The convergence of computing, sensing, and communication technology will soon permit large-scale deployment of self-driving vehicles. This will in turn permit a radical transformation of traffic control technology. This paper makes a case for the importance of addressing questions of social justice in this transformation, and sketches a preliminary framework for doing so. We explain how new forms of traffic control technology have potential implications for several dimensions of social justice, including safety, sustainability, privacy, efficiency, and equal access. Our central (...) focus is on efficiency and equal access as desiderata for traffic control design. We explain the limitations of conventional traffic control in meeting these desiderata, and sketch a preliminary vision for a next-generation traffic control tailored to address better the demands of social justice. One component of this vision is cooperative, hierarchically distributed self-organization among vehicles. Another component of this vision is a priority system enabling selection of priority levels by the user for each vehicle trip in the network, based on the supporting structure of non-monetary credits. (shrink)

The recent progress in the development of autonomous cars has seen ethical questions come to the forefront. In particular, life and death decisions regarding the behavior of self-driving cars in trolley dilemma situations are attracting widespread interest in the recent debate. In this essay we want to ask whether we should implement a mandatory ethics setting for the whole of society or, whether every driver should have the choice to select his own personal ethics setting. While the consensus view seems (...) to be that people would not be willing to use an automated car that might sacrifice themselves in a dilemma situation, we will defend the somewhat contra-intuitive claim that this would be nevertheless in their best interest. The reason is, simply put, that a PES regime would most likely result in a prisoner’s dilemma. (shrink)

Self-driving cars hold out the promise of being safer than manually driven cars. Yet they cannot be a 100 % safe. Collisions are sometimes unavoidable. So self-driving cars need to be programmed for how they should respond to scenarios where collisions are highly likely or unavoidable. The accident-scenarios self-driving cars might face have recently been likened to the key examples and dilemmas associated with the trolley problem. In this article, we critically examine this tempting analogy. We identify three important ways (...) in which the ethics of accident-algorithms for self-driving cars and the philosophy of the trolley problem differ from each other. These concern: the basic decision-making situation faced by those who decide how self-driving cars should be programmed to deal with accidents; moral and legal responsibility; and decision-making in the face of risks and uncertainty. In discussing these three areas of disanalogy, we isolate and identify a number of basic issues and complexities that arise within the ethics of the programming of self-driving cars. (shrink)

Who is responsible for a harm caused by AI, or a machine or system that relies on artificial intelligence? Given that current AI is neither conscious nor sentient, it’s unclear that AI itself is responsible for it. But given that AI acts independently of its developer or user, it’s also unclear that the developer or user is responsible for the harm. This gives rise to the so-called responsibility gap: cases where AI causes a harm, but no one is responsible for (...) it. Two central questions in the literature are whether responsibility gaps exist, and if yes, whether they’re morally problematic in a way that counts against developing or using AI. While some authors argue that responsibility gaps exist, and they’re morally problematic, some argue that they don’t exist. In this paper, I defend a novel position. First, I argue that current AI doesn’t generate a new kind of concern about responsibility that the older technologies don’t. Then, I argue that responsibility gaps exist but they’re unproblematic. (NOTE: Email me for a copy.). (shrink)

Responsibility gaps occur when autonomous machines cause harms for which nobody can be justifiably held morally responsible. The debate around responsibility gaps has focused primarily on the question of responsibility, but other approaches focus on the victims of the associated harms. In this paper I consider how the victims of ‘AI-harm’—by which I mean harms implicated in responsibility gap cases and caused by AI-agents—can make sense of what has happened to them. The reactive attitudes have an important role here. I (...) argue that regulating our reactive attitudes—withdrawing or sustaining them as our understanding of the actions, motives, status, and character of others develops—is an important part of the way in which we make sense of the harms we suffer. But, I argue, AI-agents can disrupt standard practices of regulating the reactive attitudes. This can lead victims of AI-harm to suffer a secondary hermeneutic harm (in addition to the primary AI-harm). This harm, which the responsibility gap and AI ethics literatures have neglected, can occur whether responsibility gaps are real or not. (shrink)

