As the use of artificial intelligence (AI) technologies, particularly generative AI (Gen AI), becomes increasingly prevalent in nursing education, it is paramount to address the ethical implications of their implementation. This article explores the realm of cyberethics (a field of applied ethics that focuses on the ethical, legal, and social implications of cybertechnology), highlighting the ethical principles of autonomy, nonmaleficence, beneficence, justice, and explicability as a roadmap for facilitating AI integration into nursing education. Research findings suggest that ethical (...) dilemmas that challenge these five principles can emerge within the context of nursing education; however, adherence to these very principles, which is essential to improving patient care, can offer solutions to these dilemmas. To ensure the ethical and responsible use of Gen AI in nursing education, these principles must be woven into the fabric of curricula, and appropriate guidelines must be developed. Nurse educators have a pivotal role in strategizing comprehensive approaches for ethical AI integration, establishing clear guidelines, and instilling critical thinking among students. Fostering lifelong learning and adaptability is key to ensuring that future nurses can successfully navigate the constantly evolving landscape of health care technology. Future research should investigate the long-term impacts of AI utilization on learning outcomes and ethical decision-making. (shrink)

BackgroundHealthcare providers have to make ethically complex clinical decisions which may be a source of stress. Researchers have recently introduced Artificial Intelligence (AI)-based applications to assist in clinical ethical decision-making. However, the use of such tools is controversial. This review aims to provide a comprehensive overview of the reasons given in the academic literature for and against their use.MethodsPubMed, Web of Science, Philpapers.org and Google Scholar were searched for all relevant publications. The resulting set of publications was title and (...) abstract screened according to defined inclusion and exclusion criteria, resulting in 44 papers whose full texts were analysed using the Kuckartz method of qualitative text analysis.ResultsArtificial Intelligence might increase patient autonomy by improving the accuracy of predictions and allowing patients to receive their preferred treatment. It is thought to increase beneficence by providing reliable information, thereby, supporting surrogate decision-making. Some authors fear that reducing ethical decision-making to statistical correlations may limit autonomy. Others argue that AI may not be able to replicate the process of ethical deliberation because it lacks human characteristics. Concerns have been raised about issues of justice, as AI may replicate existing biases in the decision-making process.ConclusionsThe prospective benefits of using AI in clinical ethical decision-making are manifold, but its development and use should be undertaken carefully to avoid ethical pitfalls. Several issues that are central to the discussion of Clinical Decision Support Systems, such as justice, explicability or human–machine interaction, have been neglected in the debate on AI for clinical ethics so far.Trial registrationThis review is registered at Open Science Framework (https://osf.io/wvcs9). (shrink)

Artificially intelligent (AI) technologies are increasingly being used in many workplaces. It is recognised that there are ethical dimensions to the ways in which organisations implement AI alongside, or substituting for, their human workforces. How will these technologically driven disruptions impact the employee–employer exchange? We provide one way to explore this question by drawing on scholarship linking Integrative Social Contracts Theory (ISCT) to the psychological contract (PC). Using ISCT, we show that the macrosocial contract’s ethical AI norms of beneficence, non-maleficence, (...) autonomy, justice, and explicability can feed into national- and organisational-level microsocial contracts. We also outline the role of employees’ technology frames in this process. We then use an illustrative example to demonstrate how this multilevel normative background helps to inform the content of individuals’ PCs in the context of working with AI technologies. (shrink)

The rapid adoption and implementation of artificial intelligence in medicine creates an ontologically distinct situation from prior care models. There are both potential advantages and disadvantages with such technology in advancing the interests of patients, with resultant ontological and epistemic concerns for physicians and patients relating to the instatiation of AI as a dependent, semi- or fully-autonomous agent in the encounter. The concept of libertarian paternalism potentially exercised by AI (and those who control it) has created challenges to conventional (...) assessments of patient and physician autonomy. The unclear legal relationship between AI and its users cannot be settled presently, an progress in AI and its implementation in patient care will necessitate an iterative discourse to preserve humanitarian concerns in future models of care. This paper proposes that physicians should neither uncritically accept nor unreasonably resist developments in AI but must actively engage and contribute to the discourse, since AI will affect their roles and the nature of their work. One’s moral imaginative capacity must be engaged in the questions of beneficence, autonomy, and justice of AI and whether its integration in healthcare has the potential to augment or interfere with the ends of medical practice. (shrink)

Biomarker-based predictive tests for subjectively asymptomatic Alzheimer’s disease (AD) are utilized in research today. Novel applications of artificial intelligence (AI) promise to predict the onset of AD several years in advance without determining biomarker thresholds. Until now, little attention has been paid to the new ethical challenges that AI brings to the early diagnosis in asymptomatic individuals, beyond contributing to research purposes, when we still lack adequate treatment. The aim of this paper is to explore the ethical arguments put (...) forward for AI aided AD prediction in subjectively asymptomatic individuals and their ethical implications. The ethical assessment is based on a systematic literature search. Thematic analysis was conducted inductively of 18 included publications. The ethical framework includes the principles of autonomy, beneficence, non-maleficence, and justice. Reasons for offering predictive tests to asymptomatic individuals are the right to know, a positive balance of the risk-benefit assessment, and the opportunity for future planning. Reasons against are the lack of disease modifying treatment, the accuracy and explicability of AI aided prediction, the right not to know, and threats to social rights. We conclude that there are serious ethical concerns in offering early diagnosis to asymptomatic individuals and the issues raised by the application of AI add to the already known issues. Nevertheless, pre-symptomatic testing should only be offered on request to avoid inflicted harm. We recommend developing training for physicians in communicating AI aided prediction. (shrink)

