The ability of machines to make truly independent and autonomous decisions is a goal of many, not least of military leaders who wish to take the human out of the loop as much as possible, claiming that autonomous military weaponry—most notably drones—can make decisions more quickly and with greater accuracy. However, there is no clear understanding of how autonomous weapons should be conceptualized and of the implications that their “autonomous” nature has on them as ethical agents. It will be argued (...) that autonomous weapons are not full ethical agents due to the restrictions of their coding. However, the highly complex machine-learning nature gives the impression that they are making their own decisions and creates the illusion that their human operators are protected from the responsibility of the harm they cause. Therefore, it is important to distinguish between autonomous AI weapons and an AI with autonomy, a distinction that creates two different ethical problems for their use. For autonomous weapons, their limited agency combined with machine-learning means their human counterparts are still responsible for their actions while having no ability to control or intercede in the actual decisions made. If, on the other hand, an AI could reach the point of autonomy, the level of critical reflection would make its decisions unpredictable and dangerous in a weapon. (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)

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)

Artificial intelligence increasingly executes tasks that previously only humans could do, such as drive a car, fight in war, or perform a medical operation. However, as the very best AI systems tend to be the least controllable and the least transparent, some scholars argued that humans can no longer be morally responsible for some of the AI-caused outcomes, which would then result in a responsibility gap. In this paper, I assume, for the sake of argument, that at least some of (...) the most sophisticated AI systems do indeed create responsibility gaps, and I ask whether we can bridge these gaps at will, viz. whether certain people could take responsibility for AI-caused harm simply by performing a certain speech act, just as people can give permission for something simply by performing the act of consent. So understood, taking responsibility would be a genuine normative power. I first discuss and reject the view of Champagne and Tonkens, who advocate a view of taking liability. According to this view, a military commander can and must, ahead of time, accept liability to blame and punishment for any harm caused by autonomous weapon systems under her command. I then defend my own proposal of taking answerability, viz. the view that people can makes themselves morally answerable for the harm caused by AI systems, not only ahead of time but also when harm has already been caused. (shrink)

New technologies are the source of uncertainties about the applicability of moral and morally connotated concepts. These uncertainties sometimes call for conceptual engineering, but it is not often recognized when this is the case. We take this to be a missed opportunity, as a recognition that different researchers are working on the same kind of project can help solve methodological questions that one is likely to encounter. In this paper, we present three case studies where philosophers of technology implicitly engage (...) in conceptual engineering (without naming it as such). We subsequently reflect on the case studies to find out how these illustrate conceptual engineering as an appropriate method to deal with pressing concerns in the philosophy of technology. We have two main goals. We first want to contribute to the literature on conceptual engineering by presenting concrete examples of conceptual engineering in the philosophy of technology. This is especially relevant, because the technologies that are designed based on the conceptual work done by philosophers of technology potentially have crucial moral and social implications. Secondly, we want to make explicit what choices are made when doing this conceptual work. Making explicit that some of the implicit assumptions are, in fact, debated in the literature allows for reflection on these questions. Ultimately, our hope is that conscious reflection leads to an improvement of the conceptual work done. (shrink)

The paper presents an ethical analysis and constructive critique of the current practice of AI ethics. It identifies conceptual substantive and procedural challenges and it outlines strategies to address them. The strategies include countering the hype and understanding AI as ubiquitous infrastructure including neglected issues of ethics and justice such as structural background injustices into the scope of AI ethics and making the procedures and fora of AI ethics more inclusive and better informed with regard to philosophical ethics. These measures (...) integrate the perspective of AI justice into AI ethics, strengthening its capacity to provide comprehensive normative orientation and guidance for the development and use of AI that actually improves human lives and living together. (shrink)

