated as follows: Any scientific theory admits isomorphism to some mathematical structure in a way constructive. Its investigation needs philosophical means. Husserl’s phenomenology is what is used, and then the conception of “bracketing reality” is modelled to generalize Peano arithmetic in its relation to set theory in the foundation of mathematics. The obtained model is equivalent to the generalization of Peano arithmetic by means of replacing the axiom of induction with that of transfinite induction. The sketch of the proof is organized in five steps: a generalization of epoché; involving transfinite induction in the transition between Peano arithmetic and set theory; discussing the finiteness of Peano arithmetic; applying transfinite induction to Peano arithmetic; discussing an arithmetical model of reality. Accepting or rejecting the principle, two kinds of mathematics appear differing from each other by its relation to reality. Accepting the principle, mathematics has to include reality within itself in a kind of Pythagoreanism. These two kinds are called in paper correspondingly Hilbert mathematics and Gödel mathematics. The sketch of the proof of the principle demonstrates that the generalization of Peano arithmetic as above can be interpreted as a model of Hilbert mathematics into Gödel mathematics therefore showing that the former is not less consistent than the latter, and the principle is an independent axiom. The present paper follows a pathway grounded on Husserl’s phenomenology and “bracketing reality” to achieve the generalized arithmetic necessary for the principle to be founded in alternative ontology, in which there is no reality external to mathematics: reality is included within mathematics. That latter mathematics is able to self-found itself and can be called Hilbert mathematics in honour of Hilbert’s program for self-founding mathematics on the base of arithmetic. The principle of universal mathematizability is consistent to Hilbert mathematics, but not to Gödel mathematics. Consequently, its validity or rejection would resolve the problem which mathematics refers to our being; and vice versa: the choice between them for different reasons would confirm or refuse the principle as to the being. An information interpretation of Hilbert mathematics is involved. It is a kind of ontology of information. The Schrödinger equation in quantum mechanics is involved to illustrate that ontology. Thus the problem which of the two mathematics is more relevant to our being is discussed again in a new way A few directions for future work can be: a rigorous formal proof of the principle as an independent axiom; the further development of information ontology consistent to both kinds of mathematics, but much more natural for Hilbert mathematics; the development of the information interpretation of quantum mechanics as a mathematical one for information ontology and thus Hilbert mathematics; the description of consciousness in terms of information ontology. (shrink)

There remains no consensus among social scientists as to how to measure and understand forms of information deprivation such as misinformation. Machine learning and statistical analyses of information deprivation typically contain problematic operationalizations which are too often biased towards epistemic elites' conceptions that can undermine their empirical adequacy. A mature science of information deprivation should include considerable citizen involvement that is sensitive to the value-ladenness of information quality and that doing so may improve the predictive (...) and explanatory power of extant models. (shrink)

Software application ontologies have the potential to become the keystone in state-of-the-art information management techniques. It is expected that these ontologies will support the sort of reasoning power required to navigate large and complex terminologies correctly and efficiently. Yet, there is one problem in particular that continues to stand in our way. As these terminological structures increase in size and complexity, and the drive to integrate them inevitably swells, it is clear that the level of consistency required for such (...) navigation will become correspondingly difficult to maintain. While descriptive semantic representations are certainly a necessary component to any adequate ontology-based system, so long as ontology engineers rely solely on semantic information, without a sound ontological theory informing their modeling decisions, this goal will surely remain out of reach. In this paper we describe how Language and Computing nv (L&C), along with The Institute for Formal Ontology and Medical Information Sciences (IFOMIS), are working towards developing and implementing just such a theory, combining the open software architecture of L&C’s LinkSuiteTM with the philosophical rigor of IFOMIS’s Basic Formal Ontology. In this way we aim to move beyond the more or less simple controlled vocabularies that have dominated the industry to date. (shrink)

In this paper, I argue that Constructive Empiricism (CE) is ambiguous between two interpretations: CE as a normative epistemology of science and CE as a descriptive philosophy of science. When they present CE, constructive empiricists write as if CE is supposed to be more than a normative epistemology of science and that it is meant to be responsible to actual scientific practices. However, when they respond to objections, constructive empiricists fall back on a strictly normative interpretation of (...) CE. This ambiguity seems to make CE immune to objections in a rather ad hoc fashion. (shrink)

