Informed consent bears significant relevance as a legal basis for the processing of personal data and health data in the current privacy, data protection and confidentiality legislations. The consent requirements find their basis in an ideal of personal autonomy. Yet, with the recent advent of the global pandemic and the increased use of eHealth applications in its wake, a more differentiated perspective with regards to this normative approach might soon gain momentum. This paper discusses the compatibility of a moral duty (...) to share data for the sake of the improvement of healthcare, research, and public health with autonomy in the field of data protection, privacy and medical confidentiality. It explores several ethical-theoretical justifications for a duty of data sharing, and then reflects on how existing privacy, data protection, and confidentiality legislations could obstruct such a duty. Consent, as currently defined in the General Data Protection Regulation – a key legislative framework providing rules on the processing of personal data and data concerning health – and in the recommendation of the Council of Europe on the protection of health-related data – explored here as soft-law – turns out not to be indispensable from various ethical perspectives, while the requirement of consent in the General Data Protection Regulation and the recommendation nonetheless curtails the full potential of a duty to share medical data. Also other legal grounds as possible alternatives for consent seem to constitute an impediment. (shrink)

BackgroundIncreasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorphic encryption allows computations to be performed on data without this data ever being decrypted. Therefore, homomorphic encryption represents a potential solution for conducting feasibility studies on cohorts of sensitive patient data stored in distributed locations. Distributed ledger technology provides a permanent record on all transfers and processing of patient data, (...) allowing data custodians to audit access. A significant portion of the current literature has examined how these technologies might comply with data protection and research ethics frameworks. In the Swiss context, these instruments include the Federal Act on Data Protection and the Human Research Act. There are also institutional frameworks that govern the processing of health related and genetic data at different universities and hospitals. Given Switzerland’s geographical proximity to European Union (EU) member states, the General Data Protection Regulation (GDPR) may impose additional obligations.MethodsTo conduct this assessment, we carried out a series of qualitative interviews with key stakeholders at Swiss hospitals and research institutions. These included legal and clinical data management staff, as well as clinical and research ethics experts. These interviews were carried out with two series of vignettes that focused on data discovery using homomorphic encryption and data erasure from a distributed ledger platform.ResultsFor our first set of vignettes, interviewees were prepared to allow data discovery requests if patients had provided general consent or ethics committee approval, depending on the types of data made available. Our interviewees highlighted the importance of protecting against the risk of reidentification given different types of data. For our second set, there was disagreement amongst interviewees on whether they would delete patient data locally, or delete data linked to a ledger with cryptographic hashes. Our interviewees were also willing to delete data locally or on the ledger, subject to local legislation.ConclusionOur findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies. (shrink)

Digital twinning in medicine refers to the idea of simulating a person’s organs, muscles or perhaps their entire body, in order to arrive more effectively at accurate diagnoses, to make treatment recommendations that reflect chances of success and possible side-effects, and to better understand the long-term trajectory of an individual’s overall condition. Digital twins, in these ways, build on the recent movement toward personalised medicine,1 and they undoubtedly present us with exciting opportunities to advance our health. Of course, the opportunities (...) are accompanied by newfound challenges—a common refrain in discussions surrounding emerging technologies. In a recent article, Matthias Braun surveys numerous problems, including the precision of simulations, ownership and consent to the use of digital models, and issues of justice in assuring equitable access to novel medical systems.2 In particular, he places special emphasis on the notion of representation. According to Braun, proper representation naturally calls for correspondence—namely a precise model offering dynamic, real-time feedback as well as transparency, both for the patient and the practitioner, in terms of the data being employed. While technical challenges remain, these goals are quite clear and relatively uncontroversial. Where a host of questions arise, however, is in the discussion on the interaction between the represented persons and their simulations. Alongside questions regarding ownership of one’s digital twin, Braun raises the concern that ‘giving …. (shrink)

