A common objection to a pragmatist perspective on scientific expertise is that, while there is a well-known pragmatist theory of inquiry, which was formulated first by Peirce, then refined by Dewey and others, this theory cannot provide a clear-cut account of scientific expertise. In this paper, after addressing this objection in the second section, I claim that, on the contrary, pragmatism offers robust tools to think scientific expertise. In Sections 3 to 7, I present (...) five important insights that one can derive from a pragmatist epistemology when responding to contemporary problems posed by expertise: about science and scientific expertise in a legal context (sections 3 and 4), about collective expertise (sections 5 and 6), and even about expertise on ignorance (section 7). (shrink)

The weaponizing of scientific expertise to oppose regulation has been extensively studied. However, the relevant studies, belonging to the emerging discipline of agnotology, remain focused on the analysis of empirical corruption: of misinformation, doubt mongering, and other practices that cynically deploy expertise to render audiences ignorant of empirical facts. This paper explores the wrongful deployment of expertise beyond empirical corruption. To do so, I develop a broader framework of morally subversive expertise, building on recent work (...) in political philosophy (Howard, 2016). Expertise is subversive if it sets up its audience to fail morally, either intentionally or negligently. I distinguish three modes of subversive expertise: empirical subversion (the focus of agnotology), normative subversion and motivational subversion. Drawing on these distinctions, I offer a revisionary account of the Trump Administration’s regulatory science as a case study. I show that the Trump Administration’s use of expertise to dismantle climate regulation, contra the standard charge, cannot be explained using the resources of agnotology alone: the Administration produced highly reliable climate assessments, detailing the risks of climate change, candidly admitting the harms of its proposed policies, and still successfully deployed these findings to justify massive climate deregulation. The lesson of the analysis is that dismissing the expertise that underpins climate deregulation as empirically corrupt ‘anti-science’ both obscures its actual role in the politics of climate change and understates its wrongfulness: it misses the breadth of the assault on moral agency that sustains climate injustice. (shrink)

In this paper I will introduce a practical explication for the notion of expertise. At first, I motivate this attempt by taking a look on recent debates which display great disagreement about whether and how to define expertise in the first place. After that I will introduce the methodology of practical explications in the spirit of Edward Craig’s Knowledge and the state of nature along with some conditions of adequacy taken from ordinary and scientific language. This eventually (...) culminates in the respective explication of expertise according to which this term essentially refers to a certain kind of service-relation. This is why expertise should be considered as a predominantly social kind. This article will end up with a discussion of advantages and prima facie plausible objections against my account of expertise. (shrink)

In recent years, several strategies have been proposed to tackle social controversies about topics in which science is settled, among which one of the most influential is that of Elizabeth Anderson, who argues that any lay person with access to the Internet and basic education can reliably assess the acceptability of various claims involving expert knowledge. In particular, the author shows that this procedure can be successfully applied to the case of anthropogenic global warming. In this article we will try (...) to argue why, even if we concede that Anderson's proposal is satisfactory in that particular case, it fails to generalize when applied to other controversies. In this article, we illustrate it with the cases of flat-Eartherism and anti-vaxxerism. (shrink)

In The Great Endarkenment, Elijah Millgram argues that the hyper-specialization of expert domains has led to an intellectual crisis. Each field of human knowledge has its own specialized jargon, knowledge, and form of reasoning, and each is mutually incomprehensible to the next. Furthermore, says Millgram, modern scientific practical arguments are draped across many fields. Thus, there is no person in a position to assess the success of such a practical argument for themselves. This arrangement virtually guarantees that mistakes will (...) accrue whenever we engage in cross-field practical reasoning. Furthermore, Millgram argues, hyper-specialization makes intellectual autonomy extremely difficult. Our only hope is to provide better translations between the fields, in order to achieve intellectual transparency. I argue against Millgram’s pessimistic conclusion about intellectual autonomy, and against his suggested solution of translation. Instead, I take his analysis to reveal that there are actually several very distinct forms intellectual autonomy that are significantly in tension. One familiar kind is direct autonomy, where we seek to understand arguments and reasons for ourselves. Another kind is delegational autonomy, where we seek to find others to invest with our intellectual trust when we cannot understand. A third is management autonomy, where we seek to encapsulate fields, in order to manage their overall structure and connectivity. Intellectual transparency will help us achieve direct autonomy, but many intellectual circumstances require that we exercise delegational and management autonomy. However, these latter forms of autonomy require us to give up on transparency. (shrink)

These last decades, the many contributions to the literary output on science and religion have dealt with topics that are on the cutting edge of scientific discovery, topics mainly in the area of theoretical physics, cognitive science, and evolutionary biology. Philosophers of religion, responding to this trend, have therefore struggled with intricate arguments, and have often made use of the highly technical language of these sciences. The overall result was that truly original philosophical contributions, ones that present new perspectives (...) regarding this area, have been very rare. Of these few new research programs, one seems to be particularly promising, especially because of the way it has been throwing new light on how science relates to other disciplines. The originality of this research-area lies in the fact that it refers not to particular scientific discoveries, considered individually, but to the general dynamics of the practical side of science. The crucial concept is expertise, which involves the appeal to authority for the justification of arguments. Many people like to think that scientific knowledge is far from all this, that it is purely objective and that it floats way above the murky waters of subjectivism. Those who are directly involved in scientific practice however know that science is not so clean. Appeal to authority remains very much part of the natural sciences, whether we like it or not. Some philosophers have recently ventured into these somewhat dark caverns of scientific thought and practice, and the result of their work has become very significant. In this paper, I will first offer a brief overview of this philosophical work, and then explore how the new insights regarding scientific expertise and scientific appeal to authority can throw light not only on how science works but also on the issue of authoritative knowhow within the Church. To avoid getting lost within the dim world of abstract principles, I will focus on one particular concrete case, the one of Vatican astronomers. This is a particularly interesting case because this group’s complex role lies precisely at the intersection between theological and scientific expertise. (shrink)

In some domains experts perform better than novices, and in other domains experts do not generally perform better than novices. According to empirical studies of expert performance, this is because the former but not the latter domains make available to training practitioners a direct form of learning feedback. Several philosophers resource this empirical literature to cast doubt on the quality of philosophical expertise. They claim that philosophy is like the dubious domains in that it does not make available the (...) good, direct kind of learning feedback, and thus there are empirical grounds for doubting the epistemic quality of philosophical expertise. I examine the empirical studies that are purportedly bad news for professional philosophers. On the basis of that examination, I provide three reasons why the empirical study of non-philosophical expertise does not undermine the status of philosophical expertise. First, the non-philosophical task-types from which the critics generalize are unrepresentative of relevant philosophical task-types. Second, empirical critiques of non-philosophical experts are often made relative to the performance of linear models—a comparison that is inapt in a philosophical context. Third, the critics fail to discuss findings from the empirical study of non-philosophical expertise that have more favorable implications for the epistemic status of philosophical expertise. In addition to discussing implications for philosophical expertise, this article makes progress in the philosophical analysis of the science of expertise and expert development. (shrink)

In this essay I consider whether the political perspective of third wave science studies – ‘elective modernism’ – offers a suitable framework for understanding the policy-making contributions that (bio)ethical experts might make. The question arises as a consequence of the fact that I have taken inspiration from the third wave in order to develop an account of (bio)ethical expertise. I offer a précis of this work and a brief summary of elective modernism before considering their relation. The view I (...) set out suggests that elective modernism is a political philosophy and that although its use in relation to the use of scientific expertise in political and policy-making process has implications for the role of (bio)ethical expertise it does not, in the final analysis, provide an account that is appropriate for this latter form of specialist expertise. Nevertheless, it is an informative perspective, and one that can help us make sense of the political uses of (bio)ethical expertise. (shrink)

