Often lurking below the surface of many clinical ethical issues are questions regarding background metaphysical, epistemological, meta-ethical, and political beliefs. In this issue, authors critically examine the effects of background beliefs on conscientious objection, explore ethical issues through the lenses of particular theoretical approaches like pragmatism and intersectional theory, rigorously explore the basic concepts at play within the patient safety movement, offer new theoretical approaches to old problems involving decision making for patients with dementia, explicate and explore the problems and (...) promises of machine learning in medicine, and offer us a non-rights-based argument for the just distribution of healthcare resources. (shrink)

The increasing integration of artificial intelligence (AI) in healthcare presents a host of ethical, legal, social, and political challenges involving various stakeholders. These challenges prompt various studies proposing frameworks and guidelines to tackle these issues, emphasizing distinct phases of AI development, deployment, and oversight. As a result, the notion of responsible AI has become widespread, incorporating ethical principles such as transparency, fairness, responsibility, and privacy. This paper explores the existing literature on AI use in healthcare to examine how it addresses, (...) defines, and discusses the concept of responsibility. We conducted a scoping review of literature related to AI responsibility in healthcare, searching databases and reference lists between January 2017 and January 2022 for terms related to “responsibility” and “AI in healthcare”, and their derivatives. Following screening, 136 articles were included. Data were grouped into four thematic categories: (1) the variety of terminology used to describe and address responsibility; (2) principles and concepts associated with responsibility; (3) stakeholders’ responsibilities in AI clinical development, use, and deployment; and (4) recommendations for addressing responsibility concerns. The results show the lack of a clear definition of AI responsibility in healthcare and highlight the importance of ensuring responsible development and implementation of AI in healthcare. Further research is necessary to clarify this notion to contribute to developing frameworks regarding the type of responsibility (ethical/moral/professional, legal, and causal) of various stakeholders involved in the AI lifecycle. (shrink)

This issue of The Journal of Medicine and Philosophy is dedicated to topics in clinical ethics with essays addressing clinician participation in state sponsored execution, duties to decrease ecological footprints in medicine, the concept of caring and its relationship to conscientious refusal, the dilemmas involved in dual use research, a philosophical and practical critique of principlism, conundrums that arise when applying surrogate decision-making models to patients with moderate intellectual disabilities, the phenomenology of chronic disease, and ethical concerns surrounding the use (...) of artificial intelligence in medicine. Throughout the issue, the themes of conceptual and moral boundaries in bioethics, critiques of current clinical ethics paradigms, and the importance of transparency are prominent. (shrink)