M. Sand
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Technological challenges have recently created a need to more sharply distinguish ethics from political philosophy of technology. Are there compelling arguments that warrant pursuing a political philosophy of technology as an autonomous endeavor aside from an ethics of technology and what would its content be? The present paper responds to those two questions. Via a critical discussion of three existing views on this relationship, I will argue that the best starting point for a political philosophy of technology originates from the prevalence and intractability of reasonable disagreement. I will extend this general suggestion, forcefully defended by Charles Larmore, with the condition that such reasonable disagreement needs resolution in some situations, due to urgency and the suboptimal outcomes that ensue if no decision is reached. Many current technological challenges have those characteristics. In my conclusions, I will briefly outline how investigations of technological utopias could contribute to discussions about reasonable disagreement, thereby, opening a fruitful avenue for future research in political philosophy of technology.
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Technological challenges have recently created a need to more sharply distinguish ethics from political philosophy of technology. Are there compelling arguments that warrant pursuing a political philosophy of technology as an autonomous endeavor aside from an ethics of technology and what would its content be? The present paper responds to those two questions. Via a critical discussion of three existing views on this relationship, I will argue that the best starting point for a political philosophy of technology originates from the prevalence and intractability of reasonable disagreement. I will extend this general suggestion, forcefully defended by Charles Larmore, with the condition that such reasonable disagreement needs resolution in some situations, due to urgency and the suboptimal outcomes that ensue if no decision is reached. Many current technological challenges have those characteristics. In my conclusions, I will briefly outline how investigations of technological utopias could contribute to discussions about reasonable disagreement, thereby, opening a fruitful avenue for future research in political philosophy of technology.
The Ethics and Epistemology of Clinician-AI Disagreement in Medicine
Beyond Opposition
The integration of AI systems in medical care magnifies questions related to how physicians should work with such systems to ensure the best patient outcomes. A particularly thorny issue is related to dealing with situations of possible disagreement between an AI system’s recommendation and the course of medical action envisaged by a human clinician. The current academic debate has so far suggested three possible ways of dealing with such clinician-AI disagreements. First, by considering when clinicians are justified in deferring to the AI output (what we call the deference approach), second when the human user overrules the AI system’s output in cases of disagreement (the overruling approach), and lastly when a second human opinion is deemed necessary to resolve disagreements (the second opinion approach). In this paper, we aim to spell out the shortcomings of these three approaches for dealing with clinician-AI disagreement and offer a more nuanced perspective on such disagreements. We argue that differentiation between types of disagreements, taking into account the role attributed to AI in medical practice, is essential before determining how clinician-AI disagreements should be dealt with. By drawing on a case that exemplifies how multifaceted medical decision-making is, we point out the normative implications of possible clinician-AI disagreements ensuing from it. We highlight the distinctive uncertainties inherent to medical decision-making, showing that disagreements in these contexts are not merely unavoidable but can even be epistemically valuable. Ultimately, by considering the epistemic positions of clinicians and AI systems, our analysis raises important questions for the epistemology of disagreement that need timely attention.
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The integration of AI systems in medical care magnifies questions related to how physicians should work with such systems to ensure the best patient outcomes. A particularly thorny issue is related to dealing with situations of possible disagreement between an AI system’s recommendation and the course of medical action envisaged by a human clinician. The current academic debate has so far suggested three possible ways of dealing with such clinician-AI disagreements. First, by considering when clinicians are justified in deferring to the AI output (what we call the deference approach), second when the human user overrules the AI system’s output in cases of disagreement (the overruling approach), and lastly when a second human opinion is deemed necessary to resolve disagreements (the second opinion approach). In this paper, we aim to spell out the shortcomings of these three approaches for dealing with clinician-AI disagreement and offer a more nuanced perspective on such disagreements. We argue that differentiation between types of disagreements, taking into account the role attributed to AI in medical practice, is essential before determining how clinician-AI disagreements should be dealt with. By drawing on a case that exemplifies how multifaceted medical decision-making is, we point out the normative implications of possible clinician-AI disagreements ensuing from it. We highlight the distinctive uncertainties inherent to medical decision-making, showing that disagreements in these contexts are not merely unavoidable but can even be epistemically valuable. Ultimately, by considering the epistemic positions of clinicians and AI systems, our analysis raises important questions for the epistemology of disagreement that need timely attention.
Making Pathologists Ready for the New Artificial Intelligence Era
Changes in Required Competencies
Journal article
(2025)
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Shoko Vos, Konnie Hebeda, Megan Milota, M. Sand, Jojanneke Drogt, Katrien Grünberg, Karin Jongsma
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.
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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.
Journal article
(2025)
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Nikolaos Pahos, Robert Verburg, Martin Sand, Stefan Uitermarkt, Joery de Haas
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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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.
From Practice To Theory
Three Types of Influence of Quantum Technology on Quantum Mechanics and its Foundations
Although quantum reality is often discussed as notoriously difficult to comprehend, quantum mechanics is applied with increasing success in the development of quantum technologies. In this paper, we collect and organise views on the influence of quantum technology on quantum mechanics and the foundations of quantum mechanics. We distinguish three types of influence: quantum technology helps in (1) understanding, (2) developing, and (3) evaluating quantum mechanics and its foundations. We outline several illustrations of these types by introducing examples. By mapping the influence of research and engineering practices in quantum technology on quantum mechanics and its foundations, this paper illuminates the interaction between the two areas. This paper suggests both how technological practices can aid in long-standing theoretical debates on understanding quantum mechanics, and how investigating the relation between quantum technology and quantum mechanics can inform understanding in the philosophy of science on the interaction between science and technology in general.
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Although quantum reality is often discussed as notoriously difficult to comprehend, quantum mechanics is applied with increasing success in the development of quantum technologies. In this paper, we collect and organise views on the influence of quantum technology on quantum mechanics and the foundations of quantum mechanics. We distinguish three types of influence: quantum technology helps in (1) understanding, (2) developing, and (3) evaluating quantum mechanics and its foundations. We outline several illustrations of these types by introducing examples. By mapping the influence of research and engineering practices in quantum technology on quantum mechanics and its foundations, this paper illuminates the interaction between the two areas. This paper suggests both how technological practices can aid in long-standing theoretical debates on understanding quantum mechanics, and how investigating the relation between quantum technology and quantum mechanics can inform understanding in the philosophy of science on the interaction between science and technology in general.
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.
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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.
The Questions of Hermeneutic TA
Towards a Toolbox
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.
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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.
Journal article
(2023)
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M. Sand, B. Hofbauer, J. Alleblas
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.
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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.
Serendipity, Luck and Collective Responsibility in Medical Innovation
The History of Vaccination
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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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.
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.
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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.
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.
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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.
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.
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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.
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.
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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.
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.
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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.