We introduce the Bias Network Approach (BNA) as a sociotechnical method for AI developers to identify, map, and relate biases across the AI development process. This approach addresses the limitations of what we call the "isolationist approach to AI bias," a trend in AI literature where biases are seen as separate occurrence linked to specific stages in an AI pipeline. Dealing with these multiple biases can trigger a sense of excessive overload in managing each potential bias (...) individually or promote the adoption of an uncritical approach to understanding the influence of biases in developers’ decision-making. The BNA fosters dialogue and a critical stance among developers, guided by external experts, using graphical representations to depict biased connections. To test the BNA, we conducted a pilot case study on the "waiting list” project, involving a small AI developer team creating a healthcare waiting list NPL model in Chile. The analysis showed promising findings: (i) the BNA aids in visualizing interconnected biases and their impacts, facilitating ethical reflection in a more accessible way; (ii) it promotes transparency in decision-making throughout AI development; and (iii) more focus is necessary on professional biases and material limitations as sources of bias in AI development. (shrink)

Artificial intelligence (AI) systems are increasingly being used in healthcare, thanks to the high level of performance that these systems have proven to deliver. So far, clinical applications have focused on diagnosis and on prediction of outcomes. It is less clear in what way AI can or should support complex clinical decisions that crucially depend on patient preferences. In this paper, we focus on the ethical questions arising from the design, development and deployment of AI systems to support decision- (...) class='Hi'>making around cardiopulmonary resuscitation and the determination of a patient’s Do Not Attempt to Resuscitate status (also known as code status). The COVID-19 pandemic has made us keenly aware of the difficulties physicians encounter when they have to act quickly in stressful situations without knowing what their patient would have wanted. We discuss the results of an interview study conducted with healthcare professionals in a university hospital aimed at understanding the status quo of resuscitation decision processes while exploring a potential role for AI systems in decision-making around code status. Our data suggest that (1) current practices are fraught with challenges such as insufficient knowledge regarding patient preferences, time pressure and personal bias guiding care considerations and (2) there is considerable openness among clinicians to consider the use of AI-based decision support. We suggest a model for how AI can contribute to improve decision-making around resuscitation and propose a set of ethically relevant preconditions—conceptual, methodological and procedural—that need to be considered in further development and implementation efforts. (shrink)

Artificial intelligence is set to transform healthcare. Key ethical issues to emerge with this transformation encompass the accountability and transparency of the decisions made by AI-based systems, the potential for group harms arising from algorithmic bias and the professional roles and integrity of clinicians. These concerns must be balanced against the imperatives of generating public benefit with more efficient healthcare systems from the vastly higher and accurate computational power of AI. In weighing up these issues, this paper applies (...) the deliberative balancing approach of the Ethics Framework for Big Data in Health and Research. The analysis applies relevant values identified from the framework to demonstrate how decision-makers can draw on them to develop and implement AI-assisted support systems into healthcare and clinical practice ethically and responsibly. Please refer to Xafis et al. in this special issue of the Asian Bioethics Review for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end of this paper. (shrink)

Computers are used to make decisions in an increasing number of domains. There is widespread agreement that some of these uses are ethically problematic. Far less clear is where ethical problems arise, and what might be done about them. This paper expands and defends the Ethical Gravity Thesis: ethical problems that arise at higher levels of analysis of an automated decision-making system are inherited by lower levels of analysis. Particular instantiations of systems can add new problems, but not (...) ameliorate more general ones. We defend this thesis by adapting Marr’s famous 1982 framework for understanding information-processing systems. We show how this framework allows one to situate ethical problems at the appropriate level of abstraction, which in turn can be used to target appropriate interventions. (shrink)

Background Given that AI-driven decision support systems (AI-DSS) are intended to assist in medical decision making, it is essential that clinicians are willing to incorporate AI-DSS into their practice. This study takes as a case study the use of AI-driven cardiotography (CTG), a type of AI-DSS, in the context of intrapartum care. Focusing on the perspectives of obstetricians and midwives regarding the ethical and trust-related issues of incorporating AI-driven tools in their practice, this paper explores the conditions (...) that AI-driven CTG must fulfill for clinicians to feel justified in incorporating this assistive technology into their decision-making processes regarding interventions in labor. Methods This study is based on semi-structured interviews conducted online with eight obstetricians and five midwives based in England. Participants were asked about their current decision-making processes about when to intervene in labor, how AI-driven CTG might enhance or disrupt this process, and what it would take for them to trust this kind of technology. Interviews were transcribed verbatim and analyzed with thematic analysis. NVivo software was used to organize thematic codes that recurred in interviews to identify the issues that mattered most to participants. Topics and themes that were repeated across interviews were identified to form the basis of the analysis and conclusions of this paper. Results There were four major themes that emerged from our interviews with obstetricians and midwives regarding the conditions that AI-driven CTG must fulfill: (1) the importance of accurate and efficient risk assessments; (2) the capacity for personalization and individualized medicine; (3) the lack of significance regarding the type of institution that develops technology; and (4) the need for transparency in the development process. Conclusions Accuracy, efficiency, personalization abilities, transparency, and clear evidence that it can improve outcomes are conditions that clinicians deem necessary for AI-DSS to meet in order to be considered reliable and therefore worthy of being incorporated into the decision-making process. Importantly, healthcare professionals considered themselves as the epistemic authorities in the clinical context and the bearers of responsibility for delivering appropriate care. Therefore, what mattered to them was being able to evaluate the reliability of AI-DSS on their own terms, and have confidence in implementing them in their practice. (shrink)