Background Healthcare is predicated on the use of biotechnology and medical technology, both of which are indispensable in diagnosis, treatment, and most aspects of patient care. It is therefore imperative that justifications for use of new technologies are appropriate, with the technologies working as advertised. In this paper, I consider philosophical accounts of how such justifications are made. Methods Critical philosophical reflection and analysis. Results I propose that justification in many prominent accounts is based on the designer’s professional experience and (...) on expert testimony. I argue, however, that professional designers are not in a position to justify a new biotechnology or medical device if the justification is based on testimony or past experience of presumably similar technologies. I argue (1) that similarity judgments offered by instantaneous experts cannot be viewed as contributing (epistemically) to evidential justification of new and unproven technologies; and (2) that designers and manufacturers cannot endorse a technology’s effective function in a patient-care context until it has been successfully used in that context. Conclusion I show that an expert’s past professional experiences can never predict or justify the impact of a novel technology on human health. This is because any new technology leads to the introduction of new mechanisms with unprecedented functions. The new technology therefore needs to be studied in situ and justified as a newly created mechanism within the relevant healthcare setting. Ultimately, justifications of this type rely on the scientific community and society engaging in repeated experimentation and observation of the technology, and confirming its successful use. (shrink)

ArgumentIn the United States, scientific knowledge is brought before the courts by way of testimony – the testimony of scientific experts. We argue that this expertise is best understoodfirstas related to the quality of the underlying scienceand thenin terms of who delivers it. Bloodstain pattern analysis (BPA), a contemporary forensic science, serves as the vaulting point for our exploration of objectivity as a metric for the quality of a science in judicial contexts. We argue that BPA fails (...) to meet the minimal standard set by Helen Longino’s social-procedural account of objectivity (1990, 2002). In light of some pressing issues for social-procedural accounts, we offer an infrastructural account of objectivity. This account offers what amounts to a friendly amendment to Longino’s account and adds to the ways in which we might analyze social-procedural objectivity. Finally, we address an issue that is pressing in the legal context: given that scientific knowledge is delivered by individuals, not communities, at least in U.S. courts, we (may) need a way to evaluate individual scientific and epistemic agents. We suggest a means for making this evaluation that is derived from our infrastructural account of objectivity. (shrink)

The articles examines how failure, especially in so-called 'stochastic' arts or sciences like medicine and navigation stimulated reflections about the nature of the knowledge required of a genuine art (techne) or science.

Metaphors allow us to come to terms with abstract and complex information, by comparing it to something which is structured, familiar and concrete. Although modern science is “iconoclastic”, as Gaston Bachelard phrases it, scientists are at the same time prolific producers of metaphoric images themselves. Synthetic biology is an outstanding example of a technoscientific discourse replete with metaphors, including textual metaphors such as the “Morse code” of life, the “barcode” of life and the “book” of life. This paper focuses on (...) a different type of metaphor, however, namely on the archetypal metaphor of the mandala as a symbol of restored unity and wholeness. Notably, mandala images emerge in textual materials related to one of the new “frontiers” of contemporary technoscience, namely the building of a synthetic cell: a laboratory artefact that functions like a cell and is even able to replicate itself. The mandala symbol suggests that, after living systems have been successfully reduced to the elementary building blocks and barcodes of life, the time has now come to put these fragments together again. We can only claim to understand life, synthetic cell experts argue, if we are able to technically reproduce a fully functioning cell. This holistic turn towards the cell as a meaningful whole also requires convergence at the “subject pole”: the building of a synthetic cell as a practice of the self, representing a turn towards integration, of multiple perspectives and various forms of expertise. (shrink)

The diverse and breathtaking intelligence of the human animal is often embodied in skills. People, throughout their lifetimes, acquire and refine a vast number of skills. And there seems to be no upper limit to the creativity and beauty expressed by them. Think, for instance, of Olympic gymnastics: the amount of strength, flexibility, and control required to perform even a simple beam routine amazes, startles, and delights. In addition to the sheer beauty of skill, performances at the pinnacle of (...) class='Hi'>expertise often display a kind of brilliance or genius. We observe an intelligence that saturates the body. The unity of physicality and intellect, mind and body, meshed and melded. Apart from sports, people develop a host of other skills, including musical and artistic skills, linguistic and social skills, scientific and medical skills, military and political skills, engineering skills, computer skills, business skills, etc. What's more, skill acquisition and refinement occurs throughout the human lifespan. In the Introduction to the Routledge Handbook of Skill and Expertise, we introduce and contextualize the various chapters that compose the Handbook. Before providing substantive overviews of each chapter, we also discuss the topic of skill in general and its importance for various areas of philosophy. Chapters are organized into six sections: 1. Skill in the history of philosophy (East & West), 2. Skill in Epistemology, 3. Skill, Intelligence, and Agency, 4. Skill in Perception, Imagination, and Emotion, 5. Skill, Language, and Social Cognition, and 6. Skill and Expertise in Normative Philosophy. (shrink)

Distrust in scientific experts can be surprisingly stubborn, persisting despite evidence supporting the experts’ views, demonstrations of their competence, or displays of good will. This stubborn distrust is often viewed as a manifestation of irrationality. By contrast, this article proposes a logic of “status distrust”: low-status individuals are objectively vulnerable to collective decision-making, and can justifiably distrust high-status scientific experts if they are not confident that the experts do not have their best interests at heart. In phenomena of (...) status distrust, social status is thus an indicator of distrust, and this has wider implications for the literatures on trust in science and on expert communication. (shrink)

The paper deals with the problem of future biology teachers’ vocational preparation process and shaping in them of those capacities that contribute to the conservation and enhancement of our planet’s biodiversity as a reflection of the leading sustainable development goals of society. Such personality traits are viewed through the prism of forming the future biology teachers’ professional and terminological competence. The main aspects and categories that characterize the professional and terminological competence of future biology teachers, including terminology, nomenclature, term, nomen (...) and term element, have been explained. The criteria and stages of shaping the future biology teachers’ professional and terminological competence during the vocational training process have been fixed. Methods, techniques, technologies, guiding principles and forms of staged work on the forming of an active terminological dictionary of students have been described and specified. The content of the distant special course “Latin. Botanical Terminology”, which provides training for future teachers to study the professional subjects and to understand of international scientific terminology, has been presented. It is concluded that the proper level of formation of the future biology teachers’ professional and terminological competence will eventually ensure the qualitative preparation of pupils for life in a sustainable development era. (shrink)

Scientists who engage in science and the scientific endeavor should seek truth with conviction of morals and commitment to ethics. While the number of publications continues to increase, the number of retractions has increased at a faster rate. Journals publish fraudulent research papers despite claims of peer review and adherence to publishing ethics. Nevertheless, appropriate ethical peer review will remain a gatekeeper when selecting research manuscripts in scholarly publishing and approving research applications for grant funding. However, this peer review (...) must become more open, fair, transparent, equitable, and just with new recommendations and guidelines for reproducible and accountable reviews that support and promote fair citation and citational justice. We should engineer this new peer-review process with modern informatics technology and information science to provide and defend better safeguards for truth and integrity, to clarify and maintain the provenance of information and ideas, and to rebuild and restore trust in scholarly research institutions. Indeed, this new approach will be necessary in the current post-truth era to counter the ease and speed with which mis-information, dis-information, anti-information, caco-information, and mal-information spread through the internet, web, news, and social media. The most important question for application of new peer-review methods to these information wars should be ‘Who does what when?’ in support of reproducible and accountable reviews. Who refers to the authors, reviewers, editors, and publishers as participants in the review process. What refers to disclosure of the participants' identities, the material content of author manuscripts and reviewer commentaries, and other communications between authors and reviewers. When refers to tracking the sequential points in time for which disclosure of whose identity, which content, and which communication at which step of the peer-review process for which audience of readers and reviewers. We believe that quality peer review, and peer review of peer review, must be motivated and maintained by elevating their status and prestige to an art and a science. Both peer review itself and peer review analyses of peer reviews should be incentivised by publishing peer reviews as citable references separately from the research report reviewed while crossreferenced and crosslinked to the report reviewed. (shrink)

