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.

Towards a Governance Framework for Brain Data

The increasing availability of brain data within and outside the biomedical field, combined with the application of artificial intelligence (AI) to brain data analysis, poses a challenge for ethics and governance. We identify distinctive ethical implications of brain data acquisition and processing, and outline a multi-level governance framework. This framework is aimed at maximizing the benefits of facilitated brain data collection and further processing for science and medicine whilst minimizing risks and preventing harmful use. The framework consists of four primary areas of regulatory intervention: binding regulation, ethics and soft law, responsible innovation, and human rights.

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.

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.

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.

Uninformed consent: Who knows what Ivan Ilyich would have thought?

Abstract

In the modern era, when prolonging life is not an option, the end-of-life discussions are unavoidably influenced by Neuroethics. Despite this, it is interestingly evident how the sentiments of a terminal patient of 1885 and a physician of 2020, are still comparable. This paper pre-sents the arguments behind the so-called "Therapeutic Misconception" and the aim of palliative care to provide dying patients support. It is essential to address priorities of informed consent, signed before any remedy is provided. A key component of the newest Neuroscience research is the analysis of motivation and free will. So, it is necessary to comprehend if the patient struggles to feel at peace with these aspects of his "right to die": Is he free to choose or is he influenced by the doctors? Is this confusion an example of "Therapeutic Misconception"? Is his Informed Consent totally "Informed"? In order to broaden our understanding, we account for many critical situations, such as the mentally impaired Psychiatric patients or the famous Italian case of Eluana Englaro. In addition, we suggested some current approaches such as Artificial Intelligence, useful in preserving some cognitive functions the patient may have lost. Furthermore, research in this field is very critical and in some Catholic countries like Italy, people faced difficulties accepting the idea of the "Anticipated directives". In general, whatever the mental status and whatever the terminal state, the patients seem still far from handling their own auto-determination and their Consent, even if the ultimate goal is to die with dignity.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02338-z.

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.

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.

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.

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.

Digital Predictors of Morbidity, Hospitalization, and Mortality Among Older Adults: A Systematic Review and Meta-Analysis

The widespread adoption of digital health technologies such as smartphone-based mobile applications, wearable activity trackers and Internet of Things systems has rapidly enabled new opportunities for predictive health monitoring. Leveraging digital health tools to track parameters relevant to human health is particularly important for the older segments of the population as old age is associated with multimorbidity and higher care needs. In order to assess the potential of these digital health technologies to improve health outcomes, it is paramount to investigate which digitally measurable parameters can effectively improve health outcomes among the elderly population. Currently, there is a lack of systematic evidence on this topic due to the inherent heterogeneity of the digital health domain and the lack of clinical validation of both novel prototypes and marketed devices. For this reason, the aim of the current study is to synthesize and systematically analyse which digitally measurable data may be effectively collected through digital health devices to improve health outcomes for older people. Using a modified PICO process and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, we provide the results of a systematic review and subsequent meta-analysis of digitally measurable predictors of morbidity, hospitalization, and mortality among older adults aged 65 or older. These findings can inform both technology developers and clinicians involved in the design, development and clinical implementation of digital health technologies for elderly citizens.

On The Verge of the Hybrid Mind

Recent advances in neurotechnology allow for an increasingly tight integration of the human brain and mind with artificial cognitive systems, blending persons with technologies and creating an assemblage that we call a hybrid mind. In some ways the mind has always been a hybrid, emerging from the interaction of biology, culture (including technological artifacts) and the natural environment. However, with the emergence of neurotechnologies enabling bidirectional flows of information between the brain and AI-enabled devices, integrated into mutually adaptive assemblages, we have arrived at a point where the specific examination of this new instantiation of the hybrid mind is essential. Among the critical questions raised by this development are the effects of these devices on the user’s perception of the self, and on the user’s experience of their own mental contents. Questions arise related to the boundaries of the mind and body and whether the hardware and software that are functionally integrated with the body and mind are to be viewed as parts of the person or separate artifacts subject to different legal treatment. Other questions relate to how to attribute responsibility for actions taken as a result of the operations of a hybrid mind, as well as how to settle questions of the privacy and security of information generated and retained within a hybrid mind.

