The possibility that autonomous weapons will be deployed on the battlefields of the future raises the challenge of determining who can be held responsible for how these weapons act. Robert Sparrow has argued that it would be impossible to attribute responsibility for autonomous robots' actions to their creators, their commanders, or the robots themselves. This essay reaches a much different conclusion. It argues that the problem of determining responsibility for autonomous robots can be solved by addressing it within the context (...) of the military chain of command. The military hierarchy is a system of distributing responsibility between decision makers on different levels and constraining autonomy. If autonomous weapons are employed as agents operating within this system, then responsibility for their actions can be attributed to their creators and their civilian and military superiors. (shrink)

Control-based models of moral responsibility typically employ a notion of "tracing," according to which moral responsibility requires an exercise of control either immediately prior to the behavior in question or at some suitable point prior to the behavior. Responsibility, on this view, requires tracing back to control. But various philosophers, including Manuel Vargas and Angela Smith, have presented cases in which the plausibility of tracing is challenged. In this paper we discuss the examples and we argue that they do not (...) in fact impugn an attractive and natural tracing component. Our discussion can function in part as a defense of a control-based account of moral responsibility, but also as simply a defense of tracing. (shrink)

The United States Army’s Future Combat Systems Project, which aims to manufacture a “robot army” to be ready for deployment by 2012, is only the latest and most dramatic example of military interest in the use of artificially intelligent systems in modern warfare. This paper considers the ethics of a decision to send artificially intelligent robots into war, by asking who we should hold responsible when an autonomous weapon system is involved in an atrocity of the sort that would normally (...) be described as a war crime. A number of possible loci of responsibility for robot war crimes are canvassed; the persons who designed or programmed the system, the commanding officer who ordered its use, the machine itself. I argue that in fact none of these are ultimately satisfactory. Yet it is a necessary condition for fighting a just war, under the principle of jus in bellum, that someone can be justly held responsible for deaths that occur in the course of the war. As this condition cannot be met in relation to deaths caused by an autonomous weapon system it would therefore be unethical to deploy such systems in warfare. (shrink)

Traditionally, the manufacturer/operator of a machine is held (morally and legally) responsible for the consequences of its operation. Autonomous, learning machines, based on neural networks, genetic algorithms and agent architectures, create a new situation, where the manufacturer/operator of the machine is in principle not capable of predicting the future machine behaviour any more, and thus cannot be held morally responsible or liable for it. The society must decide between not using this kind of machine any more (which is not a (...) realistic option), or facing a responsibility gap, which cannot be bridged by traditional concepts of responsibility ascription. (shrink)

Our ability to locate moral responsibility is often thought to be a necessary condition for conducting morally permissible medical practice, engaging in a just war, and other high-stakes endeavors. Yet, with increasing reliance upon artificially intelligent systems, we may be facing a wideningresponsibility gap, which, some argue, cannot be bridged by traditional concepts of responsibility. How then, if at all, can we make use of crucial emerging technologies? According to Colin Allen and Wendell Wallach, the advent of so-called ‘artificial moral (...) agents’ (AMAs) is inevitable. Still, this notion may seem to push back the problem, leaving those who have an interest in developing autonomous technology with a dilemma. We may need to scale-back our efforts at deploying AMAs (or at least maintain human oversight); otherwise, we must rapidly and drastically update our moral and legal norms in a way that ensures responsibility for potentially avoidable harms. This paper invokes contemporary accounts of responsibility in order to show how artificially intelligent systems might be held responsible. Although many theorists are concerned enough to develop artificial conceptions ofagencyor to exploit our present inability to regulate valuable innovations, the proposal here highlights the importance of—and outlines a plausible foundation for—a workable notion ofartificial moral responsibility. (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)

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)

The aim of this exploratory paper is to review an under-appreciated parallel between group agency and artificial intelligence. As both phenomena involve non-human goal-directed agents that can make a difference to the social world, they raise some similar moral and regulatory challenges, which require us to rethink some of our anthropocentric moral assumptions. Are humans always responsible for those entities’ actions, or could the entities bear responsibility themselves? Could the entities engage in normative reasoning? Could they even have rights and (...) a moral status? I will tentatively defend the (increasingly widely held) view that, under certain conditions, artificial intelligent systems, like corporate entities, might qualify as responsible moral agents and as holders of limited rights and legal personhood. I will further suggest that regulators should permit the use of autonomous artificial systems in high-stakes settings only if they are engineered to function as moral (not just intentional) agents and/or there is some liability-transfer arrangement in place. I will finally raise the possibility that if artificial systems ever became phenomenally conscious, there might be a case for extending a stronger moral status to them, but argue that, as of now, this remains very hypothetical. (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 a landmark essay, Andreas Matthias claimed that current developments in autonomous, artificially intelligent (AI) 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)

