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)

Throughout the biological and biomedical sciences there is a growing need for, prescriptive ‘minimum information’ (MI) checklists specifying the key information to include when reporting experimental results are beginning to find favor with experimentalists, analysts, publishers and funders alike. Such checklists aim to ensure that methods, data, analyses and results are described to a level sufficient to support the unambiguous interpretation, sophisticated search, reanalysis and experimental corroboration and reuse of data sets, facilitating the extraction of maximum value from data sets (...) them. However, such ‘minimum information’ MI checklists are usually developed independently by groups working within representatives of particular biologically- or technologically-delineated domains. Consequently, an overview of the full range of checklists can be difficult to establish without intensive searching, and even tracking thetheir individual evolution of single checklists may be a non-trivial exercise. Checklists are also inevitably partially redundant when measured one against another, and where they overlap is far from straightforward. Furthermore, conflicts in scope and arbitrary decisions on wording and sub-structuring make integration difficult. This presents inhibit their use in combination. Overall, these issues present significant difficulties for the users of checklists, especially those in areas such as systems biology, who routinely combine information from multiple biological domains and technology platforms. To address all of the above, we present MIBBI (Minimum Information for Biological and Biomedical Investigations); a web-based communal resource for such checklists, designed to act as a ‘one-stop shop’ for those exploring the range of extant checklist projects, and to foster collaborative, integrative development and ultimately promote gradual integration of checklists. (shrink)

Cognitivism in respect to the arts refers to a constellation of positions that share in common the idea that artworks often bear, in addition to aesthetic value, a significant kind of cognitive value. In this paper I concentrate on three things: (i) the challenge of understanding exactly what one must do if one wishes to defend a cognitivist view of the arts; (ii) common anti-cognitivist arguments; and (iii) promising recent attempts to defend cognitivism.

A viable theory of literary humanism must do justice to the idea that literature offers cognitive rewards to the careful reader. There are, however, powerful arguments to the effect that literature is at best only capable of offering idle visions of a world already well known. In this essay I argue that there is a form of cognitive awareness left unmentioned in the traditional vocabulary of knowledge acquisition, a form of awareness literature is particularly capable of offering. Thus even if (...) it is the case that literature has nothing interesting to give us in the way of knowledge, the literary humanist can consistently maintain that literary experience is thoroughly cognitive. (shrink)

What is the relation between works of fiction and the acquisition of knowledge?

This paper raises a slightly uncomfortable question: are some delusional subjects responsible for their delusions? This question is uncomfortable because we typically think that the answer is pretty clearly just ‘no’. However, we also accept that self-deception is paradigmatically intentional behavior for which the self-deceiver is prima facie blameworthy. Thus, if there is overlap between self-deception and delusion, this will put pressure on our initial answer. This paper argues that there is indeed such overlap by offering a novel philosophical account (...) of self-deception. The account offered is independently plausible and avoids the main problems that plague other views. It also yields the result that some delusional subjects are self-deceived. The conclusion is not, however, that those subjects are blameworthy. Rather, a distinction is made between blameworthiness and ‘attributability’. States or actions can be significantly attributable to a subject—in the sense that they are expressions of their wills—without it being the case that the subject is blameworthy, if the subject has an appropriate excuse. Understanding delusions within this framework of responsibility and excuses not only illuminates the ways in which the processes of delusional belief formation and maintenance are continuous with ‘ordinary’ processes of belief formation and maintenance, it also provides a way of understanding the innocence of the delusional subject that does not involve the denial of agency. (shrink)

It is often assumed that literary meaning is essentially linguistic in nature and that literary interpretation is therefore a purely linguistic affair. This essay identifies a variety of literary meaning that cannot be reduced to linguistic meaning. Meaning of this sort is generated not by a communicative act so much as through a creative one: the construction of a fictional world. The way in which a fictional world can bear meaning turns out to be strikingly unlike the way a sentence (...) can, and this, I argue, has important implications for the theory of interpretation. (shrink)