Artificial Intelligence in Clinical Neuroscience: Methodological and Ethical Challenges

Clinical neuroscience is increasingly relying on the collection of large volumes of differently structured data and the use of intelligent algorithms for data analytics. In parallel, the ubiquitous collection of unconventional data sources (e.g. mobile health, digital phenotyping, consumer neurotechnology) is increasing the variety of data points. Big data analytics and approaches to Artificial Intelligence (AI) such as advanced machine learning are showing great potential to make sense of these larger and heterogeneous data flows. AI provides great opportunities for making new discoveries about the brain, improving current preventative and diagnostic models in both neurology and psychiatry and developing more effective assistive neurotechnologies. Concurrently, it raises many new methodological and ethical challenges. Given their transformative nature, it is still largely unclear how AI-driven approaches to the study of the human brain will meet adequate standards of scientific validity and affect normative instruments in neuroethics and research ethics. This manuscript provides an overview of current AI-driven approaches to clinical neuroscience and an assessment of the associated key methodological and ethical challenges. In particular, it will discuss what ethical principles are primarily affected by AI approaches to human neuroscience, and what normative safeguards should be enforced in this domain.

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.

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.

"Hunting Down My Son's Killer": New Roles of Patients in Treatment Discovery and Ethical Uncertainty

The past few years have witnessed several media-covered cases involving citizens actively engaging in the pursuit of experimental treatments for their medical conditions-or those of their loved ones-in the absence of established standards of therapy. This phenomenon is particularly observable in patients with rare genetic diseases, as the development of effective therapies for these disorders is hindered by the limited profitability and market value of pharmaceutical research. Sociotechnical trends at the cross-section of medicine and society are facilitating the involvement of patients and creating the digital infrastructure necessary to its sustainment. Such participant-led research (PLR) has the potential to promote the autonomy of research participants as drivers of discovery and to open novel non-canonical avenues of scientific research. At the same time, however, the extra-institutional, self-appointed, and, often, oversight-free nature of PLR raises ethical concern. This paper explores the complex ethical entanglement of PLR by critically appraising case studies and discussing the conditions for its moral justification. Furthermore, we propose a path forward to ensure the safe and effective implementation of PLR within the current research ecosystem in a manner that maximizes the benefits for both individual participants and society at large, while minimizing the risks.

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.

Ethical concerns with the use of intelligent assistive technology: findings from a qualitative study with professional stakeholders

Background

Advances in artificial intelligence (AI), robotics and wearable computing are creating novel technological opportunities for mitigating the global burden of population ageing and improving the quality of care for older adults with dementia and/or age-related disability. Intelligent assistive technology (IAT) is the umbrella term defining this ever-evolving spectrum of intelligent applications for the older and disabled population. However, the implementation of IATs has been observed to be sub-optimal due to a number of barriers in the translation of novel applications from the designing labs to the bedside. Furthermore, since these technologies are designed to be used by vulnerable individuals with age- and multi-morbidity-related frailty and cognitive disability, they are perceived to raise important ethical challenges, especially when they involve machine intelligence, collect sensitive data or operate in close proximity to the human body. Thus, the goal of this paper is to explore and assess the ethical issues that professional stakeholders perceive in the development and use of IATs in elderly and dementia care.

Methods

We conducted a multi-site study involving semi-structured qualitative interviews with researchers and health professionals. We analyzed the interview data using a descriptive thematic analysis to inductively explore relevant ethical challenges.

Results

Our findings indicate that professional stakeholders find issues of patient autonomy and informed consent, quality of data management, distributive justice and human contact as ethical priorities. Divergences emerged in relation to how these ethical issues are interpreted, how conflicts between different ethical principles are resolved and what solutions should be implemented to overcome current challenges.

Conclusions

Our findings indicate a general agreement among professional stakeholders on the ethical promises and challenges raised by the use of IATs among older and disabled users. Yet, notable divergences persist regarding how these ethical challenges can be overcome and what strategies should be implemented for the safe and effective implementation of IATs. These findings provide technology developers with useful information about unmet ethical needs. Study results may guide policy makers with firsthand information from relevant stakeholders about possible solutions for ethically-aligned technology governance.

Ethical challenges associated with health-related big data research

Big data trends in biomedical and public health research hold promise for improving prevention, enabling earlier diagnosis, optimizing resource allocation, and delivering more tailored treatments to patients with specific disease trajectories. At the same time, due to their methodological novelty, algorithmic complexity and reliance on data mining for knowledge generation, big data approaches raise ethical challenges. This talk presents an overview of the major ethical challenges associated with health-related big data research. These include demarcating the boundary between personal health data and non-health data, re-defining the notion of private information, sustaining trust in health data sharing, preventing data-driven discrimination and ensuring a fair distribution of benefits and burdens among all stakeholders. Case studies from dementia research and public mental health will be discussed to illustrate these challenges and provide an ethical assessment. Furthermore, this talk will provide an overview of the normative proposals that have been recently advanced to align health-related big data research with established regulatory frameworks such as data protection regulation, regulation on human subject research and ethics review. Based on this analysis, suggestions will be made on how to maximise the benefits of big data for public health while minimizing ethical risks.

