Consent as a compositional act - a framework that provides clarity for the retention and use of data.

BACKGROUND: Informed consent is one of the key principles of conducting research involving humans. When research participants give consent, they perform an act in which they utter, write or otherwise provide an authorisation to somebody to do something. This paper proposes a new understanding of the informed consent as a compositional act. This conceptualisation departs from a modular conceptualisation of informed consent procedures. METHODS: This paper is a conceptual analysis that explores what consent is and what it does or does not do. It presents a framework that explores the basic elements of consent and breaks it down into its component parts. It analyses the consent act by first identifying its basic elements, namely: a) data subjects or legal representative that provides the authorisation of consent; b) a specific thing that is being consented to; and c) specific agent(s) to whom the consent is given. RESULTS: This paper presents a framework that explores the basic elements of consent and breaks it down into its component parts. It goes beyond only providing choices to potential research participants; it explains the rationale of those choices or consenting acts that are taking place when speaking or writing an authorisation to do something to somebody. CONCLUSIONS: We argue that by clearly differentiating the goals, the procedures of implementation, and what is being done or undone when one consent, one can better face the challenges of contemporary data-intensive biomedical research, particularly regarding the retention and use of data. Conceptualising consent as a compositional act enhances more efficient communication and accountability and, therefore, could enable more trustworthy acts of consent in biomedical science.

Out of their minds? Externalist challenges for using AI in forensic psychiatry.

Harnessing the power of machine learning (ML) and other Artificial Intelligence (AI) techniques promises substantial improvements across forensic psychiatry, supposedly offering more objective evaluations and predictions. However, AI-based predictions about future violent behaviour and criminal recidivism pose ethical challenges that require careful deliberation due to their social and legal significance. In this paper, we shed light on these challenges by considering externalist accounts of psychiatric disorders which stress that the presentation and development of psychiatric disorders is intricately entangled with their outward environment and social circumstances. We argue that any use of predictive AI in forensic psychiatry should not be limited to neurobiology alone but must also consider social and environmental factors. This thesis has practical implications for the design of predictive AI systems, especially regarding the collection and processing of training data, the selection of ML methods, and the determination of their explainability requirements.

Minding Rights: Mapping Ethical and Legal Foundations of 'Neurorights'.

The rise of neurotechnologies, especially in combination with artificial intelligence (AI)-based methods for brain data analytics, has given rise to concerns around the protection of mental privacy, mental integrity and cognitive liberty - often framed as "neurorights" in ethical, legal, and policy discussions. Several states are now looking at including neurorights into their constitutional legal frameworks, and international institutions and organizations, such as UNESCO and the Council of Europe, are taking an active interest in developing international policy and governance guidelines on this issue. However, in many discussions of neurorights the philosophical assumptions, ethical frames of reference and legal interpretation are either not made explicit or conflict with each other. The aim of this multidisciplinary work is to provide conceptual, ethical, and legal foundations that allow for facilitating a common minimalist conceptual understanding of mental privacy, mental integrity, and cognitive liberty to facilitate scholarly, legal, and policy discussions.

How I became myself after merging with a computer: Does human-machine symbiosis raise human rights issues?

Novel usages of brain stimulation combined with artificially intelligent (AI) systems promise to address a large range of diseases. These new conjoined technologies, such as brain-computer interfaces (BCI), are increasingly used in experimental and clinical settings to predict and alleviate symptoms of various neurological and psychiatric disorders. Due to their reliance on AI algorithms for feature extraction and classification, these BCI systems enable a novel, unprecedented, and direct connection between human cognition and artificial information processing. In this paper, we present the results of a study that investigates the phenomenology of human-machine symbiosis during a first-in-human experimental BCI trial designed to predict epileptic seizures. We employed qualitative semi-structured interviews to collect user experience data from a participant over a six-years period. We report on a clinical case where a specific embodied phenomenology emerged: namely, after BCI implantation, the patient reported experiences of increased agential capacity and continuity; and after device explantation, the patient reported persistent traumatic harms linked to agential discontinuity. To our knowledge, this is the first reported clinical case of a patient experiencing persistent agential discontinuity due to BCI explantation and potential evidence of an infringement on patient right, where the implanted person was robbed of her de novo agential capacities when the device was removed.

