Making good decisions in extremely complex and difficult processes and situations has always been both a key task as well as a challenge in the clinic and has led to a large amount of clinical, legal and ethical routines, protocols and reflections in order to guarantee fair, participatory and up-to-date pathways for clinical decision-making. Nevertheless, the complexity of processes and physical phenomena, time as well as economic constraints and not least further endeavours as well as achievements in medicine and healthcare (...) continuously raise the need to evaluate and to improve clinical decision-making. This article scrutinises if and how clinical decision-making processes are challenged by the rise of so-called artificial intelligence-driven decision support systems (AI-DSS). In a first step, this article analyses how the rise of AI-DSS will affect and transform the modes of interaction between different agents in the clinic. In a second step, we point out how these changing modes of interaction also imply shifts in the conditions of trustworthiness, epistemic challenges regarding transparency, the underlying normative concepts of agency and its embedding into concrete contexts of deployment and, finally, the consequences for (possible) ascriptions of responsibility. Third, we draw first conclusions for further steps regarding a ‘meaningful human control’ of clinical AI-DSS. (shrink)

When making substituted judgments for incapacitated patients, surrogates often struggle to guess what the patient would want if they had capacity. Surrogates may also agonize over having the (sole) responsibility of making such a determination. To address such concerns, a Patient Preference Predictor (PPP) has been proposed that would use an algorithm to infer the treatment preferences of individual patients from population-level data about the known preferences of people with similar demographic characteristics. However, critics have suggested that even if such (...) a PPP were more accurate, on average, than human surrogates in identifying patient preferences, the proposed algorithm would nevertheless fail to respect the patient’s (former) autonomy since it draws on the ‘wrong’ kind of data: namely, data that are not specific to the individual patient and which therefore may not reflect their actual values, or their reasons for having the preferences they do. Taking such criticisms on board, we here propose a new approach: the Personalized Patient Preference Predictor (P4). The P4 is based on recent advances in machine learning, which allow technologies including large language models to be more cheaply and efficiently ‘fine-tuned’ on person-specific data. The P4, unlike the PPP, would be able to infer an individual patient’s preferences from material (e.g., prior treatment decisions) that is in fact specific to them. Thus, we argue, in addition to being potentially more accurate at the individual level than the previously proposed PPP, the predictions of a P4 would also more directly reflect each patient’s own reasons and values. In this article, we review recent discoveries in artificial intelligence research that suggest a P4 is technically feasible, and argue that, if it is developed and appropriately deployed, it should assuage some of the main autonomy-based concerns of critics of the original PPP. We then consider various objections to our proposal and offer some tentative replies. (shrink)

In discourses on digitization and the data economy, it is often claimed that data subjects shall beownersof their data. In this paper, we provide a problem diagnosis for such calls fordata ownership: a large variety of demands are discussed under this heading. It thus becomes challenging to specify what—if anything—unites them. We identify four conceptual dimensions of calls for data ownership and argue that these help to systematize and to compare different positions. In view of this pluralism of data ownership (...) claims, we introduce, spell out and defend a constructive interpretative proposal: claims for data ownership are charitably understood as attempts to call for theredistributionof material resources and the socio-culturalrecognitionof data subjects. We argue that as one consequence of this reading, it misses the point to reject claims for data ownership on the grounds that property in data does not exist. Instead, data ownership brings to attention a claim to renegotiate such aspects of thestatus quo. (shrink)

Simulations are used in very different contexts and for very different purposes. An emerging development is the possibility of using simulations to obtain a more or less representative reproduction of organs or even entire persons. Such simulations are framed and discussed using the term ‘digital twin’. This paper unpacks and scrutinises the current use of such digital twins in medicine and the ideas embedded in this practice. First, the paper maps the different types of digital twins. A special focus is (...) put on the concrete challenges inherent in the interactions between persons and their digital twin. Second, the paper addresses the questions of how far a digital twin can represent a person and what the consequences of this may be. Against the background of these two analytical steps, the paper defines first conditions for digital twins to take on an ethically justifiable form of representation. (shrink)

Trust is one of the big buzzwords in debates about the shaping of society, democracy, and emerging technologies. For example, one prominent idea put forward by the High‐Level Expert Group on Artificial Intelligence appointed by the European Commission is that artificial intelligence should be trustworthy. In this essay, we explore the notion of trust and argue that both proponents and critics of trustworthy AI have flawed pictures of the nature of trust. We develop an approach to understanding trust in AI (...) that does not conceive of trust merely as an accelerator for societal acceptance of AI technologies. Instead, we argue, trust is granted through leaps of faith. For this reason, trust remains precarious, fragile, and resistant to promotion through formulaic approaches. We also highlight the significance of distrust in societal deliberation, as it is relevant to trust in various and intricate ways. Among the fruitful aspects of distrust is that it enables individuals to forgo technology if desired, to constrain its power, and to exercise meaningful human control. (shrink)