Correction to: Synthetic Biology and the Translational Imperative

The author group of above-mentioned review paper was incorrectly published in the online article.

Synthetic Biology and the Translational Imperative

Advances at the interface between the biological sciences and engineering are giving rise to emerging research fields such as synthetic biology. Harnessing the potential of synthetic biology requires timely and adequate translation into clinical practice. However, the translational research enterprise is currently facing fundamental obstacles that slow down the transition of scientific discoveries from the laboratory to the patient bedside. These obstacles including scarce financial resources and deficiency of organizational and logistic settings are widely discussed as primary impediments to translational research. In addition, a number of socio-ethical considerations inherent in translational research need to be addressed. As the translational capacity of synthetic biology is tightly linked to its social acceptance and ethical approval, ethical limitations may-together with financial and organizational problems-be co-determinants of suboptimal translation. Therefore, an early assessment of such limitations will contribute to proactively favor successful translation and prevent the promising potential of synthetic biology from remaining under-expressed. Through the discussion of two case-specific inventions in synthetic biology and their associated ethical implications, we illustrate the socio-ethical challenges ahead in the process of implementing synthetic biology into clinical practice. Since reducing the translational lag is essential for delivering the benefits of basic biomedical research to society at large and promoting global health, we advocate a moral obligation to accelerating translational research: the "translational imperative."

Dual use in the 21st century: emerging risks and global governance

Dual use research of concern (DURC) is defined by the World Health Organization as "life sciences research that is intended for benefit, but which might easily be misapplied to do harm." Ethical and policy discussions on DURC span the past three decades. Today, however, new and emerging technologies and associated sociocultural transformations within the scientific community are reshaping the current risk scenario. This paper identifies three major trends that are likely to characterise dual use dilemmas in the near future: the diversification of dual use domains, the digitalisation of potential threats and the proliferation of actors. This analysis illustrates an increasingly heterogeneous and fragmented risk scenario, which can hardly be effectively governed top-down from a centralised authority. We propose that in order to meet the critical challenges of dual use in the 21st century, a global and distributed governance is needed. In contrast to globally binding sets of legal mechanisms administered by a central and hierarchical authority supported by leading powers, we suggest a global and decentralised governance architecture encompassing multilevel, multipolar and bottom-up strategies that can stretch across a spectrum of stakeholders and scientific domains in an agile, proactive and adaptive manner. Finally, we discuss how Switzerland can take a leading role in the promotion and development of this global governance architecture.

Considerations for ethics review of big data health research: A scoping review

Big data trends in biomedical and health research enable large-scale and multi-dimensional aggregation and analysis of heterogeneous data sources, which could ultimately result in preventive, diagnostic and therapeutic benefit. The methodological novelty and computational complexity of big data health research raises novel challenges for ethics review. In this study, we conducted a scoping review of the literature using five databases to identify and map the major challenges of health-related big data for Ethics Review Committees (ERCs) or analogous institutional review boards. A total of 1093 publications were initially identified, 263 of which were included in the final synthesis after abstract and full-text screening performed independently by two researchers. Both a descriptive numerical summary and a thematic analysis were performed on the full-texts of all articles included in the synthesis. Our findings suggest that while big data trends in biomedicine hold the potential for advancing clinical research, improving prevention and optimizing healthcare delivery, yet several epistemic, scientific and normative challenges need careful consideration. These challenges have relevance for both the composition of ERCs and the evaluation criteria that should be employed by ERC members when assessing the methodological and ethical viability of health-related big data studies. Based on this analysis, we provide some preliminary recommendations on how ERCs could adaptively respond to those challenges. This exploration is designed to synthesize useful information for researchers, ERCs and relevant institutional bodies involved in the conduction and/or assessment of health-related big data research.