Population-level biomedical research has become crucial to the health system’s ability to improve the health of the population. This form of research raises a number of well-documented ethical concerns, perhaps the most significant of which is the inability of the researcher to obtain fully informed specific consent from participants. Two proposed technical solutions to this problem of consent in large-scale biomedical research that have become increasingly popular are meta-consent and dynamic consent. We critically examine the ethical and practical credentials of (...) these proposals and find them lacking. We suggest that the consent problem is not solved by adopting a technology driven approach grounded in a notion of ‘specific’ consent but by taking seriously the role of research governance in combination with broader conceptions of consent. In our view, these approaches misconstrue the rightful location of authority in the way in which population-level biomedical research activities are structured and organized. We conclude by showing how and why the authority for determining the nature and shape of choice making about participation ought not to lie with individual participants, but rather with the researchers and the research governance process, and that this necessarily leads to the endorsement of a fully articulated broad consent approach. (shrink)

Recent advances in medical and information technologies, the availability of new types of medical data, the requirement of increasing numbers of study participants, as well as difficulties in recruitment and retention, all present serious problems for traditional models of specific and informed consent to medical research. However, these advances also enable novel ways to securely share and analyse data. This paper introduces one of these advances—blockchain technologies—and argues that they can be used to share medical data in a secure and (...) auditable fashion. In addition, some aspects of consent and data collection, as well as data access management and analysis, can be automated using blockchain-based smart contracts. This paper demonstrates how blockchain technologies can be used to further all three of the bioethical principles underlying consent requirements: the autonomy of patients, by giving them much greater control over their data; beneficence, by greatly facilitating medical research efficiency and by reducing biases and opportunities for errors; and justice, by enabling patients with rare or under-researched conditions to pseudonymously aggregate their data for analysis. Finally, we coin and describe the novel concept of prosent, by which we mean the blockchain-enabled ability of all stakeholders in the research process to pseudonymously and proactively consent to data release or exchange under specific conditions, such as trial completion. (shrink)

In a recent article in the Journal of Medical Ethics, Neil Manson sets out to show that the meta-consent model of informed consent is not the solution to perennial debate on the ethics of biobank participation. In this response, we shall argue that Manson’s considerations on the costs of a meta-consent model are incomplete and therefore misleading; his view that a model of broad consent passes a threshold of moral acceptability rests on an analogy that misconstrues how biobank research is (...) actually conducted and a model of meta-consent is more in tune with the nature of biobank research and enables autonomous choice. (shrink)

In this response to Neil Manson’s latest intervention in our debate about the best consent model for biobank research we show, contra Manson that the ‘expiry problem’ that affects broad consent models because of changes over time in methods, purposes, types of data used and governance structures is a real and significant problem. We further show that our preferred implementation of meta consent as a national consent platform solves this problem and is not subject to the cost and burden objections (...) that Manson raises. (shrink)

Studies suggest that machine learning models may accurately predict depression and other mental health-related conditions based on social media data. I have recently argued that individuals should have sui generis right not to be subjected to AI profiling based on publicly available data without their explicit informed consent. In a comment, Holm claims that there are scenarios in which individuals have a reason to prefer attempts of social control exercised on the basis of accurate AI predictions and that the suggested (...) right burdens individuals unfairly by allowing for those individuals to consent to AI profiling. In this reply, I address both of these alleged problems and their underlying assumptions and show why they fail to provide any reasons not to introduce the suggested right. (shrink)

Research into personal health data holds great potential not only for improved treatment but also for economic growth. In these years many countries are developing policies aimed at facilitating such research often under the banner of ‘big data’. A central point of debate is whether the secondary use of health data requires informed consent if the data is anonymised. In 2013 the Danish Minister of Health established a new register collecting data about all ritual male childhood circumcisions in Denmark. The (...) main purpose of the register was to enable future research into the consequences of ritual circumcision. This article is a study into the case of the Danish Circumcision Registry. We show that such a registry may lead to various forms of harm such as 1) overreaching social pressure, 2) stigmatization, 3) medicalization of a religious practice, 4) discrimination, and 5) polarised research, and that a person may therefore have a strong and legitimate interest in deciding whether or not such data should be collected and/or used in research. This casts doubt on the claim that the requirement of informed consent could and should be waived for all types of secondary research into registries. We finally sketch a new model of informed consent – Meta consent – aimed at striking a balance between the interests in promoting research and at the same time protecting the individual. Research participants may have a strong and legitimate interest in deciding whether or not their data should be collected and used for registry-based research whether or not their data is anonymised. (shrink)