New data-driven technologies yield benefits and potentials, but also confront different agents and stakeholders with challenges in retaining control over their data. Our goal in this study is to arrive at a clear picture of what is meant by data sovereignty in such problem settings. To this end, we review 341 publications and analyze the frequency of different notions such as data sovereignty, digital sovereignty, and cyber sovereignty. We go on to map agents they concern, in which context they appear, (...) and which values they allude to. While our sample reveals a considerable degree of divergence and an occasional lack of clarity about intended meanings of data sovereignty, we propose a conceptual grid to systematize different dimensions and connotations. Each of them relates in some way to meaningful control, ownership, and other claims to data articulated by a variety of agents ranging from individuals to countries. Data sovereignty alludes to a nuanced mixture of normative concepts such as inclusive deliberation and recognition of the fundamental rights of data subjects. (shrink)

This paper argues that data-driven medicine gives rise to a particular normative challenge. Against the backdrop of a distinction between the good and the right, harnessing personal health data towards the development and refinement of data-driven medicine is to be welcomed from the perspective of the good. Enacting solidarity drives progress in research and clinical practice. At the same time, such acts of sharing could—especially considering current developments in big data and artificial intelligence—compromise the right by leading to injustices and (...) affecting concrete modes of individual self-determination. In order to address this potential tension, two key elements for ethical reflection on data-driven medicine are proposed: the controllability of information flows, including technical infrastructures that are conducive towards controllability, and a paradigm shift towards output-orientation in governance and policy. (shrink)

It is very timely and highly important to think the relationship between theological and philosophical ethics. In this issue, Michael McCarthy et al. make a plea for a stronger dialogue...

In the article ‘Represent Me: Please! Towards an Ethics of Digital Twins in Medicine’, I analysed and tried to better understand the main ethical challenges associated with Digital Twins. For those who are just entering the debate with this article: DT is a metaphor for a bundle of artificial intelligence driven simulation technologies that constantly, in real time and ad personam simulate single or multiple parts of the body and make predictions about future health states based on these simulations. My (...) argument addresses the need to look at the breadth of challenges through a perspective of representation. From such a take, key consequences can be drawn for the further development of such technologies, the required means of control and not least the way to think about the interaction between humans and ‘their’ simulations. I am very grateful for the subsequent suggestions, criticisms and further arguments, which have helped me to elaborate my arguments more clearly and have led to a substantial advancement of the debate and the discussion about ethical questions in dealing with DT. Jenny Blumenthal-Barby,1 Deborah Lupton,2 Jenny Krutzinna,3 Janina Loh,4 Brent Mittelstadt,5 Sven Nyholm,6 Daniel Tigard7 and Max Tretter8 have made excellent points, which, in the following, I will not be able to reply to individually and in detail. In this response, I will try to bundle the open points and questions along the comments and considerations mentioned above and attempt to outline their significance for an ethics of DT. Four challenges seem to be central. A first point addresses anthropological issues. It is concerned …. (shrink)

This open access book presents an ethical approach to utilizing personal medical data. It features essays that combine academic argument with practical application of ethical principles. The contributors are experts in ethics and law. They address the challenges in the re-use of medical data of the deceased on a voluntary basis. This pioneering study looks at the many factors involved when individuals and organizations wish to share information for research, policy-making, and humanitarian purposes. Today, it is easy to donate blood (...) or even organs, but it is virtually impossible to donate one’s own medical data. This is seen as ethically unacceptable. Yet, data donation can greatly benefit the welfare of our societies. This collection provides timely interdisciplinary research on biomedical big data. Topics include the ethics of data donation, the legal and regulatory challenges, and the current and future collaborations. Readers will learn about the ethical and regulatory challenges associated with medical data donations. They will also better understand the special nature of using deceased data for research purposes with regard to ethical principles of autonomy, beneficence, and justice. In addition, the contributors identify the key governance issues of such a scheme. The essays also look at what we can learn in terms of best practice from existing medical data schemes. (shrink)

