Hastings Center Report, Volume 51, Issue 5, Page 6-7, September‐October 2021.

The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...) domain and to saliva-related diagnostics following the principles of the OBO (Open Biomedical Ontologies) Foundry. The Saliva Ontology is an ongoing exploratory initiative. The ontology will be used to facilitate salivaomics data retrieval and integration across multiple fields of research together with data analysis and data mining. The ontology will be tested through its ability to serve the annotation ('tagging') of a representative corpus of salivaomics research literature that is to be incorporated into the SKB. Background Saliva (oral fluid) is an emerging biofluid for non-invasive diagnostics used in the detection of human diseases. The need to advance saliva research is strongly emphasized by the National Institute of Dental and Craniofacial Research (NIDCR), and is included in the NIDCR's 2004- 2009 expert panel long-term research agenda [1]. The ability to monitor health status, disease onset, progression, recurrence and treatment outcome through noninvasive means is highly important to advancing health care management. Saliva is a perfect medium to be explored for personalized individual medicine including diagnostics, offering a non-invasive, easy to obtain means for detecting and monitoring diseases. Saliva testing potentially allows the patient to collect their own saliva samples at home, yielding convenience for the patient and savings in health costs, and facilitating multiple sampling. Specimen collection is less objectionable to patients and easier in children and elderly individuals. Due to these advantages. (shrink)

Healthcare systems across the globe are struggling with increasing costs and worsening outcomes. This presents those responsible for overseeing healthcare with a challenge. Increasingly, policymakers, politicians, clinical entrepreneurs and computer and data scientists argue that a key part of the solution will be ‘Artificial Intelligence’ (AI) – particularly Machine Learning (ML). This argument stems not from the belief that all healthcare needs will soon be taken care of by “robot doctors.” Instead, it is an argument that rests on the (...) classic counterfactual definition of AI as an umbrella term for a range of techniques that can be used to make machines complete tasks in a way that would be considered intelligent were they to be completed by a human. Automation of this nature could offer great opportunities for the improvement of healthcare services and ultimately patients’ health by significantly improving human clinical capabilities in diagnosis, drug discovery, epidemiology, personalised medicine, and operational efficiency. However, if these AI solutions are to be embedded in clinical practice, then at least three issues need to be considered: the technical possibilities and limitations; the ethical, regulatory and legal framework; and the governance framework. In this article, we report on the results of a systematic analysis designed to provide a clear overview of the second of these elements: the ethical, regulatory and legal framework. We find that ethical issues arise at six levels of abstraction (individual, interpersonal, group, institutional, sectoral, and societal) and can be categorised as epistemic, normative, or overarching. We conclude by stressing how important it is that the ethical challenges raised by implementing AI in healthcare settings are tackled proactively rather than reactively and map the key considerations for policymakers to each of the ethical concerns highlighted. (shrink)

Malaysia had its first four patients with COVID-19 on 25 January 2020. In the same week, the World Health Organization declared it as a public health emergency of international concern. The pandemic has since challenged the ethics and practice of medicine. There is palpable tension from the conflict of interest between public health initiatives and individual’s rights. Ensuring equitable care and distribution of health resources for patients with and without COVID-19 is a recurring ethical challenge (...) for clinicians. Palliative care aims to mitigate suffering caused by a life-limiting illness, and this crisis has led to the awareness and urgency to ensure it reaches all who needs it. We share here the palliative care perspectives and ethical challenges during the COVID-19 pandemic in Malaysia. (shrink)

The use of opaque, uninterpretable artificial intelligence systems in health care can be medically beneficial, but it is often viewed as potentially morally problematic on account of this opacity—because the systems are black boxes. Alex John London has recently argued that opacity is not generally problematic, given that many standard therapies are explanatorily opaque and that we can rely on statistical validation of the systems in deciding whether to implement them. But is statistical validation sufficient to justify implementation (...) of these AI systems in health care, or is it merely one of the necessary criteria? I argue that accountability, which holds an important role in preserving the patient‐physician trust that allows the institution of medicine to function, contributes further to an account of AI system justification. Hence, I endorse the vanishing accountability principle: accountability in medicine, in addition to statistical validation, must be preserved. AI systems that introduce problematic gaps in accountability should not be implemented. (shrink)

Background Machine learning (ML) is utilized increasingly in health care, and can pose harms to patients, clinicians, health systems, and the public. In response, regulators have proposed an approach that would shift more responsibility to ML developers for mitigating potential harms. To be effective, this approach requires ML developers to recognize, accept, and act on responsibility for mitigating harms. However, little is known regarding the perspectives of developers themselves regarding their obligations to mitigate harms.Methods We conducted 40 (...) semi-structured interviews with developers of ML predictive analytics applications for health care in the United States.Results Participants varied widely in their perspectives on personal responsibility and included examples of both moral engagement and disengagement, albeit in a variety of forms. While most (70%) of participants made a statement indicative of moral engagement, most of these statements reflected an awareness of moral issues, while only a subset of these included additional elements of engagement such as recognizing responsibility, alignment with personal values, addressing conflicts of interests, and opportunities for action. Further, we identified eight distinct categories of moral disengagement reflecting efforts to minimize potential harms or deflect personal responsibility for preventing or mitigating harms.Conclusions These findings suggest possible facilitators and barriers to the development of ethical ML that could act by encouraging moral engagement or discouraging moral disengagement. Regulatory approaches that depend on the ability of ML developers to recognize, accept, and act on responsibility for mitigating harms might have limited success without education and guidance for ML developers about the extent of their responsibilities and how to implement them. (shrink)