Artificial intelligence (AI) has long been recognised as a challenge to responsibility. Much of this discourse has been framed around robots, such as autonomous weapons or self-driving cars, where we arguably lack control over a machine’s behaviour and therefore struggle to identify an agent that can be held accountable. However, most of today’s AI is based on machine-learning technology that does not act on its own, but rather serves as a decision-support tool, automatically analysing data to help human agents make (...) better decisions. I argue that decision-support tools pose a challenge to responsibility that goes beyond the familiar problem of finding someone to blame or punish for the behaviour of agent-like systems. Namely, they pose a problem for what we might call “decision ownership”: they make it difficult to identify human agents to whom we can attribute value-judgements that are reflected in decisions. Drawing on recent philosophical literature on responsibility and its various facets, I argue that this is primarily a problem of attributability rather than of accountability. This particular responsibility problem comes in different forms and degrees, most obviously when an AI provides direct recommendations for actions, but also, less obviously, when it provides mere descriptive information on the basis of which a decision is made. (shrink)

I argue for responsibility internalism. That is, moral responsibility (i.e., accountability, or being apt for praise or blame) depends only on factors internal to agents. Employing this view, I also argue that no one is responsible for what AI does but this isn’t morally problematic in a way that counts against developing or using AI. Responsibility is grounded in three potential conditions: the control (or freedom) condition, the epistemic (or awareness) condition, and the causal responsibility condition (or consequences). I argue (...) that causal responsibility is irrelevant for moral responsibility, and that the control condition and the epistemic condition depend only on factors internal to agents. Moreover, since what AI does is at best a consequence of our actions, and the consequences of our actions are irrelevant to our responsibility, no one is responsible for what AI does. That is, the so-called responsibility gap exits. However, this isn’t morally worrisome for developing or using AI. Firstly, I argue, current AI doesn’t generate a new kind of concern about responsibility that the older technologies don’t. Then, I argue that responsibility gap is not worrisome because neither responsibility gap, nor my argument for its existence, entails that no one can be justly punished, held accountable, or incurs duties in reparations when AI causes a harm. (shrink)

Danaher (2016) has argued that increasing robotization can lead to retribution gaps: Situation in which the normative fact that nobody can be justly held responsible for a harmful outcome stands in conflict with our retributivist moral dispositions. In this paper, we report a cross-cultural empirical study based on Sparrow’s (2007) famous example of an autonomous weapon system committing a war crime, which was conducted with participants from the US, Japan and Germany. We find that (i) people manifest a considerable willingness (...) to hold autonomous systems morally responsible, (ii) partially exculpate human agents when interacting with such systems, and that more generally (iii) the possibility of normative responsibility gaps is indeed at odds with people’s pronounced retributivist inclinations. We discuss what these results mean for potential implications of the retribution gap and other positions in the responsibility gap literature. (shrink)

My starting point in this article is that investigating the ethics of autonomous vehicles through the lens of the trolley problem is not only limited but also unethical. I construct my case by aligning myself with Niklas Toivakainen, who argues against David Gunkel’s reading of Levinasian ethics as an answer to the “Machine Question”. I adumbrate Toivakainen’s critique that the attempt to give a Levinasian face to the machine is an example of a compensatory logic – a way to avoid (...) a deeper exploration of the moral dynamics from which our technologies emerge. I offer an extended reading of Levinas’s formulation of the face of the other to argue that while the machine cannot signify as a face, the machine can announce or anticipate the signification of the face which the self is infinitely responsible to. I reach this conclusion through focusing on the uncertainty and ambiguity of the signification of the face. I then argue that current approaches to the ethics of autonomous vehicles, based on variations of the trolley problem, fail to locate ethical responsibility to the other, precisely in its attempts to evade uncertainty. I demonstrate how an embrace of uncertainty can make the ethics of autonomous vehicles more ethical through a consideration of the concept of shared space and naked streets in the work of the late Dutch traffic engineer Hans Monderman. (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 paper has two goals. The first is presenting the main results of the recent report Ethics of Connected and Automated Vehicles: recommendations on road safety, privacy, fairness, explainability and responsibility written by the Horizon 2020 European Commission Expert Group to advise on specific ethical issues raised by driverless mobility, of which the author of this paper has been member and rapporteur. The second is presenting some broader ethical and philosophical implications of these recommendations, and using these to contribute to (...) the establishment of Ethics of Transportation as an independent branch of applied ethics. The recent debate on the ethics of Connected and Automated Vehicles presents a paradox and an opportunity. The paradox is the presence of a flourishing debate on the ethics of one very specific transportation technology without ethics of transportation being in itself a well-established academic discipline. The opportunity is that now that a spotlight has been switched on the ethical dimensions of CAVs it may be easier to establish a broader debate on ethics of transportation. While the 20 recommendations of the EU report are grouped in three macro-areas: road safety, data ethics, and responsibility, in this paper they will be grouped according to eight philosophical themes: Responsible Innovation, road justice, road safety, freedom, human control, privacy, data fairness, responsibility. These are proposed as the first topics for a new ethics of transportation. (shrink)