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study.

BACKGROUND: Increasingly, 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. METHODS: To 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. RESULTS: For 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. CONCLUSION: Our findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies.

Misplaced Trust and Distrust: How Not to Engage with Medical Artificial Intelligence.

Artificial intelligence (AI) plays a rapidly increasing role in clinical care. Many of these systems, for instance, deep learning-based applications using multilayered Artificial Neural Nets, exhibit epistemic opacity in the sense that they preclude comprehensive human understanding. In consequence, voices from industry, policymakers, and research have suggested trust as an attitude for engaging with clinical AI systems. Yet, in the philosophical and ethical literature on medical AI, the notion of trust remains fiercely debated. Trust skeptics hold that talking about trust in nonhuman agents constitutes a category error and worry about the concept being misused for ethics washing. Proponents of trust have responded to these worries from various angles, disentangling different concepts and aspects of trust in AI, potentially organized in layers or dimensions. Given the substantial disagreements across these accounts of trust and the important worries about ethics washing, we embrace a diverging strategy here. Instead of aiming for a positive definition of the elements and nature of trust in AI, we proceed ex negativo, that is we look at cases where trust or distrust are misplaced. Comparing these instances with trust expedited in doctor-patient relationships, we systematize these instances and propose a taxonomy of both misplaced trust and distrust. By inverting the perspective and focusing on negative examples, we develop an account that provides useful ethical constraints for decisions in clinical as well as regulatory contexts and that highlights how we should not engage with medical AI.

The present and future of neural interfaces.

The 2020's decade will likely witness an unprecedented development and deployment of neurotechnologies for human rehabilitation, personalized use, and cognitive or other enhancement. New materials and algorithms are already enabling active brain monitoring and are allowing the development of biohybrid and neuromorphic systems that can adapt to the brain. Novel brain-computer interfaces (BCIs) have been proposed to tackle a variety of enhancement and therapeutic challenges, from improving decision-making to modulating mood disorders. While these BCIs have generally been developed in an open-loop modality to optimize their internal neural decoders, this decade will increasingly witness their validation in closed-loop systems that are able to continuously adapt to the user's mental states. Therefore, a proactive ethical approach is needed to ensure that these new technological developments go hand in hand with the development of a sound ethical framework. In this perspective article, we summarize recent developments in neural interfaces, ranging from neurohybrid synapses to closed-loop BCIs, and thereby identify the most promising macro-trends in BCI research, such as simulating vs. interfacing the brain, brain recording vs. brain stimulation, and hardware vs. software technology. Particular attention is devoted to central nervous system interfaces, especially those with application in healthcare and human enhancement. Finally, we critically assess the possible futures of neural interfacing and analyze the short- and long-term implications of such neurotechnologies.

Mental data protection and the GDPR.

Although decoding the content of mental states is currently unachievable, technologies such as neural interfaces, affective computing systems, and digital behavioral technologies enable increasingly reliable statistical associations between certain data patterns and mental activities such as memories, intentions, and emotions. Furthermore, Artificial Intelligence enables the exploration of these activities not just retrospectively but also in a real-time and predictive manner. In this article, we introduce the notion of 'mental data', defined as any data that can be organized and processed to make inferences about the mental states of a person, including their cognitive, affective and conative states. Further, we analyze existing legal protections for mental data by considering the lawfulness of their processing in light of different legal bases and purposes, with special focus on the EU General Data Protection Regulation (GDPR). We argue that the GDPR is an adequate tool to mitigate risks related to mental data processing. However, we recommend that interpreters focus on processing characteristics, rather than merely on the category of data at issue. Finally, we call for a 'Mental Data Protection Impact Assessment', a specific data protection impact assessment designed to better assess and mitigate the risks to fundamental rights and freedoms associated with the processing of mental data.

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study.

