AI-driven decision support systems and epistemic reliance: a qualitative study on obstetricians' and midwives' perspectives on integrating AI-driven CTG into clinical decision making.

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.

Data-driven research and healthcare: public trust, data governance and the NHS.

It is widely acknowledged that trust plays an important role for the acceptability of data sharing practices in research and healthcare, and for the adoption of new health technologies such as AI. Yet there is reported distrust in this domain. Although in the UK, the NHS is one of the most trusted public institutions, public trust does not appear to accompany its data sharing practices for research and innovation, specifically with the private sector, that have been introduced in recent years. In this paper, we examine the question of, what is it about sharing NHS data for research and innovation with for-profit companies that challenges public trust? To address this question, we draw from political theory to provide an account of public trust that helps better understand the relationship between the public and the NHS within a democratic context, as well as, the kind of obligations and expectations that govern this relationship. Then we examine whether the way in which the NHS is managing patient data and its collaboration with the private sector fit under this trust-based relationship. We argue that the datafication of healthcare and the broader 'health and wealth' agenda adopted by consecutive UK governments represent a major shift in the institutional character of the NHS, which brings into question the meaning of public good the NHS is expected to provide, challenging public trust. We conclude by suggesting that to address the problem of public trust, a theoretical and empirical examination of the benefits but also the costs associated with this shift needs to take place, as well as an open conversation at public level to determine what values should be promoted by a public institution like the NHS.

Trustworthy artificial intelligence and ethical design: public perceptions of trustworthiness of an AI-based decision-support tool in the context of intrapartum care.

BACKGROUND: Despite the recognition that developing artificial intelligence (AI) that is trustworthy is necessary for public acceptability and the successful implementation of AI in healthcare contexts, perspectives from key stakeholders are often absent from discourse on the ethical design, development, and deployment of AI. This study explores the perspectives of birth parents and mothers on the introduction of AI-based cardiotocography (CTG) in the context of intrapartum care, focusing on issues pertaining to trust and trustworthiness. METHODS: Seventeen semi-structured interviews were conducted with birth parents and mothers based on a speculative case study. Interviewees were based in England and were pregnant and/or had given birth in the last two years. Thematic analysis was used to analyze transcribed interviews with the use of NVivo. Major recurring themes acted as the basis for identifying the values most important to this population group for evaluating the trustworthiness of AI. RESULTS: Three themes pertaining to the perceived trustworthiness of AI emerged from interviews: (1) trustworthy AI-developing institutions, (2) trustworthy data from which AI is built, and (3) trustworthy decisions made with the assistance of AI. We found that birth parents and mothers trusted public institutions over private companies to develop AI, that they evaluated the trustworthiness of data by how representative it is of all population groups, and that they perceived trustworthy decisions as being mediated by humans even when supported by AI. CONCLUSIONS: The ethical values that underscore birth parents and mothers' perceptions of trustworthy AI include fairness and reliability, as well as practices like patient-centered care, the promotion of publicly funded healthcare, holistic care, and personalized medicine. Ultimately, these are also the ethical values that people want to protect in the healthcare system. Therefore, trustworthy AI is best understood not as a list of design features but in relation to how it undermines or promotes the ethical values that matter most to its end users. An ethical commitment to these values when creating AI in healthcare contexts opens up new challenges and possibilities for the design and deployment of AI.

The impact of artificial intelligence on the person-centred, doctor-patient relationship: some problems and solutions.

Artificial intelligence (AI) is often cited as a possible solution to current issues faced by healthcare systems. This includes the freeing up of time for doctors and facilitating person-centred doctor-patient relationships. However, given the novelty of artificial intelligence tools, there is very little concrete evidence on their impact on the doctor-patient relationship or on how to ensure that they are implemented in a way which is beneficial for person-centred care.Given the importance of empathy and compassion in the practice of person-centred care, we conducted a literature review to explore how AI impacts these two values. Besides empathy and compassion, shared decision-making, and trust relationships emerged as key values in the reviewed papers. We identified two concrete ways which can help ensure that the use of AI tools have a positive impact on person-centred doctor-patient relationships. These are (1) using AI tools in an assistive role and (2) adapting medical education. The study suggests that we need to take intentional steps in order to ensure that the deployment of AI tools in healthcare has a positive impact on person-centred doctor-patient relationships. We argue that the proposed solutions are contingent upon clarifying the values underlying future healthcare systems.

