:Empirical work has shown that patients and physicians have markedly divergent understandings of treatability statements in the context of serious illness. Patients often understand treatability statements as conveying good news for prognosis and quality of life. In contrast, physicians often do not intend treatability statements to convey improvement in prognosis or quality of life, but merely that a treatment is available. Similarly, patients often understand treatability statements as conveying encouragement to hope and pursue further treatment, though this may not be (...) intended by physicians. This radical divergence in understandings may lead to severe miscommunication. This paper seeks to better understand this divergence through linguistic theory—in particular, H.P. Grice’s notion of conversational implicature. This theoretical approach reveals three levels of meaning of treatability statements: the literal meaning, the physician’s intended meaning, and the patient’s received meaning. The divergence between the physician’s intended meaning and the patient’s received meaning can be understood to arise from the lack of shared experience between physicians and patients, and the differing assumptions that each party makes about conversations. This divergence in meaning raises new and largely unidentified challenges to informed consent and shared decision making in the context of serious illness, which indicates a need for further empirical research in this area. (shrink)

According to the mainstream conception of research involving human participants, researchers have been trained scientists acting within institutions and have been the individuals doing the studying, while participants, who are nonscientist members of the public, have been the individuals being studied. The relationship between the public and scientists is evolving, however, giving rise to several new concepts, including crowdsourcing and citizen science. In addition, the practice of gamification has been applied to research protocols. The role of gamified, crowdsourced citizen scientist (...) is new in the domain of scientific research and does not fit into the existing taxonomy of researchers and participants. We delineate and explicate this role and show that, while traditional roles are governed by well‐established norms and regulations, individuals engaged in gamified, crowdsourced citizen science—gamers—fall through the cracks of research protections and regulations. We consider the issues this raises, including exploitation and the absence of responsibility and accountability. Finally, we offer suggestions for how the current lack of appropriate norms may be rectified. (shrink)

The two target articles in this issue draw an important connection between disability bioethics and geriatric bioethics. Dominic JC Wilkinson makes a pragmatic case for using frailty as a fa...

In their target article, Millum and Bromwich situate their article against a backdrop of well-documented empirical research demonstrating that many participants have variable and often poor...

The new generative artificial intelligence (AI) tools, and especially the large language models (LLMs) of which ChatGPT is the most prominent example, have the potential to transform many aspects o...

Generative artificial intelligence (AI) has the potential to transform many aspects of scholarly publishing. Authors, peer reviewers, and editors might use AI in a variety of ways, and those uses might augment their existing work or might instead be intended to replace it. We are editors of bioethics and humanities journals who have been contemplating the implications of this ongoing transformation. We believe that generative AI may pose a threat to the goals that animate our work but could also be (...) valuable for achieving those goals. In the interests of fostering a wider conversation about how generative AI may be used, we have developed a preliminary set of recommendations for its use in scholarly publishing. We hope that the recommendations and rationales set out here will help the scholarly community navigate toward a deeper understanding of the strengths, limits, and challenges of AI for responsible scholarly work. (shrink)

Generative artificial intelligence (AI) has the potential to transform many aspects of scholarly publishing. Authors, peer reviewers, and editors might use AI in a variety of ways, and those uses might augment their existing work or might instead be intended to replace it. We are editors of bioethics and humanities journals who have been contemplating the implications of this ongoing transformation. We believe that generative AI may pose a threat to the goals that animate our work but could also be (...) valuable for achieving those goals. In the interests of fostering a wider conversation about how generative AI may be used, we have developed a preliminary set of recommendations for its use in scholarly publishing. We hope that the recommendations and rationales set out here will help the scholarly community navigate toward a deeper understanding of the strengths, limits, and challenges of AI for responsible scholarly work. (shrink)

The new generative artificial intelligence (AI) tools, and especially the large language models (LLMs) of which ChatGPT is the most prominent example, have the potential to transform many aspects o...

Philosophers and historians of science have tended to denigrate the status and usefulness of the practice of natural history. The development of biology in this century is seen as the replacement of an older, descriptive and speculative method with a quantitative, experimental and well-founded science. This account embodies a philosophical view about the nature of science, which deems certain kinds of evidence and certain ways of producing knowledge appropriate. Natural history is seen as inadequate, providing insufficient support for establishing theory. (...) ;I develop a case study which shows this account to be incorrect. The case study concerns the debate over the role of geographical isolation in speciation between 1905 and 1907. After some preliminary historical background to the debate, I present a detailed discussion of the arguments made by naturalist David Starr Jordan . The debate that ensued centered on the kinds of evidence one should use in doing science--fieldwork versus experiments. Thus, this case study offers excellent subject matter for understanding natural history. ;After examining the debate and its participants in some detail, we can see that at the heart of this debate is an epistemological issue over what virtues are central to science. In particular, while natural historians like Jordan were advocating an approach which emphasized the consilience of inductions--and hence a variety of kinds of evidence--a more experimentally oriented group of biologists were advocating the centrality of replication and hence argued that all non-experimental forms of evidence should be abandoned. Contrary to expectations, the naturalists had the better theory. (shrink)

A commentary on “SUPPORT and the Ethics of Study Implementation: Lessons for Comparative Effectiveness Research from the Trial of Oxygen Therapy for Premature Babies,” by John D. Lantos and Chris Feudtner, in the January‐February 2015 issue.