Artificial intelligence (AI) has sparked interest in various areas, including marketing. However, this exhilaration is being tempered by growing concerns about the moral and legal implications of using AI in marketing. Although previous research has revealed various ethical and legal issues, such as algorithmic discrimination and data privacy, there are no definitive answers. This paper aims to fill this gap by investigating AI’s ethical and legal concerns in marketing and suggesting feasible solutions.,The paper synthesises information from academic articles, industry reports, (...) case studies and legal documents through a thematic literature review. A qualitative analysis approach categorises and interprets ethical and legal challenges and proposes potential solutions.,The findings of this paper raise concerns about ethical and legal challenges related to AI in the marketing area. Ethical concerns related to discrimination, bias, manipulation, job displacement, absence of social interaction, cybersecurity, unintended consequences, environmental impact, privacy and legal issues such as consumer security, responsibility, liability, brand protection, competition law, agreements, data protection, consumer protection and intellectual property rights are discussed in the paper, and their potential solutions are discussed.,Notwithstanding the interesting insights gathered from this investigation of the ethical and legal consequences of AI in marketing, it is important to recognise the limits of this research. Initially, the focus of this study is confined to a review of the most important ethical and legal issues pertaining to AI in marketing. Additional possible repercussions, such as those associated with intellectual property, contracts and licencing, should be investigated more deeply in future studies. Despite the fact that this study gives various answers and best practices for tackling the stated ethical and legal concerns, the viability and efficacy of these solutions may differ depending on the context and industry. Thus, more research and case studies are required to evaluate the applicability and efficacy of these solutions in other circumstances. This research is mostly based on a literature review and may not represent the experiences or opinions of all stakeholders engaged in AI-powered marketing. Further study might involve interviews or surveys with marketing professionals, customers and other key stakeholders to offer a full knowledge of the practical difficulties and solutions. Because of the rapid speed of technical progress, AI’s ethical and regulatory ramifications in marketing are continually increasing. Consequently, this work should be a springboard for more research and continuing conversations on this subject.,This study’s findings have several practical implications for marketing professionals. Emphasising openness and explainability: Marketing professionals should prioritise transparency in their use of AI, ensuring that customers are fully informed about data collection and utilisation for targeted advertising. By promoting openness and explainability, marketers can foster customer trust and avoid the negative consequences of a lack of transparency. Establishing ethical guidelines: Marketing professionals need to develop ethical rules for the creation and implementation of AI-powered marketing strategies. Adhering to ethical principles ensures compliance with legal norms and aligns with the organisation’s values and ideals. Investing in bias detection tools and privacy-enhancing technology: To mitigate risks associated with AI in marketing, marketers should allocate resources to develop and implement bias detection tools and privacy-enhancing technology. These tools can identify and address biases in AI algorithms, safeguard consumer privacy and extract valuable insights from consumer data.,This study’s social implications emphasise the need for a comprehensive approach to address the ethical and legal challenges of AI in marketing. This includes adopting a responsible innovation framework, promoting ethical leadership, using ethical decision-making frameworks and conducting multidisciplinary research. By incorporating these approaches, marketers can navigate the complexities of AI in marketing responsibly, foster an ethical organisational culture, make informed ethical decisions and develop effective solutions. Such practices promote public trust, ensure equitable distribution of benefits and risk, and mitigate potential negative social consequences associated with AI in marketing.,To the best of the authors’ knowledge, this paper is among the first to explore potential solutions comprehensively. This paper provides a nuanced understanding of the challenges by using a multidisciplinary framework and synthesising various sources. It contributes valuable insights for academia and industry. (shrink)

This paper approaches the interaction of a health professional with an AI system for diagnostic purposes as a hybrid decision making process and conceptualizes epistemo-ethical constraints on this process. We argue for the importance of the understanding of the underlying machine epistemology in order to raise awareness of and facilitate realistic expectations from AI as a decision support system, both among healthcare professionals and the potential benefiters. Understanding the epistemic abilities and limitations of such systems is (...) essential if we are to integrate AI into the decision making processes in a way that takes into account its applicability boundaries. This will help to mitigate potential harm due to misjudgments and, as a result, to raise the trust—understood here as a belief in reliability of—in the AI system. We aim at a minimal requirement for AI meta-explanation which should distinguish machine epistemic processes from similar processes in human epistemology in order to avoid confusion and error in judgment and application. An informed approach to the integration of AI systems into the decision making for diagnostic purposes is crucial given its high impact on health and well-being of patients. (shrink)

Organisations increasingly use automated decision-making systems (ADMS) to inform decisions that affect humans and their environment. While the use of ADMS can improve the accuracy and efficiency of decision-making processes, it is also coupled with ethical challenges. Unfortunately, the governance mechanisms currently used to oversee human decision-making often fail when applied to ADMS. In previous work, we proposed that ethics-based auditing (EBA)—that is, a structured process by which ADMS are assessed for consistency with (...) relevant principles or norms—can (a) help organisations verify claims about their ADMS and (b) provide decision-subjects with justifications for the outputs produced by ADMS. In this article, we outline the conditions under which EBA procedures can be feasible and effective in practice. First, we argue that EBA is best understood as a ‘soft’ yet ‘formal’ governance mechanism. This implies that the main responsibility of auditors should be to spark ethical deliberation at key intervention points throughout the software development process and ensure that there is sufficient documentation to respond to potential inquiries. Second, we frame AMDS as parts of larger sociotechnical systems to demonstrate that to be feasible and effective, EBA procedures must link to intervention points that span all levels of organisational governance and all phases of the software lifecycle. The main function of EBA should, therefore, be to inform, formalise, assess, and interlink existing governance structures. Finally, we discuss the policy implications of our findings. To support the emergence of feasible and effective EBA procedures, policymakers and regulators could provide standardised reporting formats, facilitate knowledge exchange, provide guidance on how to resolve normative tensions, and create an independent body to oversee EBA of ADMS. (shrink)

The purpose of this study is to expand our understanding of the factors that influence ethical behavioral intentions of public accountants. Recent scandals have dominated the news and have caused legislators, regulators and the public to question the role of the accounting profession. Legislative changes have brought about major structural changes in the profession and continued scrutiny will surely lead to further changes. Thus, developing an understanding of the personal and contextual factors that influence ethical decisions is critical. An extension (...) of the theory of planned behavior [Ajzen, I.: 1985, Action Control-From Cognition to Behavior ], the model used in this study examined the influence of personal, social and organizational factors on ethical intentions. Specifically, the individual level model tested direct eects of attitudes, subjective norms, perceived behavioral control, moral sensitivity and ethical climate. Professionals from five accounting firms completed a survey that measured responses to ethical dilemmas related to the public accounting domain. To minimize the potential impact of common method bias, the survey instrument was administered in two phases. Hypotheses were evaluated using a structural modeling technique, partial least squares. Results show strong support for a direct relationship between attitudes and ethical intentions. The proposed direct eect of subjective norms was not supported. However, a significant relationship between subjective norms and attitudes was found. Professionals' attitudes towards ethical issues clearly influence intentions. Moreover, this study illustrates the potential influence of social factors in attitude formation. Future research should explore the factors in the public accounting domain that most strongly influence attitude formation. This study suggests that the theory of reasoned action oers a useful framework for exploring these issues. (shrink)