The task of this essay is to respond to the question concerning robots and responsibility—to answer for the way that we understand, debate, and decide who or what is able to answer for decisions and actions undertaken by increasingly interactive, autonomous, and sociable mechanisms. The analysis proceeds through three steps or movements. It begins by critically examining the instrumental theory of technology, which determines the way one typically deals with and responds to the question of responsibility when it involves technology. (...) It then considers three instances where recent innovations in robotics challenge this standard operating procedure by opening gaps in the usual way of assigning responsibility. The innovations considered in this section include: autonomous technology, machine learning, and social robots. The essay concludes by evaluating the three different responses—instrumentalism 2.0, machine ethics, and hybrid responsibility—that have been made in face of these difficulties in an effort to map out the opportunities and challenges of and for responsible robotics. (shrink)

Many ethicists writing about automated systems attribute agency to these systems. Not only that; they seemingly attribute an autonomous or independent form of agency to these machines. This leads some ethicists to worry about responsibility-gaps and retribution-gaps in cases where automated systems harm or kill human beings. In this paper, I consider what sorts of agency it makes sense to attribute to most current forms of automated systems, in particular automated cars and military robots. I argue that whereas it indeed (...) makes sense to attribute different forms of fairly sophisticated agency to these machines, we ought not to regard them as acting on their own, independently of any human beings. Rather, the right way to understand the agency exercised by these machines is in terms of human–robot collaborations, where the humans involved initiate, supervise, and manage the agency of their robotic collaborators. This means, I argue, that there is much less room for justified worries about responsibility-gaps and retribution-gaps than many ethicists think. (shrink)

There have been two recent strands of argument arguing for the pro tanto impermissibility of fully autonomous weapon systems. On Sparrow's view, AWS are impermissible because they generate a morally problematic ‘responsibility gap’. According to Purves et al., AWS are impermissible because moral reasoning is not codifiable and because AWS are incapable of acting for the ‘right’ reasons. I contend that these arguments are flawed and that AWS are not morally problematic in principle. Specifically, I contend that these arguments presuppose (...) an incoherent conception of an AWS as somehow making genuine decisions but not being morally responsible for those very same decisions. Rather than conceiving of AWS in this way, I argue that an AWS is either a socially-constructed institution that has been physically instantiated or it is a genuine agent. If it is the former, then we should treat AWS as we do any other collective action problem. If it is the latter, then we should treat AWS as responsibility-bearers, but also as bearers of rights and/or interests. To reject this disjunction is not only conceptually incoherent but also potentially morally dangerous. (shrink)

We are living through an era of increased robotisation. Some authors have already begun to explore the impact of this robotisation on legal rules and practice. In doing so, many highlight potential liability gaps that might arise through robot misbehaviour. Although these gaps are interesting and socially significant, they do not exhaust the possible gaps that might be created by increased robotisation. In this article, I make the case for one of those alternative gaps: the retribution gap. This gap arises (...) from a mismatch between the human desire for retribution and the absence of appropriate subjects of retributive blame. I argue for the potential existence of this gap in an era of increased robotisation; suggest that it is much harder to plug this gap than it is to plug those thus far explored in the literature; and then highlight three important social implications of this gap. (shrink)

This book provides a comprehensive, systematic theory of moral responsibility. The authors explore the conditions under which individuals are morally responsible for actions, omissions, consequences, and emotions. The leading idea in the book is that moral responsibility is based on 'guidance control'. This control has two components: the mechanism that issues in the relevant behavior must be the agent's own mechanism, and it must be appropriately responsive to reasons. The book develops an account of both components. The authors go on (...) to offer a sustained defense of the thesis that moral responsibility is compatible with causal determinism. (shrink)