Big data trends in health research challenge the oversight mechanism of the Research Ethics Committees (RECs). The traditional standards of research quality and the mandate of RECs illuminate deficits in facing the computational complexity, methodological novelty, and limited auditability of these approaches. To better understand the challenges facing RECs, we explored the perspectives and attitudes of the members of the seven Swiss Cantonal RECs via semi-structured qualitative interviews. Our interviews reveal limited experience among REC members with the review of big data research, insufficient expertise in data science, and uncertainty about how to mitigate big data research risks. Nonetheless, RECs could strengthen their oversight by training in data science and big data ethics, complementing their role with external experts and ad hoc boards, and introducing precise shared practices.

On Neurorights.

In recent years, philosophical-legal studies on neuroscience (mainly in the fields of neuroethics and neurolaw) have given increasing prominence to a normative analysis of the ethical-legal challenges in the mind and brain sciences in terms of rights, freedoms, entitlements and associated obligations. This way of analyzing the ethical and legal implications of neuroscience has come to be known as "neurorights." Neurorights can be defined as the ethical, legal, social, or natural principles of freedom or entitlement related to a person's cerebral and mental domain; that is, the fundamental normative rules for the protection and preservation of the human brain and mind. Although reflections on neurorights have received ample coverage in the mainstream media and have rapidly become a mainstream topic in the public neuroethics discourse, the frequency of such reflections in the academic literature is still relatively scarce. While the prominence of the neurorights debate in public opinion is crucial to ensure public engagement and democratic participation in deliberative processes on this issue, its relatively sporadic presence in the academic literature poses a risk of semantic-normative ambiguity and conceptual confusion. This risk is exacerbated by the presence of multiple and not always reconcilable terminologies. Several meta-ethical, normative ethical, and legal-philosophical questions need to be solved in order to ensure that neurorights can be used as effective instruments of global neurotechnology governance and be adequately imported into international human rights law. To overcome the shortcomings above, this paper attempts to provide a comprehensive normative-ethical, historical and conceptual analysis of neurorights. In particular, it attempts to (i) reconstruct a history of neurorights and locate these rights in the broader history of idea, (ii) outline a systematic conceptual taxonomy of neurorights, (iii) summarize ongoing policy initiatives related to neurorights, (iv) proactively address some unresolved ethico-legal challenges, and (v) identify priority areas for further academic reflection and policy work in this domain.

Digital Mental Health for Young People: A Scoping Review of Ethical Promises and Challenges.

Mental health disorders are complex disorders of the nervous system characterized by a behavioral or mental pattern that causes significant distress or impairment of personal functioning. Mental illness is of particular concern for younger people. The WHO estimates that around 20% of the world's children and adolescents have a mental health condition, a rate that is almost double compared to the general population. One approach toward mitigating the medical and socio-economic effects of mental health disorders is leveraging the power of digital health technology to deploy assistive, preventative, and therapeutic solutions for people in need. We define "digital mental health" as any application of digital health technology for mental health assessment, support, prevention, and treatment. However, there is only limited evidence that digital mental health tools can be successfully implemented in clinical settings. Authors have pointed to a lack of technical and medical standards for digital mental health apps, personalized neurotechnology, and assistive cognitive technology as a possible cause of suboptimal adoption and implementation in the clinical setting. Further, ethical concerns have been raised related to insufficient effectiveness, lack of adequate clinical validation, and user-centered design as well as data privacy vulnerabilities of current digital mental health products. The aim of this paper is to report on a scoping review we conducted to capture and synthesize the growing literature on the promises and ethical challenges of digital mental health for young people aged 0-25. This review seeks to survey the scope and focus of the relevant literature, identify major benefits and opportunities of ethical significance (e.g., reducing suffering and improving well-being), and provide a comprehensive mapping of the emerging ethical challenges. Our findings provide a comprehensive synthesis of the current literature and offer a detailed informative basis for any stakeholder involved in the development, deployment, and management of ethically-aligned digital mental health solutions for young people.

Digital health interventions for healthy ageing: a qualitative user evaluation and ethical assessment.

