Data sharing – broadly defined as the exchange of health-related data among multiple controllers and processors – has gained increased relevance in the health sciences over recent years as the need and demand for collaboration has increased. This includes data obtained through healthcare provisions, clinical trials, observational studies, public health surveillance programs, and other data collection methods. The practice of data sharing presents several notable challenges, however. Compliance with a complex and dynamic regulatory framework is (...) essential, with the General Data Protection Regulation being a prominent example in a European context. Recent regulatory developments related to clinical trial transparency, trade secrecy, data access, AI training data, and health data spaces further contribute to the difficulties. Simultaneously, government initiatives often encourage scientists to embrace principles of “open data” and “open innovation.” The variety of regulations in this domain has the potential to impede widespread data sharing and hinder innovation. This edited volume, therefore, compiles comparative case studies authored by leading scholars from diverse disciplines and jurisdictions. The book aims to outline the legal complexities of data sharing. By examining real-world scenarios from diverse disciplines and a global perspective, it explores the normative, policy, and ethical dilemmas that surround data sharing in the health sciences today. Chapter Patient Perspectives on Data Sharing, Chapter Supplementary Measures and Appropriate Safeguards for International Transfers of Health Data after Schrems II are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. (shrink)

Big data, big impact -- Values and actions -- Current practices -- Aligning values and actions.

The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of (...) the ethical implications of Big Data lags behind. In order to bridge such a gap, this article systematically and comprehensively analyses academic literature concerning the ethical implications of Big Data, providing a watershed for future ethical investigations and regulations. Particular attention is paid to biomedical Big Data due to the inherent sensitivity of medical information. By means of a meta-analysis of the literature, a thematic narrative is provided to guide ethicists, data scientists, regulators and other stakeholders through what is already known or hypothesised about the ethical risks of this emerging and innovative phenomenon. Five key areas of concern are identified: informed consent, privacy, ownership, epistemology and objectivity, and ‘Big Data Divides’ created between those who have or lack the necessary resources to analyse increasingly large datasets. Critical gaps in the treatment of these themes are identified with suggestions for future research. Six additional areas of concern are then suggested which, although related have not yet attracted extensive debate in the existing literature. It is argued that they will require much closer scrutiny in the immediate future: the dangers of ignoring group-level ethical harms; the importance of epistemology in assessing the ethics of Big Data; the changing nature of fiduciary relationships that become increasingly data saturated; the need to distinguish between ‘academic’ and ‘commercial’ Big Data practices in terms of potential harm to data subjects; future problems with ownership of intellectual property generated from analysis of aggregated datasets; and the difficulty of providing meaningful access rights to individual data subjects that lack necessary resources. Considered together, these eleven themes provide a thorough critical framework to guide ethical assessment and governance of emerging Big Data practices. (shrink)

Compartmentalizing our distinct personal identities is increasingly difficult in big data reality. Pictures of the person we were on past vacations resurface in employers’ Google searches; LinkedIn which exhibits our income level is increasingly used as a dating web site. Whether on vacation, at work, or seeking romance, our digital selves stream together. One result is that a perennial ethical question about personal identity has spilled out of philosophy departments and into the real world. Ought we possess one, unified (...) identity that coherently integrates the various aspects of our lives, or, incarnate deeply distinct selves suited to different occasions and contexts? At bottom, are we one, or many? The question is not only palpable today, but also urgent because if a decision is not made by us, the forces of big data and surveillance capitalism will make it for us by compelling unity. Speaking in favor of the big data tendency, Facebook’s Mark Zuckerberg promotes the ethics of an integrated identity, a single version of selfhood maintained across diverse contexts and human relationships. This essay goes in the other direction by sketching two ethical frameworks arranged to defend our compartmentalized identities, which amounts to promoting the dis-integration of our selves. One framework connects with natural law, the other with language, and both aim to create a sense of selfhood that breaks away from its own past, and from the unifying powers of big data technology. (shrink)

This open access book presents an ethical approach to utilizing personal medical data. It features essays that combine academic argument with practical application of ethical principles. The contributors are experts in ethics and law. They address the challenges in the re-use of medical data of the deceased on a voluntary basis. This pioneering study looks at the many factors involved when individuals and organizations wish to share information for research, policy-making, and humanitarian purposes. Today, it is easy (...) to donate blood or even organs, but it is virtually impossible to donate one’s own medical data. This is seen as ethically unacceptable. Yet, data donation can greatly benefit the welfare of our societies. This collection provides timely interdisciplinary research on biomedical big data. Topics include the ethics of data donation, the legal and regulatory challenges, and the current and future collaborations. Readers will learn about the ethical and regulatory challenges associated with medical data donations. They will also better understand the special nature of using deceased data for research purposes with regard to ethical principles of autonomy, beneficence, and justice. In addition, the contributors identify the key governance issues of such a scheme. The essays also look at what we can learn in terms of best practice from existing medical data schemes. (shrink)