The history of the relationship between Christian theology and the natural sciences has been conditioned by the initial decision of the masters of the "first scientific revolution" to disregard any necessary explanatory premiss to account for the constituting organization and the framing of naturally occurring entities. Not paying any attention to hierarchical control, they ended-up disseminating a vision and understanding in which it was no longer possible for a theology of nature to send questions in the direction of the experimental (...) sciences, as was done in the past between theology and many philosophically-based thought-systems. Presenting the history of some hinge-periods in the development of the Western-world sciences, this book first sets out to consider the conceptual revolution which has, in the 20th Century, related consciousness, physical laws and levels of organization, in order to show that a new chance existed then for theology. This discourse was invited to revise its language to open it up to the quest for meaning which we find on the periphery of the project of the experimental sciences. The Century-old reflection on the foundations of probability had prepared the ground for the introduction of the concept of information, at first linked to an effort aimed at maximizing the efficiency of electromagnetic communications. Taking the full measure of the questions that information theory poses to the biological sciences, this work attempts to identify the areas of convergence setting the stage for general systems theory, while it also tries to identify the insufficiencies of this recent vision and to highlight the questions left unanswered. Re-reading some of the traditional proofs of God's existence from the order of the world, relying on some pioneering insights of Ludwig von Bertalanffy and Norbert Wiener, the author brings those proofs and insights in contact with the fascinating initial project of cybernetics and the elements of a "mythical" nature which, from its inception, it could never entirely eliminate. This book ends with the confrontation between the conceptually most extended regulation factors in the history of Western thought. It articulates the poetic utopia concerned with an immediate grasp of the world in its "deictic" character with the concurrent one aimed at the domination over matter and energy expressed by technology's driving rational utopia. (shrink)

Although Wilhelm Dilthey and Franz Brentano apparently were pursuing roughly the same objective—to offer a description of our mental functions and of their relations to objects—and both called their respective research programs ‘descriptive psychology’, they seem to have used the term to refer to two different methods of psychological research. In this article, I compare analyses of these differences. Against the reading of Orth but also against a possible application of recent relativist accounts of the epistemology of peer disagreement to (...) this case, I argue that their apparent shared objective is not enough to support an understanding of their views as two alternatives within a given historical or scientific context, or as a mutual peer disagreement. I show that the impression of a shared objective can be explained away as stemming from the influence of their teacher Adolf Trendelenburg, and I stress that the case of introspection strongly suggests that an account in terms of peer disagreement is not plausible. Finally, I conclude that the opposition between two traditions, Austrian philosophy and historicism, might be better suited to account for the dispute and its apparent common historical context. (shrink)

Abstract: The article presents and critically discusses Walton's (and Reed's and Macagno's) argument scheme approach to a theory of good argumentation. In particular, four characteristics of Walton's approach are presented: 1. It presents normative requirements for argumentation in the form of argument schemes, i.e. relatively concrete type descriptions. 2. These schemata are enthymematic, i.e. they omit some of the premises required by other approaches. 3. The actual argument schemes are usually supplemented by critical questions. 4. The method is inductive, bottom-up, (...) gaining the normative schemata by abstraction from empirically collected groups of similar arguments. These characteristics, among others, are then discussed on the basis of four adequacy conditions: AC1: effectiveness in achieving the epistemic goal of obtaining and communicating justified acceptable opinions; AC2: completeness in capturing the good argument types; AC3: efficiency in achieving the goals; AC4: justification of the argument schemes. The discussion then reveals a number of weaknesses in Walton's argument schemes; among other things, they are neither effective (in the defined sense) nor truly justified. Contributing factors to these problems include the schema approach, i.e. not looking at the form of arguments, and the lack of epistemological foundations in the development of good types of arguments. However, the critical analyses reveal a better alternative: an epistemological approach based on epistemological principles. The article concludes with a detailed analysis of the scheme Practical Inference, which confirms the general criticism in detail. (shrink)

We review some of the major accounts in the current epistemology of modality and identify some shared issues that plague all of them. In order to provide insight into the nature of modal statements in science, philosophy, and beyond, a satisfactory epistemology of modality would need to be suitably applicable to practical and theoretical contexts by limited beings. However, many epistemologies of modality seem to work only when we have access to the kind of knowledge that is at least (...) currently beyond our reach. Or, in the extreme case, it is argued that even if we knew all the relevant information about the respective domain – or even the entire state of the world – there would still remain a special class of modal truths that would be left unaccounted for. Neither picture bodes well for practical applicability, nor for the philosophical justification of these epistemologies. This is especially the case as we hold that one of the main motivations for modal inquiry typically arises in cases of imperfect information and limited cognitive resources. We close by providing a partial remedy to the situation by suggesting an overall framework of relative modality (RM) that can be used to both unify some existing modal epistemologies and, at the same time, make them more metaphysically modest. (shrink)