The increasing implementation of and reliance on machine-learning (ML) algorithms to perform tasks, deliver services and make decisions in health and healthcare have made the need for fairness in ML, and more specifically in healthcare ML algorithms (HMLA), a very important and urgent task. However, while the debate on fairness in the ethics of artificial intelligence (AI) and in HMLA has grown significantly over the last decade, the very concept of fairness as an ethical value has not yet been (...) sufficiently explored. Our paper aims to fill this gap and address the AI ethics principle of fairness from a conceptual standpoint, drawing insights from accounts of fairness elaborated in moral philosophy and using them to conceptualise fairness as an ethical value and to redefine fairness in HMLA accordingly. To achieve our goal, following a first section aimed at clarifying the background, methodology and structure of the paper, in the second section, we provide an overview of the discussion of the AI ethics principle of fairness in HMLA and show that the concept of fairness underlying this debate is framed in purely distributive terms and overlaps with non-discrimination, which is defined in turn as the absence of biases. After showing that this framing is inadequate, in the third section, we pursue an ethical inquiry into the concept of fairness and argue that fairness ought to be conceived of as an ethical value. Following a clarification of the relationship between fairness and non-discrimination, we show that the two do not overlap and that fairness requires much more than just non-discrimination. Moreover, we highlight that fairness not only has a distributive but also a socio-relational dimension. Finally, we pinpoint the constitutive components of fairness. In doing so, we base our arguments on a renewed reflection on the concept of respect, which goes beyond the idea of equal respect to include respect for individual persons. In the fourth section, we analyse the implications of our conceptual redefinition of fairness as an ethical value in the discussion of fairness in HMLA. Here, we claim that fairness requires more than non-discrimination and the absence of biases as well as more than just distribution; it needs to ensure that HMLA respects persons both as persons and as particular individuals. Finally, in the fifth section, we sketch some broader implications and show how our inquiry can contribute to making HMLA and, more generally, AI promote the social good and a fairer society. (shrink)

This study investigates accounting students’ ethical decision-making judgments and behavioral intentions. The Multidimensional Ethics Scale (MES) was used to measure the extent to which a hypothetical behavior was consistent with three moral criteria (Moral Equity, Relativism and Contractualism). The study specifically tests the differences in ethical decision-making between students who have been exposed to a dedicated ethics unit of study compared with students who have not studied ethics. The influences of culture and gender (...) on students’ ethical decision-making are also addressed in the study. Ethical decision-making was assessed via three case studies describing moral dilemmas that an individual, business or professional person might face. The results provide support for the MES and the value added from incorporating a dedicated ethical decision-making unit in the accounting curriculum. The results also support prior evidence of gender bias and the impact of cultural differences on ethical decision-making. (shrink)

In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. In this paper the authors, with backgrounds in (...) philosophy, maternity care practice and clinical research, draw upon and extend a recent framework for shared decision-making (SDM) that identified a duty of care to the client's knowledge as a necessary condition for SDM. This duty entails the responsibility to acknowledge and overcome epistemic defeaters. This framework is applied to the use of AI in maternity care, in particular, the use of machine learning and deep learning technology to attempt to enhance electronic fetal monitoring (EFM). In doing so, various sub-kinds of epistemic defeater, namely, transparent, opaque, underdetermined, and inherited defeaters are taxonomized and discussed. The authors argue that, although effective current or future AI-enhanced EFM may impose an epistemic obligation on the part of clinicians to rely on such systems' predictions or diagnoses as input to SDM, such obligations may be overridden by inherited defeaters, caused by a form of algorithmic bias. The existence of inherited defeaters implies that the duty of care to the client's knowledge extends to any situation in which a clinician (or anyone else) is involved in producing training data for a system that will be used in SDM. Any future AI must be capable of assessing women individually, taking into account a wide range of factors including women's preferences, to provide a holistic range of evidence for clinical decision-making. (shrink)

Artificial intelligence tools used in employment decision-making cut across the multiple stages of job advertisements, shortlisting, interviews and hiring, and actual and potential bias can arise in each of these stages. One major challenge is to mitigate AI bias and promote fairness in opaque AI systems. This paper argues that the equal opportunity merit principle is an ethical approach for fair AI employment decision-making. Further, explainable AI can mitigate the opacity problem by placing greater (...) emphasis on enhancing the understanding of reasonable users and affected persons as to the AI output. Both the equal opportunity merit principle and explainable AI should be integrated in the design and implementation of AI employment decision-making systems so as to ensure, as far as possible, that the AI output is arrived at through a fair process. (shrink)

This paper is a reflection on an experiment undertaken during a Medical Ethics lecture delivered to a group of medical students in the UK as part of a project for a programme in Higher Education Practice. The aim of the project, following Paulo Freire’s idea of ‘liberating education,’ was to identify students’ ethical assumptions and biases in relation to a problem of resource allocation in healthcare, and their role in decision-making. The experiment showed the importance placed by (...) medical students on disputed values such as free will, desert, social worth and body image, and highlighted the difficulty and importance of bringing students’ process of moral decision-making to awareness in ethics teaching, in order to a) decrease the role of implicit bias in students’ decision making and b) allow students to decide whether they in fact agree with assumed values and ethical frameworks that influence their thinking. (shrink)

In this article I consider two pertinent questions that practitioners must consider when they deploy an algorithmic system as support in clinical shared decision‐making. The first question concerns how to interpret and assess the significance of different performance measures for clinical decision‐making. The second question concerns the professional obligations that practitioners have to communicate information about the quality of an algorithm's output to patients in light of the principles of autonomy, beneficence, and justice. In the (...) article I review the four standard performance measures used to evaluate and validate algorithms, outline their role in the discussion of algorithmic fairness, and discuss the professional responsibilities that practitioners face when communicating information about these measures to patients. (shrink)

This paper analyzes the collaboration between healthcare professionals and algorithms in making decisions within the realm of public healthcare. By extending the concept of ‘tinkering’ from previous research conducted by philosopher Mol (Care in practice. On tinkering in clinics, homes and farms Verlag, Amsterdam, 2010) and anthropologist Pols (Health Care Anal 18: 374–388, 2009), who highlighted the improvisational and adaptive practices of healthcare professionals, this paper reveals that in the context of digitalizing healthcare, both professionals and algorithms engage in (...) what I call ‘collaborative tinkering’ as they navigate the intricate and unpredictable nature of healthcare situations together. The paper draws upon an idea that is increasingly common in academic literature, namely that healthcare professionals and the algorithms they use can form a hybrid decision-making entity, challenging the conventional notion of agency and intelligence as being exclusively confined to individual humans or machines. Drawing upon an international, ethnographic study conducted in different hospitals around the world, the paper describes empirically how humans and algorithms come to decisions together, making explicit how, in the practice of daily work, agency and intelligence are distributed among a range of actors, including humans, technologies, knowledge resources, and the spaces where they interact. The concept of collaborative tinkering helps to make explicit how both healthcare professionals and algorithms engage in adaptive improvisation. This exploration not only enriches the understanding of collaborative dynamics between humans and AI but also problematizes the individualistic conception of AI that still exists in regulatory frameworks. By introducing empirical specificity through ethnographic insights and employing an anthropological perspective, the paper calls for a critical reassessment of current ethical and policy frameworks governing human–AI collaboration in healthcare, thereby illuminating direct implications for the future of AI ethics in medical practice. (shrink)

