As the artificial intelligence (AI) ethics field is currently working towards its operationalisation, ethics review as carried out by research ethics committees (RECs) constitutes a powerful, but so far underdeveloped, framework to make AI ethics effective in practice at the research level. This article contributes to the elaboration of research ethics frameworks for research projects developing and/or using AI. It highlights that these frameworks are still in their infancy and in need of a structure and criteria to ensure AI research (...) projects advance in a way that respects norms and principles. This article proposes to draw from the European Union’s AI Act currently in development to shape these frameworks. Although, in the current form of the draft (as of August 2023), the obligations of the AI Act do not apply to scientific research, it is most likely that they will still have a strong impact on AI research considering the need to anticipate market placement or to test new tools in real world conditions. This article investigates what the risk-based approach in the AI Act implies for research ethics and highlights some AI Act obligations of particular value to implement for ethics review processes. (shrink)

Background The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022. Methods The GFBR is an annual meeting organized by the World Health (...) Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022. Results We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships. Conclusions The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research. (shrink)

Zusammenfassung Die Forschungs- und Regulierungsebene bei datenintensiver Forschung in der Medizin liegen auseinander. Ein heterogenes Feld aus regulierenden Institutionen mit regional ungleichen Regelungen, sowohl hinsichtlich der Dichte als auch der Restriktivität von Regelungen, steht einer globalen Entwicklung der Technologien entgegen. Trotz oder gerade wegen mangelnder global-gültiger Regulierungen können auch unverbindliche oder nur bedingt verbindliche normative Vorgaben der Orientierung dienen. Doch wie soll eine solche normative Regulierung angesichts datenintensiver Forschung in der Medizin ausgestaltet werden und woran soll sie sich orientieren? Die (...) Frage, wie konkret und detailliert man eine solche Forschung regulieren sollte, lässt sich nur im Einzelfall für bestimmte Situationen und Institutionen beantworten. Ob dabei neue Normen oder Gewichtungen von Normen vorgenommen werden sollen, oder ob die Normen und deren Gewichtung weiterhin bestehen bleiben sollen, lässt sich nur mit Verweis auf starke normative Argumente beantworten. An zwingenden Argumenten für neue Normen angesichts der datenintensiven medizinischen Forschung mangelt es bisher. Dennoch ist eine Umsetzungsarbeit von Normen, egal ob neue oder alte, und deren Anwendung auf eine neue Methode oder Technologie allemal zu erbringen. Es bedarf daher – wie schon bisher – beider: sowohl etablierter und transparent kommunizierter Normen als auch des unabhängigen Urteils zur Anwendung dieser Normen. Angesichts der besonderen Eignung für diese Aufgabe sollten auch weiterhin Ethik-Kommissionen als prozedurale Instanz bei der Bewilligung von datenintensiver Forschung in der Medizin gefordert und befähigt werden, die als unabhängige Institution ein Urteil im Einzelfall anhand vorgegebener Normen fällen. Nichtsdestotrotz können sich die veränderten Praktiken datenintensiver Forschungsprojekte auch in neuen Anforderungen an Ethik-Kommissionen niederschlagen, denen mit Reformen der Arbeitsweise begegnet werden sollte. (shrink)

Mental health-related data generated by app users during the routine use of Consumer Mental Health Apps (CMHAs) are being increasingly leveraged for research and product improvement studies. However, it remains unclear which ethical safeguards and practices should be implemented by researchers and app developers to protect users during these studies, and concerns have been raised over their current implementation in CMHAs. To better understand which ethical safeguards and practices are implemented, why and how, 17 app developers and researchers were interviewed (...) who had been involved in using CMHA data for studies. Interviewees discussed the impact on stakeholder interests, sufficiency thresholds and procedural alterations of informed consent, data protection, gathering app user perspectives and representing users in app design and study conduct, and ensuring adequate support. Although the reasoning behind how and why these ethical safeguards and practices should be implemented showed considerable variability and several gaps, interviewees converged on various general lines of reasoning. This allowed for the development of a coherent and nuanced account that could prove useful for future CMHA studies and which could stimulate further normative investigation of the role of ethical safeguards and practices in these studies. (shrink)

Machine learning heralds highly transformative approaches to the automation of numerous clinical tasks, from diagnosis to risk assessment, and from prognosis to informing treatment decisions....