BackgroundHealth data holds great potential for improved treatments. Big data research and machine learning models have been shown to hold great promise for improved diagnostics and treatment planning. The potential is tied, however, to the availability of personal health data. In recent years, it has been argued that data from health records should be available for health research, and that individuals have a duty to make the data available for such research. A central point of debate is whether such secondary (...) use of health data requires informed consent.Main bodyIn response to recent writings this paper argues that a requirement of informed consent for health record research must be upheld. It does so by exploring different contrasting notions of the duty of easy rescue and arguing that none of them entail aperfectduty to participate in health record research. In part because the costs of participation cannot be limited to 1) the threat of privacy breaches, but includes 2) the risk of reduced trust and 3) suboptimal treatment, 4) stigmatization and 5) medicalisation, 6) further stratification of solidarity and 7) increased inequality in access to treatment and medicine. And finally, it defends the requirement of informed consent by arguing that the mere possibility of consent bias provides a rather weak reason for making research participation mandatory, and that there are strong, independent reasons for making.ConclusionArguments from the duty of easy rescue in combination with claims about little risk of harm and potential consent bias fail to establish not only aperfectduty to participate in health record research, but also that participation in such research should be mandatory. On the contrary, an analysis of these arguments indicates that the duty to participate in research is most adequately construed as animperfectduty, and reveals a number of strong reasons for insisting that participation in health records research is based on informed consent. (shrink)

The increased use of information technology in every day health care creates vast amounts of stored health data that can be used for research. The secondary research use of routinely collected data raises questions about appropriate consent mechanisms for such use. One option is meta consent where individuals state their own consent preferences in relation to future use of their data, e.g. whether they want the data to be accessible to researchers under conditions of specific consent, broad consent, blanket consent (...) or not at all. This study investigates whether meta consent preferences can be successfully elicited by a smartphone application in the adult Danish population. A smartphone app was developed for the elicitation of meta consent preferences. An invitation to use the app was distributed to a stratified, representative sample of the Danish adult population. The meta consent choices, the use of the app, user experience data, and demographic data were logged and analysed statistically using IBM SPSS version 20. Of 1000 potential respondents 221 used the app. One hundred eighty-eight of the respondents were female and 103 male. The age range was 19 to 79 years with an average of 51 years. Most users indicate 1) that they find the choices they are asked to make easy to understand, 2) that the application is easy to use, and 3) that this kind of choice should be offered to people. It is possible to collect meta consent preferences in the general, adult population using a smartphone app. (shrink)

Medical artificial intelligence (AI) is considered to be one of the most important assets for the future of innovative individual and public health care. To develop innovative medical AI, it is necessary to repurpose data that are primarily generated in and for the health care context. Usually, health data can only be put to a secondary use if data subjects provide their informed consent (IC). This regulation, however, is believed to slow down or even prevent vital medical research, including AI (...) development. For this reason, a number of scholars advocate a moral civic duty to share electronic health records (EHRs) that overrides IC requirements in certain contexts. In the medical AI context, the common arguments for such a duty have not been subjected to a comprehensive challenge. This article sheds light on the correlation between two normative discourses concerning informed consent for secondary health record use and the development and use of medical AI. There are three main arguments in favour of a civic duty to support certain developments in medical AI by sharing EHRs: the ‘rule to rescue argument’, the ‘low risks, high benefits argument’, and the ‘property rights argument’. This article critiques all three arguments because they either derive a civic duty from premises that do not apply to the medical AI context, or they rely on inappropriate analogies, or they ignore significant risks entailed by the EHR sharing process and the use of medical AI. Given this result, the article proposes an alternative civic responsibility approach that can attribute different responsibilities to different social groups and individuals and that can contextualise those responsibilities for the purpose of medical AI development. (shrink)