Can artificial entities be worthy of moral considerations? Can they be artificial moral agents (AMAs), capable of telling the difference between good and evil? In this essay, I explore both questions—i.e., whether and to what extent artificial entities can have a moral status (“the machine question”) and moral agency (“the AMA question”)—in light of Kazuo Ishiguro’s 2021 novel Klara and the Sun. I do so by juxtaposing two prominent approaches to machine morality that are central to the novel: the (1) (...) view “from within,” including the standard (or “metaphysical”) perspective on moral agency, and the (2) view “from outside,” which includes behaviorism, functionalism and the social-relational perspective. Importantly, while the story illustrates both views, it exposes the epistemological vulnerability of the first in relation to the practical and social reality imposed by the second. That is, regardless of what metaphysical properties the Artificial Friend Klara can be said to have (from within), her moral status as well as agency ultimately depend on the views of others (from outside), including the others’ own epistemic beliefs about the nature of consciousness and personhood. (shrink)

Are we being manipulated online? If so, is being manipulated by online technologies and algorithmic systems notably different from human forms of manipulation? And what is under threat exactly when people are manipulated online? This volume provides philosophical and conceptual depth to debates in digital ethics about online manipulation. The contributions explore the ramifications of our increasingly consequential interactions with online technologies such as online recommender systems, social media, user-friendly design, micro-targeting, default-settings, gamification, and real-time profiling. The authors in this (...) volume address four broad and interconnected themes: • What is the conceptual nature of online manipulation? And how, methodologically, should the concept be defined? • Does online manipulation threaten autonomy, freedom, and meaning in life, and if so, how? • What are the epistemic, affective, and political harms and risks associated with online manipulation? • What are legal and regulatory perspectives on online manipulation? The Philosophy of Online Manipulation brings these various considerations together to offer philosophically robust answers to critical questions concerning our online interactions with one another and with autonomous systems. It will be of interest to researchers and advanced students working in moral philosophy, digital ethics, philosophy of technology, and the ethics of manipulation. (shrink)

Recent advancements in artificial intelligence have fueled widespread academic discourse on the ethics of AI within and across a diverse set of disciplines. One notable subfield of AI ethics is machine ethics, which seeks to implement ethical considerations into AI systems. However, since different research efforts within machine ethics have discipline-specific concepts, practices, and goals, the resulting body of work is pestered with conflict and confusion as opposed to fruitful synergies. The aim of this paper is to explore ways to (...) alleviate these issues, both on a practical and theoretical level of analysis. First, we describe two approaches to machine ethics: the philosophical approach and the engineering approach and show how tensions between the two arise due to discipline specific practices and aims. Using the concept of disciplinary capture, we then discuss potential promises and pitfalls to cross-disciplinary collaboration. Drawing on recent work in philosophy of science, we finally describe how metacognitive scaffolds can be used to avoid epistemological obstacles and foster innovative collaboration in AI ethics in general and machine ethics in particular. (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)

Artificial agents have become increasingly prevalent in human social life. In light of the diversity of new human–machine interactions, we face renewed questions about the distribution of moral responsibility. Besides positions denying the mere possibility of attributing moral responsibility to artificial systems, recent approaches discuss the circumstances under which artificial agents may qualify as moral agents. This paper revisits the discussion of how responsibility might be distributed between artificial agents and human interaction partners (including producers of artificial agents) and raises (...) the question of whether attributions of responsibility should remain entirely on the human side. While acknowledging a crucial difference between living human beings and artificial systems culminating in an asymmetric feature of human–machine interactions, this paper investigates the extent to which artificial agents may reasonably be attributed a share of moral responsibility. To elaborate on criteria that can justify a distribution of responsibility in certain human–machine interactions, the role of types of criteria (interaction-related criteria and criteria that can be deferred from socially constructed responsibility relationships) is examined. Thereby, the focus will lay on the evaluation of potential criteria referring to the fact that artificial agents surpass in some aspects the capacities of humans. This is contrasted with socially constructed responsibility relationships that do not take these criteria into account. In summary, situations are examined in which it seems plausible that moral responsibility can be distributed between artificial and human agents. (shrink)