The demarcation of pseudoscience has been one of the most important philosophical tasks since the 1960s. During the 1980s, an atmosphere of defeatism started to spread among philosophers of science, some of them claimed the failure of the demarcation project. I defend that the more auspicious approach to the problem might be through the intellectual character of epistemic agents, i.e., from the point of view of vice epistemology. Unfortunately, common lists of undesirable character features are usually based on a (...) priori reasoning, and therefore might be considered artificial or too vague. When we base our position on contemporary behavioural sciences, we can see that the epistemic character of believers in pseudoscience is for the most part determined by two related factors. Firstly, these epistemic agents show a higher level of cognitive laziness. By this I mean an inability or unwillingness to engage in reflective thinking and a reluctance to account for counterevidence. Secondly, they yield more easily to metacognitive overconfidence. This can be broadly understood as so-called “knowledge illusion”, the inability to recognize one’s own intellectual limits. The deficiency usually stems from a misunderstanding of the division of cognitive labour and of the agent’s role in epistemic society. I find the proposed epistemological approach to pseudoscience crucial. Only if we understand the descriptive aspects of the problem, can we think of normative solutions to it. (shrink)

Semantic information is usually supposed to satisfy the veridicality thesis: p qualifies as semantic information only if p is true. However, what it means for semantic information to be true is often left implicit, with correspondentist interpretations representing the most popular, default option. The article develops an alternative approach, namely a correctness theory of truth (CTT) for semantic information. This is meant as a contribution not only to the philosophy of information but also to the (...) philosophical debate on the nature of truth. After the introduction, in Sect. 2, semantic information is shown to be translatable into propositional semantic information (i). In Sect. 3, i is polarised into a query (Q) and a result (R), qualified by a specific context, a level of abstraction and a purpose. This polarization is normalised in Sect. 4, where [Q + R] is transformed into a Boolean question and its relative yes/no answer [Q + A]. This completes the reduction of the truth of i to the correctness of A. In Sects. 5 and 6, it is argued that (1) A is the correct answer to Q if and only if (2) A correctly saturates Q by verifying and validating it (in the computer science’s sense of verification and validation ); that (2) is the case if and only if (3) [Q + A] generates an adequate model (m) of the relevant system (s) identified by Q; that (3) is the case if and only if (4) m is a proxy of s (in the computer science’s sense of proxy ) and (5) proximal access to m commutes with the distal access to s (in the category theory’s sense of commutation ); and that (5) is the case if and only if (6) reading/writing (accessing, in the computer science’s technical sense of the term) m enables one to read/write (access) s. Sect. 7 provides some further clarifications about CTT, in the light of semantic paradoxes. Section 8 draws a general conclusion about the nature of CTT as a theory for systems designers not just systems users. In the course of the article all technical expressions from computer science are explained. (shrink)

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [Boulnois 1999]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in chapter 4, make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information. The first section introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two discusses the intermediary but central notion of models. Section three, more exploratory, intro-duces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

The empirical study of belief is emerging at a rapid clip, uniting work from all corners of cognitive science. Reliance on belief in understanding and predicting behavior is widespread. Examples can be found, inter alia, in the placebo, attribution theory, theory of mind, and comparative psychological literatures. Research on belief also provides evidence for robust generalizations, including about how we fix, store, and change our beliefs. Evidence supports the existence of a Spinozan system of belief fixation: one that is (...) automatic and independent of belief rejection. Independent research supports the existence of a system of fragmented belief storage: one that relies on large numbers of causally isolated, context-sensitive stores of belief in memory. Finally, empirical and observational data support at least two systems of belief change. One system adheres, mostly, to epistemological norms of updating; the other, the psychological immune system, functions to guard our most centrally held beliefs from potential inconsistency with newly formed beliefs. Refining our under- standing of these systems can shed light on pressing real-world issues, such as how fake news, propaganda, and brainwashing exploit our psychology of belief, and how best to construct our modern informational world. (shrink)

