The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to (...) existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource providing details on the people, policies, and issues being addressed in association with OBI. (shrink)

What is the role of conscious experience in the epistemology of perceptual knowledge: how should we characterise what is going on in seeing that o is F in order to illuminate the contribution of seeing o to their status as cases of knowing that o is F? My proposal is that seeing o involves conscious acquaintance with o itself, the concrete worldly source of the truth that o is F, in a way that may make it evident to the subject (...) that o is an instance of ‘x is F’ as she understands this, and hence evident that o is F. Seeing that o is F is thus a way of its being evident that o is F and is therefore a way of knowing that o is F. (shrink)

Trust is both ethically important and essential for business but difficult to measure. This paper contributes toward clarifying the nature of trust in a way that is both conceptually helpful for ethical inquiries concerning business and pertinent to the measurement of trust as an element in organizations. Several papers hypothesize that increasing the role of trust in a corporation reduces the need for external monitoring and contracts. Assessing this important hypothesis requires a way to gauge whether a firm has a (...) trusting corporate culture. We develop an objective measure of trust in a firm’s corporate culture by counting the number of times 21 trust-related words appear in an important kind of document: the Management Discussion and Analysis section of the annual report. We report two significant findings: that, contrary to what one might think, firms with a trusting culture frequently use audit and control-type words and that trust is positively linked with subsequent share price volatility. We propose explanations of these findings with the hope of facilitating the objective measurement of trust and enhancement of a trusting atmosphere in corporate culture. (shrink)

The term robustness is ubiquitous in modern Machine Learning (ML). However, its meaning varies depending on context and community. Researchers either focus on narrow technical definitions, such as adversarial robustness, natural distribution shifts, and performativity, or they simply leave open what exactly they mean by robustness. In this paper, we provide a conceptual analysis of the term robustness, with the aim to develop a common language, that allows us to weave together different strands of robustness research. We define robustness as (...) the relative stability of a robustness target with respect to specific interventions on a modifier. Our account captures the various sub-types of robustness that are discussed in the research literature, including robustness to distribution shifts, prediction robustness, or the robustness of algorithmic explanations. Finally, we delineate robustness from adjacent key concepts in ML, such as extrapolation, generalization, and uncertainty, and establish it as an independent epistemic concept. (shrink)

Issues of reliability are claiming center-stage in the epistemology of machine learning. This paper unifies different branches in the literature and points to promising research directions, whilst also providing an accessible introduction to key concepts in statistics and machine learning – as far as they are concerned with reliability.

This paper examines the role that population vulnerabilities play in insurance coverage for a representative sample of Latinos and Asians in the United States. Using data from the National Latino and Asian American Study (NLAAS), these analyses compare coverage differences among and within ethnic subgroups, across states and regions, among types of occupations, and among those with or without English language proficiency. Extensive differences exist in coverage between Latinos and Asians, with Latinos more likely to be uninsured. Potential explanations include (...) the type of occupations available to Latinos and Asians, reforms in immigration laws, length of time in the United States, and regional differences in safety-net coverage. Policy implications are discussed. (shrink)

This study considers the role of different cognitive units in sound change: phonemes, contextual variants and words. We examine /u/-fronting and /j/-dropping in data from three generations of Derby English speakers. We analyze dynamic formant data and auditory judgments, using mixed effects regression methods, including generalized additive mixed models (GAMMs). /u/-fronting is reaching its end-point, showing complex conditioning by context and a frequency effect that weakens over time. /j/-dropping is declining, with low-frequency words showing more innovative variants with /j/ than (...) high-frequency words. The two processes interact: words with variable /j/-dropping (new) exhibit more fronting than words that never have /j/ (noodle) even when the /j/ is deleted. These results support models of change that rely on phonetically detailed representations for both word- and sound-level cognitive units. (shrink)