In this article, we focus on the scholarly and policy debate on autonomous weapon systems and particularly on the objections to the use of these weapons which rest on jus ad bellum principles of proportionality and last resort. Both objections rest on the idea that AWS may increase the incidence of war by reducing the costs for going to war or by providing a propagandistic value. We argue that whilst these objections offer pressing concerns in their own right, they suffer (...) from important limitations: they overlook the difficulties of calculating ad bellum proportionality; confuse the concept of proportionality of effects with the precision of weapon systems; disregard the ever-changing nature of war and of its ethical implications; mistake the moral obligation imposed by the principle of last resort with the impact that AWS may have on political decision to resort to war. Our analysis does not entail that AWS are acceptable or justifiable, but it shows that ad bellum principles are not the best set of ethical principles for tackling the ethical problems raised by AWS; and that developing adequate understanding of the transformations that the use of AWS poses to the nature of war itself is a necessary, preliminary requirement to any ethical analysis of the use of these weapons. (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)

Do we suddenly become justified in treating robots like humans by positing new notions like “artificial moral agency” and “artificial moral responsibility”? I answer no. Or, to be more precise, I argue that such notions may become philosophically acceptable only after crucial metaphysical issues have been addressed. My main claim, in sum, is that “artificial moral responsibility” betokens moral responsibility to the same degree that a “fake orgasm” betokens an orgasm.

Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, we (...) critically explore the possibilities and challenges for virtue ethics from a computational perspective. Drawing on previous conceptual and technical work, we outline a version of artificial virtue based on moral functionalism, connectionist bottom–up learning, and eudaimonic reward. We then describe how core features of the outlined theory can be interpreted in terms of functionality, which in turn informs the design of components necessary for virtuous cognition. Finally, we present a comprehensive framework for the technical development of artificial virtuous agents and discuss how they can be implemented in moral environments. (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)

The potential capacity for robots to deceive has received considerable attention recently. Many papers explore the technical possibility for a robot to engage in deception for beneficial purposes (e.g., in education or health). In this short experimental paper, I focus on a more paradigmatic case: robot lying (lying being the textbook example of deception) for nonbeneficial purposes as judged from the human point of view. More precisely, I present an empirical experiment that investigates the following three questions: (a) Are ordinary (...) people willing to ascribe deceptive intentions to artificial agents? (b) Are they as willing to judge a robot lie as a lie as they would be when human agents engage in verbal deception? (c) Do people blame a lying artificial agent to the same extent as a lying human agent? The response to all three questions is a resounding yes. This, I argue, implies that robot deception and its normative consequences deserve considerably more attention than they presently receive. (shrink)

Autonomous Weapons Systems (AWS) have not gained a good reputation in the past. This attitude is odd if we look at the discussion of other-usually highly anticipated-AI-technologies, like autonomous vehicles (AVs); whereby even though these machines evoke very similar ethical issues, philosophers' attitudes towards them are constructive. In this article, I try to prove that there is an unjust bias against AWS because almost every argument against them is effective against AVs too. I start with the definition of "AWS." Then, (...) I arrange my arguments by the Just War Theory (JWT), covering jus ad bellum, jus in bello and jus post bellum problems. Meanwhile, I draw attention to similar problems against other AI-technologies outside the JWT framework. Finally, I address an exception, as addressed by Duncan Purves, Ryan Jenkins and Bradley Strawser, who realized the unjustified double standard, and deliberately tried to construct a special argument which rules out only AWS. (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)

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)