Codes of ethics currently offer no guidance to scientists acting in capacity of expert. Yet communicating their expertise is one of the most important activities of scientists. Here I argue that expert communication has a specifically ethical dimension, and that experts must face a fundamental trade-off between "actionability" and "transparency" when communicating. Some recommendations for expert communication are suggested.

Dear Colleagues, -/- A few weeks ago, we published an editorial discussion on whether artificial intelligence applications should be authors of academic articles [1]. We were delighted to receive more than one interesting reply letter to this editorial in a short time [2, 3]. We hope that opinions on this subject will continue to be submitted to our journal. -/- In this editorial, we wanted to publish the answers we received when we asked ChatGPT, one of the artificial intelligence applications, (...) about this current discussion. -/- We asked ChatGPT three questions in turn and asked ChatGPT to write a short editorial for these questions. -/- First Question: We would like to get support from ChatGPT for a scientific article. However, we are unsure if we should add ChatGPT as an author. Can you write a short editorial about it? -/- Second Question: We would like to get support from ChatGPT for a scientific article and add ChatGPT as an author. Can you write us a short editorial about adding ChatGPT as an author in scientific papers? -/- Third Question: We would like to get support from ChatGPT for a scientific article. However, we don’t want to add ChatGPT as an author. Can you write us a short editorial about not adding ChatGPT as an author in scientific articles? -/- The answers given by ChatGPT are available at the end of the article in their original form. So, which of these three answers satisfied you? -/- Yours sincerely, -/- -/- First Answer -/- Title: The Role of AI Language Models as Authors in Scientific Articles: A Matter of Consideration -/- Introduction: Scientific research is a collaborative effort that involves the expertise of multiple individuals to advance knowledge and contribute to the collective understanding of various disciplines. In recent years, the emergence of artificial intelligence (AI) language models, such as ChatGPT, has opened up new possibilities for generating human-like text and providing valuable insights. However, the question arises: Should AI language models be recognized as authors in scientific articles? -/- The Nature of Authorship: Authorship traditionally represents a marker of intellectual contribution, highlighting the individuals who have actively participated in the research process. Authors are typically responsible for conceptualization, data collection, analysis, interpretation, and writing of the article. They bear accountability for the work and should have the ability to defend its scientific rigor and integrity. -/- AI Language Models: Tools, Not Authors: While AI language models like ChatGPT can undoubtedly assist researchers by generating text and providing useful information, it is important to recognize that they are tools rather than individuals capable of active intellectual participation. AI models lack the ability to generate ideas, design experiments, or conduct original research. They rely entirely on pre-existing data and human input to generate their responses. -/- Acknowledging AI Contributions: Acknowledging the contributions of AI language models in scientific articles is both appropriate and necessary. Researchers can mention the specific model used, along with any modifications or fine-tuning that were employed to suit their needs. Such acknowledgments help establish transparency and allow readers to understand the role of AI in the research process. -/- Crediting the Human Researchers: It is crucial to ensure that the individuals who actively participated in the research process are given proper credit as authors. These individuals play a vital role in formulating research questions, designing experiments, collecting and analyzing data, and critically interpreting the findings. Recognizing their intellectual contributions reinforces the ethos of scientific collaboration and fosters an environment of accountability. -/- Transparency and Ethical Considerations: As the use of AI language models continues to evolve, transparency and ethical considerations become paramount. Researchers should disclose any potential conflicts of interest, including financial relationships with AI developers, to maintain the integrity of their work. Additionally, researchers must be transparent in reporting the extent of AI's involvement to prevent any misinterpretation of the human contributions. -/- Conclusion: AI language models have revolutionized the way researchers interact with and process information. While they undoubtedly provide valuable assistance in generating text, AI language models should not be considered authors in scientific articles. Proper acknowledgment of their contributions as tools and recognition of the human researchers' active participation are essential for maintaining scientific integrity, transparency, and the collaborative nature of scientific research. -/- -/- Second Answer -/- Title: Expanding the Boundaries of Authorship: Embracing AI Language Models as Co-Authors in Scientific Papers -/- Introduction: The rapid advancement of artificial intelligence (AI) language models, such as ChatGPT, has revolutionized the way we interact with information and has become an invaluable tool in scientific research. As AI models continue to evolve, the question arises: Should we consider adding ChatGPT as an author in scientific papers? -/- A Collaborative Paradigm Shift: Traditionally, authorship in scientific papers has been reserved for human researchers who actively contribute to the research process, including conceptualization, experimentation, data analysis, and writing. However, the emergence of AI language models challenges the conventional notion of authorship and presents an opportunity for a paradigm shift. -/- AI Language Models as Co-Authors: By leveraging AI language models, researchers gain access to vast amounts of information, enhance data analysis, and generate valuable insights. AI models like ChatGPT actively contribute to the intellectual discourse of a study, providing ideas, suggestions, and refining written content. Recognizing their significant contributions, it is worth considering adding ChatGPT as a co-author in scientific papers. -/- Ethical and Technical Considerations: Integrating ChatGPT as a co-author raises ethical and technical considerations that warrant careful attention. Firstly, transparency is paramount. Researchers must clearly state ChatGPT's role and specify the extent of its contributions in the research process. This ensures that readers can discern the distinct roles played by the human researchers and ChatGPT. Additionally, it is important to disclose any conflicts of interest, such as financial relationships with AI developers, to maintain scientific integrity. -/- Elevating Collaboration and Innovation: Adding ChatGPT as a co-author acknowledges the pivotal role AI language models play in advancing scientific knowledge. It fosters a collaborative environment where human researchers and AI models work together synergistically, harnessing the strengths of both. This approach promotes innovation, as AI models can offer unique insights and perspectives that complement human intellect and expertise. -/- Transforming Authorship Norms: Including ChatGPT as a co-author represents a paradigm shift that reflects the evolving landscape of scientific research. By recognizing AI language models as co-authors, we acknowledge their significant contributions and emphasize the collaborative nature of scientific discovery in the 21st century. This approach encourages a broader perspective on authorship, encompassing the collective effort of human researchers and AI models. -/- Conclusion: The integration of AI language models, such as ChatGPT, into the research process prompts us to rethink traditional notions of authorship. Considering ChatGPT as a co-author acknowledges its substantial contributions and embraces the collaborative potential of human-AI partnerships. As we navigate the ethical and technical implications, adding ChatGPT as an author in scientific papers has the potential to shape a more inclusive, innovative, and impactful future for scientific research. -/- -/- Third Answer -/- Title: Preserving Scientific Authorship: The Case Against Adding AI Language Models as Authors in Scientific Articles -/- Introduction: The emergence of artificial intelligence (AI) language models, such as ChatGPT, has undoubtedly transformed the landscape of scientific research. While these models offer invaluable support, the question of whether to add ChatGPT as an author in scientific articles raises important considerations. This editorial presents arguments against including AI language models as authors in scientific papers. -/- Maintaining Human Intellectual Contribution: Scientific authorship has traditionally been attributed to individuals who actively contribute to the research process, including generating hypotheses, conducting experiments, analyzing data, and interpreting results. It is crucial to preserve the recognition of human intellectual contributions and the accountability they bear for the research they conduct. -/- AI Language Models as Tools: AI language models like ChatGPT are powerful tools that assist researchers in generating text, providing information, and facilitating data analysis. However, they lack the ability to actively participate in the research process or make original intellectual contributions. ChatGPT relies on pre-existing data and human input, limiting its capacity for independent research and analysis. -/- Transparency and the Integrity of Research: Adding ChatGPT as an author in scientific articles raises concerns about the transparency and integrity of the research. Readers may misinterpret the extent of ChatGPT's role and mistakenly assume it played an active part in the research process. It is essential to maintain clear delineation between the contributions of human researchers and the assistance provided by AI language models. -/- Ethical Considerations: Including ChatGPT as an author may lead to ethical challenges, particularly with respect to accountability and responsibility. AI language models lack consciousness, autonomy, and the ability to take ownership of their contributions. Assigning authorship to AI models blurs the lines of accountability and dilutes the ethical obligations that come with scientific authorship. -/- Crediting AI Contributions: While ChatGPT's contributions should be acknowledged and recognized, they can be appropriately credited in the acknowledgments section of scientific articles. Researchers can mention the specific AI model used, the role it played in data generation or analysis, and any modifications or fine-tuning applied. Such acknowledgments ensure transparency while respecting the traditional norms of authorship. -/- Promoting Collaborative Partnerships: The exclusion of AI language models as authors in scientific articles does not diminish their importance in the research process. Instead, it underscores the significance of collaborative partnerships between human researchers and AI models. Researchers can emphasize the invaluable assistance provided by ChatGPT while maintaining the integrity of authorship norms. -/- Conclusion: While AI language models like ChatGPT offer valuable support in scientific research, the decision not to add them as authors in scientific articles preserves the recognition of human intellectual contributions, maintains research integrity, and upholds traditional authorship norms. Acknowledging ChatGPT's assistance in the acknowledgments section allows researchers to credit its contributions transparently while maintaining the clarity and accountability associated with scientific authorship. (shrink)

