What exactly is a “wicked problem”? It is a social or economic problem that is so complex and so interconnected with other issues that it is extraordinarily difficult or impossible to resolve. This is because all proposed resolutions generate equally complex, equally wicked problems. In this essay, I argue that precision medicine, especially in the context of the U.S. healthcare system, generates numerous wicked problems related to distributive justice. Further, I argue that there are no easy solutions to these wicked problems. The need for trade-offs is inescapable. Rough justice is the best outcome we can hope for, and that outcome requires a commitment to processes of public reason that are fair and inclusive.

The question that this paper tries to answer is Q: “Can good academic bioethics be done without commitment to moral theory?” It is argued that the answer to Q is an unequivocal “Yes” for most of what we could call “critical bioethics,” that is, the kind of bioethics work that primarily criticizes positions or arguments already in the literature or put forward by policymakers. The answer is also “Yes” for much of empirical bioethics. The second part of the paper then provides an analysis of Q in relation to “constructive bioethics,” that is, bioethics work aimed at providing an argument for a particular position. In this part, it is argued that a number of the approaches or methods used that initially look like they involve no commitment to moral theory, nevertheless, involve such a commitment. This is shown to be the case for reflective equilibrium, mid-level theory, the use of theory fragments, and argument by analogy.

Artificial intelligence (AI) is a powerful tool for several healthcare tasks. AI tools are suited to optimize predictive models in medicine. Ethical debates about AI’s extension of the predictive power of medical models suggest a need to adapt core principles of medical ethics. This article demonstrates that a popular interpretation of the principle of justice in healthcare needs amendment given the effect of AI on decision-making. The procedural approach to justice, exemplified with Norman Daniels and James Sabin’s accountability for reasonableness conception, needs amendment because, as research into algorithmic fairness shows, it is insufficiently sensitive to differential effects of seemingly just principles on different groups of people. The same line of research generates methods to quantify differential effects and make them amenable for correction. Thus, what is needed to improve the principle of justice is a combination of procedures for selecting just criteria and principles and the use of algorithmic tools to measure the real impact these criteria and principles have. In this article, the author shows that algorithmic tools do not merely raise issues of justice but can also be used in their mitigation by informing us about the real effects certain distributional principles and criteria would create.

Recent global events demonstrate that analytical frameworks to aid professionals in healthcare ethics must consider the pervasive role of social structures in the emergence of bioethical issues. To address this, the authors propose a new sociologically informed approach to healthcare ethics that they term “social bioethics.” Their approach is animated by the interpretive social sciences to highlight how social structures operate vis-à-vis the everyday practices and moral reasoning of individuals, a phenomenon known as social discourse. As an exemplar, the authors use social bioethics to reframe common ethical issues in psychiatric services and discuss potential implications. Lastly, the authors discuss how social bioethics illuminates the ways healthcare ethics consultants in both policy and clinical decision-making participate in and shape broader social, political, and economic systems, which then cyclically informs the design and delivery of healthcare.

This article highlights the continuing relevance of a classic bioethical text, “Bioethics as a Discipline,” published by the Hastings Center’s cofounder Daniel Callahan in 1973. Connecting the text’s programmatic recommendations with later reflections and interventions Callahan wrote about the development of bioethics illuminates how the vision Callahan established and the reality this vision helped create were interrelated—just not in the way Callahan had hoped for. Although this portrait relies on an individual perception of the development of bioethics, it might nevertheless, through its unique linkage of different bioethical temporalities, contribute to a broader reassessment of what bioethics became and why.

This is the second paper in a two-part series describing subject and family perspectives from the CENTURY-S (CENtral Thalamic Deep Brain Stimulation for the Treatment of Traumatic Brain InjURY-Safety) first-in-human invasive neurological device trial to achieve cognitive restoration in moderate to severe traumatic brain injury (msTBI). To participate, subjects were independently assessed to formally establish decision-making capacity to provide voluntary informed consent. Here, we report on post-operative interviews conducted after a successful trial of thalamic stimulation. All five msTBI subjects met a pre-selected primary endpoint of at least a 10% improvement in completion time on Trail-Making-Test Part B, a marker of executive function. We describe narrative responses of subjects and family members, refracted against that success. Interviews following surgery and the stimulation trial revealed the challenge of adaptation to improvements in cognitive function and emotional regulation as well as altered (and restored) relationships and family dynamics. These improvements exposed barriers to social reintegration made relevant by recoveries once thought inconceivable. The study’s success sparked concerns about post-trial access to implanted devices, financing of device maintenance, battery replacement, and on-going care. Most subjects and families identified the need for supportive counseling to adapt to the new trajectory of their lives.

Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are “black boxes.” The initial response in the literature was a demand for “explainable AI.” However, recently, several authors have suggested that making AI more explainable or “interpretable” is likely to be at the cost of the accuracy of these systems and that prioritizing interpretability in medical AI may constitute a “lethal prejudice.” In this paper, we defend the value of interpretability in the context of the use of AI in medicine. Clinicians may prefer interpretable systems over more accurate black boxes, which in turn is sufficient to give designers of AI reason to prefer more interpretable systems in order to ensure that AI is adopted and its benefits realized. Moreover, clinicians may be justified in this preference. Achieving the downstream benefits from AI is critically dependent on how the outputs of these systems are interpreted by physicians and patients. A preference for the use of highly accurate black box AI systems, over less accurate but more interpretable systems, may itself constitute a form of lethal prejudice that may diminish the benefits of AI to—and perhaps even harm—patients.

One of the criteria used by many transplant centers in assessing psychosocial eligibility for solid organ transplantation is social support. Yet, social support is a highly controversial requirement that has generated ongoing debate between ethicists and clinicians who favor its consideration (i.e., utility maximizers) and those who object to its use on equity grounds (i.e., equity maximizers). The assumption underlying both of these approaches is that social support is not a commodity that can be purchased in the marketplace. This essay argues for the reconceptualization of social support as a product that can—and should—be purchased for transplant candidates to render them eligible for transplant.

Pragmatism gained considerable attention in bioethical discussions in the early 21st century. However, some dimensions and contributions of pragmatism to bioethics remain underexplored in both research and practice. It is argued that pragmatism can make a distinctive contribution to bioethics through its concept, developed by Charles S. Peirce and John Dewey, that ethical issues can be resolved through experimental inquiry. Dewey’s proposal that policies can be confirmed or disconfirmed through experimentation is developed by comparing it to the confirmation of scientific hypotheses, with a focus on the objection that the consequences of following a moral view or policy do not provide guidance on choosing among competing ethical perspectives. As confirmation of scientific hypotheses typically relies on evidence gathered from observation, the possibility of ethically relevant observation is then explored based on Peirce’s views on feelings as emotional interpretants. Finally, the connection between Dewey’s experimental ethics and democracy is outlined and compared to unfettered ethical progressivism.

Luck egalitarianism is a responsibility-sensitive theory of distributive justice. Its application to health and healthcare is controversial. This article addresses a novel critique of luck egalitarianism, namely, that it wrongfully discriminates against those responsible for their health disadvantage when allocating scarce healthcare resources. The philosophical literature about discrimination offers two primary reasons for what makes discrimination wrong (when it is): harm and disrespect. These two approaches are employed to analyze whether luck egalitarian healthcare prioritization should be considered wrongful discrimination. Regarding harm, it is very plausible to consider the policies harmful but much less reasonable to consider those responsible for their health disadvantages a socially salient group. Drawing on the disrespect literature, where social salience is typically not required for something to be discrimination, the policies are a form of discrimination. They are, however, not disrespectful. The upshot of this first assessment of the discrimination objection to luck egalitarianism in health is, thus, that it fails.

Position papers on artificial intelligence (AI) ethics are often framed as attempts to work out technical and regulatory strategies for attaining what is commonly called trustworthy AI. In such papers, the technical and regulatory strategies are frequently analyzed in detail, but the concept of trustworthy AI is not. As a result, it remains unclear. This paper lays out a variety of possible interpretations of the concept and concludes that none of them is appropriate. The central problem is that, by framing the ethics of AI in terms of trustworthiness, we reinforce unjustified anthropocentric assumptions that stand in the way of clear analysis. Furthermore, even if we insist on a purely epistemic interpretation of the concept, according to which trustworthiness just means measurable reliability, it turns out that the analysis will, nevertheless, suffer from a subtle form of anthropocentrism. The paper goes on to develop the concept of strange error, which serves both to sharpen the initial diagnosis of the inadequacy of trustworthy AI and to articulate the novel epistemological situation created by the use of AI. The paper concludes with a discussion of how strange error puts pressure on standard practices of assessing moral culpability, particularly in the context of medicine.