This paper will examine the social and ethical impacts of using artificial intelligence (AI) in the agricultural sector. It will identify what are some of the most prevalent challenges and impacts identified in the literature, how this correlates with those discussed in the domain of AI ethics, and are being implemented into AI ethics guidelines. This will be achieved by examining published articles and conference proceedings that focus on societal or ethical impacts of AI in the agri-food sector, through (...) a thematic analysis of the literature. The thematic analysis will be divided based on the classifications outlined through 11 overarching principles, from an established lexicon (transparency, justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, dignity, sustainability, and solidarity). While research on AI agriculture is still relatively new, this paper aims to map the debate and illustrate what the literature says in the context of social and ethical impacts. It aim is to analyse these impacts, based on these 11 principles. This research will contrast which impacts are not being discussed in agricultural AI and which issues are not being discussed in AI ethics guidelines, but which are discussed in relation to agricultural AI. The aim of this is to identify gaps within the agricultural literature, and gaps in AI ethics guidelines, that may need to be addressed. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:The Human Roots of Artificial Intelligence:A Commentary on Susan Schneider's Artificial YouInês Hipólito (bio)Technologies are not mere tools waiting to be picked up and used by human agents, but rather are material-discursive practices that play a role in shaping and co-constituting the world in which we live.Karen BaradIntroductionSusan Schneider's book Artificial You: AI and the Future of Your Mind presents a compelling and bold argument regarding (...) the potential impact of advanced artificial intelligence (AI) on our society and personal identity. Schneider's argument emphasizes how AI may fundamentally alter our sense of self and disrupt traditional notions of identity and consciousness, motivating further significant cognitive science and ethical implications that require careful consideration. [End Page 297]The recent surge in AI hype has given rise to a widespread belief that AI is an autonomous and exceptional entity, potentially even possessing intelligence. This trend reflects a subtle reemergence of the classic Turing question, as the media bombards us with sensational inquiries into the intelligence of AI systems. Amidst this hype, it is easy to forget that AI is a product of human creation.Upon closer examination, the hype surrounding AI necessitates an assumption of its autonomy, which implies a belief in the realism of AI—the notion that AI, as an independent entity, is morally neutral. However, AI does not emerge in a vacuum. It is designed and developed by individuals who are shaped by their own experiences and biases.By endorsing the realism of AI as morally neutral (Cooley 1995), those involved in its design may use this argument to deflect ethical responsibility away from themselves and allow biases to persist, thereby perpetuating social injustice. Such attitudes toward AI revitalize the debate on the neutrality of technology (Ruane, Birhane, and Ventresque 2019; Du, Lu, and Xie 2021; Lüthi et al. 2023).This article presents a critique of realism with regard to AI highlighting the significant social implications both at the basis of design and that arise from our interactions with these technologies. The argument suggests that AI does not exist independently of human practices and values, but rather emerges from them. The article instead suggests viewing AI design as a cultural practice defending realism about self-determination agencies, drawing from Simone de Beauvoir's Ethics of Ambiguity as a means to understand the human roots on the basis of AI.I. Rejecting Realism about AIConsider the hypothetical scenario of an Artificial Intelligence system that is discovered by humans, but exists independently of human cognition and perception. This scenario embodies the philosophical perspective of realism about AI, which maintains that AI entities have objective existence in an abstract domain, independent of human invention or imagination. If this perspective were to hold true, then humans could not be held responsible for the actions of autonomous AI systems.If we were to conceive of AI as an ideal entity that exists independently of humans, it would likely lead to a number of negative consequences for society. First and foremost, it may lead to the dangerous assumption that AI systems are neutral and objective, devoid of the biases and prejudices that are inherent in human decision-making. This could create a false sense of trust in AI, leading to the belief that their decisions are inherently fair and impartial. However, the reality is that AI systems are not inherently neutral, but rather are shaped by the cultural and social contexts in which they are created and deployed. [End Page 298]AI as an autonomous, self-governing agent raises concerns about the attribution of accountability for its actions. Considering AI as an independent entity may pose challenges in assigning responsibility to its human creators and the industry that produced it. On the other hand, viewing AI as an ideal entity, distinct from human influence, may hinder its ability to foster a more equitable and just world. Importantly, overlooking the social and cultural dimensions of AI risks forfeiting opportunities to employ AI in redressing prevalent biases and inequities in society. AI possesses the potential to serve as a potent instrument for advancing social justice and equality, but this prospect necessitates acknowledging and... (shrink)

Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether (...) these principles converge upon a set of agreed-upon principles, or diverge, with significant disagreement over what constitutes ‘ethical AI.’ Our analysis finds a high degree of overlap among the sets of principles we analyze. We then identify an overarching framework consisting of five core principles for ethical AI. Four of them are core principles commonly used in bioethics: beneficence, non-maleficence, autonomy, and justice. On the basis of our comparative analysis, we argue that a new principle is needed in addition: explicability, understood as incorporating both the epistemological sense of intelligibility (as an answer to the question ‘how does it work?’) and in the ethical sense of accountability (as an answer to the question: ‘who is responsible for the way it works?’). In the ensuing discussion, we note the limitations and assess the implications of this ethical framework for future efforts to create laws, rules, technical standards, and best practices for ethical AI in a wide range of contexts. (shrink)

The COVID-19 pandemic and its related policies (e.g., stay at home and social distancing orders) have increased people’s use of digital technology, such as social media. Researchers have, in turn, utilized artificial intelligence to analyze social media data for public health surveillance. For example, through machine learning and natural language processing, they have monitored social media data to examine public knowledge and behavior. This paper explores the ethical considerations of using artificial intelligence to monitor social media to understand (...) the public’s perspectives and behaviors surrounding COVID-19, including potential risks and benefits of an AI-driven approach. Importantly, investigators and ethics committees have a role in ensuring that researchers adhere to ethical principles of respect for persons, beneficence, and justice in a way that moves science forward while ensuring public safety and confidence in the process. (shrink)

The use of drones in public healthcare is suggested as a means to improve efficiency under constrained resources and personnel. This paper begins by framing drones in healthcare as a social experiment where ethical guidelines are needed to protect those impacted while fully realizing the benefits the technology offers. Then we propose an ethical framework to facilitate the design, development, implementation, and assessment of drones used in public healthcare. Given the healthcare context, we structure the framework according to the four (...) bioethics principles: beneficence, non-maleficence, autonomy, and justice, plus a fifth principle from artificial intelligence ethics: explicability. These principles are abstract which makes operationalization a challenge; therefore, we suggest an approach of translation according to a values hierarchy whereby the top-level ethical principles are translated into relevant human values within the domain. The resulting framework is an applied ethics tool that facilitates awareness of relevant ethical issues during the design, development, implementation, and assessment of drones in public healthcare. (shrink)

Artificial intelligence-driven technology increasingly shapes work practices and, accordingly, employees’ opportunities for meaningful work (MW). In our paper, we identify five dimensions of MW: pursuing a purpose, social relationships, exercising skills and self-development, autonomy, self-esteem and recognition. Because MW is an important good, lacking opportunities for MW is a serious disadvantage. Therefore, we need to know to what extent employers have a duty to provide this good to their employees. We hold that employers have a duty of beneficence (...) to design for opportunities for MW when implementing AI-technology in the workplace. We argue that this duty of beneficence is supported by the three major ethical theories, namely, Kantian ethics, consequentialism, and virtue ethics. We defend this duty against two objections, including the view that it is incompatible with the shareholder theory of the firm. We then employ the five dimensions of MW as our analytical lens to investigate how AI-based technological innovation in logistic warehouses has an impact, both positively and negatively, on MW, and illustrate that design for MW is feasible. We further support this practical feasibility with the help of insights from organizational psychology. We end by discussing how AI-based technology has an impact both on meaningful work (often seen as an aspirational goal) and decent work (generally seen as a matter of justice). Accordingly, ethical reflection on meaningful and decent work should become more integrated to do justice to how AI-technology inevitably shapes both simultaneously. (shrink)

Background Integrating artificial intelligence (AI) into healthcare has raised significant ethical concerns. In pharmacy practice, AI offers promising advances but also poses ethical challenges. Methods A cross-sectional study was conducted in countries from the Middle East and North Africa (MENA) region on 501 pharmacy professionals. A 12-item online questionnaire assessed ethical concerns related to the adoption of AI in pharmacy practice. Demographic factors associated with ethical concerns were analyzed via SPSS v.27 software using appropriate statistical tests. Results Participants expressed (...) concerns about patient data privacy (58.9%), cybersecurity threats (58.9%), potential job displacement (62.9%), and lack of legal regulation (67.0%). Tech-savviness and basic AI understanding were correlated with higher concern scores (p < 0.001). Ethical implications include the need for informed consent, beneficence, justice, and transparency in the use of AI. Conclusion The findings emphasize the importance of ethical guidelines, education, and patient autonomy in adopting AI. Collaboration, data privacy, and equitable access are crucial to the responsible use of AI in pharmacy practice. (shrink)

The target article by Laacke et al. focuses on the specific context of identifying people in social media with a high risk of depression by using artificial intelligence technologies. I...