Best known for his influential History of Greece, the historian and politician George Grote wrote this account of Plato's dialogues as a philosophical supplement to the History. First published in 1865 and written in dialogic form, Grote's account of Plato's works includes substantial footnotes and marginalia. This first volume focuses on Plato's early and transitional dialogues, all of which feature Socrates. It also includes a preface to the whole project which discusses the meaning and importance of philosophy itself, (...) and extensive introductory material on pre-Socratic philosophy, the life of Plato and history of the Platonic canon. With three volumes each running to over six hundred pages, Grote's scholarship is formidably comprehensive. The publication of Plato and the Other Companions of Sokrates confirmed him as one of the greatest authorities on Plato in the nineteenth century. (shrink)

When scientists act unethically, their actions can cause harm to participants, undermine knowledge creation, and discredit the scientific community. Responsible Conduct of Research training i...

This article examines the various pedagogic models suggested by widely used texts and finds them to be predominately rule-based or rule directed. These approaches to the subject matter of business ethics are quite valuable ones, but we find them to leave no room for the study of the virtues. We intend to articulate our reasons for supporting a central if not exclusive role for virtue ethics.

A taped conversational interview with Daniel Dennett and Bill Uzgalis covers a wide range of topics arising from Dennett’s thoughts about computing and human beings. The background of Dennett’s work is explored as are his views about mind-brain identity theory, artificial intelligence, functionalism, human exceptionalism, animal culture, language, pain, freedom and determinism, and quality of life.

In recent years, a plethora of high-profile scientific publications has been reporting about machine learning algorithms outperforming clinicians in medical diagnosis or treatment recommendations. This has spiked interest in deploying relevant algorithms with the aim of enhancing decision-making in healthcare. In this paper, we argue that instead of straightforwardly enhancing the decision-making capabilities of clinicians and healthcare institutions, deploying machines learning algorithms entails trade-offs at the epistemic and the normative level. Whereas involving machine learning might improve the accuracy of medical (...) diagnosis, it comes at the expense of opacity when trying to assess the reliability of given diagnosis. Drawing on literature in social epistemology and moral responsibility, we argue that the uncertainty in question potentially undermines the epistemic authority of clinicians. Furthermore, we elucidate potential pitfalls of involving machine learning in healthcare with respect to paternalism, moral responsibility and fairness. At last, we discuss how the deployment of machine learning algorithms might shift the evidentiary norms of medical diagnosis. In this regard, we hope to lay the grounds for further ethical reflection of the opportunities and pitfalls of machine learning for enhancing decision-making in healthcare. (shrink)

The application of machine-learning technologies to medical practice promises to enhance the capabilities of healthcare professionals in the assessment, diagnosis, and treatment, of medical conditions. However, there is growing concern that algorithmic bias may perpetuate or exacerbate existing health inequalities. Hence, it matters that we make precise the different respects in which algorithmic bias can arise in medicine, and also make clear the normative relevance of these different kinds of algorithmic bias for broader questions about justice and fairness in healthcare. (...) In this paper, we provide the building blocks for an account of algorithmic bias and its normative relevance in medicine. (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)

The SAGE Handbook of Complexity and Management will be the first substantive scholarly work to provide a map of the state of art research in the growing field ...

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)

In recent years, there has been a surge of high-profile publications on applications of artificial intelligence (AI) systems for medical diagnosis and prognosis. While AI provides various opportunities for medical practice, there is an emerging consensus that the existing studies show considerable deficits and are unable to establish the clinical benefit of AI systems. Hence, the view that the clinical benefit of AI systems needs to be studied in clinical trials—particularly randomised controlled trials (RCTs)—is gaining ground. However, an issue that (...) has been overlooked so far in the debate is that, compared with drug RCTs, AI RCTs require methodological adjustments, which entail ethical challenges. This paper sets out to develop a systematic account of the ethics of AI RCTs by focusing on the moral principles of clinical equipoise, informed consent and fairness. This way, the objective is to animate further debate on the (research) ethics of medical AI. (shrink)

