David Schwan

As AI moves rapidly into medicine, we explore how these technologies may over time erode core physician competencies through various stages of the clinical encounter: from preparation and diagnosis to treatment planning and patient monitoring. We identify three critical areas at risk: clinical skills (techne), where AI automation may lead to dangerous deskilling; medical knowledge (episteme), where overreliance on AI systems can erode diagnostic reasoning abilities; and moral character (ethos), where AI-mediated patient interactions may compromise empathetic care. Our analysis demonstrates how AI tools, while promising improved efficiency and accuracy, can paradoxically undermine physician expertise through automation bias, alert fatigue, and the displacement of essential human-to-human interactions. To address these challenges, we introduce a novel framework for the ethical deployment of advanced technologies in healthcare: participatory deliberative conservatism (PDC). This model emphasizes broad stakeholder participation, deliberative decision-making processes, and the preservation of core medical values.

This Conclusion identifies three lessons that follow from the chapters in the book. First, we ought to identify and critically reflect on the ideological assumptions that are embodied in new technologies. Second, we ought to design or redesign technologies with an awareness of their impact on people and how the effects vary depending on local circumstances. Third, we ought to draw on bioethics as we develop new medical technologies so that we can challenge common assumptions and appeal to deeply held moral values to inform our decisions.

Advances in medical technology—from antibiotics and organ transplantation to gene editing and artificial intelligence—have transformed healthcare and raised new ethical questions about the nature of medicine. These technologies not only alter diagnostic and therapeutic practices but also mediate how humans relate to one another and understand concepts such as health, illness, death, autonomy, and care. Drawing on ethics, law, history, and sociology, this volume offers a multidisciplinary framework for understanding how technological innovation reshapes ethical norms and social practices. As medicine becomes increasingly data-driven and technologically mediated, new frameworks and practices are needed to guide its development toward appropriate human ends.

This book provides a comprehensive survey of ethical issues raised by advanced medical technologies. The field’s leading authorities explore how artificial intelligence, telehealth, robot caregivers, genetic therapies and enhancement, stem cell research, neurotechnology, electronic health records, data collection, and digital nudging are reshaping the landscape of medical practice. Organized around core ethical themes, the chapters consider how new and emerging technologies transform personal identity, the provider-patient relationship, privacy and autonomy, and social equity. Contributors clarify the complex values involved in medical innovation and practice, and explore what is at stake in the current ethical debates around these issues. While offering a valuable introduction for advanced students, professional philosophers, medical ethicists, and policymakers, this book also advances the scholarly discussion by presenting original theses and arguments, making it essential reading for specialists.

Digital mental health tools (DMHTs) offer a potential solution to overcoming economic, cultural, and geographic barriers to the increasing demand for mental health care, but their adoption raises significant ethical, legal, and social concerns. This article identifies ethical risks related to DMHTs and, in this light, proposes three important criteria for evaluating regulatory approaches. These approaches should (a) ensure widespread access and (b) balance access with risk management while (c) acknowledging preexisting markets and digital self‐medication. Our analysis of three regulatory models—the laissez‐faire approach, a highly regulated approach, and the current U.S. Food and Drug Administration approach—reveals that none satisfactorily balances the promise of access with ethical risks. We therefore suggest modifications to the current FDA approach; these involve a voluntary certification program for nonprescription DMHTs, more‐stringent data safety and privacy practices, easily accessible diagnostic tools, continuous monitoring, and independent audits. These modifications secure the accessibility benefits of DMHTs while mitigating risks associated with widespread use.

Current national and international guidelines for the ethical design and development of artificial intelligence (AI) and robotics emphasize ethical theory. Various governing and advisory bodies have generated sets of broad ethical principles, which institutional decisionmakers are encouraged to apply to particular practical decisions. Although much of this literature examines the ethics of designing and developing AI and robotics, medical institutions typically must make purchase and deployment decisions about technologies that have already been designed and developed. The primary problem facing medical institutions is not one of ethical design but of ethical deployment. The purpose of this paper is to develop a practical model by which medical institutions may make ethical deployment decisions about ready-made advanced technologies. Our slogan is “more process, less principles.” Ethically sound decisionmaking requires that the process by which medical institutions make such decisions include participatory, deliberative, and conservative elements. We argue that our model preserves the strengths of existing frameworks, avoids their shortcomings, and delivers its own moral, practical, and epistemic advantages.

This article addresses ethical concerns with the use of electronic health records (EHRs) by physicians in clinical practice. It presents arguments for two claims. First, requiring physicians to maintain patient EHRs for medically unnecessary tasks is likely contributing to increased burnout, decreased quality of care, and potential risks to patient safety. Second, medical institutions have ethical reasons to employ medical scribes to maintain patient EHRs. Finally, this article reviews central objections to employing medical scribes and provides responses to each.

As costs decline and technology inevitably improves, current trends suggest that artificial intelligence (AI) and a variety of "carebots" will increasingly be adopted in medical care. Medical ethicists have long expressed concerns that such technologies remove the human element from medicine, resulting in dehumanization and depersonalized care. However, we argue that where shame presents a barrier to medical care, it is sometimes ethically permissible and even desirable to deploy AI/carebots because (i) dehumanization in medicine is not always morally wrong, and (ii) dehumanization can sometimes better promote and protect important medical values. Shame is often a consequence of the human-to-human element of medical care and can prevent patients from seeking treatment and from disclosing important information to their healthcare provider. Conditions and treatments that are shame-inducing offer opportunities for introducing AI/carebots in a manner that removes the human element of medicine but does so ethically. We outline numerous examples of shame-inducing interactions and how they are overcome by implementing existing and expected developments of AI/carebot technology that remove the human element from care.

Affective empathy has been variously characterized. First, I argue that we have reasons to prefer a narrower account of affective empathy, which requires the cognitive mechanisms of perspective-taking. Second, I mount a challenge to the standard account of affective matching thought to be required for affective empathy. On one widely held view, affective empathy requires an actual affective match between the subject and the target of empathy. I reject this view. While empathy often involves an actual match, we also count as empathizing with the target if we share the fitting state in their situation. This wider account better captures a number of plausible cases of empathy, and it also better explains why we care about affective empathy.

The role and importance of empathy in clinical practice has been widely discussed. This paper focuses on the ideal of clinical empathy, as involving both cognitive understanding and affective resonance. I argue that this account is subject to a number of objections. Affective resonance may serve more as a liability than as a benefit in clinical settings, and utilizing this capacity is not clearly supported by the relevant empirical literature. Instead, I argue that the ideal account of empathy in medicine remains cognitive, though there is a central role for expressing empathic concern toward patients.

This article discusses John Stuart Mill's voluntary slavery argument in On Liberty. The author shows that standard interpretations of the argument rely on the assumption that part of Mill's objection to voluntary slavery is the permanent nature of the decision. However, in correspondence, Mill also objects to voluntary ‘coolie’ labour contracts, which he regards as a form of slavery. This produces difficulties for standard interpretations of the voluntary slavery argument. Finally, the author provides a revised interpretation of Mill's argument to solve this problem.