Alex John London

BackgroundAlthough commonly used to evaluate health interventions, cluster randomized trials raise difficult ethical issues. Recognizing this, the Ottawa Statement on the Ethical Design and Conduct of Cluster Randomized Trials, published in 2012, provides 15 recommendations to address ethical issues across seven domains. But due to several developments in the design and implementation of cluster randomized trials, there are new issues requiring guidance. To inform the forthcoming update of the Ottawa Statement, we aimed to identify any gaps in the Ottawa Statement discussed within the literature.MethodsWe searched Google Scholar, Scopus, and Web of Science using the ‘cited by’ function on 11 November 2022.We included all types of publications, including articles, book chapters, commentaries, editorials, ethics guidelines, theses and trial-related publications (i.e., primary reports, protocols, and secondary analyses), that cited and engaged with the Ottawa Statement, the Ottawa Statement précis, or one or more of its four background papers. Data were extracted by four reviewers working in rotating pairs. Reviewers captured relevant text verbatim and recorded whether it reflected a gap relating to one or more of the Ottawa Statement domains. Using a thematic analysis approach, semantic coding was used to summarize the content of the data into distinct gaps within the Ottawa Statement domains, which was subsequently expanded in an inductive manner through discussion.ResultsThe qualitative analysis of the text from 53 articles resulted in the identification of 24 distinct gaps in the Ottawa Statement: 4 gaps about justifying the cluster randomized design; 2 gaps about research ethics committee review; 3 gaps about identifying research participants; 4 gaps about obtaining informed consent; 3 gaps about gatekepeers; 6 gaps about assessing benefits and harms; 1 gap about protecting vulnerable participants; and 1 gap about equity-related issues in cluster randomized trials.ConclusionIdentifying 24 gaps reveals a need to update the Ottawa Statement. Alongside additional gaps identified in ongoing empirical work and through engagement with our patient and public partners, the gaps identified through this citation analysis should be considered in the forthcoming Ottawa Statement update.

The threat of biological and chemical terrorism highlights a growing tension in research ethics between respecting the interests of individuals and safeguarding and protecting the common good. But what it actually means to protect the common good is rarely scrutinized. There are two conceptions of the common good that provide very different accounts of the limits of permissible medical research. Decisions about the limits of acceptable medical research in defense of the common good should be carried out only within the latter framework.

Recent claims that artificial intelligence (AI) systems demonstrate “emergent abilities” have fueled excitement but also fear grounded in the prospect that such systems may enable a wider range of parties to make unprecedented advances in areas that include the development of chemical or biological weapons. Ambiguity surrounding the term “emergent abilities” has added avoidable uncertainty to a topic that has the potential to destabilize the strategic landscape, including the perception of key parties about the viability of nonproliferation efforts. To avert these problems in the future, scientists, developers, policymakers, and other parties should take cred- ible steps to strengthen the health of the scientific ecosystem around AI.

Innovation is disruptive and a deeply social phenomenon. As a result, discussions of innovation in the Anglo-American philosophical tradition are often tightly bound up with concerns about individual freedom and pluralism, including pluralism about ethical values. In response, stakeholders looking to evaluate and assess ethical aspects of the innovation ecosystem are often driven to pragmatic approaches that utilize a set of ethical values that can be regarded as “free-standing,” or “thin” in the sense that they are not tied to any particular, substantive conception of the good. This set often includes values such as beneficence, nonmaleficence, respect for autonomy, fairness, and justice. Discussions focused on justice, however, are the least extensive and least well-developed. As a result, most approaches are well-suited to surfacing first-order or direct effects of the discrete activities of a relatively narrow set of stakeholders. Paradoxically, however, such analyses are often not well-suited to identifying and evaluating (a) quintessentially social or higher-order effects (such as network-level or institutional level effects), (b) the role of a larger number of stakeholders who shape the innovation ecosystem in more indirect ways, and (c) some of the positive ethical claims of individuals that are relevant to evaluating innovation. After articulating these shortcomings, I argue that they might be overcome by adopting a justice-led framework for evaluating innovation.

Recent claims that artificial intelligence (AI) systems demonstrate “emergent abilities” have fueled excitement but also fear grounded in the prospect that such systems may enable a wider range of parties to make unprecedented advances in areas that include the development of chemical or biological weapons. Ambiguity surrounding the term “emergent abilities” has added avoidable uncertainty to a topic that has the potential to destabilize the strategic landscape, including the perception of key parties about the viability of nonproliferation efforts. To avert these problems in the future, scientists, developers, policymakers, and other parties should take credible steps to strengthen the health of the scientific ecosystem around AI.