Jerry Fodor deemed informational encapsulation ‘the essence’ of a system’s modularity and argued that human perceptual processing comprises modular systems, thus construed. Nowadays, his conclusion is widely challenged. Often, this is because experimental work is seen to somehow demonstrate the cognitive penetrability of perceptual processing, where this is assumed to conflict with the informational encapsulation of perceptual systems. Here, I deny the conflict, proposing that cognitive penetration need not have any straightforward bearing on the conjecture that perceptual processing is composed (...) of nothing but informationally encapsulated modules, the conjecture that each and every perceptual computation is performed by an informationally encapsulated module, and the consequences perceptual encapsulation was traditionally expected to have for a perception-cognition border, the epistemology of perception and cognitive science. With these points in view, I propose that particularly plausible cases of cognitive penetration would actually seem to evince the encapsulation of perceptual systems rather than refute/problematize this conjecture. (shrink)

Library information science (LIS) should develop its foundation in terms of a philosophy of information (PI). This seems a rather harmless suggestion. Where else could information science look for its conceptual foundations if not in PI? However, accepting this proposal means moving away from one of the few solid alternatives currently available in the field, namely, providing LIS with a foundation in terms of social epistemology (SE). This is no trivial move, so some reasonable reluctance (...) is to be expected. To overcome it, the proposal needs to be more than just acceptable; it must be convincing. In Floridi (2002a), I have articulated some of the reasons why I believe that PI can fulfill the foundationalist needs better than SE can. I won’t rehearse them here. I find them compelling, but I am ready to change my mind if counterarguments become available. Rather, in this contribution, I wish to clarify some aspects of my proposal (Floridi, 2002a) in favor of the interpretation of LIS as applied PI. I won’t try to show you that I am right in suggesting that PI may provide a foundation for LIS better than SE. My more modest goal is to remove some ambiguities and possible misunderstandings that might prevent the correct evaluation of my position, so that disagreement can become more constructive. (shrink)

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [BOU 99]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in [AMB 07], make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information (for a first outline [CHA 76, SCH 01]). The first section 1 introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two 2 discusses the intermediary but central notion of models. Section three 3, more exploratory, introduces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

Computation is a process of making explicit, information that was implicit. In computing 5 as the solution to ∛125, for example, we move from a description that is not explicitly about 5 to one that is. We are drawing out numerical consequences to the description ∛125. We are extracting information implicit in the problem statement. Can we precisely state the difference between information thati s implicit in a state, structure or process and information that is explicit?

Is more information always better? Or are there some situations in which more information can make us worse off? Good (1967) argues that expected utility maximizers should always accept more information if the information is cost-free and relevant. But Good's argument presupposes that you are certain you will update by conditionalization. If we relax this assumption and allow agents to be uncertain about updating, these agents can be rationally required to reject free and relevant information. (...) Since there are good reasons to be uncertain about updating, rationality can require you to prefer ignorance. (shrink)

When scientists come up with some incredible results, what should we believe? This paper discusses the role of probability and statistics in helping determine what science tells us about our knowledge of the world.

While anger can derail argumentation, it can also help arguers and audiences to reason together in argumentation. Anger can provide information about premises, biases, goals, discussants, and depth of disagreement that people might otherwise fail to recognize or prematurely dismiss. Anger can also enhance the salience of certain premises and underscore the importance of related inferences. For these reasons, we claim that anger can serve as an epistemic resource in argumentation.

Much contemporary epistemology is informed by a kind of confirmational holism, and a consequent rejection of the assumption that all confirmation rests on experiential certainties. Another prominent theme is that belief comes in degrees, and that rationality requires apportioning one's degrees of belief reasonably. Bayesian confirmation models based on Jeffrey Conditionalization attempt to bring together these two appealing strands. I argue, however, that these models cannot account for a certain aspect of confirmation that would be accounted for in any adequate (...) holistic confirmation theory. I then survey the prospects for constructing a formal epistemology that better accommodates holistic insights. (shrink)