This paper develops an account of how the implementation of ML models into healthcare settings requires revising the methodological apparatus of philosophical bioethics. On this account, ML models are cognitive interventions that provide decision-support to physicians and patients. Due to reliability issues, opaque reasoning processes, and information asymmetries, ML models pose inferential problems for them. These inferential problems lay the grounds for many ethical problems that currently claim centre-stage in the bioethical debate. Accordingly, this paper argues that the best way (...) to make progress in remedying these ethical problems is to distil their epistemic core and to identify appropriate epistemic norms as guardrails. The viability of this approach will be highlighted based on four key issues: trust, responsibility, paternalism, and fairness. In that respect, the paper also contributes to a more pronounced view of the specific methodological challenges for ethical theorizing, when the point of reference are complex statistical models that make predictions, rather than individual agents, acting for reasons. (shrink)

There is much to learn from Durán and Jongsma’s paper.1 One particularly important insight concerns the relationship between epistemology and ethics in medical artificial intelligence. In clinical environments, the task of AI systems is to provide risk estimates or diagnostic decisions, which then need to be weighed by physicians. Hence, while the implementation of AI systems might give rise to ethical issues—for example, overtreatment, defensive medicine or paternalism2—the issue that lies at the heart is an epistemic problem: how can physicians (...) know whether to trust decisions made by AI systems? In this manner, various studies examining the interaction of AI systems and physicians have shown that without being able to evaluate their trustworthiness, especially novice physicians become over-reliant on algorithmic support—and ultimately are led astray by incorrect decisions.3–5 This leads to a second insight from the paper, namely that even if some AI system happens to be opaque, it is still not built on the moon. To assess its trustworthiness, AI developers or physicians have different sorts of higher order evidence at hand. Most importantly, …. (shrink)

Bill Brewer presents an original view of the role of conscious experience in the acquisition of empirical knowledge. He argues that perceptual experiences must provide reasons for empirical beliefs if there are to be any determinate beliefs at all about particular objects in the world. This fresh approach to epistemology turns away from the search for necessary and sufficient conditions for knowledge and works instead from a theory of understanding in a particular area.

Contrary to the view that Francis Hutcheson attempted to expound, defend, and further develop the philosophical system described in Shaftesbury's Characteristics, some contemporaries of Hutcheson considered Hutcheson's differences from Shaftesbury to be at least as profound as the similarities. The clearest descriptions of those differences can be found in William Leechman's preface to Hutcheson's 1755 System of Moral Philosophy, and more elaborately in a review of Hutcheson's System, probably by Hugh Blair, published in the 1755 Edinburgh Review. Examining Shaftesbury's and (...) Hutcheson's moral philosophies in light of these two descriptions reveals that Shaftesbury's defense of virtue as natural to human beings, while a plausible response to Locke, clearly did not escape Hutcheson's censure of Epicurean egoism. (shrink)

Journal of Mathematical Logic, Ahead of Print. Let [math] be an integer. We show that the set of real numbers that are Poisson generic in base [math] is [math]-complete in the Borel hierarchy of subsets of the real line. Furthermore, the set of real numbers that are Borel normal in base [math] and not Poisson generic in base [math] is complete for the class given by the differences between [math] sets. We also show that the effective versions of these results (...) hold in the effective Borel hierarchy. (shrink)

This paper presents our work on textual inference and situates it within the context of the larger goals of machine reading. The textual inference task is to determine if the meaning of one text can be inferred from the meaning of another and from background knowledge. Our system generates semantic graphs as a representation of the meaning of a text. This paper presents new results for aligning pairs of semantic graphs, and proposes the application of natural logic to derive inference (...) decisions from those aligned pairs. We consider this work as first steps toward a system able to demonstrate broad-coverage text understanding and learning abilities. (shrink)