The prevailing discourse around AI ethics lacks the language and formalism necessary to capture the diverse ethical concerns that emerge when AI systems interact with individuals. Drawing on Sen and Nussbaum’s capability approach, we present a framework formalizing a network of ethical concepts and entitlements necessary for AI systems to confer meaningful benefit or assistance to stakeholders. Such systems enhance stakeholders’ ability to advance their life plans and well-being while upholding their fundamental rights. We characterize two necessary conditions for morally permissible interactions between AI systems and those impacted by their functioning, and two sufficient conditions for realizing the ideal of meaningful benefit. We then contrast this ideal with several salient failure modes, namely, forms of social interactions that constitute unjustified paternalism, coercion, deception, exploitation and domination. The proliferation of incidents involving AI in high-stakes domains underscores the gravity of these issues and the imperative to take an ethics-led approach to AI systems from their inception.

The prevailing discourse around AI ethics lacks the language and formalism necessary to capture the diverse ethical concerns that emerge when AI systems interact with individuals. Drawing on Sen and Nussbaum's capability approach, we present a framework formalizing a network of ethical concepts and entitlements necessary for AI systems to confer meaningful benefit or assistance to stakeholders. Such systems enhance stakeholders' ability to advance their life plans and well-being while upholding their fundamental rights. We characterize two necessary conditions for morally permissible interactions between AI systems and those impacted by their functioning, and two sufficient conditions for realizing the ideal of meaningful benefit. We then contrast this ideal with several salient failure modes, namely, forms of social interactions that constitute unjustified paternalism, coercion, deception, exploitation and domination. The proliferation of incidents involving AI in high-stakes domains underscores the gravity of these issues and the imperative to take an ethics-led approach to AI systems from their inception.

ABSTRACT:The judgments of conscientious and informed experts play a central role in two elements of clinical equipoise. The first, and most widely discussed, element involves ensuring that no participant in a randomized trial is allocated to a level of treatment that everyone agrees is substandard. The second, and less often discussed, element involves ensuring that trials are likely to generate social value by producing the information necessary to resolve a clinically meaningful uncertainty or disagreement about the relative merits of a set of interventions. The distribution of judgments in expert communities can take many forms, each with important implications for whether a trial satisfies one or both elements of clinical equipoise. In this article we use a graphical approach to represent three ways in which expert community uncertainty can vary: by spread, modality, and skew. Understanding these different distributions of expert judgment has three important implications: it helps to make operational the requirement of social value, it shows that some conditions for initiating studies to promote social value diverge from common assumptions about clinical equipoise, and it has important implications for how trials should be designed and monitored, and what patients should be told during informed consent.

When health budgets are insufficient to provide care for all, allocating resources to treat a person with a rare and expensive disorder entails that we cannot treat at least one person with a more common, less expensive disorder. Since any allocation scheme will entail such trade‐offs, how should prudent policy‐makers, concerned about justice and fairness, allocate their community's health resources? In their article in this issue of the Hastings Center Report, Emily Largent and Steven Pearson frame this problem as a conflict between the “rule of rescue” and utilitarian allocation schemes that try to maximize the benefits produced by a given budget. In his article, Norman Daniels discusses the related problem of the “identified victim bias.” I doubt that the problem of crafting an equitable health policy regarding orphan diseases maps onto either of these factors in a way that sheds light on the key moral issues.

Abstract:This paper considers novel ethical issues pertaining to near-future artificial intelligence (AI) systems that seek to support, maintain, or enhance the capabilities of older adults as they age and experience cognitive decline. In particular, we focus on smart assistants (SAs) that would seek to provide proactive assistance and mediate social interactions between users and other members of their social or support networks. Such systems would potentially have significant utility for users and their caregivers if they could reduce the cognitive load for tasks that help older adults maintain their autonomy and independence. However, proactively supporting even simple tasks, such as providing the user with a summary of a meeting or a conversation, would require a future SA to engage with ethical aspects of human interactions which computational systems currently have difficulty identifying, tracking, and navigating. If SAs fail to perceive ethically relevant aspects of social interactions, the resulting deficit in moral discernment would threaten important aspects of user autonomy and well-being. After describing the dynamic that generates these ethical challenges, we note how simple strategies for prompting user oversight of such systems might also undermine their utility. We conclude by considering how near-future SAs could exacerbate current worries about privacy, commodification of users, trust calibration and injustice.

There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to overcome structural problems in the culture and practice of medicine and the organization of health systems that impact the data from which AI models are built, the environments into which they will be deployed, and the practices and incentives that structure their development. This perspective elaborates on some of these structural challenges and provides recommendations to address potential shortcomings.

Respect for patient autonomy can apply at two levels: ensuring that patient care reflects their considered values and wishes and honoring patient preferences about how to make momentous decisions. Caregivers who seek to respect patient autonomy in the context of some end-of-life decisions face a dilemma. Because these decisions are fraught, patients may prefer to approach them sequentially, only making decisions at the time they arise. However, respecting patients’ preferences for a sequential approach can increase the likelihood that surrogates and care teams wind up in situations in which they lack information needed to ensure patients receive care that conforms to their considered values after they are no longer competent to make decisions for themselves. Sequential decision-making can thus conflict with the goal of ensuring care reflects the wishes of patients. After illustrating how this dilemma can arise in the use of life-sustaining “bridge” technologies, we argue that care teams may be warranted in requiring patients to articulate their wishes in an advance care plan before treatment begins. In some cases, care teams may even be permitted to refuse to undertake certain courses of care, unless patients articulate their wishes in an advance care plan.