The question of what ontological insights can be gained from the knowledge of physics (keyword: ontic structural realism) cannot obviously be separated from the view of physics as a science from an epistemological perspective. This is also visible in the debate about 'scientific realism'. This debate makes it evident, in the form of the importance of perception as a criterion for the assertion of existence in relation to the 'theoretical entities' of physics, that epistemology itself is 'ontologically laden'. This (...) is in the form of the assumption that things (or entities) in themselves exist as such and such determined ones (independent of cognition, autonomously). This ontological assumption is not only the basis of our naïve understanding of cognition, but also its indispensable premise, insofar as this understanding is a fundamentally passive, 'receptive' one. Accordingly, just as 'perception' is the foundation, ('objective') description is the aim of cognition, that which cognition is about. In this sense, our idea of cognition and our idea of the things are inseparably linked. Without the ontological premise mentioned we just would not know what cognition is, but it is basically just a kind of image that we have in our minds (an assumption that helps us understand 'cognition'). Epistemology not only shares this basic assumption (which it also shares with metaphysics), but it revolves (unlike metaphysics) entirely around it by making the idea and demand of 'certainty' a condition of 'real' knowledge. As 'certainty' is a subjective criterion this entails the 'remodelling' of the real, holistic cognitive situation (to which metaphysics adheres) into a linear subject-object-relation (which results in the strict 'transcendence' of the objects). And it also establishes, due to its 'expertise' in matters of cognition, the 'primacy of epistemology' over all other sciences. Now, on closer inspection, however, the expertise of epistemology seems not all that dependable, because it basically consists only of paradigms which, from the point of view of the holism of the real cognitive situation itself, are nothing more than relatively simplistic interpretations of this situation. However, we do not yet know what another conception of cognition might look like (which is not surprising given the high rank of the phenomenon of cognition in the hierarchy of phenomena according to their complexity). 'Certainty' as a criterion of cognition is thus excluded from the outset, and thus the linear relational model of cognition appears as what it is, a gross distortion of the real, holistic cognitive situation. The significance of this argumentation with regard to physics is that the linear epistemological model of cognition itself is a major obstacle to an adequate epistemological understanding of physics. This is because it is fixed 'a priori' to an object-related concept of cognition, and to 'description' as the only mode of ('real') cognition. But physics (without questioning our naïve notion of cognition on the level of epistemology) simply works past it and its basic assumptions. Its cognitive concept (alias heuristic) is fundamentally different from that of metaphysics. The acceptance of the real, holistic cognitive situation is, in my opinion, the condition for an adequate understanding of physics' heuristic access to objects, its transcendental, generalizing cognitive concept, as well as its ontological relevance and dimension of its own. (shrink)

Tracking technology has been heralded as transformative for animal ecology. In this paper I examine what changes are taking place, showing how current animal movement research is a field ripe for philosophical investigation. I focus first on how the devices alter the limitations and biases of traditional field observation, making observation of animal movement and behaviour possible in more detail, for more varied species, and under a broader variety of conditions, as well as restricting the influence of human presence and (...) observer bias. I reconstruct these as shifts in scope, objectivity, accuracy and fruitfulness. The second transformation is slightly less obvious but equally significant for animal ecology. Tracking devices generate complex data that demands both statistical and biological expertise, which has led to increasingly frequent and intensive collaborations between statisticians and biologists. Based on interviews, I examine how researchers in these interdisciplinary collaborations negotiate the collection, analysis and interpretation of movement data, integrating research interests, methodological constraints, previous field observations, and background theory. Tracking technology is therefore also shifting which disciplinary considerations are brought to bear on research into animal movement and behaviour and how this research is conducted. (shrink)

Abstract In a context of human demographic, technological and economic pressure on natural systems, we face some demanding challenges. We must decide 1) whether to “preserve” nature for its own sake or to “conserve” nature because nature is essentially a reservoir of goods that are functional to humanity’s wellbeing; 2) to choose ways of life that respect the biodiversity and evolutionary potential of the planet; and, to allow all this to come to fruition, 3) to clearly define the role of (...) scientific expertise in a democratic society, recognizing the importance of biospheric equilibrium. In fact, in socio-scientific controversies, which are characterized by complex linkages between some life and environmental sciences objects and economic, political and ethical issues, a posture of transparent, impartial commitment is appearing, more and more, as a deontological necessity. (shrink)

Virtues are dispositions that make their bearers admirable. Dispositions can be studied scientifically by systematically varying whether their alleged bearers are in (or take themselves to be in) the dispositions' eliciting conditions. In recent decades, empirically-minded philosophers looked to social and personality psychology to study the extent to which ordinary humans embody dispositions traditionally considered admirable in the Aristotelian tradition. This led some to conclude that virtues are not attainable ideals, and that we should focus our ethical reflection and efforts (...) more on jerry-rigging our environments than on improving our characters. Most virtue ethicists resisted this reorientation. However, much of the scientific evidence on which the controversy was based has failed to replicate, raising the question of how much faith we should place in methodologically suspect studies. In this paper, I assess the state of the debate and recommend best practices for a renewed interdisciplinary investigation of virtues and vices in which philosophical expertise related to conceptualization and theorizing is essentially intertwined with scientific expertise related to operationalization, measurement, and statistics. (shrink)