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

Genome Editing Techniques are seen to be at the frontier of current research in the field of emerging biotechnologies. The latest revolutionary development, the so-called CRISPR technology, represents a paradigmatic example of the ambiguity of such techniques and has resulted in an international interdisciplinary debate on whether or not it is necessary to ban the application of this technique by means of a moratorium on its use for human germline modifications, particularly in human embryos in the reproduction process. However, given (...) that other germline engineering techniques like mitochondrial DNA transfer techniques are already permitted and applied, the question arises what lies at the root of the apparent social unease about the modification of the human germline by Genome Editing Techniques like CRISPR. Against this background, the book seeks to make a substantial contribution to the current debate about a responsible and participatory framework for research on emerging biotechnologies by analysing underlying perceptions, attitudes, arguments and the reasoning on Genome Editing Techniques. (shrink)

Die vorliegende Studie empfiehlt, Leistungsansprüche für Personen mit interventionsfordernden Risiken anhand einer neuen Rechtskategorie, der ‚risikoadaptieren Prävention‘, abzubilden. Spätestens seit dem bioinformatischen Innovationsschub kann eine risikoadaptierte Anwendung von prophylaktischen Maßnahmen umfassend gewährleistet werden. Jedoch können die gegebenen Rechtskategorien das medizinische Anwendungsfeld nicht adäquat steuern. Die Autoren Friedhelm Meier, Anke Harney, Kerstin Rhiem, Anja Neumann, Silke Neusser, Matthias Braun, Jürgen Wasem, Rita Schmutzler, Stefan Huster und Peter Dabrock haben zusammen im BMBF geförderten Projekt SYSKON. Re-Konfiguration von Gesundheit und Krankheit. Ethische, psychosoziale, (...) rechtliche und gesundheitsökonomische Herausforderungen der Systemmedizin die vorliegende Governance Perspective erarbeitet. This book is published open access under a CC BY 4.0 license. (shrink)

Genome editing techniques are seen to be at the frontier of current research in the field of emerging biotechnologies. However, such biotechnological research is tensioned at the interface of science, technology and society. On the one hand, this means that it offers a tremendous potential to provide new concepts, methods and – in the long run – novel applications for urgent challenges and needs within society.

According to the judgement of the European Court of Justice in 2014, human parthenogenetic stem cells are excluded from the patenting prohibition of procedures based on hESC by the European Biopatent Directive, because human parthenotes are not human embryos. This article is based on the thesis that in light of the technological advances in the field of stem cell research, the attribution of the term ‘human embryo’ to certain entities on a descriptive level as well as the attribution of a (...) normative protection status to certain entities based on the criterion of totipotency, are becoming increasingly unclear. The example of human parthenotes in particular demonstrates that totipotency is not at all a necessary condition for the attribution of the term ‘human embryo’. Furthermore, the example of hiPSC and somatic cells particularly shows that totipotency is also not a sufficient condition for the attribution of a normative protection status to certain entities. Therefore, it is not a suitable criterion for distinguishing between human embryos worthy of protection and human non-embryos not worthy of protection. Consequently, this conclusion has repercussions for the patenting question. The strict delineation between an ethically problematic commercial use of human embryos and the concomitant patenting prohibition of hESC-based procedures and an ethically unproblematic commercial use of human non-embryos and the therefore either unrestrictedly permitted or even unregulated patenting of procedures based on these alleged alternatives becomes increasingly blurred. (shrink)

Critics currently argue that applied ethics approaches to artificial intelligence (AI) are too principles-oriented and entail a theory–practice gap. Several applied ethical approaches try to prevent such a gap by conceptually translating ethical theory into practice. In this article, we explore how the currently most prominent approaches of AI ethics translate ethics into practice. Therefore, we examine three approaches to applied AI ethics: the embedded ethics approach, the ethically aligned approach, and the Value Sensitive Design (VSD) approach. We analyze each (...) of these three approaches by asking how they understand and conceptualize theory and practice. We outline the conceptual strengths as well as their shortcomings: an embedded ethics approach is context-oriented but risks being biased by it; ethically aligned approaches are principles-oriented but lack justification theories to deal with trade-offs between competing principles; and the interdisciplinary Value Sensitive Design approach is based on stakeholder values but needs linkage to political, legal, or social governance aspects. Against this background, we develop a meta-framework for applied AI ethics conceptions with three dimensions. Based on critical theory, we suggest these dimensions as starting points to critically reflect on the conceptualization of theory and practice. We claim, first, that the inclusion of the dimension of affects and emotions in the ethical decision-making process stimulates reflections on vulnerabilities, experiences of disregard, and marginalization already within the AI development process. Second, we derive from our analysis that considering the dimension of justifying normative background theories provides both standards and criteria as well as guidance for prioritizing or evaluating competing principles in cases of conflict. Third, we argue that reflecting the governance dimension in ethical decision-making is an important factor to reveal power structures as well as to realize ethical AI and its application because this dimension seeks to combine social, legal, technical, and political concerns. This meta-framework can thus serve as a reflective tool for understanding, mapping, and assessing the theory–practice conceptualizations within AI ethics approaches to address and overcome their blind spots. (shrink)

