This volume bridges contemporary philosophical conceptions of risk and responsibility and offers an extensive examination of the topic. It shows that risk and responsibility combine in ways that give rise to new philosophical questions and problems. Philosophical interest in the relationship between risk and responsibility continues to rise, due in no small part due to environmental crises, emerging technologies, legal developments, and new medical advances. Despite such interest, scholars are just now working out how to conceive of the links between (...) risk and responsibility, the implications that risks may have to conceptions of responsibility (and vice versa), as well as how such theorizing might play out in applied cases. With contributions from leading scholars, this volume brings together new work examining the interplay between risk and responsibility, exploring its varied philosophical aspects and applications to contemporary issues in law, bioethics, technology, and environmental ethics. Risk and Responsibility in Context will be of interest to philosophers working in ethics, bioethics, philosophy of law, and philosophy of technology, as well as scholars and practitioners in law, health and science management, public policy, and environmental studies. (shrink)

Can autonomous systems replace humans in the performance of their activities? How does the answer to this question inform the design of autonomous systems? The study of technical systems and their features should be preceded by the study of the activities in which they play roles. Each activity can be described by its overall goals, governing norms and the intermediate steps which are taken to achieve the goals and to follow the norms. This paper uses the activity realist approach to (...) conceptualize autonomous systems in the context of human activities. By doing so, it first argues for epistemic and logical conditions that illustrate the limitations of autonomous systems in tasks which they can and cannot perform, and then, it discusses the ramifications of the limitations of system autonomy on the design of autonomous systems. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...) by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

This chapter examines the possibility of using AI technologies to improve human moral reasoning and decision-making, especially in the context of purchasing and consumer decisions. We characterize such AI technologies as artificial ethics assistants (AEAs). We focus on just one part of the AI-aided moral improvement question: the case of the individual who wants to improve their morality, where what constitutes an improvement is evaluated by the individual’s own values. We distinguish three broad areas in which an individual might think (...) their own moral reasoning and decision-making could be improved: one’s actions, character, or other evaluable attributes fall short of one’s values and moral beliefs; one sometimes misjudges or is uncertain about what the right thing to do is in particular situations, given one’s values; one is uncertain about some fundamental moral questions or recognizes a possibility that some of one’s core moral beliefs and values are mistaken. We sketch why one might think that AI tools could be used to support moral improvement in those areas, and describe two types of assistance: preparatory assistance, including advice and training supplied in advance of moral deliberation; and on-the-spot assistance, including on-the-spot advice and facilitation of moral functioning over the course of moral deliberation. Then, we turn to some of the ethical issues that AEAs might raise, looking in particular at three under-appreciated problems posed by the use of AI for moral self-improvement: namely, reliance on sensitive moral data; the inescapability of outside influences on AEAs; and AEA usage prompting the user to adopt beliefs and make decisions without adequate reasons. (shrink)

Experimental philosophy is a relatively recent discipline that employs experimental methods to investigate the intuitions, concepts, and assumptions behind traditional philosophical arguments, problems, and theories. While experimental philosophy initially served to interrogate the role that intuitions play in philosophy, it has since branched out to bring empirical methods to bear on problems within a variety of traditional areas of philosophy—including metaphysics, philosophy of language, philosophy of mind, and epistemology. To date, no connection has been made between developments in experimental philosophy (...) and philosophy of technology. In this paper, I develop and defend a research program for an experimental philosophy of technology. (shrink)

Can nonhuman animals and artificial intelligence (AI) entities be attributed moral agency? The general assumption in the philosophical literature is that moral agency applies exclusively to humans since they alone possess free will or capacities required for deliberate reflection. Consequently, only humans have been taken to be eligible for ascriptions of moral responsibility in terms of, for instance, blame or praise, moral criticism, or attributions of vice and virtue. Animals and machines may cause harm, but they cannot be appropriately ascribed (...) moral responsibility for their behavior. This thesis challenges the conventional paradigm by proposing an alternative approach where moral agency is conceived as the competence to participate in moral responsibility practices. By shifting focus from intra-individual to contextual and socially situated features, this practice-focused approach appears to make the attribution of moral agency to nonhuman animals and AI entities more plausible than commonly assumed. Moreover, considering the current and potential future prevalence of nonhuman animals and AI entities in everyday settings and social contexts, a potential extension of moral agency to such entities could very well transform our social, moral, and legal practices. Hence, this thesis proposes that the attribution or withholding of moral agency to different entities should be carefully evaluated, considering the potential normative implications. (shrink)

