The recent advancements in artificial intelligence (AI), and data science more broadly, have led to a proliferation of new methods and tools, such as machine learning (ML), that are used in all kinds of scientific research, from biomedical research through to environmental and education research. Research ethics review bodies are increasingly required to review AI research protocols that cover these different fields of enquiry. Questions have been raised regarding the appropriateness of existing ethics governance principles, practices, and processes to deal with the ethical challenges that AI and data science are introducing to research. Universities and research institutions across the world are trying to understand how to translate and practically implement broad AI ethical principles into research ethics governance guidelines and processes. In this article, we report on an expert stakeholders’ workshop organised at the University of Oxford as part of the process of reviewing its ethics governance for AI research. We describe the workshop and present the reflections and recommendations that emerged from it. The aim of the article is to share the approach taken by the University of Oxford CUREC in reviewing its ethics governance processes, and the insights gained with the broader research community, as a way of contributing to this scarce body of literature, facilitating further dialogue, promoting debate and collaboration on this important issue.

The presumption of digital biomarkers (DBMs) is that they will enable frequent and objective assessments at scale and provide real-time insights into people’s daily lives, potentially reducing in-clinic assessment frequency, and patient and clinician burden. However, their use raises several ethical challenges. While prior literature has explored ethical issues regarding the volume of data produced and related governance questions, practical research guidance remains limited. This paper addresses this gap using a case study approach from the RADAR-AD project focusing on three core ethical areas: 1) respecting participants, particularly for their deep involvement in the research process and the intensive digital data collection; 2) ensuring sustainable research impact; and 3) providing feedback of results and duty of care to participants. To promote ethical and sustainable research, the community would benefit from standardised DBM concepts, materials, and procedures, well-defined DBM regulatory approval pathways, and clear guidance on accessibility, representativeness, and accountability. Future regulations should consider the roles and responsibilities of all parties involved, including participants, carers, and bystanders.

Health research is vital to advance human well-being, but it is also a contributor to climate change and other environmental degradation. A growing bottom-up advocacy movement is engaged in developing measures (often called tools) to help researchers better understand the ways in which they can mitigate the environmental harms associated with research. While some evidence suggests benefits of using these tools, ethical and social challenges remain. These challenges include questions about: whether these tools will place undue burdens on researchers; whether the tools will be effective in supporting large-scale mitigation of environmental harm; whether using these tools to comply with mandatory requirements will divert attention away from wider discussions about what it means to conduct research in an environmentally sustainable way; and whether these tools, which have been developed in high-income countries, reinforce existing power imbalances between high- and low-income settings and/or fail to address the needs of more marginalized research communities. In this paper, we identify and describe these ethical and social issues surrounding the use of these tools. Our aim is not to discourage their use but to urge policy-makers to reflect on these challenges as they become clearer so that tools are implemented in a way that is both effective and just.

The attribution of human concepts to conversational artificial intelligence (CAI) simulating human characteristics and conversation in psychotherapeutic settings presents significant conceptual and normative challenges. First, this article analyzes the concept of epistemic trust by identifying its problematic conditions when attributed to CAI, arguing for conceptual shift. We propose a conceptual, visual tool to navigate this shift. Second, three conceptualizations of AI are analyzed to understand their influence on the interpretation and evaluation of conceptual shift of epistemic trust and associated risks. We contrast two common AI conceptualizations from literature: a dichotomic account, distinguishing between AI's real and simulated abilities, and a relational account. Finally, we propose a novel approach: conceptualizing AI as a fictional character to combine their strengths, arguing for shifting focus from merely simulating human abilities to addressing CAI's actual strengths and weaknesses. The article sheds light on underlying theoretical assumptions that influence the ethical analysis of CAI.

