In recent years, there has been an increasing interest in developing and using artificial intelligence (AI) models in pathology. Although pathologists generally have a positive attitude toward AI, they report a lack of knowledge and skills regarding how to use it in practice. Furthermore, it remains unclear what skills pathologists would require to use AI adequately and responsibly. However, adequate training of (future) pathologists is essential for successful AI use in pathology. In this paper, we assess which entrustable professional activities (EPAs) and associated competencies pathologists should acquire in order to use AI in their daily practice. We make use of the available academic literature, including literature in radiology, another image-based discipline, which is currently more advanced in terms of AI development and implementation. Although microscopy evaluation and reporting could be transferrable to AI in the future, most of the current pathologist EPAs and competencies will likely remain relevant when using AI techniques and interpreting and communicating results for individual patient cases. In addition, new competencies related to technology evaluation and implementation will likely be necessary, along with knowing one’s own strengths and limitations in human-AI interactions. Because current EPAs do not sufficiently address the need to train pathologists in developing expertise related to technology evaluation and implementation, we propose a new EPA to enable pathology training programs to make pathologists fit for the new AI era “using AI in diagnostic pathology practice” and outline its associated competencies.@en

Employee-driven innovation (EDI) burgeons as an important mechanism to drive the exploration activities by making the general employees responsible for innovation. However, little is known about the conditions under which EDI is most effective. To get a better understanding of EDI, we examine how Stedin, an established global player within the energy distribution industry based in the Netherlands, involves its general employees in innovation activities. Stedin actively supports EDI through strategic programmes designed to stimulate employee innovation. Our findings highlight that collaboration is a main driver of EDI at Stedin. In the early implementation phases, dynamic, heterogeneous, informal and distant collaborations are essential, while the later phases benefit from more stability and intimacy. The insights from our detailed case study provide actionable guidelines for organising EDI initiatives in practice.

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This open access book advances a modest defence of technological utopias. While technological utopianism is not devoid of risks and elitism, their benefits should not be discounted in an overall assessment. Rather than rejecting them based on a too narrow definition of utopianism, we must acknowledge their potential to exceed the individualist vs. collectivist dichotomy ascribed to traditional utopias. The author argues, with reference to Rawls’ idea of the basic structure that technological utopias challenge our understanding of the scope and location of justice and, thereby, advance the idea of justice. The book critically reviews the most recent literature in political philosophy, where utopias are understood as ideal theories of justice and sides with recent contributions to Utopian Studies, where utopias’ potential to estrange from the present and galvanize action are underscored.@en

After years of missing the agreed upon goals for carbon reduction, we might conclude that global climate policies set infeasible standards to halt climate change. The widespread non-compliance of many signees with frameworks such as the Paris Agreement indicates that these frameworks were too optimistic regarding the signees’ motivation to act. One of the suggested ways out of this impasse, is geoengineering, which is seen as a “techno-fix” of the non-compliance problem, relieving signees and other actors of some, or most, of their mitigation duties. This paper scrutinizes different approaches towards climate mitigation that focus on behavioral change or on technological solutions. We argue that these different approaches do not originate from categorically different theories of climate justice. Indeed, seemingly realistic and seemingly idealistic proposals do not disagree on the substance of climate justice, but about what is to be considered feasible. Furthermore, by applying this dialectic lens on ideal vs. non-ideal theorizing in the context of climate justice, we show that (backward-looking) residual responsibility is an overlooked aspect of geoengineering as a (forward-looking) non-ideal approach to achieve climate justice. We will outline three possible consequences of this moral residue: 1) Residual responsibility can provide grounds to demand compensation, 2) it can constitute other forward-looking responsibilities (e.g., the maintenance of geoengineering technologies) and 3) it provides a reason to employ other techno-fixes equal in effectiveness and risks that do not sidestep the problem of non-compliance.@en