”Meaningful human control” is a term invented in the political and legal debate on autonomous weapons system, but it is nowadays also used in many other contexts. It is supposed to specify conditions under which an artificial system is under the right kind of control to avoid responsibility gaps: that is, situations in which no moral agent is responsible. Santoni de Sio and Van den Hoven have recently suggested a framework that can be used by system designers to operationalize this (...) kind of control. It is the purpose of this paper to facilitate further operationalization of ”meaningful human control”. -/- This paper consists of two parts. In the first part I resolve an ambiguity that plagues current operationalizations of MHC. One of the design conditions says that the system should track the reasons of the relevant agents. This condition is ambiguous between the kind of reasons involved. On one interpretation it says that a system should track motivating reasons, while it is concerned with normative reasons on the other. Current participants in the debate interpret the framework as being concerned with (something in the vicinity of) motivating reasons. I argue against this interpretation by showing that meaningful human control requires that a system tracks normative reasons. Moreover, I maintain that an operationalization of meaningful human control that fails to track the right kind of reasons is morally problematic.When this is properly understood, it can be shown that the framework of MHC is committed to the agent-relativity of reasons. More precisely, I argue in the second part of this paper that if the tracking condition of MHC plays an important role in responsibility attribution (as the proponents of the view maintain), then the framework is incompatible with first-order normative theories that hold that normative reasons are agent-neutral (such as many versions of consequentialism). In the final section I present three ways forward for the proponent of MHC as reason-responsiveness. (shrink)

The introduction of chatGPT illustrates the rapid developments within Conversational Artificial Intelligence (CAI) technologies (Gordijn and Have 2023). Ethical reflection and analysis of CAI are c...

Recent developments in AI-research suggest that an AI-driven science might not be that far off. The research of for Melnikov et al. (2018) and that of Evans et al. (2018) show that automated systems can already have a distinctive role in the design of experiments and in directing future research. Common practice in many of the papers devoted to the automation of basic research is to refer to these automated systems as ‘agents’. What is this attribution of agency based on (...) and to what extent is this an important notion in the broader context of an AI-driven science? In an attempt to answer these questions, this paper proposes a new methodological framework, introduced as the Four-Fold Framework, that can be used to conceptualize artificial agency in basic research. It consists of four modeling strategies, three of which were already identified and used by Sarkia (2021) to conceptualize ‘intentional agency’. The novelty of the framework is the inclusion of a fourth strategy, introduced as conceptual modeling, that adds a semantic dimension to the overall conceptualization. The strategy connects to the other strategies by modeling both the actual use of ‘artificial agency’ in basic research as well as what is meant by it in each of the other three strategies. This enables researchers to bridge the gap between theory and practice by comparing the meaning of artificial agency in both an academic as well as in a practical context. (shrink)

In this paper I provide an exposition and critique of the Organic View of Ethical Status, as outlined by Torrance (2008). A key presupposition of this view is that only moral patients can be moral agents. It is claimed that because artificial agents lack sentience, they cannot be proper subjects of moral concern (i.e. moral patients). This account of moral standing in principle excludes machines from participating in our moral universe. I will argue that the Organic View operationalises anthropocentric intuitions (...) regarding sentience ascription, and by extension how we identify moral patients. The main difference between the argument I provide here and traditional arguments surrounding moral attributability is that I do not necessarily defend the view that internal states ground our ascriptions of moral patiency. This is in contrast to views such as those defended by Singer (1975, 2011) and Torrance (2008), where concepts such as sentience play starring roles. I will raise both conceptual and epistemic issues with regards to this sense of sentience. While this does not preclude the usage of sentience outright, it suggests that we should be more careful in our usage of internal mental states to ground our moral ascriptions. Following from this I suggest other avenues for further exploration into machine moral patiency which may not have the same shortcomings as the Organic View. (shrink)

As technology advances and artificial agents (AAs) become increasingly autonomous, start to embody morally relevant values and act on those values, there arises the issue of whether these entities should be considered artificial moral agents (AMAs). There are two main ways in which one could argue for AMA: using intentional criteria or using functional criteria. In this article, I provide an exposition and critique of “intentional” accounts of AMA. These accounts claim that moral agency should only be accorded to entities (...) that have internal mental states. Against this thesis I argue that the requirement of internal states is philosophically unsound as it runs up against the problem of other minds. In place of intentional accounts, I provide a functionalist alternative, which makes conceptual room for the existence of AMAs. The implications of this thesis are that at some point in the future we may be faced with moral situations in which no human being is responsible, but a machine may be. Moreover, this responsibility holds, I claim, independently of whether the agent in question is “punishable” or not. (shrink)

