The integration of normative analysis with empirical data often remains unclear despite the availability of many empirical bioethics methodologies. This paper sought bioethics scholars’ experiences and reflections of doing empirical bioethics research to feed these practical insights into the debate on methods. We interviewed twenty-six participants who revealed their process of integrating the normative and the empirical. From the analysis of the data, we first used the themes to identify the methodological content. That is, we show participants’ use of familiar (...) methods explained as “back-and-forth” methods (reflective equilibrium), followed by dialogical methods where collaboration was seen as a better way of doing integration. Thereafter, we highlight methods that were deemed as inherent integration approaches, where the normative and the empirical were intertwined from the start of the research project. Second, we used the themes to express not only how we interpreted what was said but also how things were said. In this, we describe an air of uncertainty and overall vagueness that surrounded the above methods. We conclude that the indeterminacy of integration methods is a double-edged sword. It allows for flexibility but also risks obscuring a lack of understanding of the theoretical-methodological underpinnings of empirical bioethics research methods. (shrink)

BackgroundThis is the first qualitative study to investigate how researchers, who do empirical work in bioethics, relate to objectives of empirical research in bioethics (ERiB). We explore reasons that make some objectives more acceptable, while others are deemed less acceptable.MethodsUsing qualitative exploratory study design, we interviewed bioethics researchers, who were selected to represent different types of scholars working in the field. The interview data of 25 participants were analyzed in this paper using thematic analysis. ResultsFrom the eight objectives presented to (...) the study participants, understanding the context of a bioethical issue and identifying ethical issues in practice received unanimous agreement. Participants also supported other objectives of ERiB but with varying degrees of agreement. The most contested objectives were striving to draw normative recommendations and developing and justifying moral principles. The is-ought gap was not considered an obstacle to ERiB, but rather a warning sign to critically reflect on the normative implications of empirical results.ConclusionsOur results show that the most contested objectives are also the more ambitious ones, whereas the least contested ones focus on producing empirical results. The potential of empirical research to be useful for bioethics was mostly based on the reasoning pattern that empirical data can provide a testing ground for elements of normative theory. Even though empirical research can inform many parts of bioethical inquiry, normative expertise is recommended to guide ERiB. The acceptability of ambitious objectives for ERiB boils down to finding firm ground for the integration of empirical facts in normative inquiry. (shrink)

Reflective equilibrium is overdue a twenty-first century update. Despite its apparent popularity, there is scant evidence that theorists ever thoroughly implement the method, and fewer still openly and transparently publish their attempts to do so in print—stymying its supposed justificatory value. This paper proposes digitising reflective equilibrium as a solution. Inspired by the global open science movement, it advocates for coupling a novel, digital implementation of the equilibrating process with new publication norms that can capitalise on the inherent reproducibility of (...) digital data. The argument is structured around three main claims: that digitising will make it easier to (a) methodically construct, (b) widely disseminate, and (c) thoroughly critique reflective equilibria. Practical guidance is also provided throughout. Altogether, it is argued that digitisation will not only help theorists to better realise reflective equilibrium’s latent theoretical potential, but also greatly extend its value as a justificatory device in contemporary academic discourses. (shrink)

The increasing application of artificial intelligence (AI) to healthcare raises both hope and ethical concerns. Some advanced machine learning methods provide accurate clinical predictions at the expense of a significant lack of explainability. Alex John London has defended that accuracy is a more important value than explainability in AI medicine. In this article, we locate the trade-off between accurate performance and explainable algorithms in the context of distributive justice. We acknowledge that accuracy is cardinal from outcome-oriented justice because it helps (...) to maximize patients’ benefits and optimizes limited resources. However, we claim that the opaqueness of the algorithmic black box and its absence of explainability threatens core commitments of procedural fairness such as accountability, avoidance of bias, and transparency. To illustrate this, we discuss liver transplantation as a case of critical medical resources in which the lack of explainability in AI-based allocation algorithms is procedurally unfair. Finally, we provide a number of ethical recommendations for when considering the use of unexplainable algorithms in the distribution of health-related resources. (shrink)

Formulating sound and acceptable embryo research policy remains challenging especially in a pluralistic world. This challenge has acquired a new dimension of complexity with the advent of so-called embryo models, which are derived from stem cells. In this article, we present a normative strategy to facilitate the process of sound policy-making in the field of human embryology. This strategy involves seeking neutral agreements on higher level theories and doctrines as well as seeking agreements on the level of concrete policy proposals. (...) We call this strategy: going high and low. By going high and low, the plurality of reasonable moral and epistemic convictions of stakeholders involved in the domain of human embryology is respected while the process of policy-making in this area is improved. (shrink)

A human driver and an automated driving system might share control of automated vehicles in the near future. This raises many concerns associated with the assignment of responsibility for negative outcomes caused by them; one is that the human driver might be required to bear the brunt of moral and legal responsibilities. The psychological consequences of responsibility misattribution have not yet been examined. We designed a hypothetical crash similar to Uber’s 2018 fatal crash. We incorporated five legal responsibility attributions. Participants (...) chose their preferred liability attribution and then were randomly assigned into one of the five actual liability attribution conditions. They then responded to a series of questions concerning liability assignment, the crash, and AVs. Slightly more than 50% of participants thought that the human driver should bear full or primary liability. Legal responsibility misattribution negatively influenced these mentioned responses, regardless of overly attributing human or manufacturer liability. Overly attributing human liability had more negative influences. Improper liability attribution might hinder the adoption of AVs. Public opinion should not be ignored in developing a legal framework for AVs. (shrink)

Crashes involving self-driving cars at least superficially resemble trolley dilemmas. This article discusses what lessons machine ethicists working on the ethics of self-driving cars can learn from trolleyology. The article proceeds by providing an account of the trolley problem as a paradox and by distinguishing two types of solutions to the trolley problem. According to an optimistic solution, our case intuitions about trolley dilemmas are responding to morally relevant differences. The pessimistic solution denies that this is the case. An optimistic (...) solution would yield first-order moral insights for the ethics of self-driving cars, but such a solution is difficult to come by. More plausible is the pessimistic solution, and it teaches us a methodological lesson. The lesson is that machine ethicists should discount case intuitions and instead rely on intuitions and judgments at a higher level of generality. (shrink)

How should scarce healthcare resources be distributed? This is a contentious issue that became especially pressing during the pandemic. It is often emphasised that studies exploring public views about this question provide valuable input to the issue of healthcare priority setting. While there has been a vast number of such studies it is rarely articulated, more specifically, what the results from these studies would mean for the justification of principles for priority setting. On the one hand, it seems unreasonable that (...) public values would straightforwardly decide the ethical question of how resources should be distributed. On the other hand, in a democratic society, it seems equally unreasonable that they would be considered irrelevant for this question. In this paper we draw on the notion of reflective equilibrium and discuss the relevance and roles that empirical studies may plausibly have for justification in priority setting ethics. We develop a framework for analysing how different kinds of empirical results may have different kinds of implications for justification. (shrink)