Over the past couple of decades, there has been an ongoing, often fierce, debate about the ethics of biobank participation. One central element of that debate has concerned the nature of informed consent, must specific reconsent be gained for each new use, or user, or is broad consent ethically adequate? Recently, Thomas Ploug and Søren Holm have developed an alternative to both specific and broad consent: what they call a meta-consent framework. On a meta-consent framework, participants can choose the type (...) of consent framework they require, for different kinds of use, different types of user and so on. Meta-consent involves a distinctive kind of design of the consent process. Here it is argued, first, that although a meta-consent framework does not wrong participants, Ploug and Holm understate the likely costs and burdens of such a framework, so there are good practical reasons not to offer it. Second, although Ploug and Holm allude to some ethical considerations that might seem to ground an ethical argument for providing meta-consent, they do not offer any sound argument, and it does not wrong participants in any way to fail to offer them the opportunity to design their own consent process. (shrink)

In a recent article, I argued that Ploug and Holm’s ‘meta-consent’ proposal should be rejected for biobank governance. This was because, although meta-consent is permissible, it is both burdensome and ethically omissible. There is no ethical reason why funders should undertake the additional costs. Ploug and Holm have sought to respond to these arguments. Here, it is noted that not only do they fail to adequately refuse the case against meta-consent, they fail to even engage with the arguments, either misunderstanding (...) them or ignoring them. In their response, Ploug and Holm unwittingly provide the basis of an even stronger case against meta-consent. They argue that broad consent has a built in tendency to expire, while also holding that broad consent should be one of the options available in meta-consent. Meta-consent thus ends up being more like dynamic consent, but, arguably, even more burdensome and costly. (shrink)

In the 60+ years that the modern concept of informed consent has been around, researchers in various fields of practice, especially medical ethics, have developed new models to overcome theoretical and practical problems. While (systematic) literature reviews of such models exist within given fields (e.g., genetic screening), this article breaks ground by analyzing academic literature on consent models across fields. Three electronic research databases (Scopus, Google Scholar, and Web of Science) were searched for publications mentioning informed consent models. The titles, (...) abstracts, and if applicable, full publications were screened and coded. The resulting data on fields, models, and themes were then analyzed. We scanned 300 sources from three databases to find 207 uniquely named consent models, and created a network visualization displaying which models occur primarily in one field, and which models overlap between fields. This analysis identifies trends in the consent debate in different fields, as well as common goals of consent models. The most frequently occurring consent models are identified and defined. The analysis contributes toward a cross-disciplinary “consent design toolkit” and highlights that there are more interrelationships between models and fields than are acknowledged in the literature. Where some models are designed to solve distinctively field-specific issues and are specific to biomedical ethics, some may be adaptable and applicable for other fields including engineering and design. (shrink)

In the debates regarding the ethics of human organoid biobanking, the locus of donor autonomy has been identified in processes of consent. The problem is that, by focusing on consent, biobanking processes preclude adequate engagement with donor autonomy because they are unable to adequately recognise or respond to factors that determine authentic choice. This is particularly problematic in biobanking contexts associated with organoid research or the clinical application of organoids because, given the probability of unforeseen and varying purposes for which (...) a donor’s organoids could be employed and given the different ways in which a donor can relate to her biospecimens, a donor can value her organoids differently in different contexts and her reasons for autonomously permitting use of her cells and tissues in one case may not support an autonomous decision in another. In response, this paper has three aims: firstly, to make the case for why organoid biobanks ought to respect donor autonomy conceived as authentic choice; secondly, to explore the autonomy-respecting limits of established and widely prevalent models of biobank consent; and thirdly, to propose certain conditions that organoid biobanks ought to support or facilitate in order to respect donor autonomy. (shrink)