Background Artificial intelligence-driven Clinical Decision Support Systems (AI-CDSS) are increasingly being integrated into healthcare for various purposes, including resource allocation. While these systems promise improved efficiency and decision-making, they also raise significant ethical concerns. This study aims to explore healthcare professionals’ perspectives on the ethical implications of using AI-CDSS for healthcare resource allocation. Methods We conducted semi-structured qualitative interviews with 23 healthcare professionals, including physicians, nurses, administrators, and medical ethicists in Turkey. Interviews focused on participants’ views regarding (...) the use of AI-CDSS in resource allocation, potential ethical challenges, and recommendations for responsible implementation. Data were analyzed using thematic analysis. Results Participant responses are clustered around five pre-determined thematic areas: (1) balancing efficiency and equity in resource allocation, (2) the importance of transparency and explicability in AI-CDSS, (3) shifting roles and responsibilities in clinical decision-making, (4) ethical considerations in data usage and algorithm development, and (5) balancing cost-effectiveness and patient-centered care. Participants acknowledged the potential of AI-CDSS to optimize resource allocation but expressed concerns about exacerbating healthcare disparities, the need for interpretable AI models, changing professional roles, data privacy, and maintaining individualized care. Conclusions The integration of AI-CDSS into healthcare resource allocation presents both opportunities and significant ethical challenges. Our findings underscore the need for robust ethical frameworks, enhanced AI literacy among healthcare professionals, interdisciplinary collaboration, and rigorous monitoring and evaluation processes. Addressing these challenges proactively is crucial for harnessing the potential of AI-CDSS while preserving the fundamental values of equity, transparency, and patient-centered care in healthcare delivery. (shrink)

This concise book brings behavioral insights to the wide array of topics commonly taught in the required professional responsibility course, including admission to the practice of law, confidentiality, conflicts of interest, representing entities, prosecutorial and criminal defense ethics, litigation and negotiation ethics, legal billing, and managerial and subordinate responsibilities. Behavioral legal ethics relies on empirical research to explore how lawyers actually make ethical decisions in context, rather than how they predict they would decide an ethical dilemma. (...) This approach complements the law of lawyering by seeking to understand how various psychological factors and situational pressures explain and influence decision-making and resulting ethical (or unethical) action. Each chapter explores findings from behavioral science that pertain to ethical decision-making such as motivated reasoning, confirmation bias and other cognitive biases, fast thinking, the fundamental attribution error, wrongful obedience, conformity, moral disengagement, and much more. In addition, each chapter contains relevant case studies and reflection questions to deepen and cement students' understanding of the role of behavioral legal ethics in professional responsibility. Finally, the book offers ideas for individual attorneys and legal organizations to improve ethical decision-making."--Publisher's webpage. (shrink)

When ethical decisions have to be taken in critical, complex medical situations, they often involve decisions that set the course for or against life-sustaining treatments. Therefore the decisions have far-reaching consequences for the patients, their relatives, and often for the clinical staff. Although the rich psychology literature provides evidence that reasoning may be affected by undesired influences that may undermine the quality of the decision outcome, not much attention has been given to this phenomenon in health care or (...) class='Hi'>ethics consultation. In this paper, we aim to contribute to the sensitization of the problem of systematic reasoning biases by showing how exemplary individual and group biases can affect the quality of decision-making on an individual and group level. We are addressing clinical ethicists as well as clinicians who guide complex decision-making processes of ethical significance. Knowledge regarding exemplary group psychological biases (e.g. conformity bias), and individual biases (e.g. stereotypes), will be taken from the disciplines of social psychology and cognitive decision science and considered in the field of ethical decision-making. Finally we discuss the influence of intuitive versus analytical (systematical) reasoning on the validity of ethical decision-making. (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)

This study examined the relationship between nurses’ ethical decision-making levels and their professional behaviours. Data were collected from 225 nurses who were recruited from university hospitals in Ankara using proportionate sampling. Data were analysed using descriptive statistics and Pearson correlations. Most of the nurses were familiar with ethical dilemmas in nursing practice. The Nursing Principled Thinking level was above average, while the Practical Consideration level was average. Nurses’ professionalism level was low. There was a positive but weak (...) correlation between professional behaviours of the nurses and their ethical decision-making levels. Increasing nurses’ professionalism level can provide a positive contribution to the ethical decision-making level. (shrink)

The ethics sections of Critical Care Societies have issued position statements and proposed a variety of position papers and policies describing the appropriate use of critical care services. These policies describe the goals of critical care provision — to support a patient through an acute, potentially reversible, life-threatening illness — and provide broad guidance on physiological and hemodynamic criteria that require the specialized care of an ICU environment. In recent years, many critical care professionals have, however, reported providing care (...) they felt was inappropriate or futile even though most felt they should not have done so. Futile care encompasses treatments that will not work or treatments that have no chance of providing any benefit. ICU teams define care as inappropriate when it fails to restore a person to an awareness of self, and an ability to interact with their environment particularly when a lot of critical care resources are required. When patients experience significant amounts of pain and suffering, such care seems even more inappropriate. (shrink)

BackgroundCommentators believe that the ethical decision-making climate is instrumental in enhancing interprofessional collaboration in intensive care units. Our aim was twofold: to determine the perception of the ethical climate, levels of moral distress, and intention to leave one's job among nurses and physicians, and between the different ICU types and determine the association between the ethical climate, moral distress, and intention to leave.MethodsWe performed a cross-sectional questionnaire study between May 2021 and August 2021 involving 206 nurses and physicians (...) in a large urban academic hospital. We used the validated Ethical Decision-Making Climate Questionnaire and the Measure of Moral Distress for Healthcare Professionals tools and asked respondents their intention to leave their jobs. We also made comparisons between the different ICU types. We used Pearson's correlation coefficient to identify statistically significant associations between the Ethical Climate, Moral Distress, and Intention to Leave.ResultsNurses perceived the ethical climate for decision-making as less favorable than physicians. They also had significantly greater levels of moral distress and higher intention to leave their job rates than physicians. Regarding the ICU types, the Neonatal/pediatric unit had a significantly higher overall ethical climate score than the Medical and Surgical units and also demonstrated lower moral distress scores and lower “intention to leave” scores compared with both the Medical and Surgical units. The ethical climate and moral distress scores were negatively correlated ; moral distress and "intention to leave" was positively correlated ; and ethical climate and “intention to leave” were negatively correlated.ConclusionsSignificant differences exist in the perception of the ethical climate, levels of moral distress, and intention to leave between nurses and physicians and between the different ICU types. Inspecting the individual factors of the ethical climate and moral distress tools can help hospital leadership target organizational factors that improve interprofessional collaboration, lessening moral distress, decreasing turnover, and improved patient care. (shrink)