Definition of the problem The umbrella term “explicability” refers to the reduction of opacity of artificial intelligence (AI) systems. These efforts are challenging for medical AI applications because higher accuracy often comes at the cost of increased opacity. This entails ethical tensions because physicians and patients desire to trace how results are produced without compromising the performance of AI systems. The centrality of explicability within the informed consent process for medical AI systems compels an ethical reflection on the trade-offs. Which (...) levels of explicability are needed to obtain informed consent when utilizing medical AI? Arguments We proceed in five steps: First, we map the terms commonly associated with explicability as described in the ethics and computer science literature, i.e., disclosure, intelligibility, interpretability, and explainability. Second, we conduct a conceptual analysis of the ethical requirements for explicability when it comes to informed consent. Third, we distinguish hurdles for explicability in terms of epistemic and explanatory opacity. Fourth, this then allows to conclude the level of explicability physicians must reach and what patients can expect. In a final step, we show how the identified levels of explicability can technically be met from the perspective of computer science. Throughout our work, we take diagnostic AI systems in radiology as an example. Conclusion We determined four levels of explicability that need to be distinguished for ethically defensible informed consent processes and showed how developers of medical AI can technically meet these requirements. (shrink)

Recent years have witnessed intensive efforts to specify which requirements ethical artificial intelligence (AI) must meet. General guidelines for ethical AI consider a varying number of principles important. A frequent novel element in these guidelines, that we have bundled together under the term explicability, aims to reduce the black-box character of machine learning algorithms. The centrality of this element invites reflection on the conceptual relation between explicability and the four bioethical principles. This is important because the application of general ethical (...) frameworks to clinical decision-making entails conceptual questions: Is explicability a free-standing principle? Is it already covered by the well-established four bioethical principles? Or is it an independent value that needs to be recognized as such in medical practice? We discuss these questions in a conceptual-ethical analysis, which builds upon the findings of an empirical document analysis. On the example of the medical specialty of radiology, we analyze the position of radiological associations on the ethical use of medical AI. We address three questions: Are there references to explicability or a similar concept? What are the reasons for such inclusion? Which ethical concepts are referred to? (shrink)

Some properties are causally relevant for a certain effect, others are not. In this paper we describe a problem for our understanding of this notion and then offer a solution in terms of the notion of a program explanation.

In this paper, I offer an analysis of the radical disagreement over the adequacy of string theory. The prominence of string theory despite its notorious lack of empirical support is sometimes explained as a troubling case of science gone awry, driven largely by sociological mechanisms such as groupthink (e.g. Smolin 2006). Others, such as Dawid (2013), explain the controversy by positing a methodological revolution of sorts, according to which string theorists have quietly turned to nonempirical methods of theory assessment given (...) the technological inability to directly test the theory. The appropriate response, according to Dawid, is to acknowledge this development and widen the canons of acceptable scientific methods. As I’ll argue, however, the current situation in fundamental physics does not require either of these responses. Rather, as I’ll suggest, much of the controversy stems from a failure to properly distinguish the “context of justification” from the “context of pursuit”. Both those who accuse string theorists of betraying the scientific method and those who advocate an enlarged conception of scientific methodology objectionably conflate epistemic justification with judgements of pursuit-worthiness. Once we get clear about this distinction and about the different norms governing the two contexts, the current situation in fundamental physics becomes much less puzzling. After defending this diagnosis of the controversy, I’ll show how the argument patterns that have been posited by Dawid as constituting an emergent methodological revolution in science are better off if reworked as arguments belonging to the context of pursuit. (shrink)

The chapter presents Anselm’s incompatibilist account of human freedom within the context of his theodicy and presents two arguments against his account. Both arguments aim to show there is a genuine conflict between his account of freedom and the role of God’s grace in making agents just. The first argument, the problem of harmonization, highlights the conflict within the soteriological context where an agent changes from being unjust to being just. The second argument, the problem of just creation, highlights the (...) conflict within the context of the creation of agents prior to the presence of evil. Holding fixed his incompatibilist account and the necessity of divine grace, the upshot of both arguments is that Anselm must endorse a version of Pelagianism. (shrink)