Since uncertainty is a major challenge in medicine and bears the risk of causing incorrect diagnoses and harmful treatment, there are many efforts to tackle it. For some time, AI technologies have been increasingly implemented in medicine and used to reduce medical uncertainties. What initially seems desirable, however, poses challenges. We use a multimethod approach that combines philosophical inquiry, conceptual analysis, and ethical considerations to identify key challenges that arise when AI is used for medical certainty purposes. We identify several (...) challenges. Where AI is used to reduce medical uncertainties, it is likely to result in (a) patients being stripped down to their measurable data points, and being made disambiguous. Additionally, the widespread use of AI technologies in health care bears the risk of (b) human physicians being pushed out of the medical decision-making process, and patient participation being more and more limited. Further, the successful use of AI requires extensive and invasive monitoring of patients, which raises (c) questions about surveillance as well as privacy and security issues. We outline these several challenges and show that they are immediate consequences of AI-driven security efforts. If not addressed, they could entail unfavorable consequences. We contend that diminishing medical uncertainties through AI involves a tradeoff. The advantages, including enhanced precision, personalization, and overall improvement in medicine, are accompanied by several novel challenges. This paper addresses them and gives suggestions about how to use AI for certainty purposes without causing harm to patients. (shrink)

There is enormous interest in using artificial intelligence (AI) in health care contexts. But before AI can be used in such settings, we need to make sure that AI researchers and organizations follow appropriate ethical frameworks and guidelines when developing these technologies. In recent years, a great number of ethical frameworks for AI have been proposed. However, these frameworks have tended to be abstract and not explain what grounds and justifies their recommendations and how one should use these (...) recommendations in practice. In this paper, I propose an AI ethics framework that is grounded in substantive, human rights theory and one that can help us address these questions. (shrink)

The use of Artificial Intelligence and Big Data in health care opens up new opportunities for the measurement of the human. Their application aims not only at gathering more and better data points but also at doing it less invasive. With this change in health care towards its extension to almost all areas of life and its increasing invisibility and opacity, new questions of transparency arise. While the complex human-machine interactions involved in deploying and using AI (...) tend to become non-transparent, the use of these technologies makes the patient seemingly transparent. Papers on the ethical implementation of AI plead for transparency but neglect the factor of the “transparent patient” as intertwined with AI. Transparency in this regard appears to be Janus-faced: The precondition for receiving help - e.g., treatment advice regarding the own health - is to become transparent for the digitized health care system. That is, for instance, to donate data and become visible to the AI and its operators. The paper reflects on this entanglement of transparent patients and (non-) transparent technology. It argues that transparency regarding both AI and humans is not an ethical principle per se but an infraethical concept. Further, it is no sufficient basis for avoiding harm and human dignity violations. Rather, transparency must be enriched by intelligibility following Judith Butler’s use of the term. Intelligibility is understood as an epistemological presupposition for recognition and the ensuing humane treatment. Finally, the paper highlights ways to testify intelligibility in dealing with AI in health care ex ante, ex post, and continuously. (shrink)

Scenarios involving the introduction of artificially intelligent (AI) assistive technologies in health care practices raise several ethical issues. In this paper, I discuss four objections to introducing AI assistive technologies in health care practices as replacements of human care. I analyse them as demands for felt care, good care, private care, and real care. I argue that although these objections cannot stand as good reasons for a general and a priori rejection (...) of AI assistive technologies as such or as replacements of human care, they demand us to clarify what is at stake, to develop more comprehensive criteria for good care, and to rethink existing practices of care. In response to these challenges, I propose a (modified) capabilities approach to care and emphasize the inherent social dimension of care. I also discuss the demand for real care by introducing the ‘Care Experience Machine’ thought experiment. I conclude that if we set the standards of care too high when evaluating the introduction of AI assistive technologies in health care, we have to reject many of our existing, low-tech health care practices. (shrink)

When the social relevance of robotic applications is addressed today, the use of assistive technology in care settings is almost always the first example. So-called care robots are presented as a solution to the nursing crisis, despite doubts about their technological readiness and the lack of concrete usage scenarios in everyday nursing practice. We inquire into this interconnection of social robotics and care. We show how both are made available for each other in three arenas: innovation policy, (...) care organization, and robotic engineering. First, we analyze the discursive “logics” of care robotics within European innovation policy, second, we disclose how care robotics is encountering a historically grown conflict within health care organization, and third we show how care scenarios are being used in robotic engineering. From this diagnosis, we derive a threefold critique of robotics in healthcare, which calls attention to the politics, historicity, and social situatedness of care robotics in elderly care. (shrink)

Artificial Intelligence (AI) contributes to common goods and common harms in our everyday lives. In light of the Collingridge dilemma, information about both the actual and potential harm of AI is explored and myths about AI are dispelled. Catholic health care is then presented as being in a unique position to exert its influence to model the use of AI systems that minimizes the risk of harm and promotes human flourishing and the common good.

