Amitabha Palmer

While palliative medicine has a clear mandate to address the somatic suffering of patients, it remains less clear how palliative medicine should intervene—if at all—in the management of existential suffering. We detail the case of a patient with terminal gastrointestinal cancer. Through consideration of this case, we make determinations regarding what is ethically required, as well as ways in which these implications may generalize to appropriately similar cases. Specifically, we draw two conclusions. First, standard risk-benefit calculus must be recalibrated to account for the irrelevance of certain imagined harm in imminently terminal cases. Additionally, respect for autonomy in the context of a “good death” entails respecting consistent, well-considered preferences on the part of the patient.

This chapter examines how telehealth’s rapid and widespread deployment into medical practice offers valuable insights for understanding the ethical dimensions of implementing new technologies in healthcare, particularly artificial intelligence. We argue that telehealth is not merely a tool for improving healthcare accessibility and clinical effectiveness; it serves as a critical case study for understanding how technology reshapes medicine and affects non-medical domains in unexpected ways. Through analysis of telehealth’s impact on medical adherence, provider-patient relationships, and the medicalization of personal spaces, we identify three key lessons for the ethical deployment of healthcare technologies: First, while benefits are often readily quantifiable, risks to normative aspects of medicine—such as patient autonomy and identity—are subtler and harder to measure. Second, technologies affect different populations and specialties in varying and unexpected ways, demanding context-sensitive implementation strategies rather than universal solutions. Third, new technologies shape not just what we can do but who we become as healthcare providers and patients. As healthcare becomes increasingly technology-dependent, we must balance innovation with the preservation of human values and relationships that lie at the foundation of good care. These insights are particularly relevant for the ongoing integration of AI systems into healthcare practice.

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.

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.

ChatGPT – a large language model – recently passed the U.S. bar exam. The startling rise and power of generative artificial intelligence (AI) systems such as ChatGPT lead us to consider whether and how more specialized systems could be used to overcome existing barriers to the legal system. Such systems could be employed in either of the two major stages of the pursuit of justice: preliminary information gathering and formal engagement with the state’s legal institutions and professionals. We focus on the former and argue that developing and deploying publicly funded AI legal advisors can reduce economic and shame-based cultural barriers to the information-gathering stage of pursuing justice.

During a clinical ethics fellow’s first week of independent supervised service, two unhoused patients on the same floor were resisting the medical team’s recommendations to discharge. In the team’s view, both were medically stable and no longer required hospitalization in an acute setting. The medical team suspected malingering for both. The social worker and case manager had employed their usual means of gentle persuasion and eliminating psychosocial barriers to no avail. Rather than call the police, the attending physician, social worker, and case manager decided to call ethics. These cases lead the fledgling fellow to consider the appropriate role for ethicists in difficult discharge cases. The article analyzes each case, evaluates their similarities and differences in the context of suspected malingering, and comments on ethical issues surrounding cases of suspected malingering. Finally, the authors reflect on the value and importance of developing and maintaining epistemic and professional independence.

Cette étude de cas explore les complexités éthiques entourant le traitement de Mme H, une femme âgée atteinte d’un myélome multiple. Des objectifs divergents entre sa famille, ancrée dans des valeurs culturelles et religieuses, et l’équipe médicale ont suscité des délibérations éthiques. Les objectifs divergents étaient centrés sur le désir de la famille d’un traitement agressif du cancer, motivé par leurs croyances Ubuntu et chrétiennes dans le caractère sacré de la vie et l’espoir d’une intervention divine, contrastant avec l’accent mis par l’équipe médicale sur les soins palliatifs, donnant la priorité au confort plutôt qu’à des interventions médicales agressives dont les bénéfices sont peu probables. Face à cette tension, l’équipe soignante, guidée par les principes de solidarité et d’humilité culturelle, s’est engagée dans un dialogue constructif facilité par un éthicien expérimenté. La résolution respecte les croyances culturelles et religieuses de la famille tout en adhérant à l’éthique médicale. Ce cas souligne l’importance de comprendre et d’intégrer les valeurs culturelles dans la prise de décision en matière de soins de santé, afin de parvenir à une approche centrée sur le patient qui respecte la diversité des points de vue.