Modern health data practices come with many practical uncertainties. In this paper, I argue that data subjects’ trust in the institutions and organizations that control their data, and their ability to know their own moral obligations in relation to their data, are undermined by significant uncertainties regarding the what, how, and who of mass data collection and analysis. I conclude by considering how proposals for managing situations of high uncertainty might be applied to this problem. (...) These emphasize increasing organizational flexibility, knowledge, and capacity, and reducing hazard. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Convention for Protection of Human Rights and Dignity of the Human Being with Regard to the Application of Biology and Biomedicine: Convention on Human Rights and BiomedicineCouncil of EuropePreambleThe Member States of the Council of Europe, the other States and the European Community signatories hereto,Bearing in mind the Universal Declaration of Human Rights proclaimed by the General Assembly of the United Nations on 10 December 1948;Bearing in mind the (...) Convention for the Protection of Human Rights and Fundamental Freedoms of 4 November 1950;Bearing in mind the European Social Charter of 18 October 1961;Bearing in mind the International Covenant on Civil and Political Rights and the International Covenant on Economic, Social and Cultural Rights of 16 December 1966;Bearing in mind the Convention for the Protection of Individuals with Regard to Automatic Processing of Personal Data of 28 January 1981;Bearing also in mind the Convention on the Rights of the Child of 20 November 1989;Considering that the aim of the Council of Europe is the achievement of a greater unity between its members and that one of the methods by which that aim is to be pursued is the maintenance and further realisation of human rights and fundamental freedoms;Conscious of the accelerating developments in biology and medicine;Convinced of the need to respect the human being both as an individual and as a member of the human species and recognising the importance of ensuring the dignity of the human being; [End Page 277]Conscious that the misuse of biology and medicine may lead to acts endangering human dignity;Affirming that progress in biology and medicine should be used for the benefit of present and future generations;Stressing the need for international co-operation so that all humanity may enjoy the benefits of biology and medicine;Recognising the importance of promoting a public debate on the questions posed by the application of biology and medicine and the responses to be given thereto;Wishing to remind all members of society of their rights and responsibilities;Taking account of the work of the Parliamentary Assembly in this field, including Recommendation 1160 (1991) on the preparation of a Convention on bioethics;Resolving to take such measures as are necessary to safeguard human dignity and the fundamental rights and freedoms of the individual with regard to the application of biology and medicine;Have agreed as follows:Chapter IGeneral provisionsArticle 1. (Purpose and object)Parties to this Convention shall protect the dignity and identity of all human beings and guarantee everyone, without discrimination, respect for their integrity and other rights and fundamental freedoms with regard to the application of biology and medicine.Each Party shall take in its internal law the necessary measures to give effect to the provisions of this Convention.Article 2. (Primacy of the human being)The interests and welfare of the human being shall prevail over the sole interest of society or science.Article 3. (Equitable access to health care)Parties, taking into account health needs and available resources, shall take appropriate measures with a view to providing, within their jurisdiction, equitable access to health care of appropriate quality. [End Page 278]Article 4. (Professional standards)Any intervention in the health field, including research, must be carried out in accordance with relevant professional obligations and standards.Chapter IIConsentArticle 5. (General rule)An intervention in the health field may only be carried out after the person concerned has given free and informed consent to it.This person shall beforehand be given appropriate information as to the purpose and nature of the intervention as well as on its consequences and risks.The person concerned may freely withdraw consent at any time.Article 6. (Protection of persons not able to consent)1. Subject to Articles 17 and 20 below, an intervention may only be carried out on a person who does not have the capacity to consent, for his or her direct benefit.2. Where, according to law, a minor does not have the capacity to consent to an intervention, the intervention may only be carried out with the authorisation of his or her representative or an authority or a person or... (shrink)

This open access book presents an ethical approach to utilizing personal medical data. It features essays that combine academic argument with practical application of ethical principles. The contributors are experts in ethics and law. They address the challenges in the re-use of medical data of the deceased on a voluntary basis. This pioneering study looks at the many factors involved when individuals and organizations wish to share information for research, policy-making, and humanitarian purposes. -/- Today, it is (...) easy to donate blood or even organs, but it is virtually impossible to donate one’s own medical data. This is seen as ethically unacceptable. Yet, data donation can greatly benefit the welfare of our societies. This collection provides timely interdisciplinary research on biomedical big data. Topics include the ethics of data donation, the legal and regulatory challenges, and the current and future collaborations. -/- Readers will learn about the ethical and regulatory challenges associated with medical data donations. They will also better understand the special nature of using deceased data for research purposes with regard to ethical principles of autonomy, beneficence, and justice. In addition, the contributors identify the key governance issues of such a scheme. The essays also look at what we can learn in terms of best practice from existing medical data schemes. (shrink)