This paper develops an account of the opacity problem in medical machine learning (ML). Guided by pragmatist assumptions, I argue that opacity in ML models is problematic insofar as it potentially undermines the achievement of two key purposes: ensuring generalizability and optimizing clinician–machine decision-making. Three opacity amelioration strategies are examined, with explainable artificial intelligence (XAI) as the predominant approach, challenged by two revisionary strategies in the form of reliabilism and the interpretability by design. Comparing the three strategies, I argue that (...) interpretability by design is most promising to overcome opacity in medical ML. Looking beyond the individual opacity amelioration strategies, the paper also contributes to a deeper understanding of the problem space and the solution space regarding opacity in medical ML. (shrink)

Nathan Hanna has recently argued against a position I defend in a 2013 paper in this journal and in my 2016 book on punishment, namely that we can punish someone without intending to harm them. In this discussion note I explain why two alleged counterexamples to my view put forward by Hanna are not in fact counterexamples to any view I hold, produce an example which shows that, if we accept a number of Hanna’s own assumptions, punishment does not require (...) an intention to harm, and discuss whether a definition and counter-example approach is the best way to proceed in the philosophy of punishment. I conclude with a brief exegetical discussion of H.L.A Hart’s Prolegomenon to the Principles of Punishment. (shrink)

The standard paradigm for mental causation is a person’s acting for a reason. Something happens - she intentionally φ’s - the occurrence of which we explain by citing a relevant belief or desire. In the present context, I simply take for granted the following two conditions on the appropriateness of this explanation. First, the agent φ’s _because_ she believes/desires what we say she does, where this is expressive of a _causal_ dependence.1 Second, her believing/desiring this gives her a _reason_ for (...) φ-ing: recognizing that she has this belief/desire makes her φ-ing intelligible as rational in the light of her other attitudes and circumstances. A further condition must be met, though, if this is to be a genuine psychological explanation, a case of her acting _for_ the reason in question. Consider the following example of Davidson’s (1973, p. 79). An exhausted climber is desperate to rid herself of the weight and danger of holding her partner on a rope; and her sudden realization that simply letting go would achieve this so unnerves her that her grip loosens slightly and he falls. Her releasing him causally depends upon her having this belief and desire, which provide _a_ reason for doing what she does. But this is not _why_ she does it: it would be at best misleading to say that she dropped him, intentionally, because she was fed up with holding his weight, or because she thought that she might otherwise fall. Her letting go does not depend upon her having these reasons in the right way. The reason-giving relation is causally irrelevant. If we are to explain a person’s acting _for_ a reason, then her doing. (shrink)

Is the God of Calvin a fountain of blessing, or a forceful tyrant? Is Calvin's view of God coercive, leaving no place for the human qua human in redemption? These are perennial questions about Calvin's theology which have been given new life by Gift theologians such as John Milbank, Graham Ward, and Stephen Webb.J. Todd Billings addresses these questions by exploring Calvin's theology of `participation in Christ'. He argues that Calvin's theology of `participation' gives a positive place to the human, (...) such that grace fulfils rather than destroys nature, affirming a differentiated union of God and humanity in creation and redemption. Calvin's trinitarian theology of participation extends to his view of prayer, sacraments, the law, and the ecclesial and civil orders. In light of Calvin's doctrine of participation, Billings reframes the critiques of Calvin in the Gift discussion and opens up new possibilities for contemporary theology, ecumenical theology, and Calvin scholarship as well. (shrink)

Broadly defined as adherence to teachings of Christian Wolff (1679–1754), Wolffianism characterized much of the mainstream of German academic philosophy for at least half the eighteenth century. German Pietism, by contrast, defined in its narrowest sense as a late-seventeenth- and eighteenth-century movement for the renewal of the Lutheran Churches of the Holy Roman Empire, has long figured in the history of German “Enlightenment” philosophy as Wolffianism’s anti-philosophical, religious foil. The conventional portrait of Wolffianism and Pietism as antithetical to one another, (...) which has long structured the historiography of eighteenth-century German philosophy, is by no means implausible, but it has been undermined over the past several decades by a significant and growing body of new research. This essay offers a panoramic survey and critical assessment of the state of the field. (shrink)

Berichte zur Wissenschaftsgeschichte, EarlyView.