This paper explores that the topic of ethics dumping, its causes and potential remedies. In ED, the weaknesses or gaps in ethics policies and systems of lower income countries are intentionally exploited for intellectual or financial gains through research and publishing by higher income countries with a more stringent or complex ethical infrastructure in which such research and publishing practices would not be permitted. Several examples are provided. Possible ED needs to be evaluated before research takes place, and detected prior (...) to publication as an academic paper, because it might lead to a collaborative effort between a wealthier country with restrictive ethical policies and a less wealthy country with more permissive policies. Consequently, if that collaboration ultimately results in an academic paper, there are ethical ramifications of ED to scholarly communication. Institutional review board approval is central to avoid ED-based collaborations. Blind trust and goodwill alone cannot eliminate the exploitation of indigenous or “vulnerable” populations’ intellect and resources. Combining community-based participatory research using clear codes of research conduct and a simple but robust verification system in academic publishing may reduce the risks of ED-based research from being published. (shrink)

The ethical review of research using methods of artificial intelligence and machine learning in health care contexts has become an important challenge for Research Ethics Boards (also refer...

The application of artificial intelligence and machine learning technologies in healthcare have immense potential to improve the care of patients. While there are some emerging practices surro...

While open science gains prominence in South Africa with the encouragement of open data sharing for research purposes, there are stricter laws and regulations around privacy – and specifically the use, management and transfer of personal information – to consider. The Protection of Personal Information Act No. 4 of 2013 (POPIA), which came into effect in 2021, established stringent requirements for the processing of personal information and has changed the regulatory landscape for the transfer of personal information across South African (...) borders. At the same time, draft national policies on open science encourage wide accessibility to data and open data sharing in line with international best practice. As a result, the operation of research ethics committees (RECs) in South Africa is affected by the conflicting demands of the shift towards open science on the one hand, and the stricter laws protecting participants’ personal information and the transfer thereof, on the other. This article explores the continuing evolving role of RECs in the era of open data and recommends the development of a data transfer agreement (DTA) for the ethical management of personal health information, considering the challenges that RECs encounter, which centres predominantly on privacy, data sharing and access concerns following advances in genetic and genomic research and biobanking. (shrink)

BackgroundIt has been argued that ethics review committees—e.g., Research Ethics Committees, Institutional Review Boards, etc.— have weaknesses in reviewing big data and artificial intelligence research. For instance, they may, due to the novelty of the area, lack the relevant expertise for judging collective risks and benefits of such research, or they may exempt it from review in instances involving de-identified data.Main bodyFocusing on the example of medical research databases we highlight here ethical issues around de-identified data sharing which motivate the (...) need for review where oversight by ethics committees is weak. Though some argue for ethics committee reform to overcome these weaknesses, it is unclear whether or when that will happen. Hence, we argue that ethical review can be done by data access committees, since they have de facto purview of big data and artificial intelligence projects, relevant technical expertise and governance knowledge, and already take on some functions of ethical review. That said, like ethics committees, they may have functional weaknesses in their review capabilities. To strengthen that function, data access committees must think clearly about the kinds of ethical expertise, both professional and lay, that they draw upon to support their work.ConclusionData access committees can undertake ethical review of medical research databases provided they enhance that review function through professional and lay ethical expertise. (shrink)

Harms and risks to groups and third-parties can be significant in the context of research, particularly in data-centric studies involving genomic, artificial intelligence, and/or machine learning technologies. This article explores whether and how United States federal regulations should be adapted to better align with current ethical thinking and protect group interests. Three aspects of the Common Rule deserve attention and reconsideration with respect to group interests: institutional review board (IRB) assessment of the risks/benefits of research; disclosure requirements in the informed (...) consent process; and criteria for waivers of informed consent. In accordance with respect for persons and communities, investigators and IRBs should systematically consider potential group harm when designing and reviewing protocols, respectively. Research participants should be informed about any potential group harm in the consent process. We call for additional public discussion, empirical research, and normative analysis on these issues to determine the right regulatory and policy path forward. (shrink)

Developments in medical big data analytics may bring societal benefits but are also challenging privacy and other ethical values. At the same time, an overly restrictive data protection regime can form a serious threat to valuable observational studies. Discussions about whether data privacy or data solidarity should be the foundational value of research policies, have remained unresolved. We add to this debate with an empirically informed ethical analysis. First, experiences with the implementation of the General Data Protection Regulation (GDPR) within (...) a European research consortium demonstrate a gap between the aims of the regulation and its effects in practice. Namely, strictly formalised data protection requirements may cause routinisation among researchers instead of substantive ethical reflection, and may crowd out trust between actors in the health data research ecosystem; while harmonisation across Europe and data sharing between countries is hampered by different interpretations of the law, which partly stem from different views about ethical values. Then, building on these observations, we use theory to argue that the concept of trust provides an escape from the privacy-solidarity debate. Lastly, the paper details three aspects of trust that can help to create a responsible research environment and to mitigate the encountered challenges: trust as multi-agent concept; trust as a rational and democratic value; and trust as method for priority setting. Mutual cooperation in research—among researchers and with data subjects—is grounded in trust, which should be more explicitly recognised in the governance of health data research. (shrink)