According to Facebook’s Mark Zuckerberg, big data reality means, “The days of having a different image for your co-workers and for others are coming to an end, which is good because having multiple identities represents a lack of integrity.” Two sets of questions follow. One centers on technology and asks how big data mechanisms collapse our various selves (work-self, family-self, romantic-self) into one personality. The second question set shifts from technology to ethics by asking whether we want (...) the kind of integrity that Zuckerberg lauds, and that big data technology enables. The negative response is explored by sketching three ethical conceptions of selfhood that recommend personal identity be understood as dis-integrating. The success of the strategies partially depends upon an undermining use of big data platforms. (shrink)

Data analytics and data-driven approaches in Machine Learning are now among the most hailed computing technologies in many industrial domains. One major application is predictive analytics, which is used to predict sensitive attributes, future behavior, or cost, risk and utility functions associated with target groups or individuals based on large sets of behavioral and usage data. This paper stresses the severe ethical and data protection implications of predictive analytics if it is used to predict sensitive information (...) about single individuals or treat individuals differently based on the data many unrelated individuals provided. To tackle these concerns in an applied ethics, first, the paper introduces the concept of “predictive privacy” to formulate an ethical principle protecting individuals and groups against differential treatment based on Machine Learning and Big Data analytics. Secondly, it analyses the typical data processing cycle of predictive systems to provide a step-by-step discussion of ethical implications, locating occurrences of predictive privacy violations. Thirdly, the paper sheds light on what is qualitatively new in the way predictive analytics challenges ethical principles such as human dignity and the (liberal) notion of individual privacy. These new challenges arise when predictive systems transform statistical inferences, which provide knowledge about the cohort of training data donors, into individual predictions, thereby crossing what I call the “prediction gap”. Finally, the paper summarizes that data protection in the age of predictive analytics is a collective matter as we face situations where an individual’s (or group’s) privacy is violated using dataotherindividuals provide about themselves, possibly even anonymously. (shrink)

As big data techniques become widespread in journalism, both as the subject of reporting and as newsgathering tools, the ethics of data science must inform and be informed by media ethics. This article explores emerging problems in ethical research using big data techniques. It does so using the duty-based framework advanced by W.D. Ross, who has significantly influenced both research science and media ethics. A successful framework must provide stability and flexibility. Without stability, ethical (...) precommitments will vanish as technology rapidly shifts costs. Without flexibility, traditional approaches will rapidly become obsolete in the face of technological change. The article concludes that Ross's duty-based approach both provides stability in the face of rapid technological change and flexibility to innovate to achieve the original purpose of basic ethical principles. (shrink)

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe (...) consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms. (shrink)

This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. 'Biomedical Big Data' refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can (...) be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward. (shrink)

Advances in science and technology have allowed for incredible improvements in healthcare. Additionally, the digital revolution in healthcare provides new ways of collecting and storing large volum...

The paper investigates the ethics of information transparency (henceforth transparency). It argues that transparency is not an ethical principle in itself but a pro-ethical condition for enabling or impairing other ethical practices or principles. A new definition of transparency is offered in order to take into account the dynamics of information production and the differences between data and information. It is then argued that the proposed definition provides a better understanding of what sort of information should be disclosed (...) and what sort of information should be used in order to implement and make effective the ethical practices and principles to which an organisation is committed. The concepts of “heterogeneous organisation” and “autonomous computational artefact” are further defined in order to clarify the ethical implications of the technology used in implementing information transparency. It is argued that explicit ethical designs, which describe how ethical principles are embedded into the practice of software design, would represent valuable information that could be disclosed by organisations in order to support their ethical standing. (shrink)

The practice of conducting research online is in its infancy. Consequently there is debate concerning the ethical implications of online data collection. We outline three approaches to online data collection and focus specifically on the issues of consent and anonymity of participants. We conclude that ethical issues raised when planning and implementing online data collection are no different to those raised by more traditional approaches to data collection.