What Is Trust? Ethics and Risk Governance in Precision Medicine and Predictive Analytics

Trust is a ubiquitous term used in emerging technology (e.g., Big Data, precision medicine), innovation policy, and governance literatures in particular. But what exactly is trust? Even though trust is considered a critical requirement for the successful deployment of precision medicine initiatives, nonetheless, there is a need for further conceptualization with regard to what qualifies as trust, and what factors might establish and sustain trust in precision medicine, predictive analytics, and large-scale biology. These new fields of 21st century medicine and health often deal with the “futures” and hence, trust gains a temporal and ever-present quality for both the present and the futures anticipated by new technologies and predictive analytics. We address these conceptual gaps that have important practical implications in the way we govern risk and unknowns associated with emerging technologies in biology, medicine, and health broadly. We provide an in-depth conceptual analysis and an operative definition of trust dynamics in precision medicine. In addition, we identify three main types of “trust facilitators”: (1) technical, (2) ethical, and (3) institutional. This three-dimensional framework on trust is necessary to building and maintaining trust in 21st century knowledge-based innovations that governments and publics invest for progressive societal change, development, and sustainable prosperity. Importantly, we analyze, identify, and deliberate on the dimensions of precision medicine and large-scale biology that have carved out trust as a pertinent tool to its success. Moving forward, we propose a “points to consider” on how best to enhance trust in precision medicine and predictive analytics.

Ethical Design of Intelligent Assistive Technologies for Dementia: A Descriptive Review

The use of Intelligent Assistive Technology (IAT) in dementia care opens the prospects of reducing the global burden of dementia and enabling novel opportunities to improve the lives of dementia patients. However, with current adoption rates being reportedly low, the potential of IATs might remain under-expressed as long as the reasons for suboptimal adoption remain unaddressed. Among these, ethical and social considerations are critical. This article reviews the spectrum of IATs for dementia and investigates the prevalence of ethical considerations in the design of current IATs. Our screening shows that a significant portion of current IATs is designed in the absence of explicit ethical considerations. These results suggest that the lack of ethical consideration might be a codeterminant of current structural limitations in the translation of IATs from designing labs to bedside. Based on these data, we call for a coordinated effort to proactively incorporate ethical considerations early in the design and development of new products.

Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy

Emerging trends in pervasive computing and medical informatics are creating the possibility for large-scale collection, sharing, aggregation and analysis of unprecedented volumes of data, a phenomenon commonly known as big data. In this contribution, we review the existing scientific literature on big data approaches to dementia, as well as commercially available mobile-based applications in this domain. Our analysis suggests that big data approaches to dementia research and care hold promise for improving current preventive and predictive models, casting light on the etiology of the disease, enabling earlier diagnosis, optimizing resource allocation, and delivering more tailored treatments to patients with specific disease trajectories. Such promissory outlook, however, has not materialized yet, and raises a number of technical, scientific, ethical, and regulatory challenges. This paper provides an assessment of these challenges and charts the route ahead for research, ethics, and policy.

Towards new human rights in the age of neuroscience and neurotechnology

Rapid advancements in human neuroscience and neurotechnology open unprecedented possibilities for accessing, collecting, sharing and manipulating information from the human brain. Such applications raise important challenges to human rights principles that need to be addressed to prevent unintended consequences. This paper assesses the implications of emerging neurotechnology applications in the context of the human rights framework and suggests that existing human rights may not be sufficient to respond to these emerging issues. After analysing the relationship between neuroscience and human rights, we identify four new rights that may become of great relevance in the coming decades: the right to cognitive liberty, the right to mental privacy, the right to mental integrity, and the right to psychological continuity.

Proactive Ethical Design for Neuroengineering, Assistive and Rehabilitation Technologies: the Cybathlon Lesson

Background

Rapid advancements in rehabilitation science and the widespread application of engineering techniques are opening the prospect of a new phase of clinical and commercial maturity for Neuroengineering, Assistive and Rehabilitation Technologies (NARTs). As the field enters this new phase, there is an urgent need to address and anticipate the ethical implications associated with novel technological opportunities, clinical solutions, and social applications.

Main idea

In this paper we review possible approaches to the ethics of NART, and propose a framework for ethical design and development, which we call the Proactive Ethical Design (PED) framework.

Conclusion

A viable ethical framework for neuroengineering, assistive and rehabilitation technology should be characterized by the convergence of user-centered and value-sensitive approaches to product design through a proactive mode of ethical evaluation. We propose four basic normative requirements for the realization of this framework: minimization of power imbalances, compliance with biomedical ethics, translationality and social awareness. The aims and values of the CYBATHLON competition provide an operative model of this ethical framework and could drive an ethical shift in neuroengineering and rehabilitation.