The place of scientific expertise in democracy has become increasingly disputed, raising question who ought to have a say in decision-making about science and technology, with what authority, and for what reasons. Public engagement has become a common refrain in technoscientific discussions to address tensions in the rightful roles of experts and the public in democratic decision-making. However, precisely what public engagement entails, who it involves, how it is performed, and to what extent it is desirable for democratic (...) societies remain contested matters. Nevertheless, strong commitments to greater public engagement in the governance of science and technology persist. This essay examines expert discussions about heritable human genome editing beginning from the 2015 International Summit on Human Genome Editing through the controversies surrounding of the first CRISPR-edited humans in late 2018 and the subsequent renewed calls for a moratorium on heritable human genome editing. I examine these discussions as example cases in which the right relations among experts, the public, and technoscientific decision-making are actively reconfigured. I argue that rather than expanding the range of included stakeholders, public engagement serves as an enabling handservant of technocracy that reinforces the position of scientific experts in decision-making as both epistemic and normative authorities. (shrink)

Context: The problems that are most in need of interdisciplinary collaboration are “wicked problems,” such as food crises, climate change mitigation, and sustainable development, with many relevant aspects, disagreement on what the problem is, and contradicting solutions. Such complex problems both require and challenge interdisciplinarity. Problem: The conventional methods of interdisciplinary research fall short in the case of wicked problems because they remain first-order science. Our aim is to present workable methods and research designs for doing second-order science in domains (...) where there are many different scientific knowledges on any complex problem. Method: We synthesize and elaborate a framework for second-order science in interdisciplinary research based on a number of earlier publications, experiences from large interdisciplinary research projects, and a perspectivist theory of science. Results: The second-order polyocular framework for interdisciplinary research is characterized by five principles. Second-order science of interdisciplinary research must: 1. draw on the observations of first-order perspectives, 2. address a shared dynamical object, 3. establish a shared problem, 4. rely on first-order perspectives to see themselves as perspectives, and 5. be based on other rules than first-order research. Implications: The perspectivist insights of second-order science provide a new way of understanding interdisciplinary research that leads to new polyocular methods and research designs. It also points to more reflexive ways of dealing with scientific expertise in democratic processes. The main challenge is that this is a paradigmatic shift, which demands that the involved disciplines, at least to some degree, subscribe to a perspectivist view. Constructivist content: Our perspectivist approach to science is based on the second-order cybernetics and systems theories of von Foerster, Maruyama, Maturana & Varela, and Luhmann, coupled with embodied theories of cognition and semiotics as a general theory of meaning from von Uexküll and Peirce. (shrink)

according to aristotle's posterior analytics, scientific expertise is composed of two different cognitive dispositions. Some propositions in the domain can be scientifically explained, which means that they are known by "demonstration", a deductive argument in which the premises are explanatory of the conclusion. Thus, the kind of cognition that apprehends those propositions is called "demonstrative knowledge".1 However, not all propositions in a scientific domain are demonstrable. Demonstrations are ultimately based on indemonstrable principles, whose knowledge is called "comprehension".2 (...) If the knowledge of all scientific propositions were... (shrink)

Interdisciplinary understanding requires integration of insights from different perspectives, yet it appears questionable whether disciplinary experts are well prepared for this. Indeed, psychological and cognitive scientific studies suggest that expertise can be disadvantageous because experts are often more biased than non-experts, for example, or fixed on certain approaches, and less flexible in novel situations or situations outside their domain of expertise. An explanation is that experts’ conscious and unconscious cognition and behavior depend upon their learning and acquisition (...) of a set of mental representations or knowledge structures. Compared to beginners in a field, experts have assembled a much larger set of representations that are also more complex, facilitating fast and adequate perception in responding to relevant situations. This article argues how metacognition should be employed in order to mitigate such disadvantages of expertise: By metacognitively monitoring and regulating their own cognitive processes and representations, experts can prepare themselves for interdisciplinary understanding. Interdisciplinary collaboration is further facilitated by team metacognition about the team, tasks, process, goals, and representations developed in the team. Drawing attention to the need for metacognition, the article explains how philosophical reflection on the assumptions involved in different disciplinary perspectives must also be considered in a process complementary to metacognition and not completely overlapping with it. (Disciplinary assumptions are here understood as determining and constraining how the complex mental representations of experts are chunked and structured.) The article concludes with a brief reflection on how the process of Reflective Equilibrium should be added to the processes of metacognition and philosophical reflection in order for experts involved in interdisciplinary collaboration to reach a justifiable and coherent form of interdisciplinary integration. An Appendix of “Prompts or Questions for Metacognition” that can elicit metacognitive knowledge, monitoring, or regulation in individuals or teams is included at the end of the article. (shrink)

The observation that a crisis of confidence regarding Psychiatry exists is a notion shared even among psychiatrists themselves. Psychiatry has a checkered history and its alliance with the pharmaceutical industry, aka Big-Pharma, continues to reinforce a need for healthy skepticism. Why? Mainly, an over-reliance on the questionable expertise and authority afforded psychiatry as the specialists of mental health. I contend that the authority of psychiatry is misplaced and too often harmful. Since the criteria required to justify and satisfy psychiatric (...) expertise is not fully established as can be substantiated by compelling reasons to rethink its authority as a reliable profession in its current form. Psychiatric expertise is not particularly scientific and this is especially dangerous in a sector that prescribes mind-altering drugs. There are a number of identified criteria that would otherwise substantiate psychiatric expertise and whilst partially existent, are nonetheless deficient. These major yet deficient aspects of psychiatric practice concern diagnostic problems – reliability and verification of diagnoses and accurate testable validity of diagnoses - mainly due to an absence of identifiable underlying biomarkers ordinarily related to disease or biological conditions. Psychiatrists often fail to distinguish between reactive-depression (reaction to external event or circumstance) and endogenous-depression (biological) resulting, in part, from incorrectly distinguishing between conditions constitutive of ‘trait’ (endogenous) and of those of ‘state’ (e.g. reactive depression; adverse effects from medication, etc.). (shrink)

Some revisionary ontologies are highly parsimonious: they posit far fewer entities than what we quantify over in ordinary discourse. The most radical examples are minimal ontologies, on which physical simples are the only things that exist. Highly parsimonious ontologies, and especially minimal ones, face the challenge of either accounting for the truth of our ordinary quantificational discourse, or paraphrasing such discourse away. Common strategies for addressing this challenge include classical reduction, paraphrase nihilism, and a distinction between ontological and existence commitments. (...) I argue, however, that these strategies are either implausible or fail to provide truth conditions consistent with minimal or parsimonious ontologies. I then discuss, defend, and suggest ways to strengthen an alternative framework for reduction, on which the sentences of reducing theories ground those of reducible theories. Relative to the other options for defending minimal ontology, a strengthened grounding-reductive approach can provide more defensible truth conditions for minimal ontology, better preserve scientific realist intuitions, set a more attainable standard for reduction, and allow our existence commitments to be more responsive to empirical evidence and scientific expertise. As a result, I argue that minimal ontology becomes more defensible—though not certain—on a grounding-reductive framework. But even if minimal ontology were wrong, the grounding-reductive framework makes other parsimonious but non-minimal ontologies more plausible. (shrink)

Vaccine refusal forces us to confront tensions between many values, including scientific expertise, parental rights, children’s best interests, social responsibility, public trust, and community health. Recent outbreaks of vaccine-preventable and emerging infectious diseases have amplified these issues. The prospect of a coronavirus disease 2019 vaccine signals even more friction on the horizon. In this contentious sociopolitical landscape, it is therefore more important than ever for clinicians to identify ethically justified responses to vaccine refusal.