The availability of diverse sources of data related to health and illness from various types of modern communication technology presents the possibility of augmenting medical knowledge, clinical care, and the patient experience. New forms of data collection and analysis will undoubtedly transform epidemiology, public health, and clinical practice, but what ethical considerations come in to play? With a view to analysing the ethical and regulatory dimensions of burgeoning forms of biomedical big data, Brent Daniel Mittelstadt and Luciano (...) Floridi have brought together thirty scholars in an edited volume that forms part of Springer’s Law, Governance and Technology book series in a collection titled The Ethics of Biomedical Big Data. With eighteen chapters partitioned into six carefully devised sections, this volume engages with core theoretical, ethical, and regulatory challenges posed by biomedical big data. (shrink)

The availability of diverse sources of data related to health and illness from various types of modern communication technology presents the possibility of augmenting medical knowledge, clinical care, and the patient experience. New forms of data collection and analysis will undoubtedly transform epidemiology, public health, and clinical practice, but what ethical considerations come in to play? With a view to analysing the ethical and regulatory dimensions of burgeoning forms of biomedical big data, Brent Daniel Mittelstadt and Luciano (...) Floridi have brought together thirty scholars in an edited volume that forms part of Springer’s Law, Governance and Technology book series in a collection titled The Ethics of Biomedical Big Data. With eighteen chapters partitioned into six carefully devised sections, this volume engages with core theoretical, ethical, and regulatory challenges posed by biomedical big data. (shrink)

Using speech act theory from the Philosophy of Language, this paper attempts to develop an ethical framework for the phenomenon of speech processing. We use the concepts of the illocutionary force and the illocutionary content of a speech act to explain the ethics of speech processing. By emphasizing the different stages involved in speech processing, we explore the distinct ethical issues that arise in relation to each stage. Input, processing, and output are the different ethically relevant stages under which (...) a spoken item or a speech navigates within the range of speech-processing modules. Employing the illocutionary force-content distinction, we specify and characterize the input-related ethical issues, the output-related ethical issues, and the processing-related ethical issues involved in speech processing. Together with illocutionary force-content distinction, we employ the data-information distinction to characterize the stage-wise ethical issues in the phenomenon of speech processing as the ethics of collecting (speech) data, the ethics of contextualizing (speech) data/information, and the ethics of releasing the con-textualized information (processed speech). Immediate ethical issues that arise from the range of speech processing modules are distinguished from distant ethical issues. We also indicate the nature of ethical issues that arise from Speaker Independent speech technologies. (shrink)

Socially responsible publishers, such as the BMJ Publishing Group, have demonstrated a commitment to health equity and working towards rectifying the structural racism that exists both in healthcare and in medical publishing.1 The commitment of academic publishers to collecting information relevant to promoting equity and diversity is important and commendable where it leads to that result.2 However, collecting sensitive demographic data is not a morally neutral activity. Rather, it carries with it both known and potential risks. Among these are (...) issues around privacy or data misuse, as well as more basic concerns about how, when or why people should be categorised in certain ways and/or prompted to conceive of themselves or their identities in certain terms.3 If such data are to be collected, therefore, their effectiveness in achieving the stated ends must have a sufficiently compelling evidence base so as to justify the various risks involved. And where possible, these risks must also be identified and minimised. As Varcoe et al 4 argue, > While most leaders and healthcare workers and some patients [in their study] envisioned potential benefits associated with having ethnicity data, these benefits were seen as largely contingent upon action being taken to [actually] ameliorate inequities. Overwhelmingly, however, leaders from ethno-cultural communities and patients of diverse identities anticipated potential harm arising both from having ethnicity data and the process of collection. The analysis illustrates that in today’s sociopolitical context, collecting ethnicity data in clinical contexts may engender considerable harm, particularly for racialized, vulnerable patients. (p1569) Varcoe et al refer to ‘ethnicity’ data, which as they note is an ambiguous concept, potentially encompassing such diverse notions as ancestry, language, religion or culture. It is also a term that is in some contexts—for example, the USA—often used interchangeably with a different, more highly charged term: ‘race’. Data …. (shrink)

Cloud computing is rapidly gaining traction in business. It offers businesses online services on demand (such as Gmail, iCloud and Salesforce) and allows them to cut costs on hardware and IT support. This is the first paper in business ethics dealing with this new technology. It analyzes the informational duties of hosting companies that own and operate cloud computing datacenters (e.g., Amazon). It considers the cloud services providers leasing ‘space in the cloud’ from hosting companies (e.g, Dropbox, Salesforce). And (...) it examines the business and private ‘clouders’ using these services. The first part of the paper argues that hosting companies, services providers and clouders have mutual informational (epistemic) obligations to provide and seek information about relevant issues such as consumer privacy, reliability of services, data mining and data ownership. The concept of interlucency is developed as an epistemic virtue governing ethically effective communication. The second part considers potential forms of government restrictions on or proscriptions against the development and use of cloud computing technology. Referring to the concept of technology neutrality, it argues that interference with hosting companies and cloud services providers is hardly ever necessary or justified. It is argued, too, however, that businesses using cloud services (banks, law firms, hospitals etc. storing client data in the cloud, e.g.) will have to follow rather more stringent regulations. (shrink)