BackgroundIn this article, we address questions regarding how people consider what they do or do not consent to and the reasons why. This article presents the findings of a citizen forum study conducted by the University of Geneva in partnership with the Geneva University Hospitals to explore the opinions and concerns of members of the public regarding predictive oncology, genetic sequencing, and cancer. MethodsThis paper presents the results of a citizen forum that included 73 participants. A research tool titled "the (...) mechanics of consent" was designed for this study. This tool is a table encouraging participants to reflect on social and research actors, types of data, and desired levels of control while sharing different types of data with different actors. Participants’ discussion that led to the completion of each table were audio-recorded, transcribed, and analyzed using thematic analysis.ResultsThe results are a compilation of responses from the mechanics of consent tool divided into two sections; the first presents quantitative results of collective responses regarding attitudes to consent to donate their data. The second section present qualitative findings emerged from the discussion amongst participants.DiscussionChoice and control of personal data is crucial for the public to be able to decide who and how to trust. Key information to be disclosed to potential research participants shall include information about potential risks and benefits; who will be accessing and using their data; as well as assurances that their choice will be respected. Furthermore, researchers ought to make sure they are trustworthy, by acting in a competent, reliable, and honest manner. Governance systems ought to be better equipped to address ethical issues raise by the growing presence of non-traditional research actors, consent of exchanges of data via digital devices and online activity such as social media and fairness of data trading. Finally, informed consent is one of the various elements that contribute to conducting ethical research. More needs to be done to strengthen governance and ensure adequate protection of research participants, particularly to address issues related to predictive health analytics. (shrink)

Background Big data and AI applications now play a major role in many health contexts. Much research has already been conducted on ethical and social challenges associated with these technologies. Likewise, there are already some studies that investigate empirically which values and attitudes play a role in connection with their design and implementation. What is still in its infancy, however, is the comparative investigation of the perspectives of different stakeholders. Methods To explore this issue in a multi-faceted manner, we conducted (...) semi-structured interviews as well as focus group discussions with patients and clinicians. These empirical methods were used to gather interviewee’s views on the opportunities and challenges of medical AI and other data-intensive applications. Results Different clinician and patient groups are exposed to medical AI to differing degrees. Interviewees expect and demand that the purposes of data processing accord with patient preferences, and that data are put to effective use to generate social value. One central result is the shared tendency of clinicians and patients to maintain individualistic ascriptions of responsibility for clinical outcomes. Conclusions Medical AI and the proliferation of data with import for health-related inferences shape and partially reconfigure stakeholder expectations of how these technologies relate to the decision-making of human agents. Intuitions about individual responsibility for clinical outcomes could eventually be disrupted by the increasing sophistication of data-intensive and AI-driven clinical tools. Besides individual responsibility, systemic governance will be key to promote alignment with stakeholder expectations in AI-driven and data-intensive health settings. (shrink)

Clinical information about patients is increasingly being stored in electronic form and has therefore become more easily shareable. Data are collected as part of clinical care but have multiple other potential uses in relation to health system planning, audit and research. The use of clinical information for these secondary uses is controversial, and the ability to safeguard personal and sensitive data under current practices is contested.In this study, we investigate the attitudes of a representative sample of the Danish population towards (...) transfer of clinical data from their general practice for secondary use. We specifically study: patients’ trust in different types of healthcare professionals, their interest in being asked about secondary use of data and their willingness to dispense from a requirement of informed consent based on their trust in healthcare professionals.We find that adult Danes are positive towards research that use patient data, and they generally trust general practitioners, hospitals and researchers to treat their data confidentially.Nevertheless, they feel that they have a right to control the use of their data, only 7.3% disagreeing, and that the data belong to them, only 14.0% disagreeing. Answers to further questions about the relation between trust, information and consent show that although trust modifies the wish for information and consent, there is still a strong view that the patient should control the use of data. We find no differences between those who have frequent contact with the healthcare system and those who do not. (shrink)