Alan Turing, one of the fathers of computing, warned that Artificial Intelligence (AI) could one day pose an existential risk to humanity. Today, recent advancements in the field AI have been accompanied by a renewed set of existential warnings. But what exactly constitutes an existential risk? And how exactly does AI pose such a threat? In this chapter we aim to answer these questions. In particular, we will critically explore three commonly cited reasons for thinking that AI poses an existential (...) threat to humanity: the control problem, the possibility of global disruption from an AI race dynamic, and the weaponization of AI. (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 philosophy of mind, zombies are imaginary creatures that are exact physical duplicates of conscious subjects but for whom there is no first-personal experience. Zombies are meant to show that physicalism—the theory that the universe is made up entirely out of physical components—is false. In this paper, I apply the zombie thought experiment to the realm of morality to assess whether moral agency is something independent from sentience. Algorithms, I argue, are a kind of functional moral zombie, such that thinking (...) about the latter can help us better understand and regulate the former. I contend that the main reason why algorithms can be neither autonomous nor accountable is that they lack sentience. Moral zombies and algorithms are incoherent as moral agents because they lack the necessary moral understanding to be morally responsible. To understand what it means to inflict pain on someone, it is necessary to have experiential knowledge of pain. At most, for an algorithm that feels nothing, ‘values’ will be items on a list, possibly prioritised in a certain way according to a number that represents weightiness. But entities that do not feel cannot value, and beings that do not value cannot act for moral reasons. (shrink)

In two experiments (total N=693) we explored whether people are willing to consider paintings made by AI-driven robots as art, and robots as artists. Across the two experiments, we manipulated three factors: (i) agent type (AI-driven robot v. human agent), (ii) behavior type (intentional creation of a painting v. accidental creation), and (iii) object type (abstract v. representational painting). We found that people judge robot paintings and human painting as art to roughly the same extent. However, people are much less (...) willing to consider robots as artists than humans, which is partially explained by the fact that they are less disposed to attribute artistic intentions to robots. (shrink)

As artificial intelligence becomes ubiquitous, it will be increasingly involved in novel, morally significant situations. Thus, understanding what it means for a machine to be morally responsible is important for machine ethics. Any method for ascribing moral responsibility to AI must be intelligible and intuitive to the humans who interact with it. We argue that the appropriate approach is to determine how AIs might fare on a standard account of human moral responsibility: a Strawsonian account. We make no claim that (...) our Strawsonian approach is either the only one worthy of consideration or the obviously correct approach, but we think it is preferable to trying to marry fundamentally different ideas of moral responsibility into a single cohesive account. Under a Strawsonian framework, people are morally responsible when they are appropriately subject to a particular set of attitudes—reactive attitudes—and determine under what conditions it might be appropriate to subject machines to this same set of attitudes. Although the Strawsonian account traditionally applies to individual humans, it is plausible that entities that are not individual humans but possess these attitudes are candidates for moral responsibility under a Strawsonian framework. We conclude that weak AI is never morally responsible, while a strong AI with the right emotional capacities may be morally responsible. (shrink)

Recent discussion on the ethics of killer robots has focused on the supposed lack of respect their deployment would show to combatants targeted, thereby causing their undignified deaths. I present two rebuttals of this argument. The weak rebuttal maintains that while deploying killer robots is an affront to the dignity of combatants, their use should nevertheless be thought of as a pro tanto wrong, making deployment permissible if the affront is outweighed by some right-making feature. This rebuttal is, however, vulnerable (...) to the charge that killer robots would cause unnecessary suffering. The strong rebuttal, in contrast, argues that the use of killer robots would not disrespect the dignity of combatants, for reasons discussed. I also argue that, irrespective of whether killer robots disrespect the dignity of combatants, they would not necessarily bring about their undignified deaths: for one can maintain dignity in the face of indignity. (shrink)