Artificial intelligence and robotic technologies have become nearly ubiquitous. In some ways, the developments have likely helped us, but in other ways sophisticated technologies set back our interests. Among the latter sort is what has been dubbed the ‘severance problem’—the idea that technologies sever our connection to the world, a connection which is necessary for us to flourish and live meaningful lives. I grant that the severance problem is a threat we should mitigate and I ask: how can we stave (...) it off? In particular, the fact that some technologies exhibit behavior that is unclear to us seems to constitute a kind of severance. Building upon contemporary work on moral responsibility, I argue for a mechanism I refer to as ‘technological answerability’, namely the capacity to recognize human demands for answers and to respond accordingly. By designing select devices—such as robotic assistants and personal AI programs—for increased answerability, we see at least one way of satisfying our demands for answers and thereby retaining our connection to a world increasingly occupied by technology. (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)

Many optimistic responses have been proposed to bridge the threat of responsibility gaps which artificial systems create. This paper identifies a question which arises if this optimistic project proves successful. On a response-dependent understanding of responsibility, our responsibility practices themselves at least partially determine who counts as a responsible agent. On this basis, if AI or robot technology advance such that AI or robot agents become fitting participants within responsibility exchanges, then responsibility itself might be engineered. If we have good (...) reason to think such technological advances are likely, then we should take steps to address the potential for engineering responsibility. (shrink)

The notion of “responsibility gap” with artificial intelligence (AI) was originally introduced in the philosophical debate to indicate the concern that “learning automata” may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of technology, the paper proposes a broader and more comprehensive analysis of the responsibility gap. The responsibility gap, it is argued, is not one problem but a set of at least four interconnected (...) problems – gaps in culpability, moral and public accountability, active responsibility—caused by different sources, some technical, other organisational, legal, ethical, and societal. Responsibility gaps may also happen with non-learning systems. The paper clarifies which aspect of AI may cause which gap in which form of responsibility, and why each of these gaps matter. It proposes a critical review of partial and non-satisfactory attempts to address the responsibility gap: those which present it as a new and intractable problem (“fatalism”), those which dismiss it as a false problem (“deflationism”), and those which reduce it to only one of its dimensions or sources and/or present it as a problem that can be solved by simply introducing new technical and/or legal tools (“solutionism”). The paper also outlines a more comprehensive approach to address the responsibility gaps with AI in their entirety, based on the idea of designing socio-technical systems for “meaningful human control", that is systems aligned with the relevant human reasons and capacities. (shrink)

In the present article we exploit the logical notions of correctness and completeness to provide an analysis of some fundamental problems that can be encountered by a software developer when transforming norms for traffic circulation into programming instructions. Relying on this analysis, we then introduce a question and answer procedure that can be helpful, in case of an accident, to clarify which components of an existing framework should be revised and to what extent software developers can be held responsible.

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)

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)

The possible future use of lethal autonomous weapons systems (LAWS) and the challenges associated with assigning moral responsibility leads to several debates. Some authors argue that the highly autonomous capability of such systems may lead to a so-called responsibility gap in situations where LAWS cause serious violations of international humanitarian law. One proposed solution is the doctrine of command responsibility. Despite the doctrine’s original development to govern human interactions on the battlefield, it is worth considering whether the doctrine of command (...) responsibility could provide a solution by applying the notion analogously to LAWS. A fundamental condition underpinning the doctrine’s application is the control requirement, stipulating that a superior must exert some degree of control over subordinates. The aim of this article is to provide an in-depth analysis of this control condition and assess whether it leads to the impossibility of applying the doctrine of command responsibility to LAWS. To this end, the first section briefly introduces the topic of LAWS and responsibility gaps. The subsequent section provides a concise overview of the doctrine itself and the conditions typically necessitated for its application. In the third section, a comprehensive scrutiny of the control requirement is undertaken through examination of key case law, examining how the concept has been interpreted. Finally, the fourth section delves into the evaluation of commanders’ potential to exert effective control over their (non-human) subordinates. Based on this, the feasibility of considering command responsibility as a viable solution is assessed, aiming to determine whether its application should be prima facie excluded or warrants further exploration. (shrink)

Sedlakova and Trachsel (2023) consider conversational artificial intelligence (CAI) as a new way of providing psychotherapy to patients. This is an important topic, and Sedlakova and Trachsel have...