Denmark is a society that has already moved towards Big Data and a Learning Health Care System. Data from routine healthcare has been registered centrally for years, there is a nationwide tissue bank, and there are numerous other available registries about education, employment, housing, pollution, etcetera. This has allowed Danish researchers to study the link between exposures, genetics and diseases in a large population. This use of public registries for scientific research has been relatively uncontroversial and has been supported by (...) facilitative regulation that allows data to be used without the consent of data subjects. However, in the future much of the data will not be held by public authorities but by private companies. What are the implications of this shift for the governance of the research use of the data? This paper will argue that increased involvement of Research Ethics Committees and better training of researchers are necessary; and that some form of consent will have to be re-introduced. Four different consent models will be discussed: Opt-Out, Broad/Blanket consent, Dynamic consent, and Meta consent. It will be argued that a governance model including a possibility for citizens to make meta-choices strikes the best balance between individual and public interests. (shrink)

In this paper we argue that ‘informed’ consent in Big Data genomic biobanking is frequently less than optimally informative. This is due to the particular features of genomic biobanking research which render it ethically problematic. We discuss these features together with details of consent models aimed to address them. Using insights from consent theory, we provide a detailed analysis of the essential components of informed consent which includes recommendations to improve consent performance. In addition, and using insights from philosophy of (...) mind and language and psycholinguistics we support our analyses by identifying the nature and function of concepts (ideas) operational in human cognition and language together with an implicit coding/decoding model of human communication. We identify this model as the source of patients/participants poor understanding. We suggest an alternative, explicit model of human communication, namely, that of relevance‐theoretic inference which obviates the limitations of the code model. We suggest practical strategies to assist health service professionals to ensure that the specific information they provide concerning the proposed treatment or research is used to inform participants’ decision to consent. We do not prescribe a standard, formal approach to decision‐making where boxes are ticked; rather, we aim to focus attention towards the sorts of considerations and questions that might usefully be borne in mind in any consent situation. We hope that our theorising will be of real practical benefit to nurses and midwives working on the clinical and research front‐line of genomic science. (shrink)

Lee suggests a conceptualization of health data sharing not merely as an act of altruism, but as a gift. The difference is important, as the inscription of the latter in a social context inv...

BackgroundThe advent of learning healthcare systems (LHSs) raises an important implementation challenge concerning how to request and manage consent to support secondary use of data in learning cycles, particularly research activities. Current consent models in Quebec were not established with the context of LHSs in mind and do not support the agility and transparency required to obtain consent from all involved, especially the citizens. Therefore, a new approach to consent is needed. Previous work identified the meta-consent model as a promising (...) alternative to fulfill the requirements of LHSs, particularly large-scale deployments. We elicited the public’s attitude toward the meta-consent model to evaluate if the model could be understood by the citizens and would be deemed acceptable to prepare for its possible implementation in Quebec.MethodsEight focus groups, with a total of 63 members of the general public from various backgrounds were conducted in Quebec, Canada, in 2019. Explicit attention was given to literacy levels, language spoken at home and rural vs urban settings. We assessed attitudes, concerns and facilitators regarding key components of the meta-consent model: predefined categories to personalized consent requests, a dynamic web-based infrastructure to record meta-consent, and default settings. To analyse the discussions, a thematic content analysis was performed using a qualitative software.ResultsOur findings showed that participants were supportive of this new approach of consent as it promotes transparency and offers autonomy for the management of their health data. Key facilitators were identified to be considered in the implementation of a meta-consent model in the Quebec LHSs: information and transparency, awareness campaigns, development of educational tools, collaboration of front-line healthcare professionals, default settings deemed acceptable by the society as well as close partnerships with recognized and trusted institutions.ConclusionsThis qualitative study reveals the openness of a sample of the Quebec population regarding the meta-consent model for secondary use of health data for research. This first exploratory study conducted with the public is an important step in guiding decision-makers in the next phases of implementing the various strategies to support access and use of health data in Quebec. (shrink)