Before and beyond trust: reliance in medical AI.

Artificial intelligence (AI) is changing healthcare and the practice of medicine as data-driven science and machine-learning technologies, in particular, are contributing to a variety of medical and clinical tasks. Such advancements have also raised many questions, especially about public trust. As a response to these concerns there has been a concentrated effort from public bodies, policy-makers and technology companies leading the way in AI to address what is identified as a "public trust deficit". This paper argues that a focus on trust as the basis upon which a relationship between this new technology and the public is built is, at best, ineffective, at worst, inappropriate or even dangerous, as it diverts attention from what is actually needed to actively warrant trust. Instead of agonising about how to facilitate trust, a type of relationship which can leave those trusting vulnerable and exposed, we argue that efforts should be focused on the difficult and dynamic process of ensuring reliance underwritten by strong legal and regulatory frameworks. From there, trust could emerge but not merely as a means to an end. Instead, as something to work in practice towards; that is, the deserved result of an ongoing ethical relationship where there is the appropriate, enforceable and reliable regulatory infrastructure in place for problems, challenges and power asymmetries to be continuously accounted for and appropriately redressed.

Pursuing impact in research: towards an ethical approach.

BACKGROUND: Research proactively and deliberately aims to bring about specific changes to how societies function and individual lives fare. However, in the ever-expanding field of ethical regulations and guidance for researchers, one ethical consideration seems to have passed under the radar: How should researchers act when pursuing actual, societal changes based on their academic work? MAIN TEXT: When researchers engage in the process of bringing about societal impact to tackle local or global challenges important concerns arise: cultural, social and political values and institutions can be put at risk, transformed or even hampered if researchers lack awareness of how their 'acting to impact' influences the social world. With today's strong focus on research impacts, addressing such ethical challenges has become urgent within in all fields of research involved in finding solutions to the challenges societies are facing. Due to the overall goal of doing something good that is often inherent in ethical approaches, boundaries to researchers' impact of something good is neither obvious, nor easy to detect. We suggest that it is time for the field of bioethics to explore normative boundaries for researchers' pursuit of impact and to consider, in detail, the ethical obligations that ought to shape this process, and we provide a four-step framework of fair conditions for such an approach. Our suggested approach within this field can be useful for other fields of research as well. CONCLUSION: With this paper, we draw attention to how the transition from pursuing impact within the Academy to trying to initiate and achieve impact beyond the Academy ought to be configured, and the ethical challenges inherent in this transition. We suggest a stepwise strategy to identify, discuss and constitute consensus-based boundaries to this academic activity. This strategy calls for efforts from a multi-disciplinary team of researchers, advisors from the humanities and social sciences, as well as discussants from funding institutions, ethical committees, politics and the society in general. Such efforts should be able to offer new and useful assistance to researchers, as well as research funding agencies, in choosing ethically acceptable, impact-pursuing projects.

"I don't think people are ready to trust these algorithms at face value": trust and the use of machine learning algorithms in the diagnosis of rare disease.