Self‐driving cars hold out the promise of being much safer than regular cars. Yet they cannot be 100% safe. Accordingly, they need to be programmed for how to deal with crash scenarios. Should cars be programmed to always prioritize their owners, to minimize harm, or to respond to crashes on the basis of some other type of principle? The article first discusses whether everyone should have the same “ethics settings.” Next, the oft‐made analogy with the trolley problem is examined. Then (...) follows an assessment of recent empirical work on lay‐people's attitudes about crash algorithms relevant to the ethical issue of crash optimization. Finally, the article discusses what traditional ethical theories such as utilitarianism, Kantianism, virtue ethics, and contractualism imply about how cars should handle crash scenarios. The aim of the article is to provide an overview of the existing literature on these topics and to assess how far the discussion has gotten so far. (shrink)

Self‐driving cars hold out the promise of being much safer than regular cars. Yet they cannot be 100% safe. Accordingly, we need to think about who should be held responsible when self‐driving cars crash and people are injured or killed. We also need to examine what new ethical obligations might be created for car users by the safety potential of self‐driving cars. The article first considers what lessons might be learned from the growing legal literature on responsibility for crashes with (...) self‐driving cars. Next, worries about responsibility gaps and retribution gaps from the philosophical literature are introduced. This leads to a discussion of whether self‐driving cars are a form of agents that act independently of human agents. It is suggested that it is better to analyze their apparent agency in terms of human–robot collaborations, within which humans play the most important roles. The next topic is the idea that the safety potential of self‐driving cars might create a duty to either switch to self‐driving cars or seek means of making conventional cars safer. Lastly, there is a short discussion of ethical issues related to safe human–robot coordination within mixed traffic featuring both self‐driving cars and conventional cars. (shrink)

In this paper, we discuss the ethics of automated driving. More specifically, we discuss responsible human-robot coordination within mixed traffic: i.e. traffic involving both automated cars and conventional human-driven cars. We do three main things. First, we explain key differences in robotic and human agency and expectation-forming mechanisms that are likely to give rise to compatibility-problems in mixed traffic, which may lead to crashes and accidents. Second, we identify three possible solution-strategies for achieving better human-robot coordination within mixed traffic. Third, (...) we identify important ethical challenges raised by each of these three possible strategies for achieving optimized human-robot cordination in this domain. Among other things, we argue that we should not just explore ways of making robotic driving more like human driving. Rather, we ought also to take seriously potential ways of making human driving more like robotic driving. Nor should we assume that complete automation is always the ideal to aim for; in some traffic-situations, the best results may be achieved through human-robot collaboration. Ultimately, our main aim in this paper is to argue that the new field of the ethics of automated driving needs take seriously the ethics of mixed traffic and responsible human-robot coordination. (shrink)

This paper discusses the robotization of the workplace, and particularly the question of whether robots can be good colleagues. This might appear to be a strange question at first glance, but it is worth asking for two reasons. Firstly, some people already treat robots they work alongside as if the robots are valuable colleagues. It is worth reflecting on whether such people are making a mistake. Secondly, having good colleagues is widely regarded as a key aspect of what can make (...) work meaningful. In discussing whether robots can be good colleagues, the paper compares that question to the more widely discussed questions of whether robots can be our friends or romantic partners. The paper argues that the ideal of being a good colleague has many different parts, and that on a behavioral level, robots can live up to many of the criteria typically associated with being a good colleague. Moreover, the paper also argues that in comparison with the more demanding ideals of being a good friend or a good romantic partner, it is comparatively easier for a robot to live up to the ideal of being a good colleague. The reason for this is that the “inner lives” of our friends and lovers are more important to us than the inner lives of our colleagues. (shrink)

We argue that machine learning algorithms can inflict microaggressions on members of marginalized groups and that recognizing these harms as instances of microaggressions is key to effectively addressing the problem. The concept of microaggression is also illuminated by being studied in algorithmic contexts. We contribute to the microaggression literature by expanding the category of environmental microaggressions and highlighting the unique issues of moral responsibility that arise when we focus on this category. We theorize two kinds of algorithmic microaggression, stereotyping and (...) erasure microaggressions, and argue that corporations are responsible for the microaggressions their algorithms create. As a case study, we look at the problems faced by Google’s autocomplete prediction and at the insufficiency of their solutions. The case study of autocomplete demonstrates our core claim that microaggressions constitute a distinct form of algorithmic bias and that identifying them as such allows us to avoid seeming solutions that recreate the same kinds of harms. Google has a responsibility to make information freely available, without exposing users to degradation. To fulfill its duties to marginalized groups, Google must abandon the fiction of neutral prediction and instead embrace the liberatory power of suggestion. (shrink)