Automated decision making for sentencing is the use of a software algorithm to analyse a convicted offender’s case and deliver a sentence. This chapter reviews the moral arguments for and against employing automated decision making for sentencing and finds that its use is in principle morally permissible. Specifically, it argues that well-designed automated decision making for sentencing will better approximate the just sentence than human sentencers. Moreover, it dismisses common concerns about transparency, privacy and (...) bias as unpersuasive or inapplicable. The chapter also notes that moral disagreement about theories of just sentencing are plausibly resolved by applying the principle of maximising expected moral choiceworthiness, and that automated decision making is better suited to the resulting ensemble model. Finally, the chapter considers the challenge posed by penal populism. The dispiriting conclusion is that although it is in theory morally desirable to use automated decision-making for criminal sentencing, it may well be the case that we ought not to try. (shrink)

Although clinical ethics support services are becoming increasingly prevalent in Europe and North America, they remain an uncommon feature of the Irish healthcare system and Irish health professionals lack formal support when faced with ethically challenging cases. We have developed a variant on existing clinical ethics decision-making tools which is designed to build capacity and confidence amongst Irish practitioners and enable them to confront challenging situations in the absence of any dedicated support structure. The tool provided (...) below follows a transparent stepwise procedure which avoids an overcomplicated analysis while remaining sensitive to the complexity of the issues addressed. The novelty of the tool lies in the explicit association it makes between each step in the process and one or more responsibilities based on established norms of ethical decision-making in the public domain. (shrink)

Our comments focus on the ACMCode of Ethics and situate the Code within ageneral ethical decision-making process tospecify the five steps which logically precedehuman action in ethical matters and determinethat action, and the individual differencetraits in these five steps which bear upon theresolution of an ethical problem and lead tomorally responsible action. Our main purpose isto present a cognitive moral processing modelwhich computing professionals can use to betterunderstand their professional rights andduties. It is clear that the (...) Code providessubstantial guidance in the areas ofintellectual property rights, unauthorizedentry into computing systems, and privacy. Inother areas, such as obscenity onbulletin-board systems, the Code is silent. Aninteractive software program which allows theuser to see the ways in which the Code isintegrated and instructive in the six-stepmoral decision-making process is accessible viathe internet. Our secondary purpose is toreformulate the Code as a set of questionswhich allow the computing professional to seepractices which diminish the human person asunethical and those which enhance the humanperson as ethical. (shrink)

BackgroundIn gender-affirming medical care (GAMC), ethical challenges in decision-making are ubiquitous. These challenges are becoming more pressing due to exponentially increasing referrals, politico-legal contestation, and divergent normative views regarding decisional roles and models. Little is known, however, about what ethical challenges related to decision-making healthcare professionals (HCPs) themselves face in their daily work in GAMC and how these relate to, for example, the subjective nature of Gender Incongruence (GI), the multidisciplinary character of GAMC and the role (...) HCPs play in assessing GI and eligibility for interventions. Given the relevance and urgency of these questions, we conducted a qualitative study among HCPs providing GAMC to transgender adults in the Netherlands.MethodsIn this qualitative research, we conducted 11 semi-structured interviews between May 2020 and February 2021 with HCPs (six mental health professionals, two HCPs in endocrinology, two in plastic surgery, and one in nursing) working in two distinct GAMC settings. We purposively sampled for professional background and years of experience in GAMC. We analyzed our interview data using thematic analysis. As some respondents were more inclined to speak about what should or ought to be done to arrive at good or right decision-making, we identified both ethical challenges and norms. Furthermore, in our analysis, we differentiated between respondents’ explicit and implicit ethical challenges and norms and ascertained the specific context in which these challenges emerged.ResultsRespondents’ ethical challenges and norms centered on (1) dividing and defining decisional roles and bounds, (2) negotiating decision-making in a (multidisciplinary) team, and (3) navigating various decision-making temporalities. These themes arose in the context of uncertainties regarding (1) GAMC’s guidelines, evidence, and outcomes, as well as (2) the boundaries and assessment of GI.ConclusionsThis interview study provides detailed empirical insight into both the explicit and implicit ethical challenges that HCPs experience and their ethical norms regarding decision-making. It also describes how uncertainties and (implicit) normativities concerning GAMC and GI pre-structure the moral environment in which these challenges and norms manifest. We provide normative reflections and recommendations on handling these ethical challenges in a way that is sensitive to the context in which they arise. (shrink)

Background: Increasing interest in empirical ethics has enhanced understanding of healthcare professionals’ ethical problems and attendant decision-making. A four-stage decision-making model involving ethical attention, reasoning, intention and action offers further insights into how more than reasoning alone may contribute to decision-making.Aims: To explore how the four-stage model can increase understanding of decision-making in healthcare and describe the decision-making of an under-researched professional group.Methods: 23 purposively sampled UK community pharmacists (...) were asked, in semi-structured interviews, to describe ethical problems in their work and how they were resolved. Framework analysis of transcribed interviews utilised the four decision-making stages, together with constant comparative methods and deviant-case analysis.Results: Pharmacists were often inattentive and constructed problems in legal terms. Ethical reasoning was limited, but examples of appeals to consequences, the golden rule, religious faith and common-sense experience emerged. Ethical intention was compromised by frequent concern about legal prosecution. Ethical inaction was common, typified by pharmacists’ failure to report healthcare professionals’ bad practices, and ethical passivity emerged to describe these negative examples of the four decision-making stages. Pharmacists occasionally described more ethically active decision-making, but this often involved ethical uncertainty.Discussion: The four decision-making stages are a useful tool in considering how healthcare professionals try to resolve ethical problems in practice. They reveal processes often ignored in normative theories, and their recognition and the emergence of ethical passivity indicates the complexity of decision-making in practice. Ethical passivity may be deleterious to patients’ welfare, and concerns emerge about improving pharmacists’ ethical training and promoting ethical awareness and responsibility. (shrink)

This paper examines two prominent formal trade-offs in artificial intelligence (AI)---between predictive accuracy and fairness, and between predictive accuracy and interpretability. These trade-offs have become a central focus in normative and regulatory discussions as policymakers seek to understand the value tensions that can arise in the social adoption of AI tools. The prevailing interpretation views these formal trade-offs as directly corresponding to tensions between underlying social values, implying unavoidable conflicts between those social objectives. In this paper, I challenge that prevalent (...) interpretation by introducing a sociotechnical approach to examining the value implications of trade-offs. After providing a set-theoretic understanding of these model trade-offs, I argue that their implications cannot be understood in isolation from the technical, psychological, organizational, and social factors that shape the integration of AI models into decision-making pipelines. Specifically, I identify three key considerations---validity and instrumental relevance, compositionality, and dynamics---for contextualizing and characterizing these implications. These considerations reveal that the relationship between model trade-offs and corresponding values depends on critical choices and assumptions. Crucially, judicious sacrifices in one model property for another can, in fact, promote both sets of corresponding values. The proposed sociotechnical perspective thus shows that we can and should aspire to higher epistemic and ethical possibilities than the prevalent interpretation suggests, while offering practical guidance for achieving those outcomes. Finally, I draw out the broader implications of this perspective for AI design and governance, highlighting the need to broaden normative engagement across the AI lifecycle, develop legal and auditing tools sensitive to sociotechnical considerations, and rethink the vital role and appropriate structure of interdisciplinary collaboration in fostering a responsible AI workforce. (shrink)

