As artificial intelligence becomes more sophisticated and robots approach autonomous decision-making, debates about how to assign moral responsibility have gained importance, urgency, and sophistication. Answering Stenseke’s (2022a) call for scaffolds that can help us classify views and commitments, we think the current debate space can be represented hierarchically, as answers to key questions. We use the resulting taxonomy of five stances to differentiate—and defend—what is known as the “blank check” proposal. According to this proposal, a person activating a robot could (...) willingly make themselves answerable for whatever events ensue, even if those events stem from the robot’s autonomous decision(s). This blank check solution was originally proposed in the context of automated warfare (Champagne & Tonkens, 2015), but we extend it to cover all robots. We argue that, because moral answerability in the blank check is accepted voluntarily and before bad outcomes are known, it proves superior to alternative ways of assigning blame. We end by highlighting how, in addition to being just, this self-initiated and prospective moral answerability for robot harm provides deterrence that the four other stances cannot match. (shrink)

Deep learning AI systems have proven a wide capacity to take over human-related activities such as car driving, medical diagnosing, or elderly care, often displaying behaviour with unpredictable consequences, including negative ones. This has raised the question whether highly autonomous AI may qualify as morally responsible agents. In this article, we develop a set of four conditions that an entity needs to meet in order to be ascribed moral responsibility, by drawing on Aristotelian ethics and contemporary philosophical research. We encode (...) these conditions and generate a flowchart that we call the Moral Responsibility Test. This test can be used as a tool both to evaluate whether an entity is a morally responsible agent and to inform human moral decision-making over the influencing variables of the context of action. We apply the test to the case of Artificial Moral Advisors and conclude that this form of AI cannot qualify as morally responsible agents. We further discuss the implications for the use of AMAs as moral enhancement and show that using AMAs to offload human responsibility is inadequate. We argue instead that AMAs could morally enhance users if they are interpreted as enablers for moral knowledge of the contextual variables surrounding human moral decision-making, with the implication that such a use might actually enlarge human moral responsibility. (shrink)

AI has numerous applications and in various fields, including the military domain. The increase in the degree of autonomy in some decision-making systems leads to discussions on the possible future use of lethal autonomous weapons systems (LAWS). A central issue in these discussions is the assignment of moral responsibility for some AI-based outcomes. Several authors claim that the high autonomous capability of such systems leads to a so-called “responsibility gap.” In recent years, there has been a surge in philosophical literature (...) around the concept of responsibility gaps and different solutions have been devised to close or bridge these gaps. In order to move forward in the research around LAWS and the problem of responsibility, it is important to increase our understanding of the different perspectives and discussions in this debate. This paper attempts to do so by disentangling the various arguments and providing a critical overview. After giving a brief outline of the state of the technology of LAWS, I will review the debates over responsibility gaps using three differentiators: those who believe in the existence of responsibility gaps versus those who do not, those who hold that responsibility gaps constitute a new moral problem versus those who argue they do not, and those who claim that solutions can be successful as opposed to those who believe that it is an unsolvable problem. (shrink)

In a landmark essay, Andreas Matthias claimed that current developments in autonomous, artificially intelligent systems are creating a so-called responsibility gap, which is allegedly ever-widening and stands to undermine both the moral and legal frameworks of our society. But how severe is the threat posed by emerging technologies? In fact, a great number of authors have indicated that the fear is thoroughly instilled. The most pessimistic are calling for a drastic scaling-back or complete moratorium on AI systems, while the optimists (...) aim to show that the gap can be bridged nonetheless. Contrary to both camps, I argue against the prevailing assumption that there is a technology-based responsibility gap. I show how moral responsibility is a dynamic and flexible process, one that can effectively encompass emerging technological entities. (shrink)

Robotic and artificially intelligent (AI) systems are becoming prevalent in our day-to-day lives. As human interaction is increasingly replaced by human–computer and human–robot interaction (HCI and HRI), we occasionally speak and act as though we are blaming or praising various technological devices. While such responses may arise naturally, they are still unusual. Indeed, for some authors, it is the programmers or users—and not the system itself—that we properly hold responsible in these cases. Furthermore, some argue that since directing blame or (...) praise at technology itself is unfitting, designing systems in ways that encourage such practices can only exacerbate the problem. On the other hand, there may be good moral reasons to continue engaging in our natural practices, even in cases involving AI systems or robots. In particular, daily interactions with technology may stand to impact the development of our moral practices in human-to-human interactions. In this paper, we put forward an empirically grounded argument in favor of some technologies being designed for social responsiveness. Although our usual practices will likely undergo adjustments in response to innovative technologies, some systems which we encounter can be designed to accommodate our natural moral responses. In short, fostering HCI and HRI that sustains and promotes our natural moral practices calls for a co-developmental process with some AI and robotic technologies. (shrink)