The COVID-19 pandemic has represented the first global health emergency to be tackled through widespread data collection via a broad array of digital health technologies. Throughout Europe, data infrastructures for the acquisition, processing, and management of COVID-19 data were either implemented ex novo or "repurposed" towards this end. Analysing and comparing these data practices may hold great value to the upcoming European Health Data Space (EHDS) implementation. This study investigates the implementation of COVID-19 data infrastructures in four European countries - Italy, Sweden, Denmark, and England - to highlight challenges related to technical, ethical, and legal aspects of secondary uses of health-related data, particularly given the implementation of the EHDS. The data infrastructures included in the study reveal profound differences in design and data access practices, partly owing to the social contexts in which they were established. Challenges for data-sharing and integration include fragmentation of standards and requirements, ethical concerns about access by corporate actors to publicly collected datasets, and lack of robust legal bases. Investigating such infrastructures is crucial to probe challenges in data sharing practices within the European context and represents a revealing test case to anticipate opportunities and challenges in aligning current technical and legal standards with EHDS' requirements.

Digital biomarkers (DBM) explain and/or predict health outcomes by taking advantage of the advancements in digital technologies and analytics. However, while DBMs offer promising opportunities for research by enabling frequent, remote, real-time and objective assessments at scale they also raise ethical challenges. Despite growing recognition of these issues, practical guidelines remain scarce. To bridge this gap, we adopt a case study approach by drawing on the ethical challenges encountered in the RADAR-AD (Remote Assessment of Disease and Relapse – Alzheimer's Disease) project. RADAR-AD is a cross-sectional observational study ( N  = 237) aiming to find and validate remote monitoring technologies to assess cognitive and functional decline in AD. For up to eight weeks, we employed a range of digital technologies, including smartphone apps, wearables and at-home sensors. This case study addresses two key areas surrounding 1) the ensurance of respect for participants across the research process, and 2) feedback of results and sustainability. By reflecting on the lessons learned in RADAR-AD, we provide practical recommendations to enhance ethical conduct in DBM research. The first key area suggests a participatory approach by exploring participants’ needs and concerns in focus groups and involving a patient advisory board (PAB): 1) Informed consent: Explaining the complexities of digital data collection/analysis/storage while engaging large numbers of participants; 2) Burden: Balancing privacy, burden and accessibility during long-term data collection and offering protocol flexibility; 3) Assistance without being too controlling: Combining phone calls with remote technical checks. The second key area focuses on 1) Feedback of results: Providing consumer-grade feedback improves adherence and sense of security and reduces risk of harm; 2) Sustainability: Increasing translation from research to clinical implications by seeking regulatory advice, taking successful results forward to explore in future projects, and sharing data to promote further research. However, contributing tangible results to the healthcare system even after research funding has ended remains a significant challenge. The RADAR-AD study provides an exemplary case study highlighting key challenges associated with DBM research and offering valuable insights into ethical considerations that should accompany DBM research from study conception to sustainability efforts. Acknowledgment : The RADAR-AD project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 806999. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA and Software AG. See www.imi.europa.eu for more details. This communication reflects the views of the RADAR-AD consortium and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein.

BACKGROUND:Digital technologies, such as wearable devices and smartphone applications (apps), can enable the decentralisation of clinical trials by measuring endpoints in people's chosen locations rather than in traditional clinical settings. Digital endpoints can allow high-frequency and sensitive measurements of health outcomes compared to visit-based endpoints which provide an episodic snapshot of a person's health. However, there are underexplored challenges in this emerging space that require interdisciplinary and cross-sector collaboration. A multi-stakeholder Knowledge Exchange event was organised to facilitate conversations across silos within this research ecosystem. METHODS:A survey was sent to an initial list of stakeholders to identify potential discussion topics. Additional stakeholders were identified through iterative discussions on perspectives that needed representation. Co-design meetings with attendees were held to discuss the scope, format and ethos of the event. The event itself featured a cross-disciplinary selection of talks, a panel discussion, small-group discussions facilitated via a rolling seating plan and audience participation via Slido. A transcript was generated from the day, which, together with the output from Slido, provided a record of the day's discussions. Finally, meetings were held following the event to identify the key challenges for digital endpoints which emerged and reflections and recommendations for dissemination. RESULTS:Several challenges for digital endpoints were identified in the following areas: patient adherence and acceptability; algorithms and software for devices; design, analysis and conduct of clinical trials with digital endpoints; the environmental impact of digital endpoints; and the need for ongoing ethical support. Learnings taken for next generation events include the need to include additional stakeholder perspectives, such as those of funders and regulators, and the need for additional resources and facilitation to allow patient and public contributors to engage meaningfully during the event. CONCLUSIONS:The event emphasised the importance of consortium building and highlighted the critical role that collaborative, multi-disciplinary, and cross-sector efforts play in driving innovation in research design and strategic partnership building moving forward. This necessitates enhanced recognition by funders to support multi-stakeholder projects with patient involvement, standardised terminology, and the utilisation of open-source software.