Artificial intelligence holds great promise for improved health‐care outcomes. But it also poses substantial new hazards, including algorithmic discrimination. For example, an algorithm used to identify candidates for beneficial “high risk care management” programs routinely failed to select racial minorities. Furthermore, some algorithms deliberately adjust for race in ways that divert resources away from minority patients. To illustrate, algorithms have underestimated African Americans’ risks of kidney stones and death from heart failure. Algorithmic discrimination can violate Title VI (...) of the Civil Rights Act and Section 1557 of the Affordable Care Act when it unjustifiably disadvantages underserved populations. This article urges that both legal and technical tools be deployed to promote AI fairness. Plaintiffs should be able to assert disparate impact claims in health‐care litigation, and Congress should enact an Algorithmic Accountability Act. In addition, fairness should be a key element in designing, implementing, validating, and employing AI. (shrink)

This article examines the potential implications of the implementation of artificial intelligence in health care for both its delivery and the medical profession. To this end, the first section explores the basic features of AI and the yet theoretical concept of autonomous AI followed by an overview of current and developing AI applications. Against this background, the second section discusses the transforming roles of physicians and changes in the patient–physician relationship that could be a consequence of gradual expansion (...) of AI in health care. Subsequently, an examination of the responsibilities physicians should assume in this process is explored. The third section describes conceivable practical and ethical challenges that implementation of a single all-encompassing AI healthcare system would pose. The fourth section presents arguments for regulation of AI in health care to ensure that these applications do not violate basic ethical principles and that human control of AI will be preserved in the future. In the final section, fundamental components of a moral framework from which such regulation may be derived are brought forward, and some possible strategies for building a moral framework are discussed. (shrink)

Artificial Intelligence (AI), especially of the machine learning (ML) variety, is used by health care organizations to assist with a number of tasks, including diagnosing patients and optimizing operational workflows. AI products already proliferate the health care market, with usage increasing as the technology matures. Although AI may potentially revolutionize health care, the use of AI in health settings also leads to risks ranging from violating patient privacy to implementing a biased algorithm. This (...) chapter begins with a broad overview of health care AI and how it is currently used. We then adopt a “lifecycle” approach to discussing issues with health care AI. We start by discussing the legal and ethical issues pertaining to how data to build AI are gathered in health care settings, focusing on privacy. Next, we turn to issues in algorithm development, especially algorithmic bias. We then discuss AI deployment to treat patients, focusing on informed consent. Finally, we will discuss existing oversight mechanisms for health AI in the United States: liability and regulation. (shrink)

Artificial intelligence systems advising healthcare professionals will be widely introduced into healthcare settings within the next 5–10 years. This paper considers how this will sit with tort/negligence based legal approaches to compensation for medical error. It argues that the introduction of AI systems will provide an additional argument pointing towards no-fault compensation as the better legal solution to compensation for medical error in modern health care systems. The paper falls into four parts. The first part rehearses the main (...) arguments for and against no-fault compensation. The second explains why it is likely that AI systems will be widely introduced. The third part analyses why it is difficult to fit AI systems into fault-based compensation systems while the final part suggests how no-fault compensation could provide a possible solution to such challenges. (shrink)

Digital health and welfare technologies and artificial intelligence are proposed to revolutionise healthcare systems around the world by enabling new models of care. Digital health and welfare technologies enable remote monitoring and treatments, and artificial intelligence is proposed as a means of prediction instead of reaction to individuals’ health and as an enabler of proactive care and rehabilitation. The digital transformation not only affects hospital and primary care but also how the community meets older (...) people's needs. Community care is often provided by informal and formal care‐givers, most of whom are women. Gender equality is at the heart of many national strategies, but do all genders have equal rights, responsibilities and opportunities when it comes to community care and its digital transformation? The digital transformation of community care is entangled with how care is provided to older people and the working conditions of community‐care professionals. Current and, even more so, future community‐care systems are and will be partly constituted by networks of technological artefacts. These health and welfare technological artefacts and the discourse surrounding them mediate and constitute social relations and community care. This article looks into how health and welfare technology and artificial intelligence‐based devices and systems mediate and constitute gender relations in community care and presents an argument for reflexivity, embodiment, pluralism, participation and ecology as an alternative strategy to treating community care as one‐size‐fit‐all and being blind to gender‐related issues. (shrink)