In this article, I will provide a critical overview of the form of non-deductive reasoning commonly known as “Inference to the Best Explanation” (IBE). Roughly speaking, according to IBE, we ought to infer the hypothesis that provides the best explanation of our evidence. In section 2, I survey some contemporary formulations of IBE and highlight some of its putative applications. In section 3, I distinguish IBE from C.S. Peirce’s notion of abduction. After underlining some of the essential elements of IBE, (...) the rest of the entry is organized around an examination of various problems that IBE confronts, along with some extant attempts to address these problems. In section 4, I consider the question of when a fact requires an explanation, since presumably IBE applies only in cases where some explanation is called for. In section 5, I consider the difficult question of how we ought to understand IBE in light of the fact that among philosophers, there is significant disagreement about what constitutes an explanation. In section 6, I consider different strategies for justifying the truth-conduciveness of the explanatory virtues, e.g., simplicity, unification, scope, etc., criteria which play an indispensable role in any given application of IBE. In section 7, I survey some of the most recent literature on IBE, much of which consists of investigations of the status of IBE from the standpoint of the Bayesian philosophy of science. (shrink)

Purpose: The method of diagnosing diabetic retinopathy (DR) through artificial intelligence (AI)-based systems has been commercially available since 2018. This introduces new ethical challenges with regard to obtaining informed consent from patients. The purpose of this work is to develop a checklist of items to be disclosed when diagnosing DR with AI systems in a primary care setting. -/- Methods: Two systematic literature searches were conducted in PubMed and Web of Science databases: a narrow search focusing on DR and a (...) broad search on general issues of AI-based diagnosis. An ethics content analysis was conducted inductively to extract two features of included publications: (1) novel information content for AI-aided diagnosis and (2) the ethical justification for its disclosure. -/- Results: The narrow search yielded n = 537 records of which n = 4 met the inclusion criteria. The information process was scarcely addressed for primary care setting. The broad search yielded n = 60 records of which n = 11 were included. In total, eight novel elements were identified to be included in the information process for ethical reasons, all of which stem from the technical specifics of medical AI. -/- Conclusions: Implications for the general practitioner are two-fold: First, doctors need to be better informed about the ethical implications of novel technologies and must understand them to properly inform patients. Second, patient's overconfidence or fears can be countered by communicating the risks, limitations, and potential benefits of diagnostic AI systems. If patients accept and are aware of the limitations of AI-aided diagnosis, they increase their chances of being diagnosed and treated in time. (shrink)

In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational import. (...) Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends. (shrink)

Philosophy &Public Affairs, Volume 46, Issue 4, Page 363-383, Fall 2018.

This paper attempts to reconcile two apparently opposed ways of thinking about the imagination and its relationship to literature, one which casts it as essentially concerned with fiction-making and the other with culture-making. The literary imagination’s power to create fictions is what gives it its most obvious claim to “autonomy”, as Kant would have it: its freedom to venture out in often wild and spectacular excess of reality. The argument of this paper is that we can locate the literary imagination’s (...) complementary power of cultural articulation in this fictional activity. The suggestion is that we should conceive of the literary imagination as expressing its interests in culture not mimetically but by producing a certain kind of meaning. This meaning is irreducibly narratological, and understanding it helps us to see the role of narrative in bringing into harmony the literary imagination’s interests in both the imaginary and the real. (shrink)

Institutions can be strong or weak. But what does this mean? Equilibrium theories equate institutions with behavioural regularities. In contrast, rule theories explicate them in terms of a standard that people are supposed to meet. I propose that, when an institution is weak, a discrepancy exists between the regularity and the standard or rule. To capture this discrepancy, I present a hybrid theory, the Rules-and-Equilibria Theory. According to this theory, institutions are rule-governed behavioural regularities. The Rules-and-Equilibria Theory provides the basis (...) for two measures of institutional strength. First, institutions that pertain to coordination games solve problems of information. Their strength is primarily a matter of the expected degree of compliance. Second, institutions that concern mixed-motive games solve problems of motivation. Their strength can be measured in terms of the weight people attribute to its rule. (shrink)