May lethal autonomous weapons systems—‘killer robots ’—be used in war? The majority of writers argue against their use, and those who have argued in favour have done so on a consequentialist basis. We defend the moral permissibility of killer robots, but on the basis of the non-aggregative structure of right assumed by Just War theory. This is necessary because the most important argument against killer robots, the responsibility trilemma proposed by Rob Sparrow, makes the same assumptions. We show that the (...) crucial moral question is not one of responsibility. Rather, it is whether the technology can satisfy the requirements of fairness in the re-distribution of risk. Not only is this possible in principle, but some killer robots will actually satisfy these requirements. An implication of our argument is that there is a public responsibility to regulate killer robots ’ design and manufacture. (shrink)

While there are many issues to be raised in using lethal autonomous robotic weapons (beyond those of remotely operated drones), we argue that the most important question is: should the decision to take a human life be relinquished to a machine? This question is often overlooked in favor of technical questions of sensor capability, operational questions of chain of command, or legal questions of sovereign borders. We further argue that the answer must be ?no? and offer several reasons for banning (...) autonomous robots. (1) Such a robot treats a human as an object, instead of as a person with inherent dignity. (2) A machine can only mimic moral actions, it cannot be moral. (3) A machine run by a program has no human emotions, no feelings about the seriousness of killing a human. (4) Using such a robot would be a violation of military honor. We therefore conclude that the use of an autonomous robot in lethal operations should be banned. (shrink)

In this article, we focus on the attribution of moral responsibility for the actions of autonomous weapons systems (AWS). To do so, we suggest that the responsibility gap can be closed if human agents can take meaningful moral responsibility for the actions of AWS. This is a moral responsibility attributed to individuals in a justified and fair way and which is accepted by individuals as an assessment of their own moral character. We argue that, given the unpredictability of AWS, meaningful (...) moral responsibly can only be discharged by human agents who are willing to take a moral gambit: they decide to design/develop/deploy AWS despite the uncertainty about the effects an AWS may produce, hoping that unintended and unwanted or unforeseen outcomes may never occurs, but also accepting to be held responsible if such outcomes will occur. We argue that, while a moral gambit is permissible for the use of non-lethal AWS, this is not the case for the actions of lethal autonomous weapon systems. (shrink)

Much of our ordinary thought and talk about responsibility exhibits what I call the ‘pie fallacy’—the fallacy of thinking that there is a fixed amount of responsibility for every outcome, to be distributed among all those, if any, who are responsible for it. The pie fallacy is a fallacy, I argue, because how responsible an agent is for some outcome is fully grounded in facts about the agent, the outcome and the relationships between them; it does not depend, in particular, (...) on how responsible anyone else is for that same outcome. In this paper, I explore how the pie fallacy can arise by considering several different kinds of case in which two or more agents are responsible for the same outcome. I’ll end with some brief remarks on the potential consequences of my arguments for how to think about responsibility in war. (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)

Criminal liability for acts committed by AI systems has recently become a hot legal topic. This paper includes three different contributions. The first contribution is an analysis of the extent to which an AI system can satisfy the requirements for criminal liability: accomplishing an actus reus, having the corresponding mens rea, possessing the cognitive capacities needed for responsibility. The second contribution is a discussion of criminal activity accomplished by an AI entity, with reference to a recent case involving an online (...) bot, the Random Darknet Shopper. This discussion will provide the context for the analysis of commonalities and differences between criminal activities by humans and by artificial systems. The third contribution concerns the evaluation of different ways of addressing criminal activities by AI systems in a regulatory perspective. (shrink)

The import of computational learning theories and techniques on the ethics of human-robot interaction is explored in the context of recent developments of personal robotics. An epistemological reflection enables one to isolate a variety of background hypotheses that are needed to achieve successful learning from experience in autonomous personal robots. The conjectural character of these background hypotheses brings out theoretical and practical limitations in our ability to predict and control the behaviour of learning robots in their interactions with humans. Responsibility (...) ascription problems, which concern damages caused by learning robot actions, are analyzed in the light of these epistemic limitations. Finally, a broad framework is outlined for ethically motivated scientific inquiries, which aim at improving our capability to understand, anticipate, and selectively cope with harmful errors by learning robots. (shrink)