This paper discusses the ethical implications of perverse incentives with regard to autonomous driving. We define perverse incentives as a feature of an action, technology, or social policy that invites behavior which negates the primary goal of the actors initiating the action, introducing a certain technology, or implementing a social policy. As a special form of means-end-irrationality, perverse incentives are to be avoided from a prudential standpoint, as they prove to be directly self-defeating: They are not just a form of (...) unintended side effect that must be balanced against the main goal or value to be realized by an action, technology, or policy. Instead, they directly cause the primary goals of the actors—i.e., the goals that they ultimately pursue with the action, technology, or policy—to be “worse achieved”. In this paper, we elaborate on this definition and distinguish three ideal-typical phases of adverse incentives, where only in the last one the threshold for a perverse incentive is crossed. In addition, we discuss different possible relevant actors and their goals in implementing autonomous vehicles. We conclude that even if some actors do not pursue traffic safety as their primary goal, as part of a responsibility network they incur the responsibility to act on the common primary goal of the network, which we argue to be traffic safety. (shrink)

This paper discusses the ethical implications of perverse incentives with regard to autonomous driving. We define perverse incentives as a feature of an action, technology, or social policy that invites behavior which negates the primary goal of the actors initiating the action, introducing a certain technology, or implementing a social policy. As a special form of means-end-irrationality, perverse incentives are to be avoided from a prudential standpoint, as they prove to be directly self-defeating: They are not just a form of (...) unintended side effect that must be balanced against the main goal or value to be realized by an action, technology, or policy. Instead, they directly cause the primary goals of the actors—i.e., the goals that they ultimately pursue with the action, technology, or policy—to be “worse achieved”. In this paper, we elaborate on this definition and distinguish three ideal-typical phases of adverse incentives, where only in the last one the threshold for a perverse incentive is crossed. In addition, we discuss different possible relevant actors and their goals in implementing autonomous vehicles. We conclude that even if some actors do not pursue traffic safety as their primary goal, as part of a responsibility network they incur the responsibility to act on the common primary goal of the network, which we argue to be traffic safety. (shrink)

Robotization is an increasingly pervasive feature of our lives. Robots with high degrees of autonomy may cause harm, yet in sufciently complex systems neither the robots nor the human developers may be candidates for moral blame. John Danaher has recently argued that this may lead to a retribution gap, where the human desire for retribution faces a lack of appropriate subjects for retributive blame. The potential social and moral implications of a retribution gap are considerable. I argue that the retributive (...) intuitions that feed into retribution gaps are best understood as deontological intuitions. I apply a debunking argument for deontological intuitions in order to show that retributive intuitions cannot be used to justify retributive punishment in cases of robot harm without clear candidates for blame. The fundamental moral question thus becomes what we ought to do with these retributive intuitions, given that they do not justify retribution. I draw a parallel from recent work on implicit biases to make a case for taking moral responsibility for retributive intuitions. In the same way that we can exert some form of control over our unwanted implicit biases, we can and should do so for unjustifed retributive intuitions in cases of robot harm. (shrink)

Recent decades have witnessed tremendous progress in artificial intelligence and in the development of autonomous systems that rely on artificial intelligence. Critics, however, have pointed to the difficulty of allocating responsibility for the actions of an autonomous system, especially when the autonomous system causes harm or damage. The highly autonomous behavior of such systems, for which neither the programmer, the manufacturer, nor the operator seems to be responsible, has been suspected to generate responsibility gaps. This has been the cause of (...) much concern. In this article, I propose a more optimistic view on artificial intelligence, raising two challenges for responsibility gap pessimists. First, proponents of responsibility gaps must say more about when responsibility gaps occur. Once we accept a difficult-to-reject plausibility constraint on the emergence of such gaps, it becomes apparent that the situations in which responsibility gaps occur are unclear. Second, assuming that responsibility gaps occur, more must be said about why we should be concerned about such gaps in the first place. I proceed by defusing what I take to be the two most important concerns about responsibility gaps, one relating to the consequences of responsibility gaps and the other relating to violations of jus in bello. (shrink)

Advances in artificial intelligence research allow us to build fairly sophisticated agents: robots and computer programs capable of acting and deciding on their own. These systems raise questions about who is responsible when something goes wrong—when such systems harm or kill humans. In a recent paper, Sven Nyholm has suggested that, because current AI will likely possess what we might call “supervised agency”, the theory of responsibility for individual agency is the wrong place to look for an answer to the (...) question of responsibility. Instead, or so argues Nyholm, because supervised agency is a form of collaborative agency—of acting together—the right place to look is the theory of collaborative responsibility—responsibility in cases of acting together. This paper concedes that current AI will possess supervised agency, but argues that it is nevertheless wrong to think of the relevant human-AI interactions as a form of collaborative agency and, hence, that responsibility in cases of collaborative agency is not the right place to look for the responsibility-grounding relation in human-AI interactions. It also suggests that the right place to look for this responsibility-grounding relation in human-AI interactions is the use of certain sorts of agents as instruments. (shrink)