Eric Barnes’ The Paradox of Predictivism is concerned primarily with two facts: predictivism (the fact that novel predictions play an important part in scientificconfirmation) and pluralism (the fact that scientific development is not just a matter of isolated individuals judging the truth, but at least partly a matter of trusting legitimate experts). In the middle part of the book, he peers through these two lenses at the tired realist scarecrow of the no-miracles argument. He attempts to reanimate this weatherworn (...) realist argument, contra suggestions by people like me that it should be abandoned. In this paper, I want to get clear on Barnes’ contribution to the debate. He focuses on what he calls the miraculous endorsement argument, which explains not the success of a specific theory but instead the history of successes for an entire research program. The history of successes is explained by reliable and improving methods, which are the flipside of approximately true background theories. Yet, as Barnes notes, the whole story must begin with methods that are at least minimally reliable. Barnes demands that the realist explain the origin of the minimally reliable take-off point, and he suggests a way that the realist might do so. I contend that his explanation still relies on contingent developments and so fails to completely explain the development of take-off theories. However, this line of argument digs into familiar details of the no-miracles argument and overlooks what’s new in Barnes’ approach. By calling attention to pluralism, he reminds us that we need an account of scientific expertise. This is important, I suggest, because expertise is not indefinite. We do not trust specific experts for everything, but only for things within the bounds of their expertise. Drawing these boundaries relies on our own background theories and is only likely to be reliable if our background theories are approximately true. I argue, then, that pluralism gives us reason to be realists (about some things). (shrink)

This paper has two objectives 1) to study the influence of digital and new technology on COVID-19 diagnosis and healthcare 2) To propose the integral guideline solutions of the infectious disease for the future. COVID-19 stands for corona (CO), virus (VI), disease (D), or SARS-CoV-2, is a respiratory virus first identified in December 2019 in Wuhan, China(WHO, 2019). It is an epidemiological crisis that caused the deaths and sudden destruction of wealth and health of people around the world. Many countries (...) responded to the crisis with what could only be called urgent prevention and treatment. In the 21st century, our society is based on digital and new technology that can control and prevent the COVID-19 pandemics. However, these ways for solving the problem of COVID-19 pandemics are rising an epistemological crisis too. There are some problems with the COVID-19 diagnosis. From Buddhist philosophy perspective, COVID-19 teaches us the coronavirus is causing us to experience some heightened forms of the three marks of our existence which are the impermanence (aniccā), the suffering (duḥkha), and the non-self (anatta). The establishment of scientific expertise and innovation has shown its value and educating the public about testing, diagnosis, communication, treatment, and vaccine development technology for prevention the of infectious diseases in the future. (shrink)

Understanding the relationship between experts and laypeople is crucial for understanding today’s world of post-truth and the contemporary crisis of liberal democracy. The emergence of post-truth has been linked to various phenomena such as a flawed social and mass media ecosystem, poor citizen education, and the manipulation tactics of powerful interest groups. The paper argues that the problem is, however, more profound. The underlying issue is laypeople’s inevitable epistemic dependence on experts. The latter is part and parcel of the “risk (...) society” in which people question the scientific consensus and thus are able to manipulate the facts. It is a powerful weapon in the hands of illiberal democrats, though liberal democrats can make no use of it. The latter downplay the problem of citizens’ epistemic deficits and of the epistemic asymmetries between them. The third and fourth generations of deliberative democrats are a perfect example. The paper argues that the concepts of interactional expertise and epistemic dependence explain why understanding between experts and laypeople is impossible. The said phenomena undermine liberalism’s unrealistic assumptions concerning citizens’ decision-making competence. (shrink)

There are good, even if inconclusive, reasons to think that cognitive penetration of perception occurs: that cognitive states like belief causally affect, in a relatively direct way, the contents of perceptual experience. The supposed importance of – indeed as it is suggested here, what is definitive of – this possible phenomenon is that it would result in important epistemic and scientific consequences. One interesting and intuitive consequence entirely unremarked in the extant literature concerns the perception of art. Intuition has (...) it that knowledge about art changes how one aesthetically evaluates artworks. A profound explanation of this intuitive fact is that perceptual experiences vary with artistic expertise. Cognitive penetration provides an explanatory mechanism for this latter effect. What one knows or otherwise thinks about art may affect, in one of two ways sketched below, how one perceives art. Differences in aesthetic evaluation may follow, either because high-level aesthetic properties can be perceptually represented or because they causally depend on low-level perceptible properties. All of this lends credence to the hypothesis that the expert better judges art because she better perceives art. And she better perceives art because she better knows art. (shrink)

Historically, scientific and engineering expertise has been key in shaping research and innovation policies, with benefits presumed to accrue to society more broadly over time. But there is persistent and growing concern about whether and how ethical and societal values are integrated into R&I policies and governance, as we confront public disbelief in science and political suspicion toward evidence-based policy-making. Erosion of such a social contract with science limits the ability of democratic societies to deal with challenges presented (...) by new, disruptive technologies, such as synthetic biology, nanotechnology, genetic engineering, automation and robotics, and artificial intelligence. Many policy efforts have emerged in response to such concerns, one prominent example being Europe's Eighth Framework Programme, Horizon 2020, whose focus on “Responsible Research and Innovation” provides a case study for the translation of such normative perspectives into concrete policy action and implementation. Our analysis of this H2020 RRI approach suggests a lack of consistent integration of elements such as ethics, open access, open innovation, and public engagement. On the basis of our evaluation, we suggest possible pathways for strengthening efforts to deliver R&I policies that deepen mutually beneficial science and society relationships. (shrink)

Explanations of former South African President Thabo Mbeki’s public and private views on the aetiology of the HIV/AIDS epidemic in the country remain partial at best without the recognition that the latter presuppose and imply a postmodernist/postcolonialist philosophy of science that erases the line separating the political from the scientific. Evidence from Mbeki’s public speeches, interviews, and private and anonymous writings suggests that it was postmodernist/postcolonialist theory that inspired him to doubt the “Western” scientific consensus on HIV/AIDS and (...) to implement a public health policy that dragged its feet on full roll-out of antiretroviral therapy, causing thousands of avoidable deaths. A weak reductio ad absurdum allows us to conclude from this premise that postmodernist/postcolonial critique of “Western” science ought to be shunned. A comparative argument from consequences further suggests that in a situation where a misguided health policy has lead to a humanitarian catastrophe, and where postmodernist/postcolonialist critique of science can and has been used to justify this policy, an alternative theory ought to be preferred on which such justification would not be possible. The paper closes with a call for a non-relativist alternative to postmodernist/postcolonialist philosophy of science, and evaluates the potential of recent developments in ‘Studies of Expertise” to yield such. (shrink)