We motivate the desire for self-driving and explain its potential and limitations, and explore the need for—and potential implementation of—morals, ethics, and other value systems as complementary “capabilities” to the Deep Technologies behind self-driving. We consider how the incorporation of such systems may drive or slow adoption of high automation within vehicles. First, we explore the role for morals, ethics, and other value systems in self-driving through a representative hypothetical dilemma faced by a self-driving car. Through the lens of engineering, (...) we explain in simple terms common moral and ethical frameworks including utilitarianism, deontology, and virtue ethics before characterizing their relationship to the fundamental algorithms enabling self-driving. The concepts of behavior cloning, state-based modeling, and reinforcement learning are introduced, with some algorithms being more suitable for the implementation of value systems than others. We touch upon the contemporary cross-disciplinary landscape of morals and ethics in self-driving systems from a joint philosophical and technical perspective, and close with considerations for practitioners and the public, particularly as individuals may not appreciate the nuance and complexity of using imperfect information to navigate diverse scenarios and tough-to-quantify value systems, while “typical” software development reduces complex problems to black and white decision-making. (shrink)

In this paper, we argue that solutions to normative challenges associated with autonomous driving, such as real-world trolley cases or distributions of risk in mundane driving situations, face the problem of reasonable pluralism: Reasonable pluralism refers to the fact that there exists a plurality of reasonable yet incompatible comprehensive moral doctrines within liberal democracies. The corresponding problem is that a politically acceptable solution cannot refer to only one of these comprehensive doctrines. Yet a politically adequate solution to the normative challenges (...) of autonomous driving need not come at the expense of an ethical solution, if it is based on moral beliefs that are (1) shared in an overlapping consensus and (2) systematized through public reason. Therefore, we argue that a Rawlsian justificatory framework is able to adequately address the normative challenges of autonomous driving and elaborate on how such a framework might be employed for this purpose. (shrink)

As robots and Artificial Intelligences become more enmeshed in rich social contexts, it seems inevitable that we will have to make them into moral machines equipped with moral skills. Apart from the technical difficulties of how we could achieve this goal, we can also ask the ethical question of whether we should seek to create such Artificial Moral Agents (AMAs). Recently, several papers have argued that we have strong reasons not to develop AMAs. In response, we develop a comprehensive analysis (...) of the relevant arguments for and against creating AMAs, and we argue that all things considered we have strong reasons to continue to responsibly develop AMAs. The key contributions of this paper are threefold. First, to provide the first comprehensive response to the important arguments made against AMAs by Wynsberghe and Robbins (in “Critiquing the Reasons for Making Artificial Moral Agents”, Science and Engineering Ethics 25, 2019) and to introduce several novel lines of argument in the process. Second, to collate and thematise for the first time the key arguments for and against AMAs in a single paper. Third, to recast the debate away from blanket arguments for or against AMAs in general, to a more nuanced discussion about the use of what sort of AMAs, in what sort of contexts, and for what sort of purposes is morally appropriate. (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)