A multitude of legislation impacts the use of samples and data for research in South Africa. With the coming into effect of the Protection of Personal Information Act No. 4 of 2013 in July 2021, recent attention has been given to safeguarding research participants’ personal information. The protection of participants’ privacy in research is essential, but it is not the only risk at stake in the use and sharing of personal information. Other rights and interests that must also be (...) considered and safeguarded include the right to non-discrimination, the right to dignity, and the right to enjoy the benefits of scientific progress. This can be achieved by ensuring that the ethical values and universal principles that underpin the research landscape, namely equity, reciprocity, justice and solidarity, are embedded in the regulatory framework for the management and use of personal information. This paper advocates an integrated bioethics approach to the use of personal information for research in SA. A key feature in embedding such an approach is a Data Transfer Agreement that appropriately integrates the safeguards and protections set out by our regulatory framework with bioethical rules and procedures when personal information is used and shared for research purposes. This paper thus calls for the development of a national DTA that is guided by key ethical principles when data are shared for research purposes. This paper will be followed by a webinar on 23 June 2022 hosted by the Department of Science and Innovation and the SA Medical Research Council, where the recommendations and suggestions set out herein will be unpacked, discussed and debated by relevant stakeholders. (shrink)

This review is based on an expanded version of the session outcome document we prepared for WSIS. The outcome was providing a summary of the session: Data Ethics and the Ethics of Digital and Emerging Technologies – Building Trust, Serving Humanity – Globethics, which was held a few days earlier from 16:00 to 16:45, Monday, 13 March 2023 at the Geneva International Conference Center, under the auspices of the ITU.

Following the trend of sharing, and associating being on-line with being 'on-life', many people are now demanding the ownership and control of their data across all processing phases, including the erasure of their presence on the web. In Europe, recent proposals for regulation include an explicit 'Right to be Forgotten'; this right stated in the European Commission Proposal for Regulation COM 2011/12 does not emerge without controversy. It is being criticised on several grounds, including clashing with other rights, such (...) as freedom of expression, as well as setting the terrain for censorship. Besides the purely legal aspects of the proposed provisions, the chapters of this volume discuss how those legal provisions correspond in practice to worldviews and how individual and collective memory must be governed. They look into the deeper consequences of such provisions to construction of identity, culture and community formation, and how such a right affects how, what and why individuals, groups and societies remember and forget. (shrink)

In the paper ‘COVID-19 vaccine boosters for young adults: a risk–benefit assessment and ethical analysis of mandate policies at universities,’ Bardoshet alargued that college mandates of the COVID-19 booster vaccine are unethical. The authors came to this conclusion by performing three different sets of comparisons of benefits versus risks using referenced data and argued that the harm outweighs the risk in all three cases. In this response article, we argue that the authors frame their arguments by comparing values that (...) are not scientifically or reasonably comparable and that the authors used values that represent grossly different risk profiles and grouped them into a set of figures to create an illusion of fair comparisons. We argue that absent the falsely skewed portrayals of a higher level of risk over benefit in their misrepresented figures, the five ethical arguments they presented completely fall apart. (shrink)

In informationally mature societies, almost all organisations record, generate, process, use, share and disseminate data. In particular, the rise of AI and autonomous systems has corresponded to an improvement in computational power and in solving complex problems. However, the resulting possibilities have been coupled with an upsurge of ethical risks. To avoid the misuse, underuse, and harmful use of data and data-based systems like AI, we should use an ethical framework appropriate to the object of its reasoning. (...) Unfortunately, in recent years, the space for data-related ethics has not been precisely defined in organisations. As a consequence, there has been an overlapping of responsibilities and a void of clear accountabilities. Ethical issues have, therefore, been dealt with using inadequate levels of abstraction (e.g. legal, technical). Yet, if building an ethical infrastructure requires the collaboration of each body, addressing ethical issues related to data requires leaving room for the appropriate level of abstraction. This paper first aims to show how the space of data ethics is already latent in organisations. It then highlights how to redefine roles (chief data ethics officer, data ethics committee, etc.) and codes (code of data ethics) to create and maintain an environment where ethical reasoning about data, information, and AI systems may flourish. (shrink)