BACKGROUND: As the use of AI becomes more pervasive, and computerised systems are used in clinical decision-making, the role of trust in, and the trustworthiness of, AI tools will need to be addressed. Using the case of computational phenotyping to support the diagnosis of rare disease in dysmorphology, this paper explores under what conditions we could place trust in medical AI tools, which employ machine learning. METHODS: Semi-structured qualitative interviews (n = 20) with stakeholders (clinical geneticists, data scientists, bioinformaticians, industry and patient support group spokespersons) who design and/or work with computational phenotyping (CP) systems. The method of constant comparison was used to analyse the interview data. RESULTS: Interviewees emphasized the importance of establishing trust in the use of CP technology in identifying rare diseases. Trust was formulated in two interrelated ways in these data. First, interviewees talked about the importance of using CP tools within the context of a trust relationship; arguing that patients will need to trust clinicians who use AI tools and that clinicians will need to trust AI developers, if they are to adopt this technology. Second, they described a need to establish trust in the technology itself, or in the knowledge it provides-epistemic trust. Interviewees suggested CP tools used for the diagnosis of rare diseases might be perceived as more trustworthy if the user is able to vouchsafe for the technology's reliability and accuracy and the person using/developing them is trusted. CONCLUSION: This study suggests we need to take deliberate and meticulous steps to design reliable or confidence-worthy AI systems for use in healthcare. In addition, we need to devise reliable or confidence-worthy processes that would give rise to reliable systems; these could take the form of RCTs and/or systems of accountability transparency and responsibility that would signify the epistemic trustworthiness of these tools. words 294.

Taking it to the bank: the ethical management of individual findings arising in secondary research.

A rapidly growing proportion of health research uses 'secondary data': data used for purposes other than those for which it was originally collected. Do researchers using secondary data have an obligation to disclose individual research findings to participants? While the importance of this question has been duly recognised in the context of primary research (ie, where data are collected from participants directly), it remains largely unexamined in the context of research using secondary data. In this paper, we critically examine the arguments for a moral obligation to disclose individual research findings in the context of primary research, to determine if they can be applied to secondary research. We conclude that they cannot. We then propose that the nature of the relationship between researchers and participants is what gives rise to particular moral obligations, including the obligation to disclose individual results. We argue that the relationship between researchers and participants in secondary research does not generate an obligation to disclose. However, we also argue that the biobanks or data archives which collect and provide access to secondary data may have such an obligation, depending on the nature of the relationship they establish with participants.

Artificial intelligence and the ongoing need for empathy, compassion and trust in healthcare.

Empathy, compassion and trust are fundamental values of a patient-centred, relational model of health care. In recent years, the quest for greater efficiency in health care, including economic efficiency, has often resulted in the side-lining of these values, making it difficult for health-care professionals to incorporate them in practice. Artificial intelligence is increasingly being used in health care. This technology promises greater efficiency and more free time for health-care professionals to focus on the human side of care, including fostering trust relationships and engaging with patients with empathy and compassion. This article considers the vision of efficient, empathetic and trustworthy health care put forward by the proponents of artificial intelligence. The paper suggests that artificial intelligence has the potential to fundamentally alter the way in which empathy, compassion and trust are currently regarded and practised in health care. Moving forward, it is important to re-evaluate whether and how these values could be incorporated and practised within a health-care system where artificial intelligence is increasingly used. Most importantly, society needs to re-examine what kind of health care it ought to promote.

L'empathie, la compassion et la confiance sont des valeurs fondamentales d'un modèle de soins de santé centré sur les relations avec le patient. Mais ces dernières années, la quête d'efficacité dans le secteur, y compris au niveau économique, a souvent relégué ces valeurs au second plan et les professionnels de la santé ont donc eu du mal à les intégrer à leur pratique. De son côté, l'intelligence artificielle gagne en importance. Cette technologie devrait accroître l'efficacité tout en libérant du temps pour les professionnels de la santé, qui pourront ainsi se concentrer sur l'aspect humain des soins, notamment en établissant une relation de confiance et en faisant preuve d'empathie et de compassion envers les patients. Le présent article s'intéresse à l'idée d'un système de soins de santé efficace, qui repose sur l'empathie et la confiance, et à laquelle adhèrent les adeptes de l'intelligence artificielle. Il suggère que l'intelligence artificielle a le potentiel nécessaire pour transformer radicalement la manière dont l'empathie, la compassion et la confiance sont considérées et appliquées aujourd'hui dans le secteur de la santé. À l'avenir, il est essentiel de réexaminer l'importance de ces valeurs et la façon dont elles pourraient être incorporées et mises en œuvre dans un système de santé où l'intelligence artificielle devient peu à peu incontournable. Et surtout, la société a besoin de se demander quel modèle de soins de santé elle souhaite promouvoir.