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This paper draws on the ethics of care to investigate how citizens grappled with ethical tensions in the mundane practice of grocery shopping at the height of the Covid-19 pandemic. We use this case to address the broader question of what it means ‘to care’ in the context of a crisis. Based on a qualitative longitudinal cross-country interview study, we find that the pandemic transformed ordinary shopping spaces into places fraught with a sense of fear and vulnerability. Being forced to face one’s own vulnerability created an opportunity for individuals to relate to one another as significant others through a sense of “response-ability”, or the capacity of people to respond to ethical demands through situated ethical reasoning. We argue for a practical ethos of care in which seemingly small decisions such as how often to go shopping and how much to buy of a particular product serve as a means to relate to both specified and generalized others—and through this, ‘care with’ society. Our study contributes to displacing the continuing prevalence of an abstract and prescriptive morality in consumption ethics with a situated and affective politics of care. This vocabulary seems better suited to reflect on the myriad of small and unheroic care acts in times of crisis and beyond.

Innovations and efficiencies in digital technology have lately been depicted as paramount in the green transition to enable the reduction of greenhouse gas emissions, both in the information and communication technology (ICT) sector and the wider economy. This, however, fails to adequately account for rebound effects that can offset emission savings and, in the worst case, increase emissions. In this perspective, we draw on a transdisciplinary workshop with 19 experts from carbon accounting, digital sustainability research, ethics, sociology, public policy, and sustainable business to expose the challenges of addressing rebound effects in digital innovation processes and associated policy. We utilize a responsible innovation approach to uncover potential ways forward for incorporating rebound effects in these domains, concluding that addressing ICT-related rebound effects ultimately requires a shift from an ICT efficiency-centered perspective to a "systems thinking" model, which aims to understand efficiency as one solution among others that requires constraints on emissions for ICT environmental savings to be realized.

Calls for solidarity have been an ubiquitous feature in the response to the COVID-19 pandemic. However, we know little about how people have thought of and practised solidarity in their everyday lives since the beginning of the pandemic. What role does solidarity play in people’s lives, how does it relate to COVID-19 public health measures and how has it changed in different phases of the pandemic? Situated within the medical humanities at the intersection of philosophy, bioethics, social sciences and policy studies, this article explores how the practice-based understanding of solidarity formulated by Prainsack and Buyx helps shed light on these questions. Drawing on 643 qualitative interviews carried out in two phases (April–May 2020 and October 2020) in nine European countries (Austria, Belgium, France, Germany, Ireland, Italy, The Netherlands, German-speaking Switzerland and the UK), the data show that interpersonal acts of solidarity are important, but that they are not sustainable without consistent support at the institutional level. As the pandemic progressed, respondents expressed a longing for more institutionalised forms of solidarity. We argue that the medical humanities have much to gain from directing their attention to individual health issues, and to collective experiences of health or illness. The analysis of experiences through a collective lens such as solidarity offers unique insights to understandings of the individual and the collective. We propose three essential advances for research in the medical humanities that can help uncover collective experiences of disease and health crises: (1) an empirical and practice-oriented approach alongside more normative approaches; (2) the confidence to make recommendations for practice and policymaking and (3) the pursuit of cross-national and multidisciplinary research collaborations.

[This corrects the article DOI: 10.1371/journal.pone.0285807.].