The goal of this article is to deepen the concept of emerging urban mobility technology. Drawing on philosophical everyday and urban aesthetics, as well as the postphenomenological strand in the philosophy of technology, we explicate the relation between everyday aesthetic experience and urban mobility commoning. Thus, we shed light on the central role of aesthetics for providing depth to the important experiential and value-driven meaning of contemporary urban mobility. We use the example of self-driving vehicle (SDV), as potentially mundane, public, (...) dynamic, and social urban robots, for expanding the range of perspectives relevant for our relations to urban mobility technology. We present the range of existing SDV conceptualizations and contrast them with experiential and aesthetic understanding of urban mobility. In conclusion, we reflect on the potential undesired consequences from the depolitization of technological development, and potential new pathways for speculative thinking concerning urban mobility futures in responsible innovation processes. (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)

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)

Domesticated animals need to be treated as fellow citizens: only if we conceive of domesticated animals as full members of our political communities can we do justice to their moral standing—or so Sue Donaldson and Will Kymlicka argue in their widely discussed book Zoopolis. In this contribution, we pursue two objectives. Firstly, we reject Donaldson and Kymlicka’s appeal for animal citizenship. We do so by submitting that instead of paying due heed to their moral status, regarding animals as citizens misinterprets (...) their moral qualities and thus risks treating them unjustly. Secondly, we suggest that Donaldson and Kymlicka’s reinforced focus on membership should draw our attention to the moral standing of a further ‘species’, namely robots. Developments within artificial intelligence have advanced rapidly in recent years. With robots’ gaining ever greater capacities and abilities, we need to ask urgent questions about the moral ramifications of these technical advances. (shrink)

The ethics of autonomous cars and automated driving have been a subject of discussion in research for a number of years :28–58, 2016). As levels of automation progress, with partially automated driving already becoming standard in new cars from a number of manufacturers, the question of ethical and legal standards becomes virulent. For exam-ple, while automated and autonomous cars, being equipped with appropriate detection sensors, processors, and intelligent mapping material, have a chance of being much safer than human-driven cars in (...) many regards, situations will arise in which accidents cannot be completely avoided. Such situations will have to be dealt with when programming the software of these vehicles. In several instances, internationally, regulations have been passed, based on legal considerations of road safety, mostly. However, to date, there have been few, if any, cases of a broader ethics code for autonomous or automated driving preceding actual regulation and being based on a broadly composed ethics committee of independent experts. In July 2016, the German Federal Minister of Transport and Digital Infrastructure, Alexander Dobrindt, appointed a national ethics committee for automated and connected driving, which began its work in September 2016. In June 2017, this committee presented a code of ethics which was published in German and in English. It consists of 20 ethical guidelines. Having been a member of this committee, I will present the main ethical topics of these guidelines and the discussions that lay behind them. (shrink)

Danaher (2016) has argued that increasing robotization can lead to retribution gaps: Situations in which the normative fact that nobody can be justly held responsible for a harmful outcome stands in conflict with our retributivist moral dispositions. In this paper, we report a cross-cultural empirical study based on Sparrow’s (2007) famous example of an autonomous weapon system committing a war crime, which was conducted with participants from the US, Japan and Germany. We find that (1) people manifest a considerable willingness (...) to hold autonomous systems morally responsible, (2) partially exculpate human agents when interacting with such systems, and that more generally (3) the possibility of normative responsibility gaps is indeed at odds with people’s pronounced retributivist inclinations. We discuss what these results mean for potential implications of the retribution gap and other positions in the responsibility gap literature. (shrink)

The ever increasing use of generative artificial intelligence raises significant questions about authorship and related issues such as credit and accountability. In this paper, I consider whether works produced by means of users inputting natural language prompts into Generative Adversarial Networks are works of authorship. I argue that they are not. This is not due to concerns about randomness or machine-assistance compromising human labor or intellectual vision, but instead due to the syntactical and compositional limitations of existing AI systems in (...) handling natural language prompts. This, I argue, gives rise to ‘authorship gaps’. (shrink)

