New Bioethics-A Multidisciplinary Journal of Biotechnology and the Body最新文献

The lived experience of human moral agency suggests that some actions favour human flourishing while others lead to division and conflict: the universal human desire for happiness is bound up with the effort to discern and do 'good' and to avoid 'evil'. Words exist to convey an experience, and the word 'conscience' has emerged as an attempt to describe the experience of moral discernment. We offer an account of the development of the word 'conscience'. Our treatment is divided into three sections: the first beginning around 600 BCE until the arrival of Christianity; the second will cover the Christian era through to the Protestant Reformation of the sixteenth century; and the third section will cover post-Reformation and post-Christian developments to the present day. We argue that the Christian understanding of the conscience constitutes a major human achievement with durable and beneficial effects on human history, and that the progressive undermining of the Christian notion of conscience is an important contributor to the fragmentation of society today and increasing hostility to conscientious objection in medicine.

The Future Like Ours (FLO) argument, provided by Don Marquis remains one of the most persuasive arguments against the general permissibility of abortion. Marquis is aware of concerns that his argument overgeneralizes, but thinks by requiring that it is possible to specify individuals who are deprived, he is able to overcome them. In this paper, I argue that Marquis' account does overgeneralize. To do this I demonstrate that having an FLO (Future Like Ours) must be understood as having an FLO in favourable circumstances. However, once the favourable circumstances caveat is exposed, the possibility of artificial enhancement of lower order animals would entail that those animals - and the fetuses of those animals - would also have FLOs. This overgeneralization commits the defender of the Future Like Ours argument to accept conclusions that seem independently implausible and which many explicitly reject. I argue that the FLO argument should instead be rejected.

This article reads the uptake of facial-matching algorithms by fertility clinics in Spain through the lens of 'the fertility fix': a software fix to the social reconfiguration of kinship and a fixed capital investment made by competing fertility companies and firms. 'The fertility fix' is proposed as a critical, ethical lens through which to situate algorithmic facial-matching in assisted reproduction in the context of the racial politics of the face and phenotype and the spatial politics of market expansion. While an 'infertility crisis' is often mentioned when explaining the growth of the assisted reproductive technologies (ARTs) industry, the use of donated reproductive cells is tied up in societal, ecological and economic shifts. Combining Software Studies analysis with Marxist Feminist and trans*feminist perspectives on shifting re/production dynamics, the article details the role of computational technologies in promoting certain ideas and beliefs about family and fixing certain territories of capital flow.

Data Stewardship is a novel governance mechanism in the context of artificial intelligence (AI) development in healthcare. This paper examines whether the conceptual tool of stewardship can remedy inadequacies of 'AI ethics' which has fundamental problems of accountability, legitimacy and trustworthiness. A modern secular conceptual explanation of stewardship involves taking a balanced account of the interests of society, and the core element of answerability. This conception of stewardship lends itself to legal mechanisms involving fiduciary duties, which introduces accountability mechanisms into AI development. The separation of AI development from the permanent enclosure of health data presents a useful lever to counter unethical behaviour and ensure societal engagement. Stewardship offers some promise to remedy the inadequacies of AI ethics, but there are risks that a narrow technical conception of data stewardship, without fiduciary duties and decoupled from beneficiaries, will be insufficient to drive the required fundamental change.

There are few comprehensive summaries of the ethical challenges associated with the adoption of artificial intelligence in healthcare. This review utilizes a systematic search focused on identifying the barriers and facilitators to the implementation of artificial intelligence in healthcare, highlighting the diversity of ethical challenges and the complex interactions between practical challenges and ethics issues. For example, the quality of the data upon which artificial intelligence models are developed relates to several ethics principles, as does the issue of gaining user trust. Importantly, there is also the difficulty of achieving the right balance between the discussed principles, since one might not be able to maximize one principle without having to sacrifice another. For example, maximizing privacy might require minimizing data collection from patients, which might negatively affect beneficence. As such, this review highlights the variety and complexity of ethical issues associated with artificial intelligence implementation in healthcare.

The impact of machine learning in healthcare on patient informed consent is now the subject of significant inquiry in bioethics. However, the topic has predominantly been considered in the context of black box diagnostic or treatment recommendation algorithms. The impact of machine learning involved in healthcare resource allocation on patient consent remains undertheorized. This paper will establish where patient consent is relevant in healthcare resource allocation, before exploring the impact on informed consent from the introduction of black box machine learning into resource allocation. It will then consider the arguments for informing patients about the use of machine learning in resource allocation, before exploring the challenge of whether individual patients could principally contest algorithmic prioritization decisions involving black box machine learning. Finally, this paper will examine how different forms of opacity in machine learning involved in resource allocation could be a barrier to patient consent to clinical decision-making in different healthcare contexts.

This paper discusses the risk of gross negligence manslaughter (GNM) and corporate manslaughter charges (CM) when clinicians use an artificially intelligent system's (AIS's) outputs in their practice. I identify the elements of these offenses within the context of the law of England and Wales and explore how they could be applied in a potential scenario where a patient's death has followed AIS use by a clinician. The risk of a conviction due to making an AIS-augmented workplace mistake highlights the non-trivial nature of AIS adoption in healthcare, and that the consequences of its use must be considered by all interested parties prior to AIS adoption.

The number of surplus frozen human embryos in storage in the United Kingdom (UK) is at its highest level since records began in 1991 and the formation of the UK Human Fertilisation and Embryology Authority (HFEA). This study features a quantitative analysis of data from 1991 to 2019 provided by the HFEA as well as a commentary on observed trends within this data. We also discuss trends relating to the final destiny of surplus embryos. Data analysis show that at least 130,000 stored embryos have been discarded in the UK since 1991, while another 500,000 embryos are currently being stored in a frozen state, of which a significant proportion is likely to be discarded in the future. However, this creates a moral dilemma since UK legislation relating to human embryos is based on the 1984 Warnock Report which recognizes that they have a special moral status.

In a qualitative study of 15 NICU workers in a large European NICU, the author asks the subjects to consider what sorts of work environments are likely to result in moral distress and whether support by colleagues, administrators, the institution itself and even perceived societal support may reduce some kinds of moral distress. The majority of providers felt that the support of colleagues was essential; there was some disagreement about whether the larger community was aware of the nature of the work done in NICUs by health workers. These healthcare providers were also asked about memorable patient encounters.