A large part of the explainable AI literature focuses on what explanations are in general, what algorithmic explainability is more specifically, and how to code these principles of explainability into AI systems. Much less attention has been devoted to the question of why algorithmic decisions and systems should be explainable and whether there ought to be a right to explanation and why. We therefore explore the normative landscape of the need for AI to be explainable and individuals having a right (...) to such explanation. This exploration is particularly relevant to the medical domain where the (im)possibility of explainable AI is high on both the research and practitioners’ agenda. The dominant intuition overall is that explainability has and should play a key role in the health context. Notwithstanding the strong normative intuition for having a right to explanation, intuitions can be wrong. So, we need more than an appeal to intuitions when it comes to explaining the normative significance of having a right to explanation when being subject to AI-based decision-making. The aim of the paper is therefore to provide an account of what might underlie the normative intuition. We defend the ‘symmetry thesis’ according to which there is no special normative reason to have a right to explanation when ‘machines’ in the broad sense, make decisions, recommend treatment, discover tumors, and so on. Instead, we argue that we have a right to explanation in cases that involve automated processing that significantly affect our core deliberative agency and which we do not understand, because we have a general moral right to explanation when choices are made which significantly affect us but which we do not understand. (shrink)

This paper explores the role and resolution of disagreements between physicians and their diagnostic AI-based decision support systems. With an ever-growing number of applications for these independently operating diagnostic tools, it becomes less and less clear what a physician ought to do in case their diagnosis is in faultless conflict with the results of the DSS. The consequences of such uncertainty can ultimately lead to effects detrimental to the intended purpose of such machines, e.g. by shifting the burden of proof (...) towards a physician. Thus, we require normative clarity for integrating these machines without affecting established, trusted, and relied upon workflows. In reconstructing different causes of conflicts between physicians and their AI-based tools—inspired by the approach of “meaningful human control” over autonomous systems and the challenges to resolve them—we will delineate normative conditions for “meaningful disagreements”. These incorporate the potential of DSS to take on more tasks and outline how the moral responsibility of a physician can be preserved in an increasingly automated clinical work environment. (shrink)

Wearable robots and exoskeletons are relatively new technologies designed for assisting and augmenting human motor functions. Due to their different possible design applications and their intimate connection to the human body, they come with specific ethical, legal, and social issues, which have not been much explored in the recent ELS literature. This paper draws on expert consultations and a literature review to provide a taxonomy of the most important ethical, legal, and social issues of wearable robots. These issues are categorized (...) in wearable robots and the self, wearable robots and the other, and wearable robots in society. (shrink)

The advent of intelligent artificial systems has sparked a dispute about the question of who is responsible when such a system causes a harmful outcome. This paper champions the idea that this dispute should be approached as a conceptual engineering problem. Towards this claim, the paper first argues that the dispute about the responsibility gap problem is in part a conceptual dispute about the content of responsibility and related concepts. The paper then argues that the way forward is to evaluate (...) the conceptual choices we have, in the light of a systematic understanding of why the concept is important in the first place—in short, the way forward is to engage in conceptual engineering. The paper then illustrates what approaching the responsibility gap problem as a conceptual engineering problem looks like. It outlines argumentative pathways out of the responsibility gap problem and relates these to existing contributions to the dispute. (shrink)

Future weapons will make life-or-death decisions without a human in the loop. When such weapons inflict unwarranted harm, no one appears to be responsible. There seems to be a responsibility gap. I first reconstruct the argument for such responsibility gaps to then argue that this argument is not sound. The argument assumes that commanders have no control over whether autonomous weapons inflict harm. I argue against this assumption. Although this investigation concerns a specific case of autonomous weapons systems, I take (...) steps towards vindicating the more general idea that superiors can be morally responsible in virtue of being in command. (shrink)

Autonomous vehicles, and the larger socio-technical systems that they are a part of are likely to have a deep and lasting impact on our societies. Trust is a key value that will play a role in the development of autonomous driving systems. This paper suggests that trust of autonomous driving systems will impact the ways that these systems are taken up, the norms and laws that guide them and the design of the systems themselves. Further to this, in order to (...) have autonomous driving systems that are worthy of our trust, we need a superstructure of oversight and a process that designs trust into these systems from the outset. Rather than banning or avoiding all autonomous vehicles should a tragedy occur, despite these systems having some level of risk, we want resilient systems that can survive tragedies, and indeed, improve from them. I will argue that trust plays a role in developing these resilient systems. (shrink)