Physicians and other healthcare professionals are increasingly finding ways to use artificial intelligent decision support systems in their work. IBM Watson Health, for example, is a commercially available technology that is providing AI-DDS services in genomics, oncology, healthcare management and more.1 AI’s ability to scan massive amounts of data, detect patterns, and derive solutions from data is vastly more superior than that of humans. AI technology is undeniably integral to the future of healthcare and public health, and thoughtful consideration (...) of the legal, ethical and moral issues surrounding this technology is a must. The authors of the article, Responsibility, Second Opinions, and Peer-Disagreement—Ethical and Epistemological Challenges of Using AI in Clinical Diagnostic Contexts, provide an informed discussion of how AI-DSS may be used, both practically and ethically, to assist healthcare professionals in cooperative diagnostic processes2. The authors propose a process, whereby AI-DSS would provide a physician a second opinion, and when there is a mismatch between opinions, another physician would provide a third opinion. This approach maintains a ‘physician-in-charge’ perspective, and suggests that decision-making must ultimately be made by a person. This approach is also consistent with the ‘physician in-the-loop’ concept, such that even when increasingly autonomous AI-DSSs are put to use, physicians will still be providing checks and overseeing clinical decisions. The authors conceptualise AI as a replacement of human cognitive labour. That is, AI is used to supplant a human professional in particular functions …. (shrink)

Chapter 1 Who this book is for and who it is not for1 There are already too many books offering solutions to the problems of the health service. ...

The international community has proposed a comprehensive strategy to prevent congenital abnormalities. And China, with a high incidence of congenital diseases, has implemented measures including prenatal screening and diagnosis to reduce the morbidity of congenital abnormalities. However, ethical challenges arise in the practice of prenatal screening and diagnosis among healthcare professionals. Five focus group discussions were conducted with twenty-four health professionals working in maternal and child health services in Hunan Province, China, to explore the ethical challenges they encountered in prenatal (...) testing decision-making and information disclosure practices, as well as their views on these challenges. Participants were selected through purposive sampling, ensuring maximum demographic diversity. Three main themes were identified: 1) balancing between information disclosure and privacy protection; 2) patient-oriented decision-making and tensions within family-oriented decision-making; 3) the disparity between the limited help clinical ethics committees (CECs) can provide and professionals’ need for CECs. Ethical norms for information disclosure and autonomous decision-making within prenatal screening and diagnostic institutions must be established. Utilizing CECs is crucial to guide professionals in delivering prenatal testing services while simultaneously focusing on targeted improvement of communication skills among these professionals. (shrink)

A variety of cognitive biases are known to compromise ethical deliberation and decision-making processes. However, little is known about their role in clinical ethics supports (CES). We searched five electronic databases (Pubmed, PsychINFO, the Web of Science, CINAHL, and Medline) to identify articles describing cognitive bias in the context of committees that deliberate on ethical issues concerning patients, at all levels of care. We charted the data from the retrieved articles including the authors and year of (...) publication, title, CES reference, the reported cognitive bias, paper type, and approach. Of an initial 572 records retrieved, we screened the titles and abstracts of 128 articles, and identified 58 articles for full review. Four articles were selected for inclusion. Two are empirical investigations of bias in two CES, and two are theoretical, conceptual papers that discuss cognitive bias during CES deliberations. Our main result first shows an overview of bias related to the working human environment and to information gathering that concerns different types of CES. Second, several determinants of cognitive bias were highlighted. Especially, stressful environments could be at risk of cognitive bias, whatever the clinical dilemma. Whether a need for a better taxonomy of cognitive bias in CES is highlighted, a proposal is made to focus on individual, group, institutional and professional biases that can be present during clinical ethics deliberation. However, future studies need to focus on an ecological evaluation of CES deliberations, in order to better-characterize cognitive biases and to study how they impact the quality of ethical decision-making. This information would be useful in considering countermeasures to ensure that deliberation is as unbiased as possible, and allow the most appropriate ethical decision to emerge in response to the dilemma at hand. (shrink)

Family involvement in healthcare decision-making for competent patients occurs to varying degrees in many communities around the world. There are different attitudes about who should make treatment decisions, how and why. Legal and professional ethics codes in most jurisdictions reflect and support the idea that competent patients should be enabled to make their own treatment decisions, even if others, including their healthcare professionals, disagree with them. This way of thinking contrasts with some cultural norms that put (...) more emphasis on the family as a decision-making entity, in some circumstances to the exclusion of a competent patient. Possible tensions may arise between various combinations of patient, family members and healthcare professionals, and healthcare professionals must tread a careful path in navigating family involvement in the decision-making process. These tensions may be about differences of opinion about which treatment option is best and/or on who should have a say or influence in the decision-making process. While some relevant cultural, legal and policy considerations vary from community to community, there are ethical issues that healthcare professionals need to grapple with in balancing the laws and professional codes on decision-making and the ethical principle of respecting patients and their autonomy. This paper will highlight and propose that a partial resolution to these issues may lie in relational understandings of autonomy, which in principle justify interventions by healthcare professionals and family that support patients in decision-making. (shrink)

The evidence from the recent financial crisis in the USA indicates the importance of ethical decision making in the banking and finance industry. This study surveyed 90 banking and finance professionals and students in Vietnam to examine the differences in their ethical decision making. The questionnaire consisted of eight vignettes describing practical ethical dilemmas which banking and finance professionals may face in their daily work. We found significant differences in ethical decision making between these (...) two groups in their overall ethical scores and in four out of eight vignettes. We also conducted a 3-h ethics training programme for these professionals and students and found that teaching ethics was more effective for students than working adults in the banking and finance industry. These findings are important as they show how banking and financial institutions can make workplace environments more conducive to ethical decision-making by enhancing ethics education for both newcomers and existing professionals. (shrink)