Why do people comply with coronavirus disease 2019 public health guidance? This study considers cultural-psychological foundations of variation in beliefs about motivations for such compliance. Specifically, we focused on beliefs about two sources of prosocial motivation: desire to protect others and obligation to society. Across two studies, we observed that the relative emphasis on the desire to protect others as an explanation for compliance was greater in the United States settings associated with cultural ecologies of abstracted independence than in (...) Chinese settings associated with cultural ecologies of embedded interdependence. We observed these patterns for explanations of psychological experience of both others and self, and for compliance with mandates for both social distancing and face masks. Discussion of results considers both practical implications for motivating compliance with public health guidance and theoretical implications for denaturalizing prevailing accounts of prosocial motivation. (shrink)

As modern information and communication technologies (ICT) now offer new possibilities for improving almost every aspect of health care, their implementation is a very relevant and fast accelerating process around Europe and internationally. The processes themselves vary greatly from scattered single initiatives of various IT solutions to large national programmes. Often treated as purely technical in nature, ICT implementation in health care should gravitate towards the “softer/complex” i.e. people-related issues end of the change. The approach taken (...) by the Informing Healthcare programme in Wales broadens understanding on the value that engagement of stakeholders can bring to the process. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Toleration and Justice in the Laozi:Engaging with Tao Jiang's Origins of Moral-Political Philosophy in Early ChinaAi Yuan (bio)IntroductionThis review article engages with Tao Jiang's ground-breaking monograph on the Origins of Moral-Political Philosophy in Early China with particular focus on the articulation of toleration and justice in the Laozi (otherwise called the Daodejing).1 Jiang discusses a naturalistic turn and the re-alignment of values in the Laozi, resulting in a naturalization (...) of justice (impartiality) by rejecting artificial humaneness and rigid hierarchical moral-political structures. In this Laozian just world, there is no room for human intervention and rigid top-down enforcement of values, thus leaving justice to naturalized Heaven or Dao as the ultimate source of the cosmos.Based on Jiang's interpretative context, I show that there is a twofold justification for the "paradoxical" and "elusive"2 value of political toleration.3 A negative expression of toleration focuses on non-interference with choices, and non-enforcement of values toward those whom one reasonably disagrees with and regards as morally wrong. Such an attitude of toleration results in practical advantages such as avoiding entrenchment in bloodshed, abandonment, and deprivation.A positive expression of toleration operating in the Laozian ideal world requires equal protection of people as capable knowers, including those to whom we object. Such protection includes their ways of expression and an unbiased recognition of them as equally capable knowers so that they are heard without bias and prejudice. Such a kind of toleration is revealed as a constituent component of justice since it enables equal contribution toward the shaping of society without discrimination. In other words, toleration is seen as naturalized justice in a Laozian world within which no one is "being wronged with the capacity as a knower"—a kind of epistemic justice articulated by Miranda Fricker (Fricker 2007).4 [End Page 466]This article discusses how Jiang's political reconstruction of Laozian philosophy contains the seeds for a discussion of toleration, a value associated with distributive justice and against epistemic injustice. First, it introduces Jiang's arguments on a naturalization of justice and impartiality as Heavenly attributes in the Laozi. Second, it articulates the value of tolerance in the Laozi. Finally, I compare Laozian toleration with Confucian toleration using youwei- wuwei metaethical criticism.Moral-Political Philosophy in the LaoziJiang's interpretative framework about the origins of distributive justice in the Laozi starts with a discussion of the cosmogonic-mystical worldviews that signal "a new understanding of the nature of the cosmos, as well as a broad reorientation in the Heaven-human relationship in the mid-Warring States period" (p. 192). Differing from the interests in the origins of human culture or civilization in the Ru and Mo traditions, Jiang agrees with Franklin Perkins and identifies a "cosmogonic turn" in the late fourth century b.c. that reveals a demotion of anthropomorphic Heaven. By paring Heaven with earth and accordingly decentering human beings in the intellectual discourse, the Laozi directs equal values to the ten thousand things, with humans as just one among them (Perkins 2016, quoted in Jiang 2021, p. 196).5 Laozi's philosophy thus stands out by rejecting Heaven as caring for human affairs while taking Dao as the ultimate origin of the cosmos, as claimed in chapter 5 of the received text: "Heaven and earth are not humane; they treat ten-thousand things in the world as straw dogs; the sage is not humane; he treats people as straw dogs" (p. 199).With Jiang's reading of a naturalistic heaven, we see a re-alignment between cosmos and the human since sage-rulers follow the Heaven-Dao. The Laozian Dao is "self-so-ing" (ziran 自然), "accommodating" (rong 容), and "impartial" (gong 公), and thus marks a sharp contrast to Confucian familial bias resulting in "actively intervening in human affairs on behalf of the (certain) humans by appointing them to carry out its mission" (p. 200). With the sage emulating the ultimate Dao, the Laozi replaces the Confucian anthropocentric Heaven, which focuses on partiality (qin 親) and humaneness (ren 仁).This Laozian understanding of the cosmos also grounds its philosophical departure from Mohism despite both having a political... (shrink)