Artificial intelligence is currently changing many areas of society. Especially in health, where critical decisions are made, questions of control must be renegotiated: who is in control when an automated system makes clinically relevant decisions? Increasingly, the concept of meaningful human control (MHC) is being invoked for this purpose. However, it is unclear exactly how this concept is to be understood in health. Through a systematic review, we present the current state of the concept of MHC in health. The results (...) show that there is not yet a robust MHC concept for health. We propose a broader understanding of MHC along three strands of action: enabling, exercising and evaluating control. Taking into account these strands of action and the established rules and processes in the different health sectors, the MHC concept needs to be further developed to avoid falling into two gaps, which we have described as theoretical and labelling gaps. (shrink)

In today’s world, Artificial Intelligence plays a central role in many decision-making processes. However, its use can lead to structural and epistemic injustices—especially in the context of healt...

Neben grundsätzlichen konzeptionellen Fragen der sog. Individualisierten Medizin (IM), prägen ethische Bedenken und Fragen die aktuellen Debatten um die IM. Allerdings ist bislang noch nicht geklärt, in welchem methodischen Rahmen diese Fragen verortet werden können. Für die Entwicklung eines solchen Rahmens wird das Modell der First- und Second-Wave-Bioethics diskutiert und an zwei konkreten Herausforderungen – 1) dem Verhältnis der IM zur evidenz-basierten Medizin und 2) am Konzept der genetischen Risikoperson – aufgezeigt. Eine solche Kontextualisierung der IM-Debatte legt den Grundstein für (...) eine adäquate Erfassung und Bearbeitung sozialethischer Fragen (z. B. im Hinblick auf das Problem der Eigenverantwortung). (shrink)

ZusammenfassungNeben grundsätzlichen konzeptionellen Fragen der sog. Individualisierten Medizin (IM), prägen ethische Bedenken und Fragen die aktuellen Debatten um die IM. Allerdings ist bislang noch nicht geklärt, in welchem methodischen Rahmen diese Fragen verortet werden können. Für die Entwicklung eines solchen Rahmens wird das Modell der First- und Second-Wave-Bioethics diskutiert und an zwei konkreten Herausforderungen – 1) dem Verhältnis der IM zur evidenz-basierten Medizin und 2) am Konzept der genetischen Risikoperson – aufgezeigt. Eine solche Kontextualisierung der IM-Debatte legt den Grundstein für (...) eine adäquate Erfassung und Bearbeitung sozialethischer Fragen (z. B. im Hinblick auf das Problem der Eigenverantwortung). (shrink)

ZusammenfassungNeben grundsätzlichen konzeptionellen Fragen der sog. Individualisierten Medizin, prägen ethische Bedenken und Fragen die aktuellen Debatten um die IM. Allerdings ist bislang noch nicht geklärt, in welchem methodischen Rahmen diese Fragen verortet werden können. Für die Entwicklung eines solchen Rahmens wird das Modell der First- und Second-Wave-Bioethics diskutiert und an zwei konkreten Herausforderungen – 1) dem Verhältnis der IM zur evidenz-basierten Medizin und 2) am Konzept der genetischen Risikoperson – aufgezeigt. Eine solche Kontextualisierung der IM-Debatte legt den Grundstein für eine (...) adäquate Erfassung und Bearbeitung sozialethischer Fragen. (shrink)

Name der Zeitschrift: Jahrbuch für Wissenschaft und Ethik Jahrgang: 18 Heft: 1 Seiten: 173-198.

The book considers the relationship between governance and participation, and the ways participation has been understood, framed and applied in the context of synthetic biology (SB) governance approaches. Based on fundamental questions about the scope, purpose, and responsibilities assigned to public participation activities, the authors conducted an literature review of policy reports and articles on SB governance. The authors identify key characteristics of synthetic biology, such as the complex interplay of research, engineering and IT expertise in the field, as well (...) as the challenges these characteristics pose in designing governance frameworks. Drawing on insights from a literature review, the authors contest calls for “earlier” and “more” participation on the basis that such calls fail to consider the necessary structural adjustments and resources needed for such endeavors. The brief addresses ethical questions arising in synthetic biology that could be used for developing frameworks of governance in the ongoing COVID-19 crisis and the consequent innovations in vaccine research. (shrink)