Throughout the Global North, policymakers invest in large-scale integration of health-data infrastructures to facilitate the reuse of clinical data for administration, research, and innovation. Debates about the ethical implications of data repurposing have focused extensively on issues of patient autonomy and privacy. We suggest that it is time to scrutinize also how the everyday work of healthcare staff is affected by political ambitions of data reuse for an increasing number of purposes, and how different purposes are (...) prioritized. Our analysis builds on ethnographic studies within the Danish healthcare system, which is internationally known for its high degree of digitalization and well-connected data infrastructures. Although data repurposing ought to be relatively seamless in this context, we demonstrate how it involves costs and trade-offs for those who produce and use health data. Even when IT systems and automation strategies are introduced to enhance efficiency and reduce data work, they can end up generating new forms of data work and fragmentation of clinically relevant information. We identify five types of data work related to the production, completion, validation, sorting, and recontextualization of health data. Each of these requires medical expertise and clinical resources. We propose that the implications for these forms of data work should be considered early in the planning stages of initiatives for large-scale data sharing and reuse, such as the European Health Data Space. We believe that political awareness of clinical costs and trade-offs related to such data work can provide better and more informed decisions about data repurposing. (shrink)

In this issue, Ellen Fox and colleagues report on their national study on ethics consultation in U.S. hospitals, following up on the previous 1999–2000 landmark study. Th...

Ethics is a foundational competency in healthcare inherent in everyday nursing practice. Therefore, the promotion of qualified nurses’ and nursing students’ moral competence is essential to ensure ethically high-quality and sustainable healthcare. The aim of this integrative literature review is to identify the factors contributing to the promotion of qualified nurses’ and nursing students’ moral competence. The review has been registered in PROSPERO (CRD42023386947) and reported according to the PRISMA guideline. Focusing on qualified nurses’ and nursing students’ moral competence, (...) a literature search was undertaken in January 2023 in six scientific databases: CINAHL, Cochrane Library, PsycINFO, PubMed Medline, Scopus and Web of Science. Empirical studies written in English without time limitation were eligible for inclusion. A total of 29 full texts were retrieved and included out of 5233 citations. Quality appraisal was employed using Joanna Briggs Institute checklists and the Mixed Method Appraisal Tool. Data were analysed using inductive content analysis. Research about the factors contributing to the promotion of qualified nurses’ and nursing students’ moral competence is limited and mainly explored using descriptive research designs. The contributing factors were identified as comprising two main categories: (1) human factors, consisting of four categories: individual, social, managerial and professional factors, and ten sub-categories; and (2) structural factors, consisting of four categories: educational, environmental, organisational and societal factors, and eight sub-categories. This review provides knowledge about the factors contributing to the promotion of qualified nurses’ and nursing students’ moral competence for the use of researchers, nurse educators, managers, organisations and policymakers. More research about the contributing factors is needed using complex intervention, implementation and multiple methods designs to ensure ethically sustainable healthcare. (shrink)

Digital Earth applications provide a common ground for visualizing, simulating, and modeling real-world situations. The potential of Digital Earth applications has increased significantly with the evolution of artificial intelligence systems and the capacity to collect and process complex amounts of geospatial data. Yet, the widespread techno-optimism at the root of Digital Earth must now confront concerns over high-risk artificial intelligence systems and power asymmetries of a datafied society. In this commentary, we claim that not only can current debates about (...) data governance and ethical artificial intelligence inform development in the field of Digital Earth, but that the specificities of geospatial data, together with the expectations surrounding Digital Earth applications, offer a fruitful lens through which to examine current debates on data governance and artificial intelligence ethics. In particular, we argue that for the implementation of ethical artificial intelligence and inclusive approaches to data governance, Digital Earth initiatives need to involve stakeholders and communities at the local level and be sensitive to social, legal, cultural, and institutional contexts, including conflicts that might arise within those contexts. (shrink)

Count Me In (CMI) was launched in 2015 as a patient-driven research initiative aimed at accelerating the study of cancer genomics through direct participant engagement, electronic consent and open-access data sharing. It is an example of a large-scale direct-to-patient (DTP) research project which has since enrolled thousands of individuals. Within the broad scope of ‘citizen science’, DTP genomics research is defined here as a specific form of ‘top-down’ research endeavour developed and overseen by institutions within the traditional human subjects (...) research context; in novel ways, it engages and recruits patients with defined diseases, consents them for medical information and biospecimens sharing, and stores and disseminates genomic information. Importantly, these projects simultaneously aim to empower participants in the research process while increasing sample size, particularly in rare disease states. Using CMI as a case study, this paper discusses how DTP genomics research raises new questions in the context of traditional human subjects research ethics, including issues surrounding participant selection, remote consent, privacy and return of results. It aims to demonstrate how current research ethics frameworks may be insufficient in this context, and that institutions, institutional review boards and investigators should be aware of these gaps and their role in ensuring the conduct of ethical, novel forms of research together with participants. Ultimately, a broader question is raised of whether the rhetoric of participatory genomics research advocates for an ethic of personal and social duty for contributing to the advancement of generalisable knowledge about health and disease. (shrink)