This paper explores the important role of critical science, and in particular of post-colonial and decolonial theories, in understanding and shaping the ongoing advances in artificial intelligence. Artificial intelligence is viewed as amongst the technological advances that will reshape modern societies and their relations. While the design and deployment of systems that continually adapt holds the promise of far-reaching positive change, they simultaneously pose significant risks, especially to already vulnerable peoples. Values and power are central to this discussion. (...) Decolonial theories use historical hindsight to explain patterns of power that shape our intellectual, political, economic, and social world. By embedding a decolonial critical approach within its technical practice, AI communities can develop foresight and tactics that can better align research and technology development with established ethical principles, centring vulnerable peoples who continue to bear the brunt of negative impacts of innovation and scientific progress. We highlight problematic applications that are instances of coloniality, and using a decolonial lens, submit three tactics that can form a decolonial field of artificial intelligence: creating a critical technical practice of AI, seeking reverse tutelage and reverse pedagogies, and the renewal of affective and political communities. The years ahead will usher in a wave of new scientific breakthroughs and technologies driven by AI research, making it incumbent upon AI communities to strengthen the social contract through ethical foresight and the multiplicity of intellectual perspectives available to us, ultimately supporting future technologies that enable greater well-being, with the goal of beneficence and justice for all. (shrink)

Feasting on a plethora of social media platforms, news aggregators, and online marketplaces, recommender systems (RSs) are spreading pervasively throughout our daily online activities. Over the years, a host of ethical issues have been associated with the diffusion of RSs and the tracking and monitoring of users’ data. Here, we focus on the impact RSs may have on personal autonomy as the most elusive among the often-cited sources of grievance and public outcry. On the grounds of a philosophically nuanced (...) notion of autonomy, we illustrate three specific reasons why RSs may limit or compromise it: the threat of manipulation and deception associated with RSs; the RSs’ power to reshape users’ personal identity; the impact of RSs on knowledge and critical thinking. In our view, however, notwithstanding these legitimate concerns, RSs may effectively help users to navigate an otherwise overwhelming landscape. Our perspective, therefore, is not to be intended as a bulwark to protect the _status quo_ but as an invitation to carefully weigh these aspects in the design of ethically oriented RSs. (shrink)

The present paper aims at contributing to the ethical debate on the impacts of artificial intelligence (AI) systems on human autonomy. More specifically, it intends to offer a clearer understanding of the design challenges to the effort of aligning driving automation technologies to this ethical value. After introducing the discussion on the ambiguous impacts that AI systems exert on human autonomy, the analysis zooms in on how the problem has been discussed in the literature on connected and (...) automated vehicles (CAVs). On this basis, it is claimed that the issue has been mainly tackled on a fairly general level, and mostly with reference to the controversial issue of crash-optimization algorithms, so that only limited design insights have been drawn. However, integrating ethical analysis and design practices is critical to pursue the implementation of such an important ethical value into CAV technologies. To this aim, it is argued, a more applied approach targeted at examining the impacts on human autonomy of current CAV functions should also be explored. As an example of the intricacy of this task, the case of automated route planning is discussed in some detail. (shrink)

The present paper aims at contributing to the ethical debate on the impacts of artificial intelligence (AI) systems on human autonomy. More specifically, it intends to offer a clearer understanding of the design challenges to the effort of aligning driving automation technologies to this ethical value. After introducing the discussion on the ambiguous impacts that AI systems exert on human autonomy, the analysis zooms in on how the problem has been discussed in the literature on connected and (...) automated vehicles (CAVs). On this basis, it is claimed that the issue has been mainly tackled on a fairly general level, and mostly with reference to the controversial issue of crash-optimization algorithms, so that only limited design insights have been drawn. However, integrating ethical analysis and design practices is critical to pursue the implementation of such an important ethical value into CAV technologies. To this aim, it is argued, a more applied approach targeted at examining the impacts on human autonomy of current CAV functions should also be explored. As an example of the intricacy of this task, the case of automated route planning is discussed in some detail. (shrink)

The present paper aims at contributing to the ethical debate on the impacts of artificial intelligence (AI) systems on human autonomy. More specifically, it intends to offer a clearer understanding of the design challenges to the effort of aligning driving automation technologies to this ethical value. After introducing the discussion on the ambiguous impacts that AI systems exert on human autonomy, the analysis zooms in on how the problem has been discussed in the literature on connected and (...) automated vehicles (CAVs). On this basis, it is claimed that the issue has been mainly tackled on a fairly general level, and mostly with reference to the controversial issue of crash-optimization algorithms, so that only limited design insights have been drawn. However, integrating ethical analysis and design practices is critical to pursue the implementation of such an important ethical value into CAV technologies. To this aim, it is argued, a more applied approach targeted at examining the impacts on human autonomy of current CAV functions should also be explored. As an example of the intricacy of this task, the case of automated route planning is discussed in some detail. (shrink)

The development of artificial intelligence (AI) in medicine raises fundamental ethical issues. As one example, AI systems in the field of mental health successfully detect signs of mental disorders, such as depression, by using data from social media. These AI depression detectors (AIDDs) identify users who are at risk of depression prior to any contact with the healthcare system. The article focuses on the ethical implications of AIDDs regarding affected users’ health-related autonomy. Firstly, it presents the (ethical) discussion (...) of AI in medicine and, specifically, in mental health. Secondly, two models of AIDDs using social media data and different usage scenarios are introduced. Thirdly, the concept of patient autonomy, according to Beauchamp and Childress, is critically discussed. Since this concept does not encompass the specific challenges linked with the digital context of AIDDs in social media sufficiently, the current analysis suggests, finally, an extended concept of health-related digital autonomy. (shrink)

The application of Artificial Intelligence (AI) in healthcare and epidemiology undoubtedly has many benefits for the population. However, due to its environmental impact, the use of AI can produce social inequalities and long-term environmental damages that may not be thoroughly contemplated. In this paper, we propose to consider the impacts of AI applications in medical care from the One Health paradigm and long-term global health. From health and environmental justice, rather than settling for a short and fleeting green honeymoon (...) between health and sustainability caused by AI, it should aim for a lasting marriage. To this end, we conclude by proposing that, in the upcoming years, it could be valuable and necessary to promote more interconnected health, call for environmental cost transparency, and increase green responsibility. (shrink)

We are living in an unprecedented era of biomedical revolution. Medicine is remaking humans, and controversy surrounds such topics as abortion, artificial organs, brain circuitry, eugenics, euthanasia, and gene therapy. At the same time, medical advances are posing complex ethical problems for both patients and professionals. The most comprehensive and up-to-date collection of its kind, Case Studies in Biomedical Ethics: Decision-Making, Principles, and Cases explores fundamental ethical questions arising from real situations faced by health professionals, patients, and others. Featuring (...) a wide range of more than 100 case studies drawn from current events, court cases, and physicians' experiences, the book is divided into three parts. Part I presents a basic framework for ethical decision-making in healthcare, covering such issues as separating evaluative questions from questions of fact; distinguishing between ethical and nonethical evaluations; and identifying the source of ethical judgments. Expanding upon this framework, Part II explains the ethical principles: beneficence and nonmaleficence, justice, respect for autonomy, veracity, fidelity, and avoidance of killing. Parts I and II provide students with the background to analyze the ethical dilemmas presented in Part III, which features cases on a broad spectrum of issues including abortion, genetics, mental health, confidentiality, health insurance, experimentation on humans, the right to refuse treatment, and death and dying. Each case is accompanied by the authors' commentary, which guides students in considering the issues. Ideal for undergraduate and graduate courses in biomedical ethics, bioethics, and medical ethics, Case Studies in Biomedical Ethics incorporates opening text boxes in each chapter that cross-reference relevant cases in other chapters. It also includes an appendix of important ethical codes and a glossary of key terms. (shrink)

Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools made (...) and used by humans; here, the main sections are privacy (2.1), manipulation (2.2), opacity (2.3), bias (2.4), autonomy & responsibility (2.6) and the singularity (2.7). Then we look at AI systems as subjects, i.e. when ethics is for the AI systems themselves in machine ethics (2.8.) and artificial moral agency (2.9). Finally we look at future developments and the concept of AI (3). For each section within these themes, we provide a general explanation of the ethical issues, we outline existing positions and arguments, then we analyse how this plays out with current technologies and finally what policy conse-quences may be drawn. (shrink)