Machine‐learning algorithms have the potential to revolutionise diagnostic and prognostic tasks in health care, yet algorithmic performance levels can be materially worse for subgroups that have been underrepresented in algorithmic training data. Given this epistemic deficit, the inclusion of underrepresented groups in algorithmic processes can result in harm. Yet delaying the deployment of algorithmic systems until more equitable results can be achieved would avoidably and foreseeably lead to a significant number of unnecessary deaths in well‐represented populations. Faced with (...) this dilemma between equity and utility, we draw on two case studies involving breast cancer and melanoma to argue for the selective deployment of diagnostic and prognostic tools for some well‐represented groups, even if this results in the temporary exclusion of underrepresented patients from algorithmic approaches. We argue that this approach is justifiable when the inclusion of underrepresented patients would cause them to be harmed. While the context of historic injustice poses a considerable challenge for the ethical acceptability of selective algorithmic deployment strategies, we argue that, at least for the case studies addressed in this article, the issue of historic injustice is better addressed through nonalgorithmic measures, including being transparent with patients about the nature of the current epistemic deficits, providing additional services to algorithmically excluded populations, and through urgent commitments to gather additional algorithmic training data from excluded populations, paving the way for universal algorithmic deployment that is accurate for all patient groups. These commitments should be supported by regulation and, where necessary, government funding to ensure that any delays for excluded groups are kept to the minimum. We offer an ethical algorithm for algorithms—showing when to ethically delay, expedite, or selectively deploy algorithmic systems in healthcare settings. (shrink)

In recent years, research in robotics and artificial intelligence (AI) has made rapid progress. It is expected that robots and AI will play a part in the field of nursing and their role might broaden in the future. However, there are areas of nursing practice that cannot or should not be entrusted to robots and AI, because nursing is a highly humane practice, and therefore, there would, perhaps, be some practices that should not be replicated by robots or AI. Therefore, (...) this paper focuses on several ethical concepts (advocacy, accountability, cooperation, and caring) that are considered important in nursing practice, and examines whether it is possible to implement these ethical concepts in robots and AI by analyzing the concepts and the current state of robotics and AI technology. Advocacy: Among the components of advocacy, safeguarding and apprising can be more easily implemented, while elements that require emotional communication with patients, such as valuing and mediating, are difficult to implement. Accountability: Robotic nurses with explainable AI have a certain level of accountability. However, the concept of explanation has problems of infinite regression and attribution of responsibility. Cooperation: If robot nurses are recognized as members of a community, they require the same cooperation as human nurses. Caring: More difficulties are expected in care-receiving than in caregiving. However, the concept of caring itself is ambiguous and should be explored further. Accordingly, our analysis suggests that, although some difficulties can be expected in each of these concepts, it cannot be said that it is impossible to implement them in robots and AI. However, even if it were possible to implement these functions in the future, further study is needed to determine whether such robots or AI should be used for nursing care. In such discussions, it will be necessary to involve not only ethicists and nurses but also an array of society members. (shrink)

What does Artificial Intelligence (AI) have to contribute to health care? And what should we be looking out for if we are worried about its risks? In this paper we offer a survey, and initial evaluation, of hopes and fears about the applications of artificial intelligence in medicine. AI clearly has enormous potential as a research tool, in genomics and public health especially, as well as a diagnostic aid. It’s also highly likely to impact on the organisational (...) and business practices of healthcare systems in ways that are perhaps under-appreciated. Enthusiasts for AI have held out the prospect that it will free physicians up to spend more time attending to what really matters to them and their patients. We will argue that this claim depends upon implausible assumptions about the institutional and economic imperatives operating in contemporary healthcare settings. We will also highlight important concerns about privacy, surveillance, and bias in big data, as well as the risks of over trust in machines, the challenges of transparency, the deskilling of healthcare practitioners, the way AI reframes healthcare, and the implications of AI for the distribution of power in healthcare institutions. We will suggest that two questions, in particular, are deserving of further attention from philosophers and bioethicists. What does care look like when one is dealing with data as much as people? And, what weight should we give to the advice of machines in our own deliberations about medical decisions? (shrink)

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. (shrink)

Spoken communication between social robotic devices, powered by generative AI tools such as ChatGPT, and the senior population offers great potential for researching social interaction and robot identity perceptions as well as exploring the potential opportunities and challenges when implementing this human-machine interactions in real life situations and health care. In this paper we explore people’s perceptions of the social robot Furhat when administering verbal tasks similar to those used in screening for Alzheimer’s disease. We describe the Slovak (...) system mounted on the robot that includes a speech recognizer, the scenarios powered by generative large language model ChatGPT, and a speech synthesizer. We tested the functionality of the proposed approach with two groups of participants: attendees of a large science fair and a scientific conference. The observations from 87 collected questionnaires suggest good potential and applicability of such an approach for the given task and more positive attitudes of older subjects compared to younger ones. (shrink)