Abstract“Gamification” refers to adding game-like elements to non-game activities so as to encourage participation. Gamification is used in various contexts: apps on phones motivating people to exercise, employers trying to encourage their employees to work harder, social media companies trying to stimulate user engagement, and so on and so forth. Here, I focus on gamification with this property: the game-designer (a company or other organization) creates a “game” in order to encourage the players (the users) to bring about certain outcomes (...) as a side effect of playing the game. The side effect might be good for the user (e.g., improving her health) and/or good for the company or organization behind the game (e.g., advertising their products, increasing their profits, etc.). The “players” of the game may or may not be aware of creating these side effects; and they may or may not approve of/endorse the creation of those side effects. The organizations behind the games, in contrast, are typically directly aiming to create games that have the side effects in question. These aspects of gamification are puzzling and interesting from the point of view of philosophical analyses of agency and responsibility for outcomes. In this paper, I relate these just-mentioned aspects of gamification to some philosophical discussions of responsibility gaps, the ethics of side effects (including the Knobe effect and the doctrine of double effect), and ideas about the relations among different parties’ agency. (shrink)

Who is responsible when an AI machine causes something to go wrong? Or is there a gap in the ascription of responsibility? Answers range from claiming there is a unique responsibility gap, several different responsibility gaps, or no gap at all. In a nutshell, the problem is as follows: on the one hand, it seems fitting to hold someone responsible for a wrong caused by an AI machine; on the other hand, there seems to be no fitting bearer of responsibility (...) for this wrong. In this article, we focus on a particular (aspect of the) AI responsibility gap: it seems fitting that someone should bear the legal consequences in scenarios involving AI machines with design defects; however, there seems to be no such fitting bearer. We approach this problem from the legal perspective, and suggest vicarious liability of AI manufacturers as a solution to this problem. Our proposal comes in two variants: the first one has a narrower range of application, but can be easily integrated in current legal frameworks; the second one requires a revision of current legal frameworks, but has a wider range of application. The latter variant employs a broadened account of vicarious liability. We emphasise strengths of the two variants and finally highlight how vicarious liability offers important insights for addressing a moral AI responsibility gap. (shrink)

The potential development of self-driving cars (also known as autonomous vehicles or AVs – particularly Level 5 AVs) has called the attention of different interested parties. Yet, there are still only a few relevant international regulations on them, no emergency patterns accepted by communities and Original Equipment Manufacturers (OEMs), and no publicly accepted solutions to some of their pending ethical problems. Thus, this paper aims to provide some possible answers to these moral and practical dilemmas. In particular, we focus on (...) what AVs should do in no-win scenarios and on who should be held responsible for these types of decisions. A naturalistic perspective on ethics informs our proposal, which, we argue, could represent a pragmatic and realistic solution to the regulation of AVs. We discuss the proposals already set out in the current literature regarding both policy-making strategies and theoretical accounts. In fact, we consider and reject descriptive approaches to the problem as well as the option of using either a strict deontological view or a solely utilitarian one to set AVs’ ethical choices. Instead, to provide concrete answers to AVs’ ethical problems, we examine three hierarchical levels of decision-making processes: country-wide regulations, OEM policies, and buyers’ moral attitudes. By appropriately distributing ethical decisions and considering their practical implications, we maintain that our proposal based on ethical naturalism recognizes the importance of all stakeholders and allows the most able of them to take actions (the OEMs and buyers) to reflect on the moral leeway and weight of their options. (shrink)

The idea of human-like robots with artificial intelligence (AI) engaging in sports has been considered in the light of robotics, technology and culture. However, robots with AI can also be used to clarify ethical questions in sports such as boxing with its inherent risks of brain injury and even death.This article develops an innovative way to assess the ethical issues in boxing by using a thought experiment, responding to recent medical data and overall concerns about harms and risks to boxers. (...) The thought experiment imagines a fight between a human and a robot. Critical issues about head trauma and brain injuries are then discussed. These can be summed up in two ethical questions: ‘why is it acceptable for a boxer to deliver concussive and recurrent subconcussive punches to a human head (skull and brain), powerful enough to achieve a knockout, or score more points, or to potentially inflict an injury immediately or eventually resulting in death?’, with the reciprocal question, ‘why is it acceptable to allow oneself to be injured in a like manner, possibly fatally, by an opponent?’The two questions are explored using the thought experiment in two matching perspectives: where the human boxer is attacking and the robot boxer is defending; and conversely, where the human boxer is on the receiving end of punches delivered by the robot. Each perspective opens with some general remarks, followed by an analysis of the boxing contest and eliciting some implications for future opportunities for the sport. (shrink)

This article is about the role of factual uncertainty for moral decision-making as it concerns the ethics of machine decision-making. The view that is defended here is that factual uncertainties require a normative evaluation and that ethics of machine decision faces a triple-edged problem, which concerns what a machine ought to do, given its technical constraints, what decisional uncertainty is acceptable, and what trade-offs are acceptable to decrease the decisional uncertainty.