La empatía, la compasión y la confianza son valores fundamentales de un modelo relacional de atención sanitaria centrado en el paciente. En los últimos años, la búsqueda de una mayor eficiencia en la atención sanitaria, incluida la eficiencia económica, ha dado lugar con frecuencia a que estos valores se vean relegados a un segundo plano, lo que dificulta que los profesionales sanitarios los incorporen en la práctica. La inteligencia artificial se utiliza cada vez más en la atención sanitaria. Esta tecnología promete una mayor eficiencia y más tiempo libre para que los profesionales sanitarios se centren en el lado humano de la atención, lo que incluye el fomento de las relaciones de confianza y el trato a los pacientes con empatía y compasión. En este artículo se examina la visión de una atención sanitaria eficiente, empática y confiable que proponen los defensores de la inteligencia artificial. El artículo sugiere que la inteligencia artificial tiene el potencial de alterar fundamentalmente la forma en que la empatía, la compasión y la confianza se consideran y practican actualmente en la atención sanitaria. Para avanzar, es importante volver a evaluar si dichos valores se podrían incorporar y practicar en un sistema de atención sanitaria en el que se utiliza cada vez más la inteligencia artificial, y de qué manera. Lo más importante es que la sociedad debe reconsiderar qué tipo de atención sanitaria debe promover.

The need for empathetic healthcare systems.

Medicine is not merely a job that requires technical expertise, but a profession concerned with making the best decisions and recommendations with reference to, and in consultation with, the patient. This means that the skill set required for healthcare professionals in order to provide good care is a combination of scientific knowledge, technical aptitude, and affective qualities or virtues such as compassion and empathy.

Sharing whilst caring: solidarity and public trust in a data-driven healthcare system.

BACKGROUND: In the UK, the solidaristic character of the NHS makes it one of the most trusted public institutions. In recent years, the introduction of data-driven technologies in healthcare has opened up the space for collaborations with private digital companies seeking access to patient data. However, these collaborations appear to challenge the public's trust in the. MAIN TEXT: In this paper we explore how the opening of the healthcare sector to private digital companies challenges the existing social contract and the NHS's solidaristic character, and impacts on public trust. We start by critically discussing different examples of partnerships between the NHS and private companies that collect and use data. We then analyse the relationship between trust and solidarity, and investigate how this relationship changes in the context of digital companies entering the healthcare system. Finally, we show ways for the NHS to maintain public trust by putting in place a solidarity grounded partnership model with companies seeking to access patient data. Such a model would need to serve collective interests through, for example, securing preferential access to goods and services, providing health benefits, and monitoring data access. CONCLUSION: A solidarity grounded partnership model will help establish a social contract or licence that responds to the public's expectations and to principles of a solidaristic healthcare system.

The role of trust in global health research collaborations.

Collaborations in global health research are on the rise because they enhance productivity, facilitate capacity building, accelerate output and make tackling big, multifactorial research questions possible. In this paper, I examine the concepts of trust and reliance in scientific collaborations in general, but also in the particular context of collaborations in global health research between high-income countries and low-and-middle income countries (LMIC). I propose and defend the argument that given the particular characteristics of collaborations and demands of trust relationships, reliance is a better relational mode for successful collaborations. Although reliance can be difficult to establish in situations where asymmetry of power exists, trust should not be the only relational mode available to LMIC researchers because of the type of vulnerability it introduces to the relationship. I conclude that the promotion of good collaborations requires addressing the power imbalances between partners, and establishing an even playing field in global health research.

Empathy and Efficiency in Healthcare at Times of Austerity.