BACKGROUND: Digital health technologies are being increasingly developed with the aim of allowing older adults to maintain functional independence throughout the old age, a process known as healthy ageing. Such digital health technologies for healthy ageing are expected to mitigate the socio-economic effects of population ageing and improve the quality of life of older people. However, little is known regarding the views and needs of older people regarding these technologies. AIM: The aim of this study was to explore the views, needs and perceptions of community-dwelling older adults regarding the use of digital health technologies for healthy ageing. METHOD: Face-to-face, in-depth qualitative interviews were conducted with community-dwelling older adults (median age 79.6 years). The interview process involved both abstract reflections and practical demonstrations. The interviews were transcribed verbatim and analyzed according to inductive content analysis. RESULTS: Three main themes and twelve sub-themes addressing our study aim resulted from the data obtained. The main themes revolved around favorable views and perceptions on technology-assisted living, usability evaluations and ethical considerations. CONCLUSIONS: Our study reveals a generally positive attitude towards digital health technologies as participants believed digital tools could positively contribute to improving their overall wellbeing, especially if designed in a patient-centered manner. Safety concerns and ethical issues related to privacy, empowerment and lack of human contact were also addressed by participants as key considerations.

Benefits, challenges, and contributors to success for national eHealth systems implementation: a scoping review.

OBJECTIVE: Our scoping review aims to assess what legal, ethical, and socio-technical factors contribute to or inhibit the success of national eHealth system implementations. In addition, our review seeks to describe the characteristics and benefits of eHealth systems. MATERIALS AND METHODS: We conducted a scoping review of literature published in English between January 2000 and 2020 using a keyword search on 5 databases: PubMed, Scopus, Web of Science, IEEEXplore, and ProQuest. After removal of duplicates, abstract screening, and full-text filtering, 86 articles were included from 8276 search results. RESULTS: We identified 17 stakeholder groups, 6 eHealth Systems areas, and 15 types of legal regimes and standards. In-depth textual analysis revealed challenges mainly in implementation, followed by ethico-legal and data-related aspects. Key factors influencing success include promoting trust of the system, ensuring wider acceptance among users, reconciling the system with legal requirements, and ensuring an adaptable technical platform. DISCUSSION: Results revealed support for decentralized implementations because they carry less implementation and engagement challenges than centralized ones. Simultaneously, due to decentralized systems' interoperability issues, federated implementations (with a set of national standards) might be preferable. CONCLUSION: This study identifies the primary socio-technical, legal, and ethical factors that challenge and contribute to the success of eHealth system implementations. This study also describes the complexities and characteristics of existing eHealth implementation programs, and suggests guidance for resolving the identified challenges.

Ethics review of big data research: What should stay and what should be reformed?

BACKGROUND: Ethics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts. MAIN TEXT: In this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC's scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC's way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science. CONCLUSIONS: We believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large.

The long shadow of childhood cancer: a qualitative study on insurance hardship among survivors of childhood cancer.

BACKGROUND: The long-term consequences of childhood cancer have received increasing attention due to the growing number of survivors over the past decades. However, insurance hardships of survivors are mostly unknown. This study explored qualitatively, in a sample of childhood cancer survivors (CCS), (i) the experiences and needs of CCS living in Switzerland with a special focus on hardships related to insurance; and (ii) the views of insurance and law experts with experience on childhood cancer. METHODS: Semi-structured interviews were conducted with 28 childhood cancer survivors and 3 experts (one legal expert, two insurance experts). Data was analysed using qualitative content analysis. RESULTS: Three key themes emerged from the interviews with the CCS: 1) experiences with insurance, 2) perception of discrimination, and 3) needs and barriers for support. The interviewed experts provided further detailed clarification of CCS' concerns. Our findings indicated that some CCS can move past their cancer history, while others continue to face hardships. CCS reported confusion about the opportunities and services within the social security system and most relied on their personal contacts for guidance. Finally, CCS expressed a strong need for socio-economic and legal support for social insurance questions, especially related to disability insurance. CONCLUSIONS: With the growing population of CCS, it is essential to further assess the interplay between medical and psychosocial health and socio-economic hardship. Supportive psychosocial services should aim to ameliorate insurance hardships. Better understanding of the relationship between childhood cancer and insurance hardships during survivorship will inform efforts to improve long-term financial security and health outcomes for survivors. We call for the public, lawmakers, researchers, insurers, and patient organizations to come together and discuss future perspectives to avoid the risk of discrimination for cancer survivors.