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)

The debate about the ethical implications of Artificial Intelligence dates from the 1960s :741–742, 1960; Wiener in Cybernetics: or control and communication in the animal and the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles—the (...) ‘what’ of AI ethics —rather than on practices, the ‘how.’ Awareness of the potential issues is increasing at a fast rate, but the AI community’s ability to take action to mitigate the associated risks is still at its infancy. Our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the Machine Learning development pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs. (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)

Ethical thought experiments such as the trolley dilemma have been investigated extensively in the past, showing that humans act in utilitarian ways, trying to cause as little overall damage as possible. These trolley dilemmas have gained renewed attention over the past few years, especially due to the necessity of implementing moral decisions in autonomous driving vehicles. We conducted a set of experiments in which participants experienced modified trolley dilemmas as drivers in virtual reality environments. Participants had to make decisions between (...) driving in one of two lanes where different obstacles came into view. Eventually, the participants had to decide which of the objects they would crash into. Obstacles included a variety of human-like avatars of different ages and group sizes. Furthermore, the influence of sidewalks as potential safe harbors and a condition implicating self-sacrifice were tested. Results showed that participants, in general, decided in a utilitarian manner, sparing the highest number of avatars possible with a limited influence by the other variables. Derived from these findings, which are in line with the utilitarian approach in moral decision making, it will be argued for an obligatory ethics setting implemented in ADVs. (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)

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)

This article puts forward solutions to some of the ethical and legal dilemmas posed in the current discussion on how to program crash algorithms in autonomous or self-driving cars. The first part of the paper defines the scope of the problem in the criminal legal field, and the next section gives a critical analysis of the proposal to always prioritise the interest of the occupant of the vehicle in situations with conflict of interests. The principle of minimizing social damage as (...) a model for configuring self-driving cars is examined in the third section. Despite its apparent plausibility, within the framework of a liberal legal system that recognises humans as free agents who have rights and responsibilities, maximizing the function of social utility does not justify harmful interference into a person’s legal sphere. Therefore, in the fourth part, the author argues the need to program the crash algorithms of autonomous cars based on a deontological understanding of the system of justifications in criminal law. The solution to the dilemma lies in a prior analysis of the legal positions of all agents involved in the conflict, from a perspective of the principles of autonomy and solidarity as the core of the system of justifications. (shrink)

Every year, 1.35 million people are killed on roads worldwide and even more people are injured. Emerging self-driving car technology promises to cut this statistic down to a fraction of the current rate. On the face of it, this consideration alone constitutes a strong reason to legally require — once self-driving car technology is widely available and affordable — that all vehicles on public roads be self-driving. Here I critically investigate the question of whether self-driving, or autonomous, vehicles should be (...) legally mandated. I develop an argument — premised upon Mill’s Harm Principle — that any legislation mandating the use of self-driving vehicles on public roads is morally impermissible. The Harm Principle, under its most plausible interpretation, has it that the state is warranted in legislating against some activity only if that activity violates the rights of others. In brief, I argue that a human driver, who opts to drive herself on public roads rather than rely on self-driving technology, does not violate anyone’s rights when she so acts. Consequently, when granting the Harm Principle, it follows that the state is not warranted in mandating the use of self-driving vehicles on public roads. If I am correct, the proponent of a self-driving vehicle mandate must reject the Harm Principle. Given its intuitive plausibility and central place in liberal philosophical thought, this is a weighty cost. (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)