The present chapter begins by exploring whether the project of a hermeneutic technology assessment (TA) squares well with some of TA's most fundamental presuppositions and commitments including, for instance, to provide assessments that are relevant for policymakers and can guide the shaping of emerging technologies in a responsible manner. If – as will be shown – the hermeneutic idea can be coherently established within TA, we must ask what does an understanding of emerging technologies in their guise as futuristic narratives entail? Which questions do we have to ask, to gain a better understanding of future technologies in their manifold present representations? The present chapter approaches these questions by examining the cases of nanotechnology and “Slaughterbots.” This will result in a demarcation of various dimensions and a list of questions about the origins and guise of those narratives that can be posed at other narratives of this sort. Taken together, this chapter makes some major steps towards a toolkit for applying the hermeneutic research lens to various socio-technical visions and narratives.@en

Der vorliegende Aufsatz geht zwei Fragen nach: Sind digitale Utopien „echte Utopien“? Und, was ist der Wert solcher Narrative? Diese Fragen sind von besonderer Signifikanz: Anlehnend an klassische Argumente in der politischen Philosophie stehen digitalen Utopien in der Kritik. Wie politische Utopien, die häufig als unrealisierbar gelten, lenkten auch digitale Utopien von Wichtigerem ab und schürten Hoffnungen, die unerfüllt bleiben müssen. Träfe dies zu, wären digitale Utopien gefährlich und man müsse Abstand halten. Aber was ist deren Wert? Einem vernünftigen Begriff von „Utopie“ folgend, lässt sich diese Frage in drei Teilfragen untergliedern: Stellen sie einen wünschenswerten Zustand dar, sind sie realisierbar und stellen sie eine Kritik der vorherrschenden Gesellschaftsordnung vor? Insbesondere letzterer Aspekt lohnt sich genauerer Prüfung. Dazu werden wir uns zwei paradigmatische, digitale Utopien ansehen: Digitalisierte Medizin und den Transhumanismus. Jüngere Argumente in der politischen Philosophie suggerieren, dass es intrinsisch wertvoll ist, ein besseres Verständnis von einer idealen Gesellschaft zu haben. Ginge es in digitalen Utopien also ebenfalls um die ideale Gesellschaft, träfe das Argument des intrinsischen Wertes auch auf digitale Utopien zu. @en

In the medical literature, promising results regarding accuracy of medical AI are presented as claims for its potential to increase efficiency. This elision of concepts is misleading and incorrect. First, the promise that AI will reduce human workload rests on a too narrow assessment of what constitutes workload in the first place. Human operators need new skills and deal with new responsibilities, these systems need an elaborate infrastructure and support system that all contribute to an increased amount of human work and short-term efficiency wins may become sources of long-term inefficiency. Second, for the realization of increased efficiency, the human-side of technology implementation is determinate. Human knowledge, competencies and trust can foster or undermine efficiency. We conclude that is important to remain conscious and critical about how we talk about expected benefits of AI, especially when referring to systemic changes based on single studies.@en

Martin Sand and Luca Chiapperino find in the concept of serendipity a versatile umbrella term to reassess their previous work on moral luck and collective responsibility. Moral luck supposedly occurs when someone receives praise or blame for things beyond control. Given the ubiquity of luck, this seems to be a seriously disquieting aspect of ordinary morality. The rewards and recognition for serendip-itous discoveries fall into exactly this category. That is: more than the intentions, actions, and characters of scientists matters for discoveries to obtain, just as in cases of moral luck something beyond morality affects our moral judgments. Even if a theo-retical way of resolving the conceptual ambiguities that underlie this debate were found, there remain practical questions of how to perform stratification in science and innovation in ways that both hinge on, and yet refrain from, considerations of desert and achievement. With the example of Edward Jenner's luck-and serendipity-infused discovery of vaccination, the authors attempt to better understand the intricate value trade-offs that underlie stratification policies in science, which have to be constantly re-negotiated to maintain their legitimacy. Thereby, Sand and Ciapperino aim to take a bold step towards understanding the ethics of serendipity.