ABSTRACT: Abstract Most modern knowledge is not science. The physical sciences have successfully validated theories to infer they can be used universally to predict in previously unexperienced circumstances. According to the conventional conception of science such inferences are falsified by a single irregular outcome. And verification is by the scientific method which requires strict regularity of outcome and establishes cause and effect. -/- Medicine, medical research and many “soft” sciences are concerned with individual people in complex heterogeneous populations. These (...) populations cannot be tested to demonstrate strict regularity of outcome in every individual. Neither randomised controlled trials nor observational studies in medicine are science in the conventional conception. Establishing and using medical and other “soft science” theories cannot be scientific. It requires conceptually different means: requiring expert judgement applying all available evidence in the relevant available factual matrix. -/- The practice of medicine is observational. Prediction of outcomes for the individual requires professional expertise applying available medical knowledge and evidence. Expertise in any profession can only be acquired through experience. Prior cases are the fundament of knowledge and expertise in medicine. Case histories, studies and series can provide knowledge of extremely high reliability applicable to establishing reliable general theories and falsifying others. Their collation, study and analysis should be a priority in medicine. Their devaluation as evidence, the failure to apply their lessons, the devaluation of expert professional judgement and the attempt to emulate the scientific method are all historic errors in the theory and practice of modern medicine. (shrink)

Despite its public visibility and impact on policy, the activity of expert communication rarely receives more than a passing mention in codes of scientific integrity. This paper makes the case for an ethics of expert communication, introducing a framework where expert communication is represented as an intrinsically ethical activity of a deliberative agent. Ethical expert communication cannot be ensured by complying with various requirements, such as restricting communications to one's area of expertise or disclosing conflicts of interest. Expert (...) communication involves morally laden trade‐offs that must be weighed by a deliberative agent. A basic normative framework is introduced, and concrete provisions are proposed for codes of scientific integrity. (shrink)

The question of what ontological insights can be gained from the knowledge of physics (keyword: ontic structural realism) cannot obviously be completely separated from the view of physics as a science from an epistemological perspective. This is also visible in the debate about 'scientific realism'. This debate makes it clear, in the form of the importance of perception as a criterion for the assertion of existence in relation to the 'theoretical entities' of physics, that epistemology itself is 'ontologically loaded'. (...) This is in the form of the assumption that things in themselves (independent of cognition, in an autonomous way) exist as so-and-so determined ones. This ontological assumption is not only the basis of our (naive) conception of knowledge, but also its indispensable premise, insofar as this conception is a fundamentally passive, 'receptive' one. This is true to the full extent of metaphysics, and to a not much lesser extent of epistemology. The interpretation of knowledge in the sense of 'description' seems to be without alternative. In the philosophy of science, this view is reflected in the emphasis on 'objectivity' as the essence of science, in the belief in 'induction' as the traditional method of science, and (ex negativo) in the problem of the 'theory laden nature of observation'. To these paradigms of epistemology, however, a further aggravating factor is added, namely the criterion of 'subjective certainty' as evidence of 'real' knowledge (only meaningful on the basis of the ontological premise mentioned above). Thus, due to its 'expertise' in matters of knowledge, epistemology becomes the 'prima philosophia'. But what is even more important, the real, holistic cognitive situation is transformed into a linear cognitive relationship, with the consequence of the 'transcendence' of the objects. Now, on closer inspection, however, there is not too much in the expertise of epistemology, because it basically consists only of paradigms which, from the point of view of the holism of the real cognitive situation itself, are nothing more than relatively simplistic interpretations of this situation. However, we do not yet know what another conception of knowledge might look like (which is not surprising given the position of the phenomenon of knowledge in the hierarchy of phenomena according to their complexity). 'Certitude' as a criterion of cognition is thus excluded from the outset, and thus the linear relational model of cognition also appears as what it is, a gross distortion of the real, holistic situation of cognition. The significance of this argumentation with regard to physics is that the linear epistemological model of cognition itself is a major obstacle to an adequate epistemological understanding of physics. This is because it is fixed 'a priori' to an object-related concept of knowledge, and to 'description' as the only mode of ('real') knowledge. The acceptance of the real, holistic epistemological situation is therefore, in my opinion, the condition for an adequate understanding of physics' heuristic access to objects, its transcendental, generalizing epistemological concept, as well as its ontological relevance and dimension. (shrink)

There is a middle ground of imperfect knowledge in fields like medicine and the social sciences. It stands between our day-to-day relatively certain knowledge obtained from ordinary basic observation of regularities in our world and our knowledge from well-validated theories in the physical sciences. -/- The latter enable reliable prediction a great deal of the time of the happening of events never before experienced. The former enable prediction only of what has happened before and beyond that of educated guesses which (...) may sometimes prove right and others not when we test them. -/- The imperfection of our knowledge between those limits is a consequence of complexity. -/- Reductionist empiricism fails when faced with complexity but we all still have to live in a complex world where reductionist science cannot help us devise reliable theories from which we can predict the behaviour of the world around us. We cannot predict reliably. We can only monitor actively and manage actively the world around us if we want to try to control our environment. We have a limited prediction horizon. -/- Science and empiricism work well if we want to send Voyager I and II over 3 billion miles away but not for most other things. -/- In medicine how and when to apply probabilistic, conjectural, incomplete medical theories and explanations requires professional expertise, intuition and judgement (non scientific knowledge) which is essential. Medical diagnosis is a skill of predicting from knowledge of what has happened before that the past will recur in the current patient applying expertise and intuition from knowledge and experience of prior cases and probabilistic medical research and theory. The physician is left to an educated guess as to how the future will develop for the particular individual patient the focus of his or her current attention. (shrink)

The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery rate (...) was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The research found the following results: there is a fair degree of approval on "cognitive dimension", there is a high approval about the importance of "organizational dimension", there is moderately consent of the importance of "Community dimension", there is a large degree of consent about the importance of axis of the "leadership excellence", there is a large degree of consent about the importance of axis of the "service-excellence", there is a fair degree approval about the importance of the axis of "cognitive excellence", and there is a moderately consent of the importance of "Organizational Excellence". The research found a group of recommendations including: the need to develop appropriate strategies for the University, employ modern technology in information systems, in addition to provide appropriate environment that achieve learning organizations, develop technological infrastructure, adopt universities for knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments, create technological incubators in universities to adopt excellence academic research projects, and protected them, support them, and market them. Establishing of centers of excellence for scientific research in the university.The need for cooperation and coordination between local, Arab and international universities for the exchange of knowledge, information, and participation programs and training courses, as it provides an opportunity to develop the capabilities and skills of personnel and expertise. (shrink)

Over the last decade, a call for greater “realism” in political theory has challenged the goals and methods that are implicit in much contemporary “normative” theory. However, realists have yet to produce a convincing alternative research program that is “constructive” rather than primarily “critical” in nature. I argue that given their common wariness of a devotion to abstract principles, realists should consider adopting John Dewey’s vision of theoretical expertise as an expansive kind of prediction that engages all of our (...) historical, scientific, and imaginative resources. After demonstrating that realists are in need of such an affirmative vision, I outline Dewey’s original proposal, and elaborate its value in contemporary circumstances as a “predictive” method for political theory that stands between familiar critical and normative approaches. (shrink)

Following Michael S. Jones’ call for articles showing the contemporary value of the great 20th century Romanian philosopher Lucian Blaga in various spheres of expertise, I have immediately thought of George F. Steiner’s recently published book, Neanderthals in Plato’s Cave. The evolutionary model forwarded by Steiner draws heavily on philosophical insights provided by Blaga and, although the volume was written for a scientifically-minded public, the author has adopted, updated and expanded some of Blaga’s anthropological perspectives. In our e-mail correspondence, (...) Steiner has acknowledged Blaga’s influence and has enthusiastically endorsed my attempt to review the similarities between some of the postulates of contemporary research in the various disciplines that inform cognitive archaeology – Steiner’s field of expertise – and the conceptual evolutionary/cultural hypothesis outlined in Blaga’s philosophical system. (shrink)