The foundations of research ethics are riven with fault lines emanating from a fear that if research is too closely connected to weighty social purposes an imperative to advance the common good through research will justify abrogating the rights and welfare of study participants. The result is an impoverished conception of the nature of research, an incomplete focus on actors who bear important moral responsibilities, and a system of ethics and oversight highly attuned to the dangers of research but largely silent about threats of ineffective, inefficient, and inequitable medical practices and health systems. In For the Common Good: Philosophical Foundations of Research Ethics, Alex John London defends a conception of the common good that grounds a moral imperative with two requirements. The first is to promote research that generates the information necessary to enable key social institutions to effectively, efficiently, and equitably safeguard the basic interests of individuals. The second is to ensure that research is organized as a voluntary scheme of social cooperation that respects its various contributors' moral claims to be treated as free and equal. Connecting research to the goals of a just social order grounds a framework for assessing and managing research risk that reconciles these requirements and justifies key oversight practices in non-paternalistic terms. Reconceiving research ethics as resolving coordination problems and providing credible assurance that these requirements are being met expands the issues and actors that fall within the purview of the field and provides the foundation for a more unified and coherent approach to domestic and international research. This is an open access title available under the terms of a CC BY-NC-ND 4.0 license. It is free to read at Oxford Scholarship Online and offered as a free PDF download from OUP and selected open access locations.

Little research has explored the possible effects of government institutions in emerging economies on ethical reviews of multinational research. We conducted semi-structured, in-depth telephone interviews with 15 researchers, Research Ethics Committees personnel, and a government agency member involved in multinational HIV Prevention Trials Network research in emerging economies. Ministries of Health or other government agencies often play pivotal roles as facilitators or barriers in the research ethics approval process. Government agency RECs reviewing protocols may face particular challenges, as they can lack resources, be poorly organized, have inconsistent review processes and limited expertise, and use differing definitions of national interests, including upholding national reputation and avoiding potential exploitation and stigma of the country's population. The MOH/governmental review body may be affected by power dynamics and politics in study reviews; may consider issues both related and unrelated to research ethics as understood elsewhere; and may prioritize particular diseases, treatments, or interventions over other topics/types of research. Poor communication and deeply-rooted tensions may exist between sponsor and host countries, impeding optimal interactions and reviews. Investigators must understand and plan for the potential effects of governmental agencies on multinational collaborative research, including preserving adequate time for agency review, and contacting these agencies beforehand to address issues that may arise. Better understanding of these issues can aid and advance appropriate global scientific collaboration.

International non-governmental organisations face a dilemma when deciding whether to intervene in crisis situations where their efforts can be exploited or co-opted by others: intervene and risk becoming complicit with wrongdoing or sit on the sidelines and consign vulnerable people to the ravages of neglect or oppression. In “‘He who helps the guilty, shares the crime’? INGOs, moral narcissism and complicity in wrongdoing,” Buth et al argue that concerns about complicity often stifle ethical debate and encourage moral narcissism. We argue that neglecting concerns about complicity can foster a different form of moral narcissism and that where worries of complicity are present, aid efforts face three types of risk: risks to others created by contributing to wrongful acts or bad outcomes; risks to the moral integrity of the INGO and its personnel; and risks to social trust in the INGO. In the end, we challenge the assumption that there is a unique, ethically best way to reconcile these values. We suggest that the causes of justice and humanity might be better served by a diverse community of INGOs who each gives different weight to these concerns, than if each INGO adopts the same framework for reconciling these competing demands.

This dissertation explores Plato's conception of the nature and value of wisdom and its relationship to the ethical virtues. It is argued that throughout what are referred to as Plato's early and middle dialogues, wisdom is identified with the political art and that, as such, those, dialogues consistently treat moral knowledge as a kind of craft knowledge. When this conception of wisdom is combined with the Socratic doctrine of the unity of the virtues, however, it raises serious problems for Socrates' ethical theory. It is argued that the dilemma that results in the Euthydemus highlights these problems and that there is an important sense in which the Lysis, Gorgias, and Republic represent attempts to solve this dilemma. It is argued that in the early dialogues Plato focuses solely on the contributive value of virtue but that in these latter dialogues Plato changes his account of the nature and value of the ethical virtues. In these dialogues Plato articulates what I will call the "constitutive value" of virtue, where the value of the virtues is rooted the way in which they constitute the good order of the soul. Ultimately, this allows the ethical virtues to be put forth as the beneficial work that wisdom provides for us. A central goal of the dissertation, then, is to explain this new account of the value of the virtues and to explain the sense in which wisdom rules over or governs the other parts of the soul so as to make the soul good. In this way, the dissertation deals centrally with Plato's conception of value and his moral psychology