Machine learning-driven clinical decision support systems (ML-CDSSs) seem impressively promising for future routine and emergency care. However, reflection on their clinical implementation reveals a wide array of ethical challenges. The preferences, concerns and expectations of professional stakeholders remain largely unexplored. Empirical research, however, may help to clarify the conceptual debate and its aspects in terms of their relevance for clinical practice. This study explores, from an ethical point of view, future healthcare professionals’ attitudes to potential changes of responsibility and decision-making (...) authority when using ML-CDSS. Twenty-seven semistructured interviews were conducted with German medical students and nursing trainees. The data were analysed based on qualitative content analysis according to Kuckartz. Interviewees’ reflections are presented under three themes the interviewees describe as closely related: (self-)attribution of responsibility, decision-making authority and need of (professional) experience. The results illustrate the conceptual interconnectedness of professional responsibility and its structural and epistemic preconditions to be able to fulfil clinicians’ responsibility in a meaningful manner. The study also sheds light on the four relata of responsibility understood as a relational concept. The article closes with concrete suggestions for the ethically sound clinical implementation of ML-CDSS. (shrink)

It is an understatement to say we live in an exciting time considering the increasingly widespread applications of artificial intelligence (AI). This observation is brought to the fore by Sedlakova...

AI has numerous applications and in various fields, including the military domain. The increase in the degree of autonomy in some decision-making systems leads to discussions on the possible future use of lethal autonomous weapons systems (LAWS). A central issue in these discussions is the assignment of moral responsibility for some AI-based outcomes. Several authors claim that the high autonomous capability of such systems leads to a so-called “responsibility gap.” In recent years, there has been a surge in philosophical literature (...) around the concept of responsibility gaps and different solutions have been devised to close or bridge these gaps. In order to move forward in the research around LAWS and the problem of responsibility, it is important to increase our understanding of the different perspectives and discussions in this debate. This paper attempts to do so by disentangling the various arguments and providing a critical overview. After giving a brief outline of the state of the technology of LAWS, I will review the debates over responsibility gaps using three differentiators: those who believe in the existence of responsibility gaps versus those who do not, those who hold that responsibility gaps constitute a new moral problem versus those who argue they do not, and those who claim that solutions can be successful as opposed to those who believe that it is an unsolvable problem. (shrink)

Background The use of Artificial Intelligence (AI) has the potential to provide relief in the challenging and often stressful clinical setting for physicians. So far, however, the actual changes in work for physicians remain a prediction for the future, including new demands on the social level of medical practice. Thus, the question of how the requirements for physicians will change due to the implementation of AI is addressed. Methods The question is approached through conceptual considerations based on the potentials that (...) AI already offer and the focus on central normative concepts of trust, explainability, and responsibility which play an important role when implementing AI in everyday clinical practice. Conclusion Interpersonal communication will not disappear upon implementation of AI. Instead, it is much more likely that the exchange between various actors in medical practice will become increasingly important. This adds another level of complexity to practical concepts such as Shared-Decision-Making, which must be addressed in empirical research, including the involvement of AI systems as actors in communication. (shrink)

Este estudio reflexionar pretende críticamente sobre la posibilidad de un enfoque dataficado, hiperconectado y algoritmizado de clarificación, fundamentación y aplicación de lo moral: la hiperética artificial. Para ello, se mostrará la ética como un saber práctico que, preocupado por la racionalización de los comportamientos libres, ha encontrado en el diálogo entre afectados el criterio de moralidad desde el cual poder criticar tanto el conocimiento como el comportamiento. Posteriormente, se profundizará en la etificación, el intento de establecer procesos de transformación de (...) la realidad social y moral en datos y metadatos computables en línea. Después, se expondrá cómo los modelos matemáticos artificialmente inteligentes están colonizando progresiva e implacablemente los procesos de racionalización con arreglo a sentido, produciendo falta de sentido, anomia y psicopatologías en las democracias maduras. Finalmente, se reflexionará críticamente sobre el diseño, aplicación y uso de algoritmos de inteligencia artificial como instrumento para establecer qué es justo y felicitante para una sociedad digitalmente hiperconectada. (shrink)