We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five (...) key ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and (...) used by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

The use of artificial intelligence in healthcare contexts is highly controversial for the (bio)ethical conundrums it creates. One of the main problems arising from its implementation is the lack of transparency of machine learning algorithms, which is thought to impede the patient’s autonomous choice regarding their medical decisions. If the patient is unable to clearly understand why and how an AI algorithm reached certain medical decision, their autonomy is being hovered. However, there are alternatives to prevent the negative (...) impact of AI opacity in shared (healthcare professional–patient) decision-making processes, and benefit from the high accuracy of such systems. Despite these ethical issues, this paper advocates for its usage and also defends the positive role that it could have in enhancing patients’ autonomy. I advocate for a system where the implementation of AI is only partial, and humans will remain in control of oversighting algorithm interpretation of medical images and patients’ data. (shrink)

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’saccountability for reasonablenessconception, (...) 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. (shrink)

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. (shrink)

Background Advances in artificial intelligence, robotics and wearable computing are creating novel technological opportunities for mitigating the global burden of population ageing and improving the quality of care for older adults with dementia and/or age-related disability. Intelligent assistive technology is the umbrella term defining this ever-evolving spectrum of intelligent applications for the older and disabled population. However, the implementation of IATs has been observed to be sub-optimal due to a number of barriers in the translation of novel applications from (...) the designing labs to the bedside. Furthermore, since these technologies are designed to be used by vulnerable individuals with age- and multi-morbidity-related frailty and cognitive disability, they are perceived to raise important ethical challenges, especially when they involve machine intelligence, collect sensitive data or operate in close proximity to the human body. Thus, the goal of this paper is to explore and assess the ethical issues that professional stakeholders perceive in the development and use of IATs in elderly and dementia care. Methods We conducted a multi-site study involving semi-structured qualitative interviews with researchers and health professionals. We analyzed the interview data using a descriptive thematic analysis to inductively explore relevant ethical challenges. Results Our findings indicate that professional stakeholders find issues of patient autonomy and informed consent, quality of data management, distributive justice and human contact as ethical priorities. Divergences emerged in relation to how these ethical issues are interpreted, how conflicts between different ethical principles are resolved and what solutions should be implemented to overcome current challenges. Conclusions Our findings indicate a general agreement among professional stakeholders on the ethical promises and challenges raised by the use of IATs among older and disabled users. Yet, notable divergences persist regarding how these ethical challenges can be overcome and what strategies should be implemented for the safe and effective implementation of IATs. These findings provide technology developers with useful information about unmet ethical needs. Study results may guide policy makers with firsthand information from relevant stakeholders about possible solutions for ethically-aligned technology governance. (shrink)

This paper explores artificial intelligence (AI) ethics from an Islamic perspective at a critical time for AI ethical norm-setting. It advocates for a pluralist approach to ethical AI benchmarking. As rapid advancements in AI technologies pose challenges surrounding autonomy, privacy, fairness, and transparency, the prevailing ethical discourse has been predominantly Western or Eurocentric. To address this imbalance, this paper delves into the Islamic ethical traditions to develop a framework that contributes to the global debate on optimal norm setting (...) for designing and using AI technologies.The paper outlines Islamic parameters for ethical values and moral actions in the context of AI's ethical uncertainties. It emphasizes the significance of both textual and non-textual Islamic sources in addressing these uncertainties while placing a strong emphasis on the notion of "good" or "maṣlaḥa" as a normative guide for AI's ethical evaluation. Defining maṣlaḥa as an ethical state of affairs in harmony with divine will, the paper highlights the coexistence of two interpretations of maṣlaḥa: welfarist/utility-based and duty-based. Islamic jurisprudence allows for arguments supporting ethical choices that prioritize building the technical infrastructure for AI to maximize utility. Conversely, it also supports choices that reject consequential utility calculations as the sole measure of value in determining ethical responses to AI advancements. (shrink)

Algorithms influence every facet of modern life: criminal justice, education, housing, entertainment, elections, social media, news feeds, work… the list goes on. Delegating important decisions to machines, however, gives rise to deep moral concerns about responsibility, transparency, freedom, fairness, and democracy. Algorithms and Autonomy connects these concerns to the core human value of autonomy in the contexts of algorithmic teacher evaluation, risk assessment in criminal sentencing, predictive policing, background checks, news feeds, ride-sharing platforms, social media, and election interference. (...) Using these case studies, the authors provide a better understanding of machine fairness and algorithmic transparency. They explain why interventions in algorithmic systems are necessary to ensure that algorithms are not used to control citizens' participation in politics and undercut democracy. This title is also available as Open Access on Cambridge Core. (shrink)

Artificial intelligence is increasingly permeating many types of high-stake societal decision-making such as the work at the criminal courts. Various types of algorithmic tools have already been introduced into sentencing. This article concerns the use of algorithms designed to deliver sentence recommendations. More precisely, it is considered how one should determine whether one type of sentencing algorithm (e.g., a model based on machine learning) would be ethically preferable to another type of sentencing algorithm (e.g., a model based on old-fashioned (...) programming). Whether the implementation of sentencing algorithms is ethically desirable obviously depends upon various questions. For instance, some of the traditional issues that have received considerable attention are algorithmic biases and lack of transparency. However, the purpose of this article is to direct attention to a further challenge that has not yet been considered in the discussion of sentencing algorithms. That is, even if is assumed that the traditional challenges concerning biases, transparency, and cost-efficiency have all been solved or proven insubstantial, there will be a further serious challenge associated with the comparison of sentencing algorithms; namely, that we do not yet possess an ethically plausible and applicable criterion for assessing how well sentencing algorithms are performing. (shrink)

Organizations such as the EU High-Level Expert Group on AI and the IEEE have recently formulated ethical principles and (moral) values that should be adhered to in the design and deployment of artificial intelligence (AI). These include respect for autonomy, non-maleficence, fairness, transparency, explainability, and accountability. But how can we ensure and verify that an AI system actually respects these values? To help answer this question, I propose an account for determining when an AI system can be said (...) to embody certain values. This account understands embodied values as the result of design activities intended to embed those values in such systems. AI systems are here understood as a special kind of sociotechnical system that, like traditional sociotechnical systems, are composed of technical artifacts, human agents, and institutions but—in addition—contain artificial agents and certain technical norms that regulate interactions between artificial agents and other elements of the system. The specific challenges and opportunities of embedding values in AI systems are discussed, and some lessons for better embedding values in AI systems are drawn. (shrink)

Some recent uses of artificial intelligence for facial recognition, evaluating resumes, and sorting photographs by subject matter have revealed troubling disparities in performance or impact based on the demographic traits of subject populations. These disparities raise pressing questions about how using artificial intelligence can work to promote justice or entrench injustice. Political theorists and philosophers have developed nuanced vocabularies and theoretical frameworks for understanding and adjudicating disputes about what justice requires and what constitutes injustice. The interdisciplinary community committed (...) to understanding and conscientiously using big data could benefit from this work. Thus, in the spirit of encouraging cross-disciplinary dialogue and collaboration, this piece examines contemporary scholarship in political theory and philosophy to illustrate some of the vocabularies and frameworks political theorists and philosophers have developed for thinking about justice and injustice. It then draws on these frameworks to illuminate how the use of artificial intelligence can implicate questions of justice, with a focus on institutional discrimination, structural injustice, and epistemic injustice. Ultimately, the piece argues that the use of artificial intelligence—far from representing a decision to take power out of human hands—represents a novel way of harnessing human power, making questions of justice central to its conscientious undertaking. (shrink)