The introduction of self-driving vehicles gives rise to a large number of ethical issues that go beyond the common, extremely narrow, focus on improbable dilemma-like scenarios. This article provides a broad overview of realistic ethical issues related to self-driving vehicles. Some of the major topics covered are as follows: Strong opinions for and against driverless cars may give rise to severe social and political conflicts. A low tolerance for accidents caused by driverless vehicles may delay the introduction of driverless systems (...) that would substantially reduce the risks. Trade-offs will arise between safety and other requirement on the road traffic system. Over-reliance on the swift collision-avoiding reactions of self-driving vehicles can induce people to take dangerous actions, such as stepping out in front of a car, relying on its fast braking. Children travelling alone can violate safety instructions such as the use of seatbelts. Digital information about routes and destinations can be used to convey commercial and political messages to car users. If fast passage can be bought, then socio-economic segregation of road traffic may result. Terrorists and other criminals can hack into a vehicle and make it crash. They can also use self-driving vehicles for instance to carry bombs to their designed places of detonation or to wreak havoc on a country’s road system. (shrink)

The article discusses the challenges, benefits, and risks that, from a bioethical perspective, arise because of the the development of eHealth projects. The conceptual framework of the research is based on H. Jonas’ principles of the ethics of responsibility and B.G. Yudin’s anthropological ideas on human beings as agents who constantly change their own boundaries in the “zone of phase transitions.” The article focuses on the events taking place in the zone of phase transitions between humans and machines in eHealth. (...) It is shown that for innovative practices related to digitalization and datafication in medicine, it is needed to rethink central bioethical concepts of personal autonomy and informed consent. In particular, the concept of broad or open informed consent is discussed, which allows the idea of moral responsibility in the field of biomedical technologies to be extended to events of uncertain future. The authors draw attention to the problems associated with the emergence of new autonomous subjects/agents in relationship between doctors and patients. The humanization of machines occurring in eHealth is accompanied by a counter trend – the formation of conceptions and practices of the quantified self. There emerges the practices of self-care and bio-power caused by the datafication and digitization of personality. The authors conclude that bioethics should proactively develop norms for the evolving interaction between doctor and patients. (shrink)

We applaud Sedlakova and Trachsel’s work and their description of conversational artificial intelligence (CAI) as possessing a hybrid nature with features of both a tool and an agent (Sedlakova and...

Through modern driver assistant systems, algorithmic decisions already have a significant impact on the behavior of vehicles in everyday traffic. This will become even more prominent in the near future considering the development of autonomous driving functionality. The need to consider ethical principles in the design of such systems is generally acknowledged. However, scope, principles and strategies for their implementations are not yet clear. Most of the current discussions concentrate on situations of unavoidable crashes in which the life of human (...) beings is existentially affected. In this paper, we argue that ethical considerations should be mandatory for any algorithmic decision of autonomous vehicles, instead of a limitation to hazard situations. Such an ethically aligned behavior is relevant because autonomous vehicles, like any other traffic participants, operate in a shared public space, where every behavioral decision impacts the operational possibilities of others. These possibilities concern the fulfillment of a road-user’s safety, utility and comfort needs. We propose that, to operate ethically in such space, an autonomous vehicle will have to take its behavior decisions according to a just distribution of operational possibilities among all traffic participants. Using an application on a partially-autonomous prototype vehicle, we describe how to apply and implement concepts of distributive justice to the driving environment and demonstrate the impact on its behavior in comparison to an advanced but egoistic decision maker. (shrink)

The article discusses the challenges, benefits, and risks that, from a bioethical perspective, arise because of the the development of eHealth projects. The conceptual framework of the research is based on H. Jonas’ principles of the ethics of responsibility and B.G. Yudin’s anthropological ideas on human beings as agents who constantly change their own boundaries in the “zone of phase transitions.” The article focuses on the events taking place in the zone of phase transitions between humans and machines in eHealth. (...) It is shown that for innovative practices related to digitalization and datafication in medicine, it is needed to rethink central bioethical concepts of personal autonomy and informed consent. In particular, the concept of broad or open informed consent is discussed, which allows the idea of moral responsibility in the field of biomedical technologies to be extended to events of uncertain future. The authors draw attention to the problems associated with the emergence of new autonomous subjects/agents (machines with artificial intelligence) in relationship between doctors and patients. The humanization of machines occurring in eHealth is accompanied by a counter trend – the formation of conceptions and practices of the quantified self. There emerges the practices of self-care and bio-power (M. Foucault) caused by the datafication and digitization of personality. The authors conclude that bioethics should proactively develop norms for the evolving interaction between doctor and patients. (shrink)