This article suggests several design principles intended to assist in the development of ethical algorithms exemplified by the task of fighting fake news. Although numerous algorithmic solutions have been proposed, fake news still remains a wicked socio-technical problem that begs not only engineering but also ethical considerations. We suggest employing insights from ethics of care while maintaining its speculative stance to ask how algorithms and design processes would be different if they generated care and fight fake news. After (...) reviewing the major characteristics of ethics of care and the phases of care, we offer four algorithmic design principles. The first principle highlights the need to develop a strategy to deal with fake news on the part of the software designers. The second principle calls for the involvement of various stakeholders in the design processes in order to increase the chances of successfully fighting fake news. The third principle suggests allowing end-users to report on fake news. Finally, the last principle proposes keeping the end-user updated on the treatment in the suspected news items. Implementing these principles as care practices can render the developmental process more ethically oriented as well as improve the ability to fight fake news. (shrink)

Lifestyle diseases constitute an increasing proportion of health problems and this trend is likely to continue. A better understanding of the responsibility argument is important for the assessment of policies aimed at meeting this challenge. Holding individuals accountable for their choices in the context of health care is, however, controversial. There are powerful arguments both for and against such policies. In this article the main arguments for and the traditional arguments against the use of individual responsibility as (...) a criterion for the distribution of scarce health resources will be briefly outlined. It is argued that one of the most prominent contemporary normative traditions, liberal egalitarianism, presents a way of holding individuals accountable for their choices that avoids most of the problems pointed out by the critics. The aim of the article is to propose a plausible interpretation of liberal egalitarianism with respect to responsibility and health care and assess it against reasonable counter-arguments. (shrink)

Public collective hunger strikes take place in complex social and political contexts, require medical attention and present ethical challenges to physicians. Empirical research, the ethical debate to date and existing guidelines by the World Medical Association focus almost exclusively on hunger strikes in detention. However, the public space differs substantially with regard to the conditions for the provision of health care and the diverse groups of healthcare providers or stakeholders involved. By reviewing empirical research on the experience of (...) health professionals with public collective hunger strikes, we identified the following ethical challenges: (1) establishment of a trustful physician–striker relationship, (2) balancing of medico‐ethical principles in medical decision‐making, (3) handling of loyalty conflicts and (4) preservation of professional independence and the risk of political instrumentalization. Some of these challenges have already been described and discussed, yet not contextualized for public collective strikes, while others are novel. The presence of voluntary physicians may offer opportunities for a trustful relationship and, hence, for ethical treatment decisions. According to our findings, it requires more attention to how to realise autonomous medical decisions in the complex context of a dynamic, often unstructured and politically charged setting, which ethical norms should shape the professional role of voluntary physicians, and what is the influence of the hunger strikers' collective on individual healthcare decisions. Our article can serve as a starting point for further ethical discussion. It can also provide the basis for the development of potential guidelines to support health professionals involved in public collective hunger strikes. (shrink)

The purpose of this study was to identify how older Korean people seek information and their desire to participate in decision making about their health care. A total of 165 elderly people living in Seoul, South Korea, participated in the study. Data were collected during individual interviews using the Autonomy Preference Index. The mean information-seeking score was high. The mean score for their desire to participate with a physician in decision making was lower, but this was higher when (...) family members were involved. The study indicates that many older people want to receive information about their health care. Families (or guardians), as well as older people themselves, should be included in the decision-making process. Nurses can encourage older people to express their wishes, while treating each individual with respect. (shrink)

In July 1993, the Scottish Highlands Centre for Human Caring sponsored a conference with the title Exploring the Spirituality in Caring. The papers given at the conference and included in this volume are offered as a contribution to the debate that must take place in nursing and in the wider context of health care provision. Ann Bradshaw's paper puts the debate in context arguing that nursing is fundamentally a loving response to the human being created in the image (...) of God. (shrink)

Background Caring behaviour is critical for nursing quality, and the clinical internship environment is a crucial setting for preparing nursing students for caring behaviours. Evidence about how to develop nursing students’ caring behaviour in the clinical environment is still emerging. However, the mechanism between the clinical internship environment and caring behaviour remains unclear, especially the mediating role of moral sensitivity and the moderating effect of self-efficacy. Research objective This study aimed to examine the mediating effect of moral sensitivity and the (...) moderating function of self-efficacy on the association between the clinical internship environment and caring behaviours. Research design A cross-sectional design used acceptable validity scales. The hypothesised moderated mediation model was tested in the SPSS PROCESS macro. Participants and research context This survey collected data from 504 nursing students in an internship at a teaching hospital in Changsha, China. Ethical considerations This study was pre-approved by the ethics committee of the medical school (No. E2022210). Informed consent was obtained from all students. Results The clinical internship environment ( B = 0.450, 95% CI = [0.371, 0.530]) and moral sensitivity ( B = 1.352, 95% CI = [1.090, 1.615]) had positive direct effects on nursing students' caring behaviours. Clinical internship environment also indirectly influenced students’ caring behaviours via moral sensitivity ( B = 0.161, 95% CI = [0.115, 0.206]). In addition, self-efficacy played a moderating role between the clinical internship environment and caring behaviours ( B = 0.019, 95% CI = [0.007, 0.031]), as well as the relationship between the clinical internship environment and moral sensitivity ( B = 0.006, 95% CI = [0.003, 0.010]). Conclusion Moral sensitivity mediates the effect of the clinical internship environment on caring behaviour, and self-efficacy strengthens both direct and indirect effects. This study emphasises the importance of self-efficacy in developing moral sensitivity and caring behaviours in nursing students. (shrink)