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AI is believed to have the potential to radically change modern medicine. Medical AI systems are developed to improve diagnosis, prediction, and treatment of a wide array of medical conditions. It is assumed to enable more accurate and efficient ways to diagnose diseases and “to restore the precious and time-honored connection and trust – the human touch – between patients and doctors“ (Topol, 2019, p. 18), by enabling health care professionals to spend more time with their patients. Sophisticated self-learning AI systems that do not follow predetermined decision rules – often referred to as black-boxes (Esteva et al 2019; Shortliffe et al 2018) – have spawned philosophical debate: the black-box nature of AI systems is believed to be a major ethical challenge for the use of these systems in medicine and it remains disputed whether explainability is philosophically and computationally possible. This special issue focuses on the ethics and epistemology of explainability in medical AI broadly construed.@en

Governments and companies are increasingly promoting and organizing Responsible Innovation. It is, however, unclear how the seemingly incompatible demands for responsibility, which is associated with care and caution, can be harmonized with demands for innovation, which is associated with risk-taking and speed. We turn to the tradition of virtue ethics and argue that it can be a strong accomplice to Responsible Innovation by focussing on the agential side of innovation. Virtue ethics offers an adequate response to the epistemic and moral complexity in innovation and encourages moral behaviour. We enumerate a number of virtues that people involved in Responsible Innovation would need to cultivate both related to responsibility, such as justice, anticipation, civility and inclusion, and virtues related to innovation, such as courage, dedication, curiosity and creativity. We put forward practical wisdom (phronesis) as a key virtue to regulate relevant virtues and to deal with the tension between responsibility and innovation. Practical wisdom helps an agent to find an appropriate mean in exercising and expressing the other virtues—where the mean is relative to the specific context of action and the role and abilities of the agent.@en

Medical AI is increasingly being developed and tested to improve medical diagnosis, prediction and treatment of a wide array of medical conditions. Despite worries about the explainability and accuracy of such medical AI systems, it is reasonable to assume that they will be increasingly implemented in medical practice. Current ethical debates focus mainly on design requirements and suggest embedding certain values such as transparency, fairness, and explainability in the design of medical AI systems. Aside from concerns about their design, medical AI systems also raise questions with regard to physicians' responsibilities once these technologies are being implemented and used. How do physicians’ responsibilities change with the implementation of medical AI? Which set of competencies do physicians have to learn to responsibly interact with medical AI? In the present article, we will introduce the notion of forward-looking responsibility and enumerate through this conceptual lens a number of competencies and duties that physicians ought to employ to responsibly utilize medical AI in practice. Those include amongst others understanding the range of reasonable outputs, being aware of own experience and skill decline, and monitoring potential accuracy decline of the AI systems.@en

The nexus of the moral luck debate is the control principle, which says that people are responsible only for things within their control. In this paper, I will first argue that the control principle should be restrained to blameworthiness, because responsibility is too wide a concept to square with control. Many deniers of moral luck appeal to the intuitiveness of the control principle. Defenders of moral luck do not share this intuition and demand a stronger defence of the control principle. I will establish a defence of the control principle based on the value of simplicity for selecting a theory of blameworthiness. A simpler theory of blameworthiness is more likely to be true, and not being falsely judged blameworthy is desirable. I will conclude that simplicity advices the acceptance of the control principle over other theories of blameworthiness that embrace factors beyond control.@en

Scientific discoveries are often to some degree influenced by luck. Whether luck’s influence is at odds with common-sense intuitions about responsibility, is the central concern of the philosophical debate about moral luck. Do scientists acknowledge that luck plays a role in their work and–if so–do they consider it morally problematic? The present article discusses the results of four focus groups with scientists, who were asked about their views on luck in their fields and its moral implications. The participants underscored circumstantial luck as a key dimension of luck in science. Nevertheless, most participants insisted that there are ways of executing ‘control’ in science: They believe that virtues and skills can increase one’s chances for success. The cultivation of these skills and virtues was considered a reasonable ground for pride. Prizes and rewards were rarely tied to personal desert, but instead to their societal function.

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