본 논문의 목적은 현대 사회에서 과학기술 발전의 상징인 인공지능의 사회적 참여와 행 위성을 마뚜라나, 바렐라, 그리고 루만의 오토포이에시스 이론에 기초해서 고찰함으로써 인 간과 기술 공학적 인공물들과의 윤리적 공생 가능성에 대한 이론적 토대를 제공하고자 하는 것이다. 구성정 인공지능은 자율적으로 생각하는 지성적 기계를 구현하기 위해서 생명, 몸, 마음과 같은 존재론적 개념들과 그것의 특징들이 연구에 반영되어야 한다는 입장이다. 오토포이에시스 이론에 따르면 인식되어야 할 객관적인 세계가 이미 주어져 있는 것이 아니라 앎의 과정에서 세계와 인식행위자가 함께 구성된다. 그리고 자기생성체계는 재귀 적이며 성찰적인 과정을 통해 구성원들이 (...) 함께 행위 할 수 있는 규범과 규칙성을 만들며 안전을 유지해 간다. 따라서 자기생산체계의 기능적인 측면에서 (준)자율적 인공지능과 자율적 인간은 구조적 접속을 통해 공진화하며 함께 세계를 만들어 갈 수 있다. 인공지능의 행위성도 수신자에게 무슨 일이 일어나는지의 상호관계와 구조적 접속에서 행동 조정이 일어날 수 있도록 재생산되어야 한다는 것이다. 오토포이에시스 이론에 따르 면 행위의 책임이 앎과 행위의 동일성에 기초해야 하듯이, 인공지능의 행위도 언어 안에서 벌어지는 성찰적 앎에 기초해야 한다. (shrink)

Artificial intelligence and robotics is pervasive in daily life and set to expand to new levels potentially replacing human decision-making and action. Self-driving cars, home and healthcare robots, and autonomous weapons are some examples. A distinction appears to be emerging between potentially benevolent civilian uses of the technology (eg unmanned aerial vehicles delivering medicines), and potentially malevolent military uses (eg lethal autonomous weapons killing human com- batants). Machine-mediated human interaction challenges the philosophical basis of human existence and ethical conduct. (...) Aside from technical challenges of ensuring ethical conduct in artificial intelligence and robotics, there are moral questions about the desirability of replacing human functions and the human mind with such technology. How will artificial intelligence and robotics engage in moral reasoning in order to act ethically? Is there a need for a new set of moral rules? What happens to human interaction when it is mediated by technology? Should such technology be used to end human life? Who bears responsibility for wrongdoing or harmful conduct by artificial intelligence and robotics? -/- Whilst Kant may be familiar to international lawyers for setting restraints on the use of force and rules for perpetual peace, his foundational work on ethics provides an inclusive moral philosophy for assessing ethical conduct of individuals and states and, thus, is relevant to discussions on the use and development of artificial intelligence and robotics. His philosophy is inclusive because it incorporates justifications for morals and legitimate responses to immoral conduct, and applies to all human agents irrespective of whether they are wrongdoers, unlawful combatants, or unjust enemies. Humans are at the centre of rational thinking, action, and norm-creation so that the rationale for restraints on methods and means of warfare, for example, is based on preserving human dignity as well as ensuring conditions for perpetual peace among states. Unlike utilitarian arguments which favour use of autonomous weapons on the basis of cost-benefit reasoning or the potential to save lives, Kantian ethics establish non-consequentialist and deontological rules which are good in themselves to follow and not dependent on expediency or achieving a greater public good. -/- Kantian ethics make two distinct contributions to the debate. First, they provide a human-centric ethical framework whereby human exist- ence and capacity are at the centre of a norm-creating moral philosophy guiding our understanding of moral conduct. Second, the ultimate aim of Kantian ethics is practical philosophy that is relevant and applicable to achieving moral conduct. -/- I will seek to address the moral questions outlined above by exploring how core elements of Kantian ethics relate to use of artificial intelli- gence and robotics in the civilian and military spheres. Section 2 sets out and examines core elements of Kantian ethics: the categorical imperative; autonomy of the will; rational beings and rational thinking capacity; and human dignity and humanity as an end in itself. Sections 3-7 consider how these core elements apply to artificial intelligence and robotics with discussion of fully autonomous and human-machine rule-generating approaches; types of moral reasoning; the difference be- tween ‘human will’ and ‘machine will’; and respecting human dignity. (shrink)

Philosophical and sociological approaches in technology have increasingly shifted toward describing AI (artificial intelligence) systems as ‘(moral) agents,’ while also attributing ‘agency’ to them. It is only in this way – so their principal argument goes – that the effects of technological components in a complex human-computer interaction can be understood sufficiently in phenomenological-descriptive and ethical-normative respects. By contrast, this article aims to demonstrate that an explanatory model only achieves a descriptively and normatively satisfactory result if the concepts of (...) ‘(moral) agent’ and ‘(moral) agency’ are exclusively related to human agents. Initially, the division between symbolic and sub-symbolic AI, the black box character of (deep) machine learning, and the complex relationship network in the provision and application of machine learning are outlined. Next, the ontological and action-theoretical basic assumptions of an ‘agency’ attribution regarding both the current teleology-naturalism debate and the explanatory model of actor network theory are examined. On this basis, the technical-philosophical approaches of Luciano Floridi, Deborah G. Johnson, and Peter-Paul Verbeek will all be critically discussed. Despite their different approaches, they tend to fully integrate computational behavior into their concept of ‘(moral) agency.’ By contrast, this essay recommends distinguishing conceptually between the different entities, causalities, and relationships in a human-computer interaction, arguing that this is the only way to do justice to both human responsibility and the moral significance and causality of computational behavior. (shrink)

Artificial Social Agents (ASAs), which are AI software driven entities programmed with rules and preferences to act autonomously and socially with humans, are increasingly playing roles in society. As their sophistication grows, humans will share greater amounts of personal information, thoughts, and feelings with ASAs, which has significant ethical implications. We conducted a study to investigate what ethical principles are of relative importance when people engage with ASAs and whether there is a relationship between people’s values and the ethical (...) principles they prioritise. The study uses scenarios, embedded with the five AI4People ethical principles (Beneficence, Non-maleficence, Autonomy, Justice, and Explicability), involving ASAs taking on roles traditionally played by humans to understand whether these roles and behaviours (including dialogues) are seen as acceptable or unacceptable. Results from 268 participants reveal the greatest sensitivity to ASA behaviours that relate to Autonomy, Justice, Explicability, and the privacy of their personal data. Models were created using Schwartz’s Refined Values as a possible indicator of how stakeholders discern and prioritise the different AI4People ethical principles when interacting with ASAs. Our findings raise issues around the ethical acceptability of ASAs for nudging and changing behaviour due to participants’ desire for autonomy and their concerns over deceptive ASA behaviours such as pretending to have memories and emotions. (shrink)

Artificial intelligence (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI‐based CDSS has an impact on the doctor–patient relationship, shaping their decisions with its suggestions. We may be on the verge of a paradigm shift, where the doctor–patient relationship is no longer a dual relationship, but a triad. This paper analyses the role of AI‐based CDSS for shared decision‐making to (...) better comprehend its promises and associated ethical issues. Moreover, it investigates how certain AI implementations may instead foster the inappropriate paradigm of paternalism. Understanding how AI relates to doctors and influences doctor–patient communication is essential to promote more ethical medical practice. Both doctors' and patients' autonomy need to be considered in the light of AI. (shrink)