Background: Research suggests that nurses generally do not participate in ethical decision-making in accordance with ethical guidelines for nurses. In addition to completing their training, nurses need to reflect on and use ethically grounded arguments and defined ethical values such as patient’s dignity in their clinical work. Objectives: The purpose of this article is to gain a deeper understanding of how nurses deal with ethical decision-making in daily practice. The chosen research question is “How do nurses (...) participate in ethical decision-making for the patient?” Design and method: We use Gadamer’s philosophical hermeneutics as well as Kvale and Brinkmann’s three levels of understanding in interpreting the data material. Nine registered nurses were interviewed. Ethical considerations: The Ombudsman of Norwegian Social Science Data and the head of the hospital approved the investigation. The participants received both oral and written information about the study and they gave their consent. We informed the participants that the participation was voluntary and that they were free to withdraw at any point in the course of the study. The requirement of anonymity and proper data storage was in accordance with the World Medical Association Declaration of Helsinki (1964). The participants were assured that privacy, and confidentiality would be duly protected. Results: Four key themes emerged: (1) confusion in relation to professional and operational expectations of role, (2) ideal somnolence, (3) inadequate argumentation skills, and (4) compound pressure. Conclusion: Ethical ideals appear to be latent in the mindset of the participants; however, the main finding of this investigation is that nurses need to activate the ideals and apply them into practice. Furthermore, management needs to initiate professional reasoning and interdisciplinary discussions leading to common goals for patients. (shrink)

Purpose Artificial intelligence and automation are currently changing human life with a great implication in the communication field. This research focusses on understanding the current and growing impact of AI and automation in the role of communication professionals to identify what skills and training are needed to face its impacts leading to a recommendation. Design/methodology/approach The research involves methodological triangulation, analysing and comparing data gathered from consulting with experts using the Delphi method, focus group with communication students, and literature review. (...) Findings Findings show that the likely impacts are on the one hand the enhancing of efficiency and productivity, as well as freeing communication professionals to focus on the creative side, strategy and analytical thinking, on the other hand, repetitive and low-level jobs could be lost, being higher position jobs or those involving creativity and decision making harder to automate. Two types of training are needed: to gather experience with the current AI and automated tools, and to focus on developing human qualities that AI cannot replicate. Originality/value The outcomes of this research are valuable to help current and future communication practitioners, as well as organisations, to be one step ahead and survive the age AI and automation, being aware of its current and near-future impacts. The paper offers a list of recommended soft and technical skills, as well as training needed, categorizing them in low, medium and high priority. (shrink)

Machine learning-driven clinical decision support systems (ML-CDSSs) seem impressively promising for future routine and emergency care. However, reflection on their clinical implementation reveals a wide array of ethical challenges. The preferences, concerns and expectations of professional stakeholders remain largely unexplored. Empirical research, however, may help to clarify the conceptual debate and its aspects in terms of their relevance for clinical practice. This study explores, from an ethical point of view, future healthcare professionals’ attitudes to potential changes of responsibility (...) and decision-making authority when using ML-CDSS. Twenty-seven semistructured interviews were conducted with German medical students and nursing trainees. The data were analysed based on qualitative content analysis according to Kuckartz. Interviewees’ reflections are presented under three themes the interviewees describe as closely related: (self-)attribution of responsibility, decision-making authority and need of (professional) experience. The results illustrate the conceptual interconnectedness of professional responsibility and its structural and epistemic preconditions to be able to fulfil clinicians’ responsibility in a meaningful manner. The study also sheds light on the four relata of responsibility understood as a relational concept. The article closes with concrete suggestions for the ethically sound clinical implementation of ML-CDSS. (shrink)

Introduction to ethics -- The counselor as a person and professional identity -- Ethical decision making -- Ethics & diversity -- Clients' rights and counselors' responsibilities -- Confidentiality and privileged communication -- Ethics in theory, practice, and professional relationships -- Appropriate boundaries and multiple relationships -- Ethics and technology -- Ethics in group work, couples, and families -- Ethics in school counseling -- Ethics in counselor education -- Ethics (...) in supervision -- Ethics in research and publications. (shrink)

Background: Emergency care providers are frequently faces with situations in which they have to make decisions quickly in stressful situations. They face barriers to ethical decision-making and recognizing and finding solutions to these barriers helps them to make ethical decision. Objectives: The purpose of this study was to identify barriers of ethical decision-making in Iranian Emergency Medical Service personnel. Methods: In this qualitative research, the participants (n = 15) were selected using the purposive sampling method, (...) and the data were collected by deep and semi-structured interviews. Finally, the data are analyzed using the content analysis approach. Ethical considerations: Permission to conduct the study was obtained from the Ethics Committee of the Shahid Beheshti University of Medical Sciences. The objectives of the study were explained to the participants and written consent was received from them. Also, participants were assured that necessary measures were taken to protect their anonymity and confidentiality. Findings: The results of the analysis are classified in five main categories. It encompasses the following areas: perception of situation, patient-related factors, input and output imbalance, uncoordinated health system, and paradoxes. Conclusion: Emergency Medical Service personnel make ethical decisions every day. It is important that prehospital personnel know how to manage those decisions properly so that clients’ moral rights are respected. Hence, by identifying the dimensions and obstacles of ethical decision-making in Emergency Medical Service personnel, it is possible to enhance the moral judgment and ethical accountability of the personnel and develop the strategies necessary for ethical decision-making in them. (shrink)

Operational psychology is an emerging subdiscipline that has enhanced the U.S. military's combat capabilities during the Global War on Terrorism. What makes this subdiscipline unique is its use of psychological principles and skills to improve a commander's decision making as it pertains to conducting combat (or related operations). Due to psychology's expanding role in combat support, psychologists are being confronted with challenges that require the application of their professional ethics in areas in which little if any (...) guidance has been provided. Operational psychologists are at the forefront of this expansion. Accordingly, they need a decision model to assist them in this complex dynamic environment. To this end, this article reviews various decision models and ethical frameworks, selects the most appropriate, and then applies it to the challenges faced by operational psychologists. A naturalistic decision model that integrates rational and intuitive elements is recommended. (shrink)

New and experienced psychotherapists alike can find themselves overwhelmed by an ethical quandary where there doesn't seem to be an easy solution. This book presents positive ethics as a means to overcome such ethical challenges. The positive approach focuses on not just avoiding negative consequences, but reaching the best possible outcomes for both the psychotherapist and the client. The authors outline a clear decision-making process that is based on three practical strategies: the ethics acculturation model to (...) help therapists incorporate personal ethics into their professional roles, the quality enhancement model for dealing with high-risk patients who are potentially harmful, and ethical choice-making strategies to make the most ethical decision in a situation where two ethical principles conflict. Throughout the decision-making process, psychotherapists are encouraged to follow four basic guidelines: Focus on overarching ethical principles Consider intuitive, emotional, and other nonrational factors Accept that some problems have elusive solutions Solicit input from colleagues and consultation groups Numerous vignettes illustrate how to apply positive ethics to many different ethical challenges that psychotherapists will likely encounter in practice. (shrink)