This article probes the practical ethical implications of AI system design by reconsidering the important topic of bias in the datasets used to train autonomous intelligent systems. The discussion draws on recent work concerning behaviour-guiding technologies, and it adopts a cautious form of technological utopianism by assuming it is potentially beneficial for society at large if AI systems are designed to be comparatively free from the biases that characterise human behaviour. However, the argument presented here critiques the common well-intentioned requirement (...) that, in order to achieve this, all such datasets must be debiased prior to training. By focusing specifically on gender-bias in Neural Machine Translation systems, three automated strategies for the removal of bias are considered – downsampling, upsampling, and counterfactual augmentation – and it is shown that systems trained on datasets debiased using these approaches all achieve general translation performance that is much worse than a baseline system. In addition, most of them also achieve worse performance in relation to metrics that quantify the degree of gender bias in the system outputs. By contrast, it is shown that the technique of domain adaptation can be effectively deployed to debias existing NMT systems after they have been fully trained. This enables them to produce translations that are quantitatively far less biased when analysed using gender-based metrics, but which also achieve state-of-the-art general performance. It is hoped that the discussion presented here will reinvigorate ongoing debates about how and why bias can be most effectively reduced in state-of-the-art AI systems. (shrink)

Part of understanding the meaning and power of algorithms means asking what new demands they might make of ethical frameworks, and how they might be held accountable to ethical standards. I develop a definition of networked information algorithms as assemblages of institutionally situated code, practices, and norms with the power to create, sustain, and signify relationships among people and data through minimally observable, semiautonomous action. Starting from Merrill’s prompt to see ethics as the study of “what we ought (...) to do,” I examine ethical dimensions of contemporary NIAs. Specifically, in an effort to sketch an empirically grounded, pragmatic ethics of algorithms, I trace an algorithmic assemblage’s power to convene constituents, suggest actions based on perceived similarity and probability, and govern the timing and timeframes of ethical action. (shrink)

This article examines the recent transformations of the Italian welfare state from a familist welfare model to what I term transnational market familism. In this model, families buy in care labour, commonly provided by migrant workers. There is now a growing literature exploring both the transformations of the Italian welfare model and the experiences of migrant workers providing care in Italy. However, what has been overlooked in the current literature is the ethical aspect of this model of welfare provision, which (...) is part of the transnational political economy of care. The article analyses the ethical implications of the migrant-in-the-family model, which transforms the care relationship between the caregiver and care receiver into a complex relationship between the family member organising care, the migrant caregiver and the dependent care receiver. The context of such welfare provision is transnational. Examining this care triangle, I draw on care ethics and individualization perspective for an analysis of how social policies safeguard, or overlook, human interaction and care relationships in the context of global hierarchies. The article draws on ethnographic data gathered in Naples, Italy, during 2004–2005, including interviews with Neapolitan employers and elderly care-receivers, interviews with migrant workers, as well as participant observations. (shrink)

There is increasing concern about “surveillance capitalism,” whereby for-profit companies generate value from data, while individuals are unable to resist (Zuboff 2019). Non-profits using data-enabled surveillance receive less attention. Higher education institutions (HEIs) have embraced data analytics, but the wide latitude that private, profit-oriented enterprises have to collect data is inappropriate. HEIs have a fiduciary relationship to students, not a narrowly transactional one (see Jones et al, forthcoming). They are responsible for facets of student life beyond (...) education. In addition to classrooms, learning management systems, and libraries, HEIs manage dormitories, gyms, dining halls, health facilities, career advising, police departments, and student employment. HEIs collect and use student data in all of these domains, ostensibly to understand learner behaviors and contexts, improve learning outcomes, and increase institutional efficiency through “learning analytics” (LA). ID card swipes and Wi-Fi log-ins can track student location, class attendance, use of campus facilities, eating habits, and friend groups. Course management systems capture how students interact with readings, video lectures, and discussion boards. Application materials provide demographic information. These data are used to identify students needing support, predict enrollment demands, and target recruiting efforts. These are laudable aims. However, current LA practices may be inconsistent with HEIs’ fiduciary responsibilities. HEIs often justify LA as advancing student interests, but some projects advance primarily organizational welfare and institutional interests. Moreover, LA advances a narrow conception of student interests while discounting privacy and autonomy. Students are generally unaware of the information collected, do not provide meaningful consent, and express discomfort and resigned acceptance about HEI data practices, especially for non-academic data (see Jones et al. forthcoming). The breadth and depth of student information available, combined with their fiduciary responsibility, create a duty that HEIs exercise substantial restraint and rigorous evaluation in data collection and use. (shrink)