A 10-year retrospective analysis of consent documentation for the donation of leftover or residual human tissue from surgical interventions at a major academic healthcare institution in Singapore was conducted. Findings suggest that demographics like gender, religious belief and socioeconomic status could be indicators of the willingness of a patient to donate residual tissue to a tissue repository or biobank for future research use. Patients in general did not decide to donate based on specific details that were provided to them. Instead, (...) those who donated were of a background that engendered a level of security or confidence that harm would not befall them. It is argued that willingness to donate depended more on this sense or perception of security that arose from systemic trustworthiness than from the rigour of consent-taking. In 2015, changes to the regulation of tissue banking and related activities in Singapore include legislative requirement for a prescribed list of information to be provided to a prospective tissue donor in consent-taking. While this and other legislative changes are important to ensure that tissue donation for research remains informed and voluntary, it is argued that trust and trustworthiness remain an unfinished project. Tissue repositories or biobanks more broadly must be constituted as moral institutions that safeguard the interests and rights of altruistic tissue donors. More critically, they must advance security and trustworthiness through good stewardship that is directed at promoting the common good through accountability, transparency and control. (shrink)

The future of health research will be characterised by three continuing trends: rising demand for health data; increasing impracticability of obtaining specific consent for secondary research; and decreasing capacity to effectively anonymise data. In this context, governments, clinicians and the research community must demonstrate that they can be responsible stewards of health data. IRBs and RECs sit at heart of this process because in many jurisdictions they have the capacity to grant consent waivers when research is judged to be of (...) particular value. However, several different terms are used to refer to this value, indicating a lack of conceptual clarity regarding the appropriate test for access to health data for research without consent. In this paper we do three things. First we describe the current confusion and instability in terminology relating to public interest in the context of consent waivers. Second we argue for harmonisation of terminology on the grounds of clarity, transparency and consistency. Third we argue that the term ‘public interest’ best reflects the normative work required to justify consent waivers because it is the broadest of the competing terms. ‘Public interest’ contains within its scope positive and negative implications of a study, as well as welfare, justice and rights considerations. In making this argument, we explain the normative basis for consent waivers, and provide a starting place for further discussion about the precise conditions in which a given study can be said to advance the public interest. Ipsos MORI study found that: … the public would be broadly happy with administrative data linking for research projects provided Those projects have social value, broadly defined. Data are de-identified. Data are kept secure. Businesses are not able to access the data for profit. (shrink)

Experimental design is one aspect of a scientific method. A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate causal effects and thereby maximize internal validity, support causal inferences, and guarantee reliable results. Traditionally employed in the natural sciences, experimental design has become an important part of research in the social and behavioral sciences. Experimental methods are also endorsed as the most reliable guides to policy effectiveness. Through a discussion of some of the central concepts (...) associated with experimental design, including controlled variation and randomization, this chapter will provide a summary of key ethical issues that tend to arise in experimental contexts. In addition, by exploring assumptions about the nature of causation and by analyzing features of causal relationships, systems, and inferences in social contexts, this chapter will summarize the ways in which experimental design can undermine the integrity of not only social and behavioral research but policies implemented on the basis of such research. (shrink)

It has been suggested that to overcome the challenges facing the UK’s National Health Service (NHS) of an ageing population and reduced available funding, the NHS should be transformed into a more informationally mature and heterogeneous organisation, reliant on data-based and algorithmically-driven interactions between human, artificial, and hybrid (semi-artificial) agents. This transformation process would offer significant benefit to patients, clinicians, and the overall system, but it would also rely on a fundamental transformation of the healthcare system in a way that (...) poses significant governance challenges. In this article, we argue that a fruitful way to overcome these challenges is by adopting a pro-ethical approach to design that analyses the system as a whole, keeps society-in-the-loop throughout the process, and distributes responsibility evenly across all nodes in the system. (shrink)