Automated technologies and robots make decisions that cannot always be fully controlled or predicted. In addition to that, they cannot respond to punishment and blame in the ways humans do. Therefore, when automated cars harm or kill people, for example, this gives rise to concerns about responsibility-gaps and retribution-gaps. According to Sven Nyholm, however, automated cars do not pose a challenge on human responsibility, as long as humans can control them and update them. He argues that the agency exercised in (...) automated cars should be understood in terms of human–robot collaborations. This brief note focuses on the problem that arises when there are multiple people involved, but there is no obvious shared collaboration among them. Building on John Danaher’s discussion of command responsibility, it is argued that, although Nyholm might be right that autonomous cars cannot be regarded as acting on their own, independently of any human beings, worries about responsibility-gaps and retribution-gaps are still justified, because it often remains unclear how to allocate or distribute responsibility satisfactorily among the key humans involved after they have been successfully identified. (shrink)

The growth of self-tracking and personal surveillance has given rise to the Quantified Self movement. Members of this movement seek to enhance their personal well-being, productivity, and self-actualization through the tracking and gamification of personal data. The technologies that make this possible can also track and gamify aspects of our interpersonal, romantic relationships. Several authors have begun to challenge the ethical and normative implications of this development. In this article, we build upon this work to provide a detailed ethical analysis (...) of the Quantified Relationship. We identify eight core objections to the QR and subject them to critical scrutiny. We argue that although critics raise legitimate concerns, there are ways in which tracking technologies can be used to support and facilitate good relationships. We thus adopt a stance of cautious openness toward this technology and advocate the development of a research agenda for the positive use of QR technologies. (shrink)

There is a concern that the widespread deployment of autonomous machines will open up a number of ‘responsibility gaps’ throughout society. Various articulations of such techno-responsibility gaps have been proposed over the years, along with several potential solutions. Most of these solutions focus on ‘plugging’ or ‘dissolving’ the gaps. This paper offers an alternative perspective. It argues that techno-responsibility gaps are, sometimes, to be welcomed and that one of the advantages of autonomous machines is that they enable us to embrace (...) certain kinds of responsibility gap. The argument is based on the idea that human morality is often tragic. We frequently confront situations in which competing moral considerations pull in different directions and it is impossible to perfectly balance these considerations. This heightens the burden of responsibility associated with our choices. We cope with the tragedy of moral choice in different ways. Sometimes we delude ourselves into thinking the choices we make were not tragic ; sometimes we delegate the tragic choice to others ; sometimes we make the choice ourselves and bear the psychological consequences. Each of these strategies has its benefits and costs. One potential advantage of autonomous machines is that they enable a reduced cost form of delegation. However, we only gain the advantage of this reduced cost if we accept that some techno-responsibility gaps are virtuous. (shrink)

What is techno-optimism and how can it be defended? Although techno-optimist views are widely espoused and critiqued, there have been few attempts to systematically analyse what it means to be a techno-optimist and how one might defend this view. This paper attempts to address this oversight by providing a comprehensive analysis and evaluation of techno-optimism. It is argued that techno-optimism is a pluralistic stance that comes in weak and strong forms. These vary along a number of key dimensions but each (...) shares the view that technology plays a key role in ensuring that the good prevails over the bad. Whatever its strength, to defend this stance, one must flesh out an argument with four key premises. Each of these premises is highly controversial and can be subjected to a number of critiques. The paper discusses five such critiques in detail. The paper also considers possible responses from the techno-optimist. Finally, it is concluded that although strong forms of techno-optimism are not intellectually defensible, a modest, agency-based version of techno-optimism may be defensible. (shrink)

In “Accepting Moral Responsibility for the Actions of Autonomous Weapons Systems—a Moral Gambit” (2022), Mariarosaria Taddeo and Alexander Blanchard answer one of the most vexing issues in current ethics of technology: how to close the so-called “responsibility gap”? Their solution is to require that autonomous weapons systems (AWSs) may only be used if there is some human being who accepts the ex ante responsibility for those actions of the AWS that could not have been predicted or intended (in such cases, (...) the human being takes what the authors call the “moral gambit”). The authors then propose several institutional safeguards to implement in order to ensure that the moral gambit is taken in a fair and just way. This paper explores this suggestion in the context of the institutional settings within which AWSs are most likely to be deployed. It raises some concerns as to the feasibility of Taddeo and Blanchard’s proposal, in light of the recent empirical work on the incentive structures likely to exist within militaries. It then presents a potential problem that may arise in case the accountability mechanisms are successfully implemented. (shrink)