In this paper, I examine Cicero’s oft-neglected De Divinatione, a dialogue investigating the legitimacy of the practice of divination. First, I offer a novel analysis of the main arguments for divination given by Quintus, highlighting the fact that he employs two logically distinct argument forms. Next, I turn to the first of the main arguments against divination given by Marcus. Here I show, with the help of modern probabilistic tools, that Marcus’ skeptical response is far from the decisive, proto-naturalistic assault (...) on superstition that it is sometimes portrayed to be. Then, I offer an extended analysis of the second of the main arguments against divination given by Marcus. Inspired by Marcus’ second main argument, I formulate, explicate, and defend a substantive principle of scientific methodology that I call the “Ciceronian Causal-Nomological Requirement” (CCR). Roughly, this principle states that causal knowledge is essential for relying on correlations in predictive inference. Although I go on to argue that Marcus’ application of the CCR in his debate with Quintus is dialectically inadequate, I conclude that De Divinatione deserves its place in Cicero’s philosophical corpus, and that ultimately, its significance for the history and philosophy of science ought to be recognized. (shrink)

In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are in tension with a (...) prominent account of scientific method, often called “Inference to the Best Explanation”. Later on, in Section 3, I consider an argument against IBE that will be congenial to proponents of Big Data, namely, the argument due to Roche and Sober Analysis, 73:659–668, that “explanatoriness is evidentially irrelevant.” This argument is based on Bayesianism, one of the most prominent general accounts of theory-confirmation. In Section 4, I consider some extant responses to this argument, especially that of Climenhaga Philosophy of Science, 84:359–368,. In Section 5, I argue that Roche and Sober’s argument does not show that explanatory reasoning is dispensable. In Section 6, I argue that there is good reason to think explanatory reasoning will continue to prove indispensable in scientific practice. Drawing on Cicero’s oft-neglected De Divinatione, I formulate what I call the “Ciceronian Causal-nomological Requirement”, which states, roughly, that causal-nomological knowledge is essential for relying on correlations in predictive inference. I defend a version of the CCR by appealing to the challenge of “spurious correlations,” chance correlations which we should not rely upon for predictive inference. In Section 7, I offer some concluding remarks. (shrink)

We develop a Bayesian framework for thinking about the way evidence about the here and now can bear on hypotheses about the qualitative character of the world as a whole, including hypotheses according to which the total population of the world is infinite. We show how this framework makes sense of the practice cosmologists have recently adopted in their reasoning about such hypotheses.

Environmental health research produces scientific knowledge about environmental hazards crucial for public health and environmental justice movements that seek to prevent or reduce exposure to these hazards. The environment in environmental health research is conceptualized as the range of possible social, biological, chemical, and/or physical hazards or risks to human health, some of which merit study due to factors such as their probability and severity, the feasibility of their remediation, and injustice in their distribution. This paper explores the ethics of (...) identifying the relevant environment for environmental health research, as judgments involved in defining an environmental hazard or risk, judgments of that hazard or risk's probability, severity, and/ or injustice, as well as the feasibility of its remediation, all ought to appeal to non-epistemic as well as epistemic values. I illustrate by discussing the case of environmental lead, a housing-related hazard that remains unjustly distributed by race and class and is particularly dangerous to children. Examining a controversy in environmental health research ethics where researchers tested multiple levels of lead abatement in lead-contaminated households, I argue that the broader perspective on the ethics of environmental health research provided in the first part of this paper may have helped prevent this controversy. (shrink)