In this paper I critically evaluate the value neutrality thesis regarding technology, and find it wanting. I then introduce the various ways in which artifacts can come to influence moral value, and our evaluation of moral situations and actions. Here, following van de Poel and Kroes, I introduce the idea of value sensitive design. Specifically, I show how by virtue of their designed properties, artifacts may come to embody values. Such accounts, however, have several shortcomings. In agreement with Michael Klenk, (...) I raise epistemic and metaphysical issues with respect to designed properties embodying value. The concept of an affordance, borrowed from ecological psychology, provides a more philosophically fruitful grounding to the potential way(s) in which artifacts might embody values. This is due to the way in which it incorporates key insights from perception more generally, and how we go about determining possibilities for action in our environment specifically. The affordance account as it is presented by Klenk, however, is insufficient. I therefore argue that we understand affordances based on whether they are meaningful, and, secondly, that we grade them based on their force. (shrink)

Recent research shows – somewhat astonishingly – that people are willing to ascribe moral blame to AI-driven systems when they cause harm [1]–[4]. In this paper, we explore the moral- psychological underpinnings of these findings. Our hypothesis was that the reason why people ascribe moral blame to AI systems is that they consider them capable of entertaining inculpating mental states (what is called mens rea in the law). To explore this hypothesis, we created a scenario in which an AI system (...) runs a risk of poisoning people by using a novel type of fertilizer. Manipulating the computational (or quasi-cognitive) abilities of the AI system in a between-subjects design, we tested whether people’s willingness to ascribe knowledge of a substantial risk of harm (i.e., recklessness) and blame to the AI system. Furthermore, we investigated whether the ascription of recklessness and blame to the AI system would influence the perceived blameworthiness of the system’s user (or owner). In an experiment with 347 participants, we found (i) that people are willing to ascribe blame to AI systems in contexts of recklessness, (ii) that blame ascriptions depend strongly on the willingness to attribute recklessness and (iii) that the latter, in turn, depends on the perceived “cognitive” capacities of the system. Furthermore, our results suggest (iv) that the higher the computational sophistication of the AI system, the more blame is shifted from the human user to the AI system. (shrink)

The fact that real-world decisions made by artificial intelligences (AI) are often ethically loaded has led a number of authorities to advocate the development of “moral machines”. I argue that the project of building “ethics” “into” machines presupposes a flawed understanding of the nature of ethics. Drawing on the work of the Australian philosopher, Raimond Gaita, I argue that ethical dilemmas are problems for particular people and not (just) problems for everyone who faces a similar situation. Moreover, the force of (...) an ethical claim depends in part on the life history of the person who is making it. For both these reasons, machines could at best be engineered to provide a shallow simulacrum of ethics, which would have limited utility in confronting the ethical and policy dilemmas associated with AI. (shrink)

The Laws of Armed Conflict require that war crimes be attributed to individuals who can be held responsible and be punished. Yet assigning responsibility for the actions of Lethal Autonomous Weapon...

What does Artificial Intelligence (AI) have to contribute to health care? And what should we be looking out for if we are worried about its risks? In this paper we offer a survey, and initial evaluation, of hopes and fears about the applications of artificial intelligence in medicine. AI clearly has enormous potential as a research tool, in genomics and public health especially, as well as a diagnostic aid. It’s also highly likely to impact on the organisational and business practices (...) of healthcare systems in ways that are perhaps under-appreciated. Enthusiasts for AI have held out the prospect that it will free physicians up to spend more time attending to what really matters to them and their patients. We will argue that this claim depends upon implausible assumptions about the institutional and economic imperatives operating in contemporary healthcare settings. We will also highlight important concerns about privacy, surveillance, and bias in big data, as well as the risks of over trust in machines, the challenges of transparency, the deskilling of healthcare practitioners, the way AI reframes healthcare, and the implications of AI for the distribution of power in healthcare institutions. We will suggest that two questions, in particular, are deserving of further attention from philosophers and bioethicists. What does care look like when one is dealing with data as much as people? And, what weight should we give to the advice of machines in our own deliberations about medical decisions? (shrink)