Throughout the COVID-19 pandemic, the concept of solidarity has been invoked frequently. Much interest has centred around how citizens and communities support one another during times of uncertainty. Yet, empirical research which accounts and understands citizen’s views on pandemic solidarity, or their actual practices has remained limited. Drawing upon the analysis of data from 35 qualitative interviews, this article investigates how residents in England and Scotland enacted, understood, or criticised (the lack of) solidarity during the first national lockdown in the United Kingdom in April 2020—at a time when media celebrated solidarity as being at an all-time high. It finds that although solidarity was practiced by some people, the perceived lack of solidarity was just as pronounced. We conclude that despite frequent mobilisations of solidarity by policy makers and other public actors, actual practices of solidarity are poorly understood—despite the importance of solidarity for public health and policy.

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.

The sudden and dramatic advent of the COVID-19 pandemic led to urgent demands for timely, relevant, yet rigorous research. This paper discusses the origin, design, and execution of the SolPan research commons, a large-scale, international, comparative, qualitative research project that sought to respond to the need for knowledge among researchers and policymakers in times of crisis. The form of organization as a research commons is characterized by an underlying solidaristic attitude of its members and its intrinsic organizational features in which research data and knowledge in the study is shared and jointly owned. As such, the project is peer-governed, rooted in (idealist) social values of academia, and aims at providing tools and benefits for its members. In this paper, we discuss challenges and solutions for qualitative studies that seek to operate as research commons.

Introduction: There has been no work that identifies the hidden or implicit normative assumptions on which participants base their views during the COVID-19 pandemic, and their reasoning and how they reach moral or ethical judgements. Our analysis focused on participants' moral values, ethical reasoning and normative positions around the transmission of SARS-CoV-2.Methods: We analyzed data from 177 semi-structured interviews across five European countries (Germany, Ireland, Italy, Switzerland and the United Kingdom) conducted in April 2020.Results: Findings are structured in four themes: ethical contention in the context of normative uncertainty; patterns of ethical deliberation when contemplating restrictions and measures to reduce viral transmission; moral judgements regarding "good" and "bad" people; using existing structures of meaning for moral reasoning and ethical judgement.Discussion: Moral tools are an integral part of people's reaction to and experience of a pandemic. 'Moral preparedness' for the next phases of this pandemic and for future pandemics will require an understanding of the moral values and normative concepts citizens use in their own decision-making. Three important elements of this preparedness are: conceptual clarity over what responsibility or respect mean in practice; better understanding of collective mindsets and how to encourage them; and a situated, rather than universalist, approach to the development of normative standards.

This paper explores ethical debates associated with the UK COVID-19 contact tracing app that occurred in the public news media and broader public policy, and in doing so, takes ethics debate as an object for sociological study. The research question was: how did UK national newspaper news articles and grey literature frame the ethical issues about the app, and how did stakeholders associated with the development and/or governance of the app reflect on this? We examined the predominance of different ethical issues in news articles and grey literature, and triangulated this using stakeholder interview data. Findings illustrate how news articles exceptionalised ethical debate around the app compared to the way they portrayed ethical issues relating to ‘manual’ contact tracing. They also narrowed the debate around specific privacy concerns. This was reflected in the grey literature, and interviewees perceived this to have emerged from a ‘privacy lobby’. We discuss the findings, and argue that this limited public ethics narrative masked broader ethical issues.

The concept of ‘digital phenotyping’ was originally developed by researchers in the mental health field, but it has travelled to other disciplines and areas. This commentary draws upon our experiences of working in two scientific projects that are based at the University of Oxford’s Big Data Institute – The RADAR-AD project and The Minerva Initiative – which are developing algorithmic phenotyping technologies. We describe and analyse the concepts of digital biomarkers and computational phenotyping that underlie these projects, explain how they are linked to other research in digital phenotyping and compare and contrast some of their epistemological and ethical implications. In particular, we argue that the phenotyping paradigm in both projects is grounded on an assumption of ‘objectivity’ that is articulated in different ways depending on the role that is given to the computational/digital tools. Using the concept of ‘affordance’, we show how specific functionalities relate to potential uses and social implications of these technologies and argue that it is important to distinguish among them as the concept of digital phenotyping is increasingly being used with a variety of meanings.