This article discusses mechanisms and principles for assignment of moral responsibility to intelligent robots, with special focus on military robots. We introduce the concept autonomous power as a new concept, and use it to identify the type of robots that call for moral considerations. It is furthermore argued that autonomous power, and in particular the ability to learn, is decisive for assignment of moral responsibility to robots. As technological development will lead to robots with increasing autonomous power, we should be (...) prepared for a future when people blame robots for their actions. It is important to, already today, investigate the mechanisms that control human behavior in this respect. The results may be used when designing future military robots, to control unwanted tendencies to assign responsibility to the robots. Independent of the responsibility issue, the moral quality of robots’ behavior should be seen as one of many performance measures by which we evaluate robots. How to design ethics based control systems should be carefully investigated already now. From a consequentialist view, it would indeed be highly immoral to develop robots capable of performing acts involving life and death, without including some kind of moral framework. (shrink)

There has recently been increasing interest in the possibility and ethics of lethal autonomous weapons systems (LAWS), which would combine sophisticated AI with machinery capable of deadly force. One objection to LAWS is that their use will create a troubling responsibility gap, where no human agent can properly be held accountable for the outcomes that they create. While some authors have attempted to show that individual agents can, in fact, be responsible for the behaviour of LAWS in various circumstances, this (...) will not be possible in all cases. This article argues, however, that by assigning responsibilities to group agents operating within the military‐industrial complex, as well as the military‐industrial complex as a whole, we may be able to close the responsibility gap, or at least reduce its costs. Insofar as the potential for responsibility gaps poses an ethical barrier to the development and deployment of LAWS, this argument, if sound, may show their use to be morally permissible in a greater range of cases. (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)

The leading idea of our theory of moral responsibility is that responsibility is associated with control. But we contend that there are two distinct kinds of control. Regulative control involves alternative possibilities: it is a kind of dual power of free action. In contrast, guidance control does not, by its nature, involve alternative possibilities. Whereas typically it might be thought that regulative and guidance control go together, the Frankfurt-type cases show that they are separate and distinct sorts of control. And, (...) whereas typically it is thought that moral responsibility requires regulative control, we claim that moral responsibility—for actions, omissions, and consequences—simply requires guidance control. Thus, although we do not believe that moral responsibility requires alternative possibilities, we preserve the traditional association of moral responsibility with control. (shrink)

Editors’ Overview: Moral Responsibility in Technology and Engineering Content Type Journal Article Category Original Paper Pages 1-11 DOI 10.1007/s11948-011-9285-z Authors Neelke Doorn, Department of Technology, Policy and Management, Delft University of Technology, P.O. Box 5015, 2600 GA Delft, The Netherlands Ibo van de Poel, Department of Technology, Policy and Management, Delft University of Technology, P.O. Box 5015, 2600 GA Delft, The Netherlands Journal Science and Engineering Ethics Online ISSN 1471-5546 Print ISSN 1353-3452 Journal Volume Volume 18 Journal Issue Volume 18, (...) Number 1. (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)

This paper argues that it is permissible for computer scientists and engineers—working with advanced militaries that are making good faith efforts to follow the laws of war—to engage in the research and development of lethal autonomous weapons systems. Research and development into a new weapons system is permissible if and only if the new weapons system can plausibly generate a superior risk profile for all morally relevant classes and it is not intrinsically wrong. The paper then suggests that these conditions (...) are satisfied by at least some potential LAWS development programs. More specifically, since LAWS will lead to greater force protection, warfighters are free to become more risk-acceptant in protecting civilian lives and property. Further, various malicious motivations that lead to war crimes will not apply to LAWS or will apply to no greater extent than with human warfighters. Finally, intrinsic objections—such as the claims that LAWS violate human dignity or that it creates ‘responsibility gaps’—are rejected on the basis that they rely upon implausibly idealized and atomized understandings of human decision-making in combat. (shrink)

Epistemic limitations concerning prediction and explanation of the behaviour of robots that learn from experience are selectively examined by reference to machine learning methods and computational theories of supervised inductive learning. Moral responsibility and liability ascription problems concerning damages caused by learning robot actions are discussed in the light of these epistemic limitations. In shaping responsibility ascription policies one has to take into account the fact that robots and softbots - by combining learning with autonomy, pro-activity, reasoning, and planning - (...) can enter cognitive interactions that human beings have not experienced with any other non-human system. (shrink)