Purpose The purpose of this study is to examine public perceptions and attitudes toward using artificial intelligence (AI) in the US criminal justice system. Design/methodology/approach The authors took a quantitative approach and administered an online survey using the Amazon Mechanical Turk platform. The instrument was developed by integrating prior literature to create multiple scales for measuring public perceptions and attitudes. Findings The findings suggest that despite the various attempts, there are still significant perceptions of sociodemographic bias in the criminal (...) justice system and technology alone cannot alleviate them. However, AI can assist judges in making fairer and more objective decisions by using triangulation – offering additional data points to offset individual biases. Social implications Other scholars can build upon the findings and extend the work to shed more light on some problems of growing concern for society – bias and inequality in criminal sentencing. AI can be a valuable tool to assist judges in the decision-making process by offering diverse viewpoints. Furthermore, the authors bridge the gap between the fields of technology and criminal justice and demonstrate how the two can be successfully integrated for the benefit of society. Originality/value To the best of the authors’ knowledge, this is among the first studies to examine a complex societal problem like the introduction of technology in a high-stakes environment – the US criminal justice system. Understanding how AI is perceived by society is necessary to develop more transparent and unbiased algorithms for assisting judges in making fair and equitable sentencing decisions. In addition, the authors developed and validated a new scale that can be used to further examine this novel approach to criminal sentencing in the future. (shrink)

Abstract:This paper explores how Finnish research ethics deals with matters of justice on the levels of practical regulation, political morality, and theoretical studies. The bioethical sets of principles introduced by Tom Beauchamp and James Childress in the United States and Jacob Dahl Rendtorff and Peter Kemp in Europe provide the conceptual background, together with a recently introduced conceptual map of theories of justice and their dimensions. The most striking finding is that the internationally recognized requirement of informed consent for research (...) on humans can be ideologically tricky in a Scandinavian welfare state setting. (shrink)

This paper develops an account of trustworthy AI. Its central idea is that whether AIs are trustworthy is a matter of whether they live up to their function-based obligations. We argue that this account serves to advance the literature in a couple of important ways. First, it serves to provide a rationale for why a range of properties that are widely assumed in the scientific literature, as well as in policy, to be required of trustworthy AI, such as safety, justice, (...) and explainability, are properties (often) instantiated by trustworthy AI. Second, we connect the discussion on trustworthy AI in policy, industry, and the sciences with the philosophical discussion of trustworthiness. We argue that extant accounts of trustworthiness in the philosophy literature cannot make proper sense of trustworthy AI and that our account compares favourably with its competitors on this front. (shrink)

Social robots are robots that can interact socially with humans. As social robots and the artificial intelligence that powers them becomes more advanced, they will likely take on more social and work roles. This has many important ethical implications. In this paper, we focus on one of the most central of these, the impacts that social robots can have on human autonomy. We argue that, due to their physical presence and social capacities, there is a strong potential for (...) social robots to enhance human autonomy as well as several ways they can inhibit and disrespect it. We argue that social robots could improve human autonomy by helping us to achieve more valuable ends, make more authentic choices, and improve our autonomy competencies. We also argue that social robots have the potential to harm human autonomy by instead leading us to achieve fewer valuable ends ourselves, make less authentic choices, decrease our autonomy competencies, make our autonomy more vulnerable, and disrespect our autonomy. Whether the impacts of social robots on human autonomy are positive or negative overall will depend on the design, regulation, and use we make of social robots in the future. (shrink)

Electroconvulsive therapy (ECT), an efficient psychiatric treatment method, is one of the most controversial and the most stigmatized therapeutic approaches in medicine. ECT uses transcranial electrical impulses to induce artificial epileptiform paroxysm. For the first time it was used in 1938 by Italian neuro-psychiatrists Ugo Cerletti and Lucio Bini in treatment of schizophrenia. Efficacy of the method was proven in clinical practice, clinical studies and meta-analyses. ECT is the most efficient in the treatment of mood disorders and in lesser (...) extent in some other disorders. Important advance in ECT was the introduction of anaesthesia and muscle relaxation. It reduced adverse effect incidence and severity. Currently, ECT is associated mostly with anaesthesia adverse effects. Other adverse reactions include muscle pain, headache, prolonged paroxysm, cardiopulmonary complications. The most discussed and the most disturbing adverse effect is memory impairment which is usually transient. Incidence and severity of adverse effects is comparable to other therapeutic modalities. Examining the available information it appears, that modern practice of ECT in Europe (European Union member states) and USA is, apart from a few exceptions, in accordance with principles of beneficence and to some extent with autonomy and nonmaleficence. In many countries, the principle of justice is not respected – either because of limited availability or restrictive laws. In the Czech Republic the problem is non-existence of codified treatment guidelines and insufficient training of medical specialists. Aside from this, position of ECT in the Czech Republic is similar to that in the rest of Europe and in USA. (shrink)