Revolutionizing Medical Data Sharing Using Advanced Privacy-Enhancing Technologies: Technical, Legal, and Ethical Synthesis.

Multisite medical data sharing is critical in modern clinical practice and medical research. The challenge is to conduct data sharing that preserves individual privacy and data utility. The shortcomings of traditional privacy-enhancing technologies mean that institutions rely upon bespoke data sharing contracts. The lengthy process and administration induced by these contracts increases the inefficiency of data sharing and may disincentivize important clinical treatment and medical research. This paper provides a synthesis between 2 novel advanced privacy-enhancing technologies-homomorphic encryption and secure multiparty computation (defined together as multiparty homomorphic encryption). These privacy-enhancing technologies provide a mathematical guarantee of privacy, with multiparty homomorphic encryption providing a performance advantage over separately using homomorphic encryption or secure multiparty computation. We argue multiparty homomorphic encryption fulfills legal requirements for medical data sharing under the European Union's General Data Protection Regulation which has set a global benchmark for data protection. Specifically, the data processed and shared using multiparty homomorphic encryption can be considered anonymized data. We explain how multiparty homomorphic encryption can reduce the reliance upon customized contractual measures between institutions. The proposed approach can accelerate the pace of medical research while offering additional incentives for health care and research institutes to employ common data interoperability standards.

Big Data, Biomedical Research, and Ethics Review: New Challenges for IRBs.

The increased use of big data in the medical field has shifted the way in which biomedical research is designed and carried out. The novelty of techniques and methods brought by big data research brings new challenges to institutional review boards (IRBs). Yet it is unclear if IRBs should be the responsible oversight bodies for big data research and, if so, which criteria they should use. A large but heterogenous set of ethics guidelines and normative responses have emerged to address these issues. In this study, we conducted a scoping review of soft-law documents and guidelines with the aim of assessing ongoing normative efforts that are proliferating in this domain. We also synthesize a set of recurrent guidelines that could work as a baseline to create a harmonized process for big data research ethics.

Data protection and ethics requirements for multisite research with health data: a comparative examination of legislative governance frameworks and the role of data protection technologies.

Personalised medicine can improve both public and individual health by providing targeted preventative and therapeutic healthcare. However, patient health data must be shared between institutions and across jurisdictions for the benefits of personalised medicine to be realised. Whilst data protection, privacy, and research ethics laws protect patient confidentiality and safety they also may impede multisite research, particularly across jurisdictions. Accordingly, we compare the concept of data accessibility in data protection and research ethics laws across seven jurisdictions. These jurisdictions include Switzerland, Italy, Spain, the United Kingdom (which have implemented the General Data Protection Regulation), the United States, Canada, and Australia. Our paper identifies the requirements for consent, the standards for anonymisation or pseudonymisation, and adequacy of protection between jurisdictions as barriers for sharing. We also identify differences between the European Union and other jurisdictions as a significant barrier for data accessibility in cross jurisdictional multisite research. Our paper concludes by considering solutions to overcome these legislative differences. These solutions include data transfer agreements and organisational collaborations designed to `front load' the process of ethics approval, so that subsequent research protocols are standardised. We also allude to technical solutions, such as distributed computing, secure multiparty computation and homomorphic encryption.

Digital tools against COVID-19: taxonomy, ethical challenges, and navigation aid.

Data collection and processing via digital public health technologies are being promoted worldwide by governments and private companies as strategic remedies for mitigating the COVID-19 pandemic and loosening lockdown measures. However, the ethical and legal boundaries of deploying digital tools for disease surveillance and control purposes are unclear, and a rapidly evolving debate has emerged globally around the promises and risks of mobilising digital tools for public health. To help scientists and policy makers to navigate technological and ethical uncertainty, we present a typology of the primary digital public health applications that are in use. These include proximity and contact tracing, symptom monitoring, quarantine control, and flow modelling. For each, we discuss context-specific risks, cross-sectional issues, and ethical concerns. Finally, recognising the need for practical guidance, we propose a navigation aid for policy makers and other decision makers for the ethical development and use of digital public health tools.