Evidence-based medicine (EBM) calls for medical practitioners to “integrate” our best available evidence into clinical practice. A significant amount of the literature on EBM takes this integration to be unproblematic, focusing on questions like how to interpret evidence and engage with patient values, rather than critically looking at how these features of EBM can be implemented together. Other authors have also commented on this gap in the literature, for example, identifying the lack of clarity about how patient preferences and evidence (...) from trials is supposed to be integrated in practice. In this paper, I look at this issue from an epistemological perspective, (looking at how different types of knowledge in EBM can be used to make sounds judgements). In particular, I introduce an epistemological issue for this integration problem, which I call the epistemic integration problem. This is essentially the problem of how we can use information that is both general (eg, about a population sample) and descriptive (eg, about what expected outcomes are) to reach clinical judgements that are individualized (applying to a particular patient) and normative (about what is best for their health). (shrink)

Quantum mechanics was reformulated as an information theory involving a generalized kind of information, namely quantum information, in the end of the last century. Quantum mechanics is the most fundamental physical theory referring to all claiming to be physical. Any physical entity turns out to be quantum information in the final analysis. A quantum bit is the unit of quantum information, and it is a generalization of the unit of classical information, a bit, as (...) well as the quantum information itself is a generalization of classical information. Classical information refers to finite series or sets while quantum information, to infinite ones. Quantum information as well as classical information is a dimensionless quantity. Quantum information can be considered as a “bridge” between the mathematical and physical. The standard and common scientific epistemology grants the gap between the mathematical models and physical reality. The conception of truth as adequacy is what is able to transfer “over” that gap. One should explain how quantum information being a continuous transition between the physical and mathematical may refer to truth as adequacy and thus to the usual scientific epistemology and methodology. If it is the overall substance of anything claiming to be physical, one can question how different and dimensional physical quantities appear. Quantum information can be discussed as the counterpart of action. Quantum information is what is conserved, action is what is changed in virtue of the fundamental theorems of Emmy Noether (1918). The gap between mathematical models and physical reality, needing truth as adequacy to be overcome, is substituted by the openness of choice. That openness in turn can be interpreted as the openness of the present as a different concept of truth recollecting Heidegger’s one as “unconcealment” (ἀλήθεια). Quantum information as what is conserved can be thought as the conservation of that openness. (shrink)

A fundamental problem in science is how to make logical inferences from scientific data. Mere data does not suffice since additional information is necessary to select a domain of models or hypotheses and thus determine the likelihood of each model or hypothesis. Thomas Bayes’ Theorem relates the data and prior information to posterior probabilities associated with differing models or hypotheses and thus is useful in identifying the roles played by the known data and the assumed prior (...) class='Hi'>information when making inferences. Scientists, philosophers, and theologians accumulate knowledge when analyzing different aspects of reality and search for particular hypotheses or models to fit their respective subject matters. Of course, a main goal is then to integrate all kinds of knowledge into an all-encompassing worldview that would describe the whole of reality. A generous description of the whole of reality would span, in the order of complexity, from the purely physical to the supernatural. These two extreme aspects of reality are bridged by a nonphysical realm, which would include elements of life, man, consciousness, rationality, mental and mathematical abstractions, etc. An urgent problem in the theory of knowledge is what science is and what it is not. Albert Einstein’s notion of science in terms of sense perception is refined by defining operationally the data that makes up the subject matter of science. It is shown, for instance, that theological considerations included in the prior information assumed by Isaac Newton is irrelevant in relating the data logically to the model or hypothesis. In addition, the concepts of naturalism, intelligent design, and evolutionary theory are critically analyzed. Finally, Eugene P. Wigner’s suggestions concerning the nature of human consciousness, life, and the success of mathematics in the natural sciences is considered in the context of the creative power endowed in humans by God. (shrink)

I argue that normative formal epistemology (NFE) is best understood as modelling, in the sense that this is the reconstruction of its methodology on which NFE is doing best. I focus on Bayesianism and show that it has the characteristics of modelling. But modelling is a scientific enterprise, while NFE is normative. I thus develop an account of normative models on which they are idealised representations put to normative purposes. Normative assumptions, such as the transitivity of comparative credence, are characterised (...) as modelling idealisations motivated normatively. I then survey the landscape of methodological options: what might formal epistemologists be up to? I argue the choice is essentially binary: modelling or theorising. If NFE is theorising it is doing very poorly: generating false claims with no clear methodology for separating out what is to be taken seriously. Modelling, by contrast, is a successful methodology precisely suited to the management of useful falsehoods. Regarding NFE as modelling is not costless, however. First, our normative inferences are less direct and are muddied by the presence of descriptive idealisations. Second, our models are purpose-specific and limited in their scope. I close with suggestions for how to adapt our practice. (shrink)