In this paper, we report on the development and validity of the Professional Decision-Making in Research measure, a vignette-based test that examines decision-making strategies used by investigators when confronted with challenging situations in the context of empirical research. The PDR was administered online with a battery of validity measures to a group of NIH-funded researchers and research trainees who were diverse in terms of age, years of experience, types of research, and race. The PDR demonstrated (...) adequate reliability and parallel form correlation. As hypothesized, the PDR was significantly negatively correlated with narcissism, cynicism, moral disengagement, and compliance disengagement; it was not correlated with socially desirable responding. In regression analysis, the strongest predictors of higher PDR scores were low compliance disengagement, speaking English as a native language, conducting clinical research with human subjects, and low levels of narcissism. Given that the PDR was written at an eighth grade reading level to be suitable for use with English as a second language participants and that only one-fourth of items focused on clinical research, further research into the possible roles of culture and research ethics training across specialties is warranted. This initial validity study demonstrates the potential usefulness of the PDR as an educational outcome assessment measure and a research instrument for studies on professionalism and integrity in research. (shrink)

Background Making appropriate end-of-life decisions in the intensive care unit (ICU) requires shared interprofessional decision-making. Thus, a decision-making climate that values the contributions of all team members, addresses diverse opinions and seeks consensus among team members is necessary. Little is known about religion’s influence on ethical decision-making climates. Therefore, this study aimed to examine the association between religious belief and ethical decision-making climates. Methods The study was a cross-sectional analytical observation study (...) as a part of the prospective observational DISPROPRICUS study. A total of 2,275 nurses and 717 physicians from 68 ICUs representing 12 countries in Europe and the US participated. All participants were asked which religion (if any) they belonged to and how important their religion (if any) was for their professional attitude towards end-of-life care. Perceptions of ethical decision-making climates were evaluated using a validated, 35-item self-assessment questionnaire that evaluates seven factors. Using cluster analysis, ICUs were categorised into four ethical decision-making climates: good, average (with nurses’ involvement at the end of life), average (without nurses’ involvement at the end of life) and poor. Results Of the 2,992 participants, 453 (15%) were religious (had religious convictions and found them important or very important for their attitude towards end-of-life care). The remaining 2,539 were non-religious (i.e. had religious convictions but assessed that they were not important for their attitude towards end-of-life care). When adjusting for country and ICU, the overall perception of the four ethical climates was associated with religious beliefs, with non-religious healthcare providers having more positive perceptions of the ethical climates compared to religious healthcare providers (p < 0.01). Within good climates, non-religious healthcare providers rated leadership by physicians (p < 0.01), interdisciplinary reflection (p = 0.049) and active decision-making by physicians (p = 0.02) as more positive compared to religious participants. In poor climates, religious healthcare providers had a more positive perception of the active involvement of nurses (p = 0.01). Within the other climates, no differences were found. Conclusions Overall perceptions of ethical decision-making climates were associated with religious beliefs, with non-religious healthcare providers generally having a more positive perception of the ethical climates than religious healthcare providers. (shrink)

In the present study business managers in Kabi Pharmacia Company were trained in the use of the autonomous method in their decision-making about solving real life business ethics problems. According to the psychological theories of Piaget, Vygotsky, and Kohlberg, it is possible to promote the acquisition of the autonomous ethical skill by instruction and training. Indeed, participation in a one-day educational programme which focused on the training of the autonomous cognitive ability and not on the transfer of (...) moral content, was sufficient to provide a shift in the mode of decision-making about business ethics problems towards the autonomous ethical function. This change was still stable one month later. A test was constructed by items representing current business ethics conflicts in order to assess ethical function. (shrink)

This book is the most comprehensive treatment available of one of the most urgent - and yet in some respects most neglected - problems in bioethics: decision-making for incompetents. Part I develops a general theory for making treatment and care decisions for patients who are not competent to decide for themselves. It provides an in-depth analysis of competence, articulates and defends a coherent set of principles to specify suitable surrogate decisionmakers and to guide their choices, examines the (...) value of advance directives, and investigates the role that considerations of cost ought to play in decisions concerning incompetents. Part II applies this theoretical framework to the distinctive problems of three important classes of individuals, many of whom are incompetent: minors, the elderly and psychiatric patients. The authors' approach combines a probing analysis of fundamental issues in ethical theory with a sensitive awareness of the concrete realities of health care institutions and the highly personal and individual character of difficult practical problems. Its broad scope will appeal to health professionals, moral philosophers and lawyers alike. (shrink)

When considering the introduction of AI to support medical decision-making, one must take an end-to-end, holistic approach to development, evaluation, integration and governance. (Cabitza and Zeito...

Artificial intelligence (AI) systems are quickly gaining ground in healthcare and clinical decision-making. However, it is still unclear in what way AI can or should support decision-making that is based on incapacitated patients’ values and goals of care, which often requires input from clinicians and loved ones. Although the use of algorithms to predict patients’ most likely preferred treatment has been discussed in the medical ethics literature, no example has been realised in clinical practice. This (...) is due, arguably, to the lack of a structured approach to the epistemological, ethical and pragmatic challenges arising from the design and use of such algorithms. The present paper offers a new perspective on the problem by suggesting that preference predicting AIs be viewed as sociotechnical systems with distinctive life-cycles. We explore how both known and novel challenges map onto the different stages of development, highlighting interdisciplinary strategies for their resolution. (shrink)

This research on the ethics of meaningful work examined how types of job-related harm and their magnitude of consequences influenced components of ethical decision-making. The research also investigated the moderating effects of individual differences on the relation between the MOC and the ethical decision-making elements for each type of harm. Using a sample of 185 Chinese professionals, a between-subjects, fully crossed experimental scenario design revealed that physical and economic job-related harm were recognized as moral issues (...) to a greater extent than cognitive or emotional harm. Second, physical job-related harm stimulated a higher level of moral evaluations than economic and cognitive harm. Third, individuals intended to act ethically when MOC was high versus low. Finally, experience with layoffs and IMO helped explain the relations between MOC and moral evaluations for economic and cognitive job-related harm, respectively. Implications for research and management are discussed. (shrink)

Families frequently act as substitute decisionmakers for their older members who suffer from diminished mental capacity to make and express their own medical choices. Substitute decisionmaking takes on particular ethical and legal urgency within the nursing home environment, especially when choices concern potential medical treatment near the end of the nursing home resident's life. This article examines current legal mechanisms in the United States that enable a family to make substitute medical decisions, the ethical underpinnings of those mechanisms, and specific (...) ethical and legal considerations implicated by their application to the nursing home setting. The article offers advice to nursing home professionals, including physicians, in working with families as substitute decisionmakers. (shrink)