Justified by spectacular achievements facilitated through applied deep learning methodology, the “Everything is possible” view dominates this new hour in the “boom and bust” curve of AI performance. The optimistic view collides head on with the “It is not possible”—ascertainments often originating in a skewed understanding of both AI and medicine. The meaning of the conflicting views can be assessed only by addressing the nature of medicine. Specifically: Which part of medicine, if any, can and should be entrusted to AI—now (...) or at some moment in the future? AI or not, medicine should incorporate the anticipation perspective in providing care. (shrink)

Equity in health and health care is animportant issue. It has been proposed that thepursuit of equity in health care is beinghampered by the dominance of individualism inhealth care practices. This paper explores theway in which communitarian ideals and practicesmight lend themselves to the pursuit of equity.Communitarians acknowledge, respect and fosterthe bonds that unite and identify communities.The paper argues that, to achieve equity inhealth care, these bonds need to be recognisedand harnessed rather than (...) ignored. The notionof individual autonomy in the context of thecommunity is examined. Alternative concepts ofautonomy – social autonomy and communityautonomy – are seen to be more respectful andnurturing of both the individual and thecommunity. Moreover, these concepts appeardesirable for the pursuit of health care equitygoals. The paper concludes with some thoughtsabout how equity in Australia's health caresystem can reasonably progress within acommunitarian vision. Disadvantaged communitiesare discussed throughout, in particular,Australian Aboriginal communities. (shrink)

This paper presents the author's model of humility structures that can be operationalized as behaviours and incorporated into healthcare practice, the Humility in Health Care Model. The Humility in Health Care Model expands and combines the concepts of cultural humility, holistic nursing, servant leadership and the Chinese concept ‘QIAN’. The paper identifies ways to create a regular practice of humility behaviours on the personal/interpersonal, leadership, systems and policy levels. The paper discusses the benefits of operationalizing humility, (...) forces that favour humility and barriers to practicing its behaviours. Suggestions for future research on humility in the healthcare professions are offered. (shrink)

Health care systems can positively influence our personal decision-making and health-related behavior only if we trust them. I propose a conceptual analysis of the trust relation between the public and a healthcare system, drawing from healthcare studies and philosophical proposals. In my account, the trust relation is based on an epistemic component, epistemic authority, and on a value component, the benevolence of the healthcare system. I argue that it is also modified by the vulnerability of the public (...) on healthcare matters, and by the system’s credibility. I apply my proposed analysis of public trust in health care systems to the phenomenon of vaccine hesitancy, a tendency to question vaccine policies, and to seek alternative vaccine schedules or to refuse vaccination. Understanding the role of trust and its components can be key to understanding the phenomenon. (shrink)

Faith has been shown to serve a protective role in the mental health of African Americans and European Americans. However, little research has examined whether any association exists in Asian Americans. Using the National Latino and Asian American Study dataset, we examined the effect of religious attendance on the mental health of Asian Americans in the United States. The present study focused on Chinese Americans because they are the largest Asian American group. The results revealed that almost 80% (...) of the respondents were foreign-born and that their English proficiency had a positive association with their self-rated mental health. Being male correlated significantly to higher levels of mental health self-rating. After controlling for known predictive variables, such as demographics, cultural and immigration variables, more frequent religious attendance significantly predicted higher self-rating of mental health. These findings suggest that faith may have a unique protective role in Chinese Americans’ mental health. (shrink)

Rapid advancements in artificial intelligence and machine learning (AI/ML) in healthcare raise pressing questions about how much users should trust AI/ML systems, particularly for high stakes clinical decision-making. Ensuring that user trust is properly calibrated to a tool’s computational capacities and limitations has both practical and ethical implications, given that overtrust or undertrust can influence over-reliance or under-reliance on algorithmic tools, with significant implications for patient safety and health outcomes. It is, thus, important to better understand how variability in (...) trust criteria across stakeholders, settings, tools and use cases may influence approaches to using AI/ML tools in real settings. As part of a 5-year, multi-institutional Agency for Health Care Research and Quality-funded study, we identify trust criteria for a survival prediction algorithm intended to support clinical decision-making for left ventricular assist device therapy, using semistructured interviews (n=40) with patients and physicians, analysed via thematic analysis. Findings suggest that physicians and patients share similar empirical considerations for trust, which were primarilyepistemicin nature, focused on accuracy and validity of AI/ML estimates. Trust evaluations considered the nature, integrity and relevance of training data rather than the computational nature of algorithms themselves, suggesting a need to distinguish ‘source’ from ‘functional’ explainability. To a lesser extent, trust criteria were also relational (endorsement from others) and sometimes based on personal beliefs and experience. We discuss implications for promoting appropriate and responsible trust calibration for clinical decision-making use AI/ML. (shrink)