Les éthiciens cliniques doivent être à l’écoute des signaux non verbaux et des questions plus profondes qu’ils soulèvent, et être prêts et agiles pour changer de cap si nécessaire, de la discussion des objectifs de soins à l’établissement de la confiance. Nous présentons une étude de cas où une famille et une équipe de soins sont en désaccord sur la question de savoir si l’absence d’ordonnance de non-réanimation et de non-intubation (ONR/ONI) pour un patient dont le pronostic est en phase terminale conduit à des décisions médicalement justifiables et éthiquement défendables. Un éthicien a convoqué une réunion de famille pour discuter de l’ordonnance, mais a déterminé, après avoir lu les remèdes non verbaux de la famille, qu’il fallait d’abord établir la confiance pour avoir cette discussion, et que cette confiance pouvait être établie en ne discutant pas de l’ordonnance.

During a clinical ethics fellow’s first week of independent supervised service, two unhoused patients on the same floor were resisting the medical team’s recommendations to discharge. In the team’s view, both were medically stable and no longer required hospitalization in an acute setting. The medical team suspected malingering for both. The social worker and case manager had employed their usual means of gentle persuasion and eliminating psychosocial barriers to no avail. Rather than call the police, the attending physician, social worker, and case manager decided to call ethics. These cases lead the fledgling fellow to consider the appropriate role for ethicists in difficult discharge cases. The article analyzes each case, evaluates their similarities and differences in the context of suspected malingering, and comments on ethical issues surrounding cases of suspected malingering. Finally, I reflect on the value and importance of developing and maintaining epistemic and professional independence.

Under conditions of high social and political polarization, expressing political anger online toward systemic injustice faces an apparent trilemma: Express none but lose anger's valuable goods; express anger to heterogeneous audiences but risk aggravating inter-group polarization; or express anger to like-minded people but succumb to the epistemic pitfalls and extremist tendencies inherent to homogeneous groups. Solving the trilemma requires cultivating an online environment as a deliberative system composed of four kinds of groups—each with distinct purposes and norms. I argue that applying empirically-guided design principles to this systems framework provides political anger a place where its powers can serve justice without damaging the epistemic, ethical, emotional, and community resources required for a democratic path to correcting systemic injustice.

Cette étude de cas aborde les défis de la prise de décision en fin de vie dans la pratique, en se concentrant sur l’équilibre délicat entre le paternalisme médical, la prise de décision partagée et les droits des décideurs de substitution. La famille a d’abord du mal à saisir la gravité de l’état de santé de l’être cher, mais un moment charnière lors de la réunion sur les objectifs de soins apporte une clarté soudaine. Ce cas explore la pertinence et les implications de la pratique du non-dissentiment éclairé. Cette analyse suggère que cette pratique est inappropriée à moins qu’il n’y ait des preuves irréfutables de paralysie de la décision. Des stratégies pratiques sont proposées pour faciliter l’accompagnement de la mort dans la compassion, tout en tenant compte des contraintes de l’urgence clinique.

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.

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.

Nurses have traditionally been regarded as clinicians that deliver compassionate, safe, and empathetic health care (Nurses again outpace other professions for honesty & ethics, 2018). Caring is a fundamental characteristic, expectation, and moral obligation of the nursing and caregiving professions (Nursing: Scope and standards of practice, American Nurses Association, Silver Spring, MD, 2015). Along with caring, nurses are expected to undertake ever‐expanding duties and complex tasks. In part because of the growing physical, intellectual and emotional demandingness, of nursing as well as technological advances, artificial intelligence (AI) and AI care robots are rapidly changing the healthcare landscape. As technology becomes more advanced, efficient, and economical, opportunities and pressure to introduce AI into nursing care will only increase. In the first part of the article, we review recent and existing applications of AI in nursing and speculate on future use. Second, situate our project within the recent literature on the ethics of nursing and AI. Third, we explore three dominant theories of caring and the two paradigmatic expressions of caring (touch and presence) and conclude that AI—at least for the foreseeable future—is incapable of caring in the sense central to nursing and caregiving ethics. We conclude that for AI to be implemented ethically, it cannot transgress the core values of nursing, usurp aspects of caring that can only meaningfully be carried out by human beings, and it must support, open, or improve opportunities for nurses to provide the uniquely human aspects of care.