Organoids and specifically human cerebral organoids (HCOs) are one of the most relevant novelties in the field of biomedical research. Grown either from embryonic or induced pluripotent stem cells, HCOs can be used as in vitro three-dimensional models, mimicking the developmental process and organization of the developing human brain. Based on that, and despite their current limitations, it cannot be assumed that they will never at any stage of development manifest some rudimentary form of consciousness. In the absence of behavioral indicators of consciousness, the theoretical neurobiology of consciousness being applied to unresponsive brain-injured patients can be considered with respect to HCOs. In clinical neurology, it is difficult to discern a capacity for consciousness in unresponsive brain-injured patients who provide no behavioral indicators of consciousness. In such scenarios, a validated neurobiological theory of consciousness, which tells us what the neural mechanisms of consciousness are, could be used to identify a capacity for consciousness. Like the unresponsive patients that provide a diagnostic difficulty for neurologists, HCOs provide no behavioral indicators of consciousness. Therefore, this article discusses how three prominent neurobiological theories of consciousness apply to human cerebral organoids. From the perspective of the Temporal Circuit Hypothesis, the Global Neuronal Workspace Theory, and the Integrated Information Theory, we discuss what neuronal structures and functions might indicate that cerebral organoids have a neurobiological capacity to be conscious.

Advances in brain–brain interface technologies raise the possibility that two or more individuals could directly link their minds, sharing thoughts, emotions, and sensory experiences. This paper explores conceptual and ethical issues posed by such mind-merging technologies in the context of clinical neuroethics. Using hypothetical examples along a spectrum from loosely connected pairs to fully merged minds, the authors sketch out a range of factors relevant to identifying the degree of a merger. They then consider potential new harms like loss of identity, psychological domination, loss of mental privacy, and challenges for notions of autonomy and patient benefit when applied to merged minds. While radical technologies may seem to necessitate new ethical paradigms, the authors suggest the individual-focus underpinning clinical ethics can largely accommodate varying degrees of mind mergers so long as individual patient interests remain identifiable. However, advanced decisionmaking and directives may have limitations in addressing the dilemmas posed. Overall, mind-merging possibilities amplify existing challenges around loss of identity, relating to others, autonomy, privacy, and the delineation of patient interests. This paper lays the groundwork for developing resources to address the novel issues raised, while suggesting the technologies reveal continuity with current healthcare ethics tensions.

The paper aims to present a critical analysis of the phenomenon and notion of exceptionalism in bioethics. The authors demonstrate that exceptionalism pertains to phenomena that are not (yet) entirely familiar to us and could potentially bear risks regarding their regulation. After an overview of the state of the art, we briefly describe the origins and evolution of the concept, compared to exception and exclusion. In the second step, they look at the overall development debates on genetic exceptionalism, compared to other bioethical debates on exceptionalism, before presenting a detailed analysis of a specific case of early regulation of genetic screening. In the last part, the authors explain the historical background behind the connection between exceptionalism and exclusion in these debates. Their main conclusion is that while the initial stage of the discussion is shaped by the concept of exceptionalism and awareness of risks of exclusion, the later development centers around exceptions that are needed in detailed regulatory procedures.

It is a common view that artificial systems could play an important role in dealing with the shortage of caregivers due to demographic change. One argument to show that this is also in the interest of care-dependent persons is that artificial systems might significantly enhance user autonomy since they might stay longer in their homes. This argument presupposes that the artificial systems in question do not require permanent supervision and control by human caregivers. For this reason, they need the capacity for some degree of moral decision-making and agency to cope with morally relevant situations (artificial morality). Machine ethics provides the theoretical and ethical framework for artificial morality. This article scrutinizes the question how artificial moral agents that enhance user autonomy could look like. It discusses, in particular, the suggestion that they should be designed as moral avatars of their users to enhance user autonomy in a substantial sense.

Capacity evaluation has become a widely used assessment device in clinical practice to determine whether patients have the cognitive ability to render their own medical decisions. Such evaluations, which might be better thought of as “capacity challenges,” are generally thought of as benign tools used to facilitate care. This paper proposes that such challenges should be reconceptualized as significant medical interventions with their own set of risks, side effects, and potentially deleterious consequences. As a result, a cost–benefit analysis should be implemented prior to imposing such capacity challenges, and efforts should be made to minimize such challenges in situations where they are unlikely to alter the course of treatment.