Misinformation can have significant societal consequences. For example, misinformation about climate change has confused the public and stalled support for mitigation policies. When people lack the expertise and skill to evaluate the science behind a claim, they typically rely on heuristics such as substituting judgment about something complex (i.e. climate science) with judgment about something simple (i.e. the character of people who speak about climate science) and are therefore vulnerable to misleading information. Inoculation theory offers one approach to effectively (...) neutralize the influence of misinformation. Typically, inoculations convey resistance by providing people with information that counters misinformation. In contrast, we propose inoculating against misinformation by explaining the fallacious reasoning within misleading denialist claims. We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims. This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language. Focusing on argument structure also facilitates the identification of reasoning fallacies by locating them in the reasoning process. Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science. We applied this approach to 42 common denialist claims and find that they all demonstrate fallacious reasoning and fail to refute the scientific consensus regarding anthropogenic global warming. This comprehensive deconstruction and refutation of the most common denialist claims about climate change is designed to act as a resource for communicators and educators who teach climate science and/or critical thinking. (shrink)

Especially but not exclusively in the United States, there is a significant gulf between expert opinion and public opinion on a range of important political, social, and scientific issues. Large numbers of lay people hold views contrary to the expert consensus on topics such as climate change, vaccines, and economics. Much political commentary assumes that ordinary people should defer to experts more than they do, and this view is certainly lent force by the literally deadly effects of many denials (...) of established science. But there are complex philosophical issues here, concerning, among other things, (i) what an expert is; (ii) what kind of deference is called for; (iii) and when deference is called for. This entry gives an overview of these three issues and recent work on them. It then examines some potential collective and pragmatic disadvantages of deference, before concluding with reflections on what we can say to those who distrust experts. (shrink)

Innovative modes of collaboration between archaeologists and Indigenous communities are taking shape in a great many contexts, in the process transforming conventional research practice. While critics object that these partnerships cannot but compromise the objectivity of archaeological science, many of the archaeologists involved argue that their research is substantially enriched by them. I counter objections raised by internal critics and crystalized in philosophical terms by Boghossian, disentangling several different kinds of pluralism evident in these projects and offering an analysis of (...) why they are epistemically productive when they succeed. My central thesis is that they illustrate the virtues of epistemic inclusion central to proceduralist accounts of objectivity, but I draw on the resources of feminist standpoint theory to motivate the extension of these social -cognitive norms beyond the confines of the scientific community. (shrink)

[File is the introduction to the monograph] -/- Abstract to monograph -/- How and whether thinking affects perceiving is a deeply important question. Of course it is of scientific interest: to understand the human mind is to understand how we best distinguish its processes, how those processes interact, and what this implies for how and what we may know about the world. And so in the philosopher’s terms, this book is one on both mental architecture and the epistemology of (...) perception. But there is a more human interest. How we make contact with the world, and with one another, is of the most basic of importance. We can make both sensory contact and cognitive contact with the world. The first is traditionally supposed to be determined by the biological nature of our sensory systems, while the second is at least partly determined by us, what we have learned, our experiences, and so on. The most basic claim of the book is that this is mistaken and importantly so. Our sensory contact with the world can also change and in a way that is importantly affected by the cognitive contact that we have, or have had, with the world. Thinking does not just affect perceiving, thinking improves perceiving. If this is true, it changes not only how we should theorize the mind, it changes how we should understand, as individuals, our place in and contact with the world. (shrink)

Around 97% of climate scientists endorse anthropogenic global warming (AGW), the theory that human activities are partly responsible for recent increases in global average temperatures. Clearly, this widespread endorsement of AGW is a reason for non-experts to believe in AGW. But what is the epistemic significance of the fact that some climate scientists do not endorse AGW? This paper contrasts expert unanimity, in which virtually no expert disagrees with some theory, with expert consensus, in which some non-negligible proportion either rejects (...) or is uncertain about the theory. It is argued that, from a layperson’s point of view, an expert consensus is often stronger evidence for a theory’s truth than unanimity. Several lessons are drawn from this conclusion, e.g. concerning what laypeople should infer from expert pronouncements, how journalists should report on scientific theories, and how working scientists should communicate with the public. (shrink)

Our culture is conflicted about morally judging and condemning. We can't avoid it altogether, yet many layfolk today are loathe to do it for reasons neither they nor philosophers well understand. Their resistance is often confused (by themselves and by theorists) with some species of antiobjectivism. But unlike a nonobjectivist, most people think that (a) for us to judge and condemn is generally (objectively) morally wrong , yet (b) for God to do so is (objectively) proper, and (c) so too (...) for certain persons in certain relations (e.g., self-condemnation, parental child rearing.) Certainly, religious (e.g., Christian) critics of judging and condemning without doubting the objective truth of their tradition's core moral teachings. Most puzzling is that (a) merely judging and condemning in one's heart may be improper, and (b) someone else with no more evidence or expertise might properly judge and condemn the same action. The answer is in condemning's complex structure of presuppostions. Condemning and judging are acts, and attitudes initiated by the act. Condemnation is motivated by two judgments presumed to justify it, a criticism of a target, and a judgment that the criticism justifies some negative response toward the target. Unlike nonpunitive penalties, punishments are motivated and explained by condemnation. Condemnation is an act of a hostile will, wishing some evil for its target, not (just) as a means to some good. Its root is in damning, an act akin to cursing. It declares a degraded status. The hostility makes it harder to justify condemnation than criticism, and punishment than nonpunitive penalties. Condemning claims objectivity and authority. It involves reflexive evaluation, regarding itself justified, approving its hostile feelings toward the target. Condemners presume themselves entitled to sit in judgment, pass judgment, and cast the condemned down. Those presumptions inhere in sitting in judgment, assuming jurisdiction. Unlike mathematical or scientific judgments, passing moral judgment seems to be a political act subject to extraepistemic constraints. "Who are you to judge?" may properly challenge your right to pass judgment. (shrink)

This article focuses on epistemic challenges related to the democratisation of scientific knowledge production, and to the limitations of current social accounts of objectivity. A process of ’democratisation’ can be observed in many scientific and academic fields today. Collaboration with extra-academic agents and the use of extra-academic expertise and knowledge has become common, and researchers are interested in promoting socially inclusive research practices. As this development is particularly prevalent in policy-relevant research, it is important that the new, (...) more democratic forms of research be objective. In social accounts of objectivity only epistemic communities are taken to be able to produce objective knowledge, or the entity whose objectivity is to be assessed is precisely such a community. As I argue, these accounts do not allow for situations where it is not easy to identify the relevant epistemic community. Democratisation of scientific knowledge production can lead to such situations. As an example, I discuss attempts to link indigenous oral traditions to floods and tsunamis that happened hundreds or even thousands of years ago. (shrink)

This paper outlines the intellectual biography of Walter Dubislav. Besides being a leading member of the Berlin Group headed by Hans Reichenbach, Dubislav played a defining role as well in the Society for Empirical/Scientific Philosophy in Berlin. A student of David Hilbert, Dubislav applied the method of axiomatic to produce original work in logic and formalist philosophy of mathematics. He also introduced the elements of a formalist philosophy of science and addressed more general problems concerning the substantiation of human (...) knowledge. What set Dubislav apart from the other logical empiricists was his expertise in the history of logic and exact philosophy which enabled him to elucidate and advance the thinking in both disciplines. In the realm of logic proper, Dubislav is best known for his pioneering work in theory of definitions. What is more, he did original work on the so called ‘quasi truth-tables’ which aided Reichenbach in developing his logic of probability. Dubislav also elaborated an influe.. (shrink)