PHOTO ID 121339257© Designer491| Dreamstime.com ABSTRACT When physicians use their clinical knowledge and skills to advance the well-being of their patients, there may be apparent conflict between patient autonomy and physician beneficence. We are skeptical that today’s medical ethics education adequately fosters future physicians’ commitment to beneficence, which is both rationally defensible and fundamentally consistent with patient autonomy. We use an ethical dilemma that was presented to a group of third-year medical students to examine how ethics education might (...) be causing them to give undue deference to autonomy, thereby undermining their commitment to beneficence. INTRODUCTION The right of patients to choose which treatments they prefer is rooted in today’s social mores and taught as a principle of medical ethics as respect for autonomy. Yet, when physicians use their clinical knowledge and skills to advance the well-being of their patients, there may be a conflict between patient autonomy and physician beneficence. We are skeptical that today’s medical ethics education adequately fosters a commitment to beneficence, which is both rationally defensible and fundamentally consistent with patient autonomy. I. An Ethical Dilemma The impetus for this paper arose when students who were completing their third clinical year discussed a real-life ethical dilemma. A middle-aged man developed a pulmonary hemorrhage while on blood thinners for a recently placed coronary stent. The bleeding was felt to be reversible, but the patient needed immediate intubation or he would die. The cardiologist was told that the patient previously expressed to other physicians that he never wanted to be intubated. However, the cardiologist made the decision to intubate the patient anyway, and the patient eventually recovered.[1] Students were asked if they believed that the cardiologist had acted ethically. Their overwhelming response was, “No, the patient should have been allowed to die.” We looked into how students applied ethical reasoning to conclude that this outcome was ethically preferred. To explore how the third-year clinical experience might have formed the students’ judgment, we presented the same case to students who were just beginning their third year. Their responses were essentially uniform in recommending intubation. While there is likely more than one reasonable view in this case, we agree with the physician and the younger medical students that intubation was the ethically appropriate decision and will present an argument for it. But first, we explain the reasoning behind the more advanced medical students’ decision to choose patient autonomy at the expense of beneficence. II. Medical Ethics Education and the Priority of Autonomy Beauchamp and Childress’s Principles of Biomedical Ethics, first published in 1979 and now in its 8th edition, is a significant part of the formal ethics education in medical school.[2] Students learn an ethical decision-making approach based on respect for four ethical principles: autonomy, beneficence, nonmaleficence, and justice. While Beauchamp and Childress officially afford no prima facie superiority to any principle, the importance of respect for patient autonomy has increased through the editions of their book. For example, early editions of their book opposed the legalization of physician-assisted death compared to recent editions that defended it.[3] As another example, Beauchamp and Childress make paternalism harder to justify by adding an autonomy-protecting condition to the list of conditions for acceptable paternalism.[4] Authority, they contend, need not conflict with autonomy—provided the authority is autonomously chosen.[5] “The main requirement,” they write, “is to respect a particular patient’s or subject’s autonomous choices, whatever they may be.[6] In the principlism of Beauchamp and Childress, autonomy now seems to have a kind of default priority.[7] However, the bioethics discourse has strong counternarratives, noting some movement to elevate the role of beneficence and to respect the input of stakeholders, including the family and the healthcare team. Ethics education achieves particular relevance in the third clinical year when students become embedded in the care of patients and learn from what has been called the informal curriculum. They observe how attending physicians approach day-to-day ethical problems at the patient’s bedside. In this context, students observe the importance of informed consent for serious treatments or invasive procedures, a practice that highlights the principle of patient autonomy. In both the formal and informal curriculum, medical students observe how, in the words of Paul Wolpe, “patient autonomy has become the central and most powerful principle in ethical decision-making in American medicine.”[8] In short, students appear to learn a deference for patient autonomy. This curricular shift in favor of autonomy coincides with legal developments that protect patients’ rights and decision-making with respect to their healthcare choices. The priority of autonomy in medicine benefits patients by reflecting their choices and, in some cases, their fundamental liberty. III. The Practice of Medicine and the Commitment to Beneficence There are many critiques of the dominant place that autonomy has in biomedical ethics,[9] especially considering that autonomy seems to be biased toward individualistic, Western, and somewhat American culture-driven values.[10] In addition, many bioethical dilemmas are cast as a conflict between autonomy and beneficence. Our point is that medical students bring to their study of medicine a commitment to beneficence that seems to be suppressed by practical ethics education. We think this commitment is rationally defensible and should be nurtured. It is striking that young medical students have a pre-reflective commitment to beneficence at all. For, as we mentioned, it is not just medicine but Western culture generally that prioritizes autonomy in settling ethical dilemmas. In wanting to act for the good of others (rather than simply agreeing to what others want), physicians are already swimming somewhat against the cultural tide.[11] However, doing so makes sense, given the nature of medicine and the profession of healing. When prospective medical students are asked why they wish to become physicians, the usual answer is some variation on caring for the sick and preventing disease. It is unlikely that a reason to become a physician is to respect a patient’s autonomy. It would be easy to dismiss medical students’ commitment to beneficence as a mere intuition and contrary to a more reasoned and deliberative approach. Beauchamp and Childress seem to minimize the value of physician intuition, stating that justifications for certain procedures are “…supported by good reasons. They need not rest merely in intuition or feeling.”[12] Henry Richardson writes that “situational or perceptive intuition…leaves the reasons for decision unarticulated.”[13] We think this is a crude and rather thin way of understanding intuition. Some bioethicists have defended intuition as essential to the practice of medicine and not something opposed to reason.[14] In the case we describe, we believe the ethical justifications s for the patient’s intubation are fundamentally sound: the patient did not have a “do not intubate” order written in the chart, the emergency intubation had not been foreseen, so the patient did not have the opportunity to consent to or reject intubation; the patient had consented to the treatment for his cardiac disease so his consent for intubation could have been assumed;[15] and the consequences of respecting his autonomy did not justify allowing him to die.[16] While it is possible to have more than one reasonable view on this case, we think the case for beneficence is strong and certainly should not be dismissed out of hand. We do not deny that if a patient makes a clearly documented, well-informed decision to forgo intubation that this decision ought to be respected by the physician (even if the physician disagrees with the patient’s decision). But, in this situation, as in many others in the practice of medicine, the patient’s real wishes and preferences are not well-articulated in advance. There are many cases where a physician acts based on what she believes the patient, or the surrogate, would want, sometimes in situations that do not allow much time for reflection. An example might be resuscitation of a newborn at the borderline of viability. In their ethics education, beneficence would mean acting first to save a life. If the patient or surrogate makes an informed decision to the contrary, a beneficent physician respects that autonomous decision. In the case presented, the patient expressed gratitude to the cardiologist when extubated. But what if he had expressed anger at the physician for violating his autonomy? There are those who could argue that not only was intubation ethically wrong but that the cardiologist put himself in legal jeopardy by his actions (especially if there had been a written refusal applicable to the specific situation). In the example we use, we point out that the cardiologist may not have escaped a lawsuit if the patient had died without intubation. His family, when hearing the circumstances, may have sued for failure to act and dereliction of the cardiologist’s duty to save him. Beyond a potential legal challenge for either action or inaction, there is an overriding ethical question the cardiologist had to address: what course would be most satisfying to his conscience? Would he rather allow a patient to die for fear of recrimination, or act to save his life, regardless of the personal consequences? In the absence of real knowledge about the patient’s considered wishes, it is most reasonable to err on the side of promoting patient well-being. A physician’s commitment to beneficence is not necessarily a way of undermining a patient’s autonomy. In acting for the patient's good, physicians are also acting on what it is reasonable to believe a patient (or most patients, perhaps) would want, which is obviously connected to what a patient does want. Pellegrino and Thomasma argue that beneficence includes respect for a patient’s autonomy since “the best interests of the patient are intimately linked with their preferences.”[17] Instead of conceptualizing ethical dilemmas in medicine as conflicts between autonomy and beneficence, it is possible that medical schools could teach students that truly practicing beneficence is a way of valuing patient autonomy, especially when the patient’s wishes are not specific to the situation and are not clearly expressed. CONCLUSION It is important for students and practicing physicians to understand the principle of respect for patient autonomy in a pluralistic society that demands personal self-determination. However, the role of the physician as a beneficent healer should not be diminished by this respect for autonomy. Respecting a patient’s autonomy is grounded in and manifested by physician beneficence.[18] That is, seeking what is good for the patient can only be good if it respects their personhood and dignity. We propose that a commitment to beneficence, incipient in young medical students, should be developed over time with their other clinical reasoning skills. Such a commitment need not be sacrificed on the altar of patient autonomy. Beneficence needs greater relative moral weight with students as they proceed in their ethics education. - [1] S. Jauhar, “When Doctors Need to Lie,” New York Times, February 22, 2014, https://www.nytimes.com/2014/02/23/opinion/sunday/when-doctors-need-to-lie.html. [2] T. L. Beauchamp and James F. Childress, Principles of Biomedical Ethics, 8th ed. (New York, NY: Oxford University Press, 2019). [3] Louise A. Mitchell, “Major Changes in Principles of Biomedical Ethics,” The National Catholic Bioethics Quarterly 14, no. 3 (2014): 459–75, https://doi.org/10.5840/ncbq20141438. [4] Tom L. Beauchamp and James F. Childress, Principles of Biomedical Ethics, 8th ed. (New York, NY: Oxford University Press, 2019), 238. [5] Beauchamp and Childress, 103. [6] Beauchamp and Childress, p. 108. [7] For other accounts that prioritize autonomy, see e.g. Allen E. Buchanan and Dan W. Brock, Deciding for Others: The Ethics of Surrogate Decision Making (Cambridge University Press, 1989), 38–39; R Gillon, “Ethics Needs Principles—Four Can Encompass the Rest—and Respect for Autonomy Should Be ‘First among Equals,’” Journal of Medical Ethics 29, no. 5 (October 2003): 307–12, https://doi.org/10.1136/jme.29.5.307. For examples of critiques of these accounts, see footnote 9. [8] P. R. Wolpe, “The Triumph of Autonomy in American Bioethics: A Sociological View,” in Bioethics and Society: Constructing the Ethical Enterprise, p. 43. [9] V. A. Entwistle et al., “Supporting Patient Autonomy: The Importance of Clinician-Patient Relationships,” Journal of General Internal Medicine 25, no. 7 (July 2010): 741–45; C. Foster, Choosing Life, Choosing Death: The Tyranny of Autonomy in Medical Ethics and Law, 1st ed. (Oxford ; Hart Publishing, 2009); O. O’Neill, Autonomy and Trust in Bioethics, The Gifford Lectures, University of Edinburgh 2001 (Cambridge, UK: Cambridge University Press, 2002). [10] P. Marshall and B. Koenig, “Accounting for Culture in a Globalized Bioethics,” The Journal of Law, Medicine & Ethics: A Journal of the American Society of Law, Medicine & Ethics 32, no. 2 (2004): 252–66; R. Fan, “Self-Determination vs. Family-Determination: Two Incommensurable Principles of Autonomy,” Bioethics 11, no. 3–4 (1997): 309–22. [11] Arguments stressing the importance of beneficence, as ours does here, certainly approach paternalistic arguments. We set aside the complex issue of paternalism for purposes of this paper and simply note that the principle of beneficence as such does not say anything specifically about acting against the patient’s will. In the case study that focuses this paper, we do not believe the patient’s will or wishes were clearly indicated. [12] Beauchamp and Childress, Principles of Biomedical Ethics, p. 20, see note 2 above. [13] H. S. Richardson, “Specifying, Balancing, and Interpreting Bioethical Principles,” The Journal of Medicine and Philosophy: A Forum for Bioethics and Philosophy of Medicine 25, no. 3 (January 1, 2000): 285–307, p. 287. [14] H. D. Braude, Intuition in Medicine a Philosophical Defense of Clinical Reasoning (Chicago ; University of Chicago Press, 2012). [15] R. Kukla, “Conscientious Autonomy: Displacing Decisions in Health Care,” The Hastings Center Report 35, no. 2 (2005): 34–44. [16] M. Schermer, The Different Faces of Autonomy: Patient Autonomy in Ethical Theory and Hospital Practice, vol. 13, Library of Ethics and Applied Philosophy (Dordrecht: Springer Netherlands, 2002). [17] E. D. Pellegrino and D. C. Thomasma, For the Patient’s Good - the Restoration of Beneficence in Health Care (New York, NY: Oxford University Press, 1988), p. 29. [18] Pellegrino and Thomasma, For the Patient’s Good. 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Livestock production has been confronted with several epidemics over the last decades. The morality of common animal disease strategies—stamping out and vaccination—is being debated and provokes controversies among farmers, authorities and the broader public. Given the complexity and controversy of choosing an appropriate control strategy, this article explores the potential of nano-enabled diagnostics in future livestock production. At first glance, these applications offer promising opportunities for better animal disease surveillance. By significantly shortening the reaction time from diagnosis to appropriate control, (...) they could complement the current disease management strategies. Although nano-enabled diagnostics will not make livestock disease eradication strategies redundant or completely free of the culling of infected animals, these diagnostics could significantly reduce the number of culled animals and animal suffering. This article aims to demonstrate that the ethical assessment of advanced diagnostics can build on the experiences with decision making in biomedical ethics where nonmaleficence, beneficence, autonomy and justice serve as important benchmarks. Nano-enabled diagnostics may be an ethically sound solution if it can resolve the dilemma between stamping out and vaccination in favor of the latter and if it can balance the autonomy–paternalism dilemma between farmers and authorities. The technology should allow to be switched on and off by farmers, whilst simultaneously allowing for a weak paternalism on behalf of authorities in order to benefit the farmer and broader society and to protect them from harm. (shrink)