Purpose – Investments in the technologies of borders and their securitisation continue to be a focal point for many governments across the globe. This paper is concerned with a particular example of such technologies, namely, “Big Data” analytics. In the past two years, the technology of Big Data has gained a remarkable popularity within a variety of sectors, ranging from business and government to scientific and research fields. While Big Data techniques are often extolled as the next (...) frontier for innovation and productivity, they are also raising many ethical and political issues. The aim of this paper is to consider some of these issues and provide a critical reflection on the implications of using Big Data for the governance of borders. Design/methodology/approach – The author draws on the example of the new Big Data solution recently developed by IBM for the Australian Customs and Border Protection Service. The system, which relies on data collected from Passenger Name Records, aims to facilitate and automate mechanisms of profiling enable the identification of “high-risk” travellers. It is argued that the use of such Big Data techniques risks augmenting the function and intensity of borders. Findings – The main concerns addressed here revolve around three key elements, namely, the problem of categorisation, the projective and predictive nature of Big Data techniques and their approach to the future and the implications of Big Data on understandings and practices of identity. Originality/value – By exploring these issues, the paper aims to contribute to the debates on the impact of information and communications technology-based surveillance in border management. (shrink)

In 2008, a group of researchers publicly released profile data collected from the Facebook accounts of an entire cohort of college students from a US university. While good-faith attempts were made to hide the identity of the institution and protect the privacy of the data subjects, the source of the data was quickly identified, placing the privacy of the students at risk. Using this incident as a case study, this paper articulates a set of ethical concerns that (...) must be addressed before embarking on future research in social networking sites, including the nature of consent, properly identifying and respecting expectations of privacy on social network sites, strategies for data anonymization prior to public release, and the relative expertise of institutional review boards when confronted with research projects based on data gleaned from social media. (shrink)

This article offers several contributions to the interdisciplinary project of responsible research and innovation in data science and AI. First, it provides a critical analysis of current efforts to establish practical mechanisms for algorithmic auditing and assessment to identify limitations and gaps with these approaches. Second, it provides a brief introduction to the methodology of argument-based assurance and explores how it is currently being applied in the development of safety cases for autonomous and intelligent systems. Third, it generalises this (...) method to incorporate wider ethical, social, and legal considerations, in turn establishing a novel version of argument-based assurance that we call ‘ethical assurance.’ Ethical assurance is presented as a structured method for unifying the myriad practical mechanisms that have been proposed. It is built on a process-based form of project governance that enlists reflective innovation practices to operationalise normative principles, such as sustainability, accountability, transparency, fairness, and explainability. As a set of interlocutory governance mechanisms that span across the data science and AI lifecycle, ethical assurance supports inclusive and participatory ethical deliberation while also remaining grounded in social and technical realities. Finally, this article sets an agenda for ethical assurance, by detailing current challenges, open questions, and next steps, which serve as a springboard to build an active (and interdisciplinary) research programme as well as contribute to ongoing discussions in policy and governance. (shrink)

There is growing interest for a communitarian approach to the governance of genomics, and for such governance to be grounded in principles of justice, equity and solidarity. However, there is a near absence of conceptual studies on how communitarian-based principles, or values, may inform, support or guide the governance of genomics research. Given that solidarity is a key principle in Ubuntu, an African communitarian ethic and theory of justice, there is emerging interest about the extent to which Ubuntu could offer (...) guidance for the governance of genomics research in Africa. To this effect, we undertook a conceptual analysis of Ubuntu with the goal of identifying principles that could inform equity-oriented governance of genomics research. Solidarity, reciprocity, open sharing, accountability, mutual trust, deliberative decision-making and inclusivity were identified as core principles that speak directly to the different macro-level ethical issues in genomics research in Africa such as: the exploitation of study populations and African researchers, equitable access and use of genomics data, benefit sharing, the possibility of genomics to widen global health inequities and the fair distribution of resources such as intellectual property and patents. We use the identified the principles to develop ethical guidance for genomics governance in Africa. (shrink)

Herbert Spencer (1820–1903), Victorian philosopher, biologist, sociologist and political theorist, one of the founders of Social Darwinism and author of the phrase 'survival of the fittest', was nominated for the Nobel Prize for Literature in 1902, losing out to Theodor Mommsen. Spencer left his post at The Economist in 1857 to focus on writing his ten-volume System of Synthetic Philosophy, a work that offers an ethics-based guide to human conduct to replace that provided by conventional religious belief. Published in (...) 1879, this volume seeks to demonstrate that social evolution tends towards greater individualism, altruism and co-operation. Spencer argues that it is possible to establish rules of right conduct on a scientific basis, and declares that this work is the culmination of his life's study. He was anxious to publish it outside the planned order of the System, because he feared (wrongly) that his death would prevent its completion. (shrink)