Almost all participants in the debate about the ethics of accidents with self-driving cars have so far assumed moral universalism. However, universalism may be philosophically more controversial than is commonly thought, and may lead to undesirable results in terms of non-moral consequences and feasibility. There thus seems to be a need to also start considering what I refer to as the “relativistic car” — a car that is programmed under the assumption that what is morally right, wrong, good, bad, etc. (...) is determined by the moral beliefs of one’s society or culture. My investigation of this idea involves six steps. First, I explain why and how the moral universalism/relativism debate is relevant to the issue of self-driving cars. Second, I argue that there are good reasons to consider accident algorithms that assume relativism. Third, I outline how a relativistic car would be programmed to behave. Fourth, I address what advantages such a car would have, both in terms of its non-moral consequences and feasibility. Fifth, I address the relativistic car’s disadvantages. Finally, I qualify and conclude my considerations. (shrink)

The rapid advances in Artificial Intelligence and Robotics will have a profound impact on society as they will interfere with the people and their interactions. Intelligent autonomous robots, independent if they are humanoid/anthropomorphic or not, will have a physical presence, make autonomous decisions, and interact with all stakeholders in the society, in yet unforeseen manners. The symbiosis with such sophisticated robots may lead to a fundamental civilizational shift, with far-reaching effects as philosophical, legal, and societal questions on consciousness, citizenship, rights, (...) and legal entity of robots are raised. The aim of this work is to understand the broad scope of potential issues pertaining to law and society through the investigation of the interplay of law, robots, and society via different angles such as law, social, economic, gender, and ethical perspectives. The results make it evident that in an era of symbiosis with intelligent autonomous robots, the law systems, as well as society, are not prepared for their prevalence. Therefore, it is now the time to start a multi-disciplinary stakeholder discussion and derive the necessary policies, frameworks, and roadmaps for the most eminent issues. (shrink)

The discourse around self-driving cars has been dominated by an emphasis on their potential to reduce the number of accidents. At the same time, proponents acknowledge that self-driving cars would inevitably be involved in fatal accidents where moral algorithms would decide the fate of those involved. This is a necessary trade-off, proponents suggest, in order to reap the benefits of this new technology. In this article, I engage this argument, demonstrating how an undue optimism and enthusiasm about this technology is (...) obscuring our ability to see what is at stake and explaining how moving beyond the dominant utilitarian framings around this technology opens up a space for both ethical inquiry and innovative design. I suggest that a genuine caring concern for the many lives lost in car accidents now and in the future—a concern that transcends false binary trade-offs and that recognizes the systemic biases and power structures that make certain groups more vulnerable than others—could serve as a starting point to rethink mobility, as it connects to the design of our cities, the well-being of our communities, and the future of our planet. (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)

The transfer of tasks with sometimes far-reaching implications to autonomous systems raises a number of ethical questions. In addition to fundamental questions about the moral agency of these systems, behavioral issues arise. We investigate the empirically accessible question of whether the imposition of harm by an agent is systematically judged differently when the agent is artificial and not human. The results of a laboratory experiment suggest that decision-makers can actually avoid punishment more easily by delegating to machines than by delegating (...) to other people. Our results imply that the availability of artificial agents could provide stronger incentives for decision-makers to delegate sensitive decisions. (shrink)

The philosophical–ethical literature and the public debate on autonomous vehicles have been obsessed with ethical issues related to crashing. In this article, these discussions, including more empirical investigations, will be critically assessed. It is argued that a related and more pressing issue is questions concerning safety. For example, what should we require from autonomous vehicles when it comes to safety? What do we mean by ‘safety’? How do we measure it? In response to these questions, the article will present a (...) foundation for a continued discussion on these issues and an argument for why discussions about safety should be prioritized over ethical concerns related to crashing. (shrink)

The present article is devoted to a logical treatment of some fundamental concepts involved in responsibility attribution. We specify a theoretical framework based on a language of temporal deontic logic with agent-relative operators for deliberate causal contribution. The framework is endowed with a procedure to solve normative conflicts which arise from the assessment of different normative sources. We provide a characterization result for a basic system within this framework and illustrate how the concepts formalized can be put at work in (...) the analysis of examples of legal reasoning. (shrink)

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)