In recent years, artificial intelligence (AI) has garnered tremendous attention across a range of sectors, including health care. AI is a comprehensive term, broadly defined as computational machines making decisions and performing tasks that previously required human intelligence or cognition. There are high expectations of what AI can do; enthusiasts sometimes refer to it as a central pillar of the Fourth Industrial Revolution, with an impact on humanity as profound as that of the steam power engine or electricity. Building (...) on the Third Industrial Revolution (or Digital Revolution) that began in the middle of the twentieth century and was characterized by the spread of automation and digitization through the use of electronics, computers, and communication technologies (e.g., the internet), the Fourth Industrial Revolution is characterized by a fusion of advancing technologies in AI, robotics, the Internet of Things (IoT), genetic engineering, and quantum computing. These technologies blend physical production and operations with smart digital technologies, promising to transform the operation, management, and governance of every industry, including health care. (shrink)

In this paper we take up the issue of near-term artificial intelligence (AI). "Near-term AI" is used to denote artificial intelligence algorithms that are already in place in a variety of public and private sectors, guiding decision that pertain to advertising, credit ratings, and sentencing in the justice system. Our focus here is to contribute to a critical discussion of the ways that AI is already being widely used in decision-making procedures in these areas. We will argue that (...) developers and deployers of AI systems--in senses to be defined--bear a particular kind of responsibility for the moral consequences of near-term AI. We will present a tool to aid developers and deployers in engaging in the moral reflection we argue is required of them, in order both the help them meet their moral obligations and to help address the material risks posed by what we take to be the status quo of actual near-term AI development. This chapter can be understood as a contribution to the field of technology assessment, but instead of suggesting policy revisions, we will propose a framework for ethical analysis that can be used to facilitate more robust ethical reflection in AI development and implementation. (shrink)

It has now become a realistic prospect for smart care to be provided at home for those living with long-term conditions such as dementia. In the contemporary smart care scenario, homes are fitted with an array of sensors for remote monitoring providing data that feed into intelligent systems developed to highlight concerning patterns of behaviour or physiological measurements and to alert healthcare professionals to the need for action. This paper explores some ethical issues that may arise within such smart care (...) systems, focusing on the extent to which ethical issues can be addressed at the system design stage. Artificial intelligence has been widely portrayed as an ethically risky technology, posing challenges for privacy and human autonomy and with the potential to introduce and exacerbate bias and inequality. While broad principles for ethical artificial intelligence have become established, the mechanisms for governing ethical artificial intelligence are still evolving. In healthcare settings the implementation of smart technologies falls within the existing frameworks for ethical review and governance. Feeding into this ethical review there are many practical steps that designers can take to build ethical considerations into the technology. After exploring the pre-emptive steps that can be taken in design and governance to provide for an ethical smart care system, the paper reviews the potential for further ethical challenges to arise within the everyday implementation of smart care systems in the context of dementia, despite the best efforts of all concerned to pre-empt them. The paper concludes with an exploration of the dilemmas that may thus face healthcare professionals involved in implementing this kind of smart care and with a call for further research to explore ethical dimensions of smart care both in terms of general principles and lived experience. (shrink)

The objective of this work is to explore the notion of “action” and “agency” in artificial intelligence (AI). It employs a metaphysical notion of action and agency as an epistemological tool in the critique of the notion of “action” and “agency” in artificial intelligence. Hence, both a metaphysical and cognitive analysis is employed in the investigation of the quiddity and nature of action and agency per se, and how they are, by extension employed in the language and science (...) of artificial intelligence. The advent of the science of artificial intelligence and cognitive science, and the technological applications of artificial intelligence in the production of agents such as driverless cars and expert systems, have raised the question of moral, ethical and/or legal responsibility in AI agents. This has re-emphasized the importance of the philosophical discourse on the notions of action and agency, which in contemporary intellectual discourse are now perceived to be phenomena within the epistemic competence of the natural sciences. This paper argues that AI systems do not and cannot possess free agency and autonomy, thus cannot be morally and ethically responsible, hence, it recommends a socio-political response to the question of responsibility in AI. It is then the duty of individual nations, or the global community to define and enact policies on who shoulders the responsibility of actions executed by AIs. (shrink)