Readings in Health Care Ethics provides a wide-ranging selection of important and engaging contributions to the field of health care ethics. The second edition adds a chapter on health care in Canada, and the introduction has been expanded to include discussion of a new direction in feminist naturalized ethics. The book presupposes no prior knowledge, only an interest in the bioethical issues that are shaping our world.

This manuscript draws on the moral norms arising from the nuanced accounts of epistemic (in)justice and social identity in relational autonomy to normatively assess and articulate the ethical problems associated with using AI in patient care in light of the Black Box problem. The article also describes how black-boxed AI may be used within the healthcare system. The manuscript highlights what needs to happen to align AI with the moral norms it draws on. Deeper thinking – from other backgrounds (...) other than decolonial scholarship and relational autonomy – about the impact of AI on the human experience needs to be done to appreciate any other barriers that may exist. Future studies can take up this task. (shrink)

Historically associated with military service, conscientious objection has become a significant phenomenon in health care. Mark Wicclair offers a comprehensive ethical analysis of conscientious objection in three representative health care professions: medicine, nursing and pharmacy. He critically examines two extreme positions: the 'incompatibility thesis', that it is contrary to the professional obligations of practitioners to refuse provision of any service within the scope of their professional competence; and 'conscience absolutism', that they should be exempted from performing (...) any action contrary to their conscience. He argues for a compromise approach that accommodates conscience-based refusals within the limits of specified ethical constraints. He also explores conscientious objection by students in each of the three professions, discusses conscience protection legislation and conscience-based refusals by pharmacies and hospitals, and analyzes several cases. His book is a valuable resource for scholars, professionals, trainees, students, and anyone interested in this increasingly important aspect of health care. (shrink)

Through an analysis of several high‐profile scandals in health‐care in the UK, this article discusses the nature of scandal and its impact on policy reform. The nursing profession is compared to social work and medicine, which have also undergone considerable examination and change as a result of scandals. The author draws on reports from public inquiries from 1945 to 2013 to form the basis of the discussion about policy responses following scandals in health‐care. In each case, (...) the nature of the scandal, the public and government discourses generated by events and the policy response to those failings are explored. These scandals are compared to the recent scandal at Mid Staffordshire Hospital. Conclusions are drawn about the impact of these events on the future of the profession and on health policy directions. Recent events have raised public anxieties about caring practices in nursing. Health policy reform driven by scandal may obscure the effect of under resourcing in health services and poses a very real threat to the continued support for state‐run services. Understanding the socially constructed nature of scandal enables the nurse to develop a greater critical awareness of policy contexts in order that they can influence health service reform. (shrink)

A frenetic search for equality lies at the center of much secular and even “Christian” bioethics. In a secular world, if one does not believe in God, if this life is one's whole existence, it would seem that one could not settle for less than equal approbation, especially equality before the risks of suffering and death, which medicine promises to ameliorate. Yet, the concern for equality in health care is puzzling. After a modest level of access to (...) class='Hi'>health care there is little difference in average life expectancy. Are concerns for equality in health care even vaguely Christian? The pursuit of Christian perfection has never been correctly equated with state-imposed egalitarianism. Furthermore, an all-encompassing, secular, egalitarian health care system may provide equal access to significantly immoral medical treatments. In contrast to secular thought, the call of Christianity is a call to holiness, not a call to an egalitarianism that superficially resonates with certain elements of Christian thought. (shrink)

Tännsjö’s book Setting Health-Care Priorities defends the view that there are three main normative theories in the domain of distributive justice, and that these theories are both highly plausible in themselves, and practically convergent in their normative conclusions. All three theories point to a somewhat radical departure from the present distribution of medical resources: in particular, they suggest redirecting resources from marginal life extension to the care of mentally ill patients. In this paper I wish to argue, (...) firstly, that prioritarianism should not be considered as an amendment to utilitarianism, as it is in Tännsjö’s view, but as a distinctive fourth option. This can best be appreciated if we focus on a reading of the theory that emphasizes its derivation from egalitarianism and its attempt to develop an intermediate approach between utilitarian and egalitarian intuitions. Secondly, in response to Tännsjö’s central objection to prioritarianism, I will argue that the theory does not apply in intrapersonal cases but is only relevant for decisions regarding the interpersonal distribution of benefits. Finally, I will suggest that a practical convergence of the four theories on specific issues such as artificial reproduction or mood enhancement is far less likely than Tännsjö seems to believe. (shrink)