Efficiency is an important value for all publicly funded healthcare systems. Limited resources need to be used prudently and wisely in order to ensure best possible outcomes and waste avoidance. Since 2010, the drive for efficiency, in the UK, has acquired a new impetus, as the country embarked on an 'age of austerity' purportedly to balance its books and reduce national deficit. Although the NHS did not suffer any direct budget cuts, the austerity policies imposed on the welfare system, including social and mental healthcare, have had a direct and detrimental impact on the healthcare service. This paper draws from a qualitative study conducted in three A&E Departments in England to explore the effects of austerity policies on the everyday experiences of doctors and nurses working in Emergency Departments. It discusses the operationalisation of efficiency in A&E, in a climate of austerity, and its effects on the experiences and practices of healthcare professionals. It uses the empirical data as a springboard to highlight the role of structures and regulations, in this case targets and protocols, in how core healthcare ethical values, such as empathy, are exercised in practice. It provides an analysis of the normative role structures and regulations can play on the perception and practice of professional duties and obligations in healthcare.

Trust me, I'm a researcher!: The role of trust in biomedical research.

In biomedical research lack of trust is seen as a great threat that can severely jeopardise the whole biomedical research enterprise. Practices, such as informed consent, and also the administrative and regulatory oversight of research in the form of research ethics committees and Institutional Review Boards, are established to ensure the protection of future research subjects and, at the same time, restore public trust in biomedical research. Empirical research also testifies to the role of trust as one of the decisive factors in research participation and lack of trust as a barrier for consenting to research. However, what is often missing is a clear definition of trust. This paper seeks to address this gap. It starts with a conceptual analysis of the term trust. It compares trust with two other related terms, those of reliance and trustworthiness, and offers a defence of Baier's attribute of 'good will' a basic characteristic of trust. It, then, proceeds to consider trust in the context of biomedical research by examining two questions: First, is trust necessary in biomedical research?; and second, do increases in regulatory oversight of biomedical research also increase trust in the field? This paper argues that regulatory oversight is important for increasing reliance in biomedical research, but it does not improve trust, which remains important for biomedical research. It finishes by pointing at professional integrity as a way of promoting trust and trustworthiness in this field.

"You have to keep fighting": maintaining healthcare services and professionalism on the frontline of austerity in Greece.

BACKGROUND: Greece has been severely affected by the 2008 global economic crisis and its health system was, and still is, among the national institutions most shaped by its effects. METHODS: In 2014, this qualitative study examined these changes through in-depth interviews with 22 frontline healthcare professionals in five different locations in mainland Greece. These interviews with nurses, doctors and pharmacists explored perceptions of austerity and how ideas of professionalism were challenged and revised by these measures. RESULTS: Participants reported working conditions characterised by dramatic increases in public hospital admissions alongside decreases in personnel, consumables, materials, and also many hospital closures. Many drew on analogies of war and fighting to describe the effects of healthcare reforms on their working lives and professional conduct. Despite accounts of deteriorating conditions and numerous challenges, healthcare professionals presented themselves as making every effort to meet patients' needs, while battling to resist guidelines which they perceived diminished their roles to production-line operatives. CONCLUSIONS: Participants considered it their duty to defend their professional ethos and serve patients without compromising standards, even if this meant liberal interpretation and implementation of regulations. These professionals regarded themselves on the frontline of healthcare provision but also the frontline defence in a war on their professional standards from austerity.

Making space for empathy: supporting doctors in the emotional labour of clinical care.