Warfare is becoming increasingly automated, from automatic missile defense systems to micro-UAVs (WASPs) that can maneuver through urban environments with ease, and each advance brings with it ethical questions in need of resolving. Proponents of lethal autonomous weapons systems (LAWS) provide varied arguments in their favor; robots are capable of better identifying combatants and civilians, thus reducing "collateral damage"; robots need not protect themselves and so can incur more risks to protect innocents or gather more information before using deadly force; (...) robots can assess situations more quickly and do so without emotion, reducing the likelihood of fatal mistakes due to human error; and sending robots to war protects our own soldiers from harm. However, these arguments only point in favor of autonomous weapons systems, failing to demonstrate why such systems need be made *lethal*. In this paper I argue that if one grants all of the proponents' points in favor of LAWS, then, contrary to what might be expected, this leads to the conclusion that it would be both immoral and illegal to deploy *lethal* autonomous weapons, because the many features that speak in favor of them also undermine the need for them to be programmed to take lives. In particular, I argue that such systems, if lethal, would violate the moral and legal principle of necessity, which forbids the use of weapons that impose superfluous injury or unnecessary harm. I conclude by highlighting that the argument is not against autonomous weapons per se, but only against *lethal* autonomous weapons. (shrink)

The potential capacity for robots to deceive has received considerable attention recently. Many papers focus on the technical possibility for a robot to engage in deception for beneficial purposes (e.g. in education or health). In this short experimental paper, I focus on a more paradigmatic case: Robot lying (lying being the textbook example of deception) for nonbeneficial purposes as judged from the human point of view. More precisely, I present an empirical experiment with 399 participants which explores the following three (...) questions: (i) Are ordinary people willing to ascribe intentions to deceive to artificial agents? (ii) Are they as willing to judge a robot lie as a lie as they would be when human agents engage in verbal deception? (iii) Do they blame a lying artificial agent to the same extent as a lying human agent? The response to all three questions is a resounding yes. This, I argue, implies that robot deception and its normative consequences deserve considerably more attention than it presently attracts. (shrink)

Debates about terrorism and technology often focus on the potential uses of technology by non-state terrorist actors and by states as forms of counterterrorism. Yet, little has been written about how technology shapes how we think about terrorism. In this chapter I argue that technology, and the language we use to talk about technology, constrains and shapes our understanding of the nature, scope, and impact of terrorism, particularly in relation to state terrorism. After exploring the ways in which technology shapes (...) moral thinking, I use two case studies to demonstrate how technology simultaneously hides and enables terroristic forms of state violence: police control technologies and Unmanned Aerial Vehicles (UAVs), or drones. In both these cases, I argue that features of these technologies, combined with a narrative of precision and efficiency, serves to mask the terroristic nature of the violence that these practices inflict and reinforces the moral exclusion of those against whom these technologies are deployed. In conclusion, I propose that identifying acts of terrorism requires a focus on the impact of technologies of violence (whether they are “high tech” or not) on those most affected, regardless of whether users of these technologies conceive of their actions as terroristic. (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)

To many, the idea of autonomous weapons systems (AWS) killing human beings is grotesque. Yet critics have had difficulty explaining why it should make a significant moral difference if a human combatant is killed by an AWS as opposed to being killed by a human combatant. The purpose of this paper is to explore the roots of various deontological concerns with AWS and to consider whether these concerns are distinct from any concerns that also apply to long- distance, human-guided weaponry. (...) We suggest that at least one major driver of the intuitive moral aversion to lethal AWS is that their use disrespects their human targets by violating the martial contract between human combatants. On our understanding of this doctrine, service personnel cede a right not to be directly targeted with lethal violence to other human agents alone. Artificial agents, of which AWS are one example, cannot understand the value of human life. A human combatant cannot transfer his privileges of targeting enemy combatants to a robot. Therefore, the human duty-holder who deploys AWS breaches the martial contract between human combatants and disrespects the targeted combatants. We consider whether this novel deontological objection to AWS forms the foundation of several other popular yet imperfect deontological objections to AWS. (shrink)

