Amitabha Palmer

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.

This case study discusses the challenges of end-of-life decision-making in practice, focusing on the delicate balance between medical paternalism, shared decision-making, and the rights of surrogate decision makers. The family initially struggles to grasp the severity of their loved one’s medical condition but a pivotal moment during the Goals of Care meeting brings sudden clarity. This case explores the appropriateness and implications of the practice of informed non-dissent; and our analysis suggests that it is inappropriate unless there is compelling evidence for decision paralysis. Practical strategies are offered that facilitate compassionate dying care within the constraints of clinical urgency.

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.