BACKGROUND: The academic and medical literature highlights the positive effects of empathy for patient care. Yet, very little attention has been given to the impact of the requirement for empathy on the physicians themselves and on their emotional wellbeing. DISCUSSION: The medical profession requires doctors to be both clinically competent and empathetic towards the patients. In practice, accommodating both requirements can be difficult for physicians. The image of the technically skilful, rational, and emotionally detached doctor dominates the profession, and inhibits physicians from engaging emotionally with their patients and their own feelings, which forms the basis for empathy. This inhibition has a negative impact not only on the patients but also on the physicians. The expression of emotions in medical practice is perceived as unprofessional and many doctors learn to supress and ignore their feelings. When facing stressful situations, these physicians are more likely to suffer from depression and burnout than those who engage with and reflect on their feelings. Physicians should be supported in their emotional work, which will help them develop empathy. Methods could include questionnaires that aid self-reflection, and discussion groups with peers and supervisors on emotional experiences. Yet, in order for these methods to work, the negative image associated with the expression of emotions should be questioned. Also, the work conditions of physicians should improve to allow them to make use of these tools. Empathy should not only be expected from doctors but should be actively promoted, assisted and cultivated in the medical profession.

The Concept of Dignity and Its Use in End-of-Life Debates in England and France.

Dignity is one of the most controversial and yet commonly used terms in debates regarding end-of-life issues. The term "dignity" can take various meanings. For example, it can be used to denote the respect owed to an individual person, or to signify the intrinsic value of humankind as a whole. These two different understandings of dignity inevitably lead to different approaches to end-of-life decisionmaking. This article explores the meaning of the term "dignity" in two European countries, England and France. Our analysis compares public debates and legislation on end-of-life-related issues in these two countries. We argue that in England dignity is most commonly understood as respect for individual autonomy, whereas in France dignity usually signifies respect for humanity as a whole. We demonstrate that the difference in the conceptualization of the term leads to different ethical, and hence legal and practical, approaches to end-of-life issues and vulnerable patients. Our particular focus is on (1) withdrawing/withholding life-sustaining treatment, (2) respect for patient preferences, and (3) assistance in dying. Given the difference in the understanding of dignity, and the underlying philosophical approaches, it appears that there is still a long way to go before we can establish common guidelines on end-of-life decisions across Europe and beyond. However, clarifying the use of the term "dignity" in different discussions around Europe could hopefully facilitate this endeavor.

Genetic determinants of anti-malarial acquired immunity in a large multi-centre study.

BACKGROUND: Many studies report associations between human genetic factors and immunity to malaria but few have been reliably replicated. These studies are usually country-specific, use small sample sizes and are not directly comparable due to differences in methodologies. This study brings together samples and data collected from multiple sites across Africa and Asia to use standardized methods to look for consistent genetic effects on anti-malarial antibody levels. METHODS: Sera, DNA samples and clinical data were collected from 13,299 individuals from ten sites in Senegal, Mali, Burkina Faso, Sudan, Kenya, Tanzania, and Sri Lanka using standardized methods. DNA was extracted and typed for 202 Single Nucleotide Polymorphisms with known associations to malaria or antibody production, and antibody levels to four clinical grade malarial antigens [AMA1, MSP1, MSP2, and (NANP)4] plus total IgE were measured by ELISA techniques. Regression models were used to investigate the associations of clinical and genetic factors with antibody levels. RESULTS: Malaria infection increased levels of antibodies to malaria antigens and, as expected, stable predictors of anti-malarial antibody levels included age, seasonality, location, and ethnicity. Correlations between antibodies to blood-stage antigens AMA1, MSP1 and MSP2 were higher between themselves than with antibodies to the (NANP)4 epitope of the pre-erythrocytic circumsporozoite protein, while there was little or no correlation with total IgE levels. Individuals with sickle cell trait had significantly lower antibody levels to all blood-stage antigens, and recessive homozygotes for CD36 (rs321198) had significantly lower anti-malarial antibody levels to MSP2. CONCLUSION: Although the most significant finding with a consistent effect across sites was for sickle cell trait, its effect is likely to be via reducing a microscopically positive parasitaemia rather than directly on antibody levels. However, this study does demonstrate a framework for the feasibility of combining data from sites with heterogeneous malaria transmission levels across Africa and Asia with which to explore genetic effects on anti-malarial immunity.