The Preface Paradox is often discussed for its implications for rational belief. Much less discussed is a variant of the Preface Paradox for knowledge. In this paper, I argue that the most plausible closure-friendly resolution to the Preface Paradox for Knowledge is to say that in any given context, we do not know much. I call this view “Socraticism”. I argue that Socraticism is the most plausible view on two accounts—(1) this view is compatible with the claim that most of (...) our knowledge ascriptions are true, and (2) provided that (1) is true, the costs of accepting Socraticism are much less than the costs of accepting any other resolution to the Paradox. I argue for (1) in Section 2 by developing a question-sensitive contextualist model for knowledge that shows how Socraticism is compatible with the claim that most of our knowledge ascriptions are true. I also argue how this contextualist model can achieve this result where other contextualist models fail. I then consider other closure-friendly solutions to the paradox in Section 3 and show how accepting those solutions forces us to give up a number of plausible epistemic principles. (shrink)

If a future AI system can enjoy far more well-being than a human per resource, what would be the best way to allocate resources between these future AI and our future descendants? It is obvious that on total utilitarianism, one should give everything to the AI. However, it turns out that every Welfarist axiology on the market also gives this same recommendation, at least if we assume consequentialism. Without resorting to non-consequentialist normative theories that suggest that we ought not always (...) create the world with the most value, or non-welfarist theories that tell us that the best world may not be the world with the most welfare, I propose a new theory that justifies giving some resources to humanity in the face of overwhelming AI well-being. I call this new theory, “Group Prioritarianism". (shrink)

Philosophers of literature do not take much of an interest in autobiography.1 In one sense this is not surprising. As a certain prejudice has it, autobiography is, along with biography, the preferred reading of people who do not really like to read. The very words can conjure up images of what one finds on bookshelves in Florida retirement communities and in underfunded public libraries, books with titles like Under the Rainbow: The Real Liza Minnelli or Me: Stories of My Life (...) (Katharine Hepburn).2 Hardly rousing material, at least from the philosophical point of view. But on a moment’s reflection, it becomes clear that the initial prejudice is unfounded. Never mind the fact that there are obviously .. (shrink)

This paper discusses ethical issues surrounding Integrated Assessment Models (IAMs) of the economic effects of climate change, and how climate economists acting as policy advisors ought to represent the uncertain possibility of catastrophe. Some climate economists, especially Martin Weitzman, have argued for a precautionary approach where avoiding catastrophe should structure climate economists’ welfare analysis. This paper details ethical arguments that justify this approach, showing how Weitzman’s “fat tail” probabilities of climate catastrophe pose ethical problems for widely used IAMs. The main (...) claim is that economists who ignore or downplay catastrophic risks in their representations of uncertainty likely fall afoul of ethical constraints on scientists acting as policy advisors. Such scientists have duties to honestly articulate uncertainties and manage (some) inductive risks, or the risks of being wrong in different ways. (shrink)

There are infinitely many ways the world might be, and there may well be infinitely many people in it. These facts raise moral paradoxes. We explore a conflict between two highly attractive principles: a Pareto principle that says that what is better for everyone is better overall, and a statewise dominance principle that says that what is sure to turn out better is better on balance. We refine and generalize this paradox, showing that the problem is faced by many theories (...) of interpersonal aggregation besides utilitarianism, and by many decision theories besides expected value theory. Considering the range of consistent responses, we find all of them to be quite radical. (shrink)

In this chapter we identify three potentially morally problematic behaviours that are common among users of dating and hook-up apps (DHAs) and provide arguments as to why they may or may not be considered (a) in a category of their own, distinct from similar behaviours outside of DHAs; (b) caused or facilitated by affordances and business logic of DHAs; (c) as indeed morally wrong. We also consider ways in which morally problematic behaviours can be anticipated, mitigated, or even prevented by (...) analysis of the ethical and moral dimensions of technologies and their afforded uses. Finally, we offer some possible directions for future work on these topics in particular and on the ethical consequences of DHAs in general. (shrink)

These essays draw on work in the history and philosophy of science, the philosophy of mind and language, the development of concepts in children, conceptual..