In this paper I provide an exposition and critique of Johnson and Noorman’s (2014) three conceptualizations of the agential roles artificial systems can play. I argue that two of these conceptions are unproblematic: that of causally efficacious agency and “acting for” or surrogate agency. Their third conception, that of “autonomous agency,” however, is one I have reservations about. The authors point out that there are two ways in which the term “autonomy” can be used: there is, firstly, the engineering sense (...) of the term, which simply refers to the ability of some system to act independently of substantive human control. Secondly, there is the moral sense of the term, which has traditionally grounded many notions of human mor-al responsibility. I argue that the continued usage of “autonomy” in discussions of artificial agency complicates matters unnecessarily. This occurs in two ways: firstly, the condition of autonomy, even in its engineering sense, fails to accurately describe the way “autonomous” systems are developed in practice. Secondly, the continued usage of autonomy in the moral sense introduces unnecessary meta-physical baggage form the free will debate into discussions about moral agency. In order to understand the debate surrounding autonomy, we would therefore first need to settle many seemingly intractable metaphysical questions regarding the existence of free will in human beings. (shrink)

In this panel, we explore the future of value sensitive design (VSD). The stakes are high. Many in public and private sectors and in civil society are gradually realizing that taking our values seriously implies that we have to ensure that values effectively inform the design of technology which, in turn, shapes people’s lives. Value sensitive design offers a highly developed set of theory, tools, and methods to systematically do so.

Ethics settings allow for morally significant decisions made by humans to be programmed into autonomous machines, such as autonomous vehicles or autonomous weapons. Customizable ethics settings are a type of ethics setting in which the users of autonomous machines make such decisions. Here two arguments are provided in defence of customizable ethics settings. Firstly, by approaching ethics settings in the context of failure management, it is argued that customizable ethics settings are instrumentally and inherently valuable for building resilience into the (...) larger socio-technical systems in which autonomous machines operate. Secondly, after defining the preliminary condition of responsibility attribution and demonstrating how ethics settings enable humans to exert control over the outcomes of morally significant incidents, it is shown that ethics settings narrow the responsibility gap. (shrink)

This paper proposes a methodological redirection of the philosophical debate on artificial moral agency in view of increasingly pressing practical needs due to technological development. This “normative approach” suggests abandoning theoretical discussions about what conditions may hold for moral agency and to what extent these may be met by artificial entities such as AI systems and robots. Instead, the debate should focus on how and to what extent such entities should be included in human practices normally assuming moral agency and (...) responsibility of participants. The proposal is backed up by an analysis of the AMA debate, which is found to be overly caught in the opposition between so-called standard and functionalist conceptions of moral agency, conceptually confused and practically inert. Additionally, we outline some main themes of research in need of attention in light of the suggested normative approach to AMA. (shrink)

Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools made and (...) used by humans; here, the main sections are privacy (2.1), manipulation (2.2), opacity (2.3), bias (2.4), autonomy & responsibility (2.6) and the singularity (2.7). Then we look at AI systems as subjects, i.e. when ethics is for the AI systems themselves in machine ethics (2.8.) and artificial moral agency (2.9). Finally we look at future developments and the concept of AI (3). For each section within these themes, we provide a general explanation of the ethical issues, we outline existing positions and arguments, then we analyse how this plays out with current technologies and finally what policy conse-quences may be drawn. (shrink)