The literature on ethics and user attitudes towards AVs discusses user concerns in relation to automation; however, we show that there are additional relevant issues at stake. To assess adolescents’ attitudes regarding the ‘car of the future’ as presented by car manufacturers, we conducted two studies with over 400 participants altogether. We used a mixed methods approach in which we combined qualitative and quantitative methods. In the first study, our respondents appeared to be more concerned about other aspects of AVs (...) than automation. Instead, their most commonly raised concerns were the extensive use of AI, recommender systems, and related issues of autonomy, invasiveness and personal privacy. The second study confirmed that several AV impacts were negatively perceived. The responses were, however, ambivalent. This confirms previous research on AV attitudes. On one hand, the AV features were perceived as useful, while on the other hand, their impacts were negatively assessed. We followed theoretical insights form futures studies and responsible research and innovation, which helped to identify that there are additional user concerns than what has been previously discussed in the literature on public attitudes and ethics of AVs, as well what has been envisioned by car manufactures. (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 literature on self-driving cars and ethics continues to grow. Yet much of it focuses on ethical complexities emerging from an individual vehicle. That is an important but insufficient step towards determining how the technology will impact human lives and society more generally. What must complement ongoing discussions is a broader, system level of analysis that engages with the interactions and effects that these cars will have on one another and on the socio-technical systems in which they are embedded. To (...) bring the conversation of self-driving cars to the system level, we make use of two traffic scenarios which highlight some of the complexities that designers, policymakers, and others should consider related to the technology. We then describe three approaches that could be used to address such complexities and their associated shortcomings. We conclude by bringing attention to the “Moral Responsibility for Computing Artifacts: The Rules”, a framework that can provide insight into how to approach ethical issues related to self-driving cars. (shrink)

With their prospect for causing both novel and known forms of damage, harm and injury, the issue of responsibility has been a recurring theme in the debate concerning autonomous vehicles. Yet, the discussion of responsibility has obscured the finer details both between the underlying concepts of responsibility, and their application to the interaction between human beings and artificial decision-making entities. By developing meaningful distinctions and examining their ramifications, this article contributes to this debate by refining the underlying concepts that together (...) inform the idea of responsibility. Two different approaches are offered to the question of responsibility and autonomous vehicles: targeting and risk distribution. The article then introduces a thought experiment which situates autonomous vehicles within the context of crash optimisation impulses and coordinated or networked decision-making. It argues that guiding ethical frameworks overlook compound or aggregated effects which may arise, and which can lead to subtle forms of structural discrimination. Insofar as such effects remain unrecognised by the legal systems relied upon to remedy them, the potential for societal inequalities is increased and entrenched, situations of injustice and impunity may be unwittingly maintained. This second set of concerns may represent a hitherto overlooked type of responsibility gap arising from inadequate accountability processes capable of challenging systemic risk displacement. (shrink)

There are two dominant trends in the humanitarian care of 2019: the ‘technologizing of care’ and the centrality of the humanitarian principles. The concern, however, is that these two trends may conflict with one another. Faced with the growing use of drones in the humanitarian space there is need for ethical reflection to understand if this technology undermines humanitarian care. In the humanitarian space, few agree over the value of drone deployment; one school of thought believes drones can provide a (...) utility serving those in need while another believes the large scale deployment of drones will exacerbate the already prevalent issues facing humanitarian aid providers. We suggest in this paper that the strength of the humanitarian principles approach to answer questions of aid provision can be complimented by a technology-facing approach, namely that of robot ethics. We have shown that for humanitarian actors we ought to be concerned with the risks of a loss of contextualization and de-skilling. For the beneficiary, we raise three concerns associated with the threat to the principle of humanity for this group: a loss of dignity by reducing human-to-human interactions; a threat to dignity through a lack of informational transparency; and, a threat to dignity by failing to account for the physiological and behavioral impacts of the drone on human actors. Although we acknowledge the obstacles associated with understanding the physiological and behavioral impacts we insist that the moral acceptability and desirability of drones in humanitarian contexts is dependent on the findings from such studies and that tailored ethical guidelines for drone deployment in humanitarian action be created to reflect the results of such studies. (shrink)