The aim of this thesis is to advance a philosophically justifiable account of Artificial Moral Agency (AMA). Concerns about the moral status of Artificial Intelligence (AI) traditionally turn on questions of whether these systems are deserving of moral concern (i.e. if they are moral patients) or whether they can be sources of moral action (i.e. if they are moral agents). On the Organic View of Ethical Status, being a moral patient is a necessary condition for an entity to qualify as (...) a moral agent. This view claims that because artificial agents (AAs) lack sentience, they cannot be proper subjects of moral concern and hence cannot be considered to be moral agents. I raise conceptual and epistemic issues with regards to the sense of sentience employed on this view, and I argue that the Organic View does not succeed in showing that machines cannot be moral patients. Nevertheless, irrespective of this failure, I also argue that the entire project is misdirected in that moral patiency need not be a necessary condition for moral agency. Moreover, I claim that whereas machines may conceivably be moral patients in the future, there is a strong case to be made that they are (or will very soon be) moral agents. Whereas it is often argued that machines cannot be agents simpliciter, let alone moral agents, I claim that this argument is predicated on a conception of agency that makes unwarranted metaphysical assumptions even in the case of human agents. Once I have established the shortcomings of this “standard account”, I move to elaborate on other, more plausible, conceptions of agency, on which some machines clearly qualify as agents. Nevertheless, the argument is still often made that while some machines may be agents, they cannot be moral agents, given their ostensible lack of the requisite phenomenal states. Against this thesis, I argue that the requirement of internal states for moral agency is philosophically unsound, as it runs up against the problem of other minds. In place of such intentional accounts of moral agency, 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 situations for which no human being is morally responsible, but a machine may be. Moreover, this responsibility holds, I claim, independently of whether the agent in question is “punishable” or not. (shrink)

This paper discusses the problem of responsibility attribution raised by the use of artificial intelligence technologies. It is assumed that only humans can be responsible agents; yet this alone already raises many issues, which are discussed starting from two Aristotelian conditions for responsibility. Next to the well-known problem of many hands, the issue of “many things” is identified and the temporal dimension is emphasized when it comes to the control condition. Special attention is given to the epistemic condition, which draws (...) attention to the issues of transparency and explainability. In contrast to standard discussions, however, it is then argued that this knowledge problem regarding agents of responsibility is linked to the other side of the responsibility relation: the addressees or “patients” of responsibility, who may demand reasons for actions and decisions made by using AI. Inspired by a relational approach, responsibility as answerability thus offers an important additional, if not primary, justification for explainability based, not on agency, but on patiency. (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)

I analyse an argument according to which medical artificial intelligence represents a threat to patient autonomy—recently put forward by Rosalind McDougall in the Journal of Medical Ethics. The argument takes the case of IBM Watson for Oncology to argue that such technologies risk disregarding the individual values and wishes of patients. I find three problems with this argument: it confuses AI with machine learning; it misses machine learning’s potential for personalised medicine through big data; it fails to distinguish between evidence-based (...) advice and decision-making within healthcare. I conclude that how much and which tasks we should delegate to machine learning and other technologies within healthcare and beyond is indeed a crucial question of our time, but in order to answer it, we must be careful in analysing and properly distinguish between the different systems and different delegated tasks. (shrink)

Autonomous Weapon Systems (AWS) are the next logical advancement for military technology. There is a significant concern though that by allowing such systems on the battlefield, we are collectively abdicating our moral responsibility. In this thesis, I will examine two arguments that advocate for a total ban on the use of AWS. I call these arguments the “Responsibility” and the “Agency” arguments. After presenting these arguments, I provide my own objections and demonstrate why these arguments fail to convince. I then (...) provide an argument as to why the use of AWS is a rational choice in the evolution of warfare. I conclude my thesis by providing a framework upon which future international regulations regarding AWS could be built. (shrink)

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)

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)

We study whether robots can satisfy the conditions of an agent fit to be held morally responsible, with a focus on autonomy and self-control. An analogy between robots and human groups enables us to modify arguments concerning collective responsibility for studying questions of robot responsibility. We employ Mele’s history-sensitive account of autonomy and responsibility to argue that even if robots were to have all the capacities required of moral agency, their history would deprive them from autonomy in a responsibility-undermining way. (...) We will also study whether humans and technological artifacts like robots can form hybrid collective agents that could be morally responsible for their actions and give an argument against such a possibility. (shrink)