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)

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)

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)

In order to determine whether current (or future) machines have a welfare that we as agents ought to take into account in our moral deliberations, we must determine which capacities give rise to interests and whether current machines have those capacities. After developing an account of moral patiency, I argue that current machines should be treated as mere machines. That is, current machines should be treated as if they lack those capacities that would (...) give rise to psychological interests. Therefore, they are moral patients only if they have non-psychological interests. I then provide an account of what I call teleo interests that constitute the most plausible type of non-psychological interest that a being might have. I then argue that even if current machines have teleo interests, they are such that agents need not concern themselves with these interests. Therefore, for all intents and purposes, current machines are not moral patients. (shrink)

In light of recent breakneck pace in machine learning, questions about whether near-future artificial systems might be conscious and possess moral status are increasingly pressing. This paper argues that as matters stand these debates lack any clear criteria for resolution via the science of consciousness. Instead, insofar as they are settled at all, it is likely to be via shifts in public attitudes brought about by the increasingly close relationships between humans and AI users. Section 1 of the paper (...) I briefly lays out the current state of the science of consciousness and its limitations insofar as these pertain to machine consciousness, and claims that there are no obvious consensus frameworks to inform public opinion on AI consciousness. Section 2 examines the rise of conversational chatbots or Social AI, and argues that in many cases, these elicit strong and sincere attributions of consciousness, mentality, and moral status from users, a trend likely to become more widespread. Section 3 presents an inconsistent triad for theories that attempt to link consciousness, behaviour, and moral status, noting that the trends in Social AI systems will likely make the inconsistency of these three premises more pressing. Finally, Section 4 presents some limited suggestions for how consciousness and AI research communities should respond to the gap between expert opinion and folk judgment. (shrink)

Lake et al. propose three criteria which, they argue, will bring artificial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine learning. (...) We also discuss how work in embodied and situated cognition could provide a valu- able perspective on future research. (shrink)

The advance of mechanism in science and philosophy in the 17th century created a great interest to machines or automata. Leibniz was no exception - in an early memoir Drôle de pensée he wrote admiringly about a machine that could walk on water, exhibited in Paris. The idea of automatic processing in general had a large role in his thought, as can be seen, for example, in his invention of the binary code and the so-called Calculemus!-model for solving controversies. (...) In metaphysics, the idea of an automata was expressed most clearly in the 1695 article New System of the Nature of Substances and their Communication, and the ensuing correspondence with, among others, Foucher, Bayle, Lamy, Jaquelot and Masham. In the article Leibniz discusses the soul as a spiritual machine in the context of pre-established harmony, arguing that God can "give to a substance at the outset a nature or internal force which could produce in it an orderly way (as in spiritual or formal automaton; but a free one, in the case of a substance which is endowed with a share of reason) everything that is going to happen to it, that is to say, all the appearances or expressions it is going to have, and all without the help of any created thing." The basic idea of Leibniz's spiritual machine is that the soul or entelechy is an autonomous and spontaneous unity, consisting of internal active force and producing its own perceptions (both confused and distinct). It is a self-moving machine, driven by its perceptions and appetites, but it follows (without being conscious of it) a lawful series or programme created by God. The entelechy remains the same despite undergoing an infinite number of changes. To Foucher he explained that each state of the individual substance is a consequence of its preceding one, "as if there were only God and the substance in the world". Despite this, the spiritual machine is related not only to God, but through the pre-established harmony to bodies or natural machines. However, as it is not dependent on them, the spiritual machine is superiot to natural machines. In this paper I concentrate on three moral themes related to the spiritual machine: moral deliberation, moral identity and the goal of moral action. All these themes are more or less implicit in the New System, but are discussed in more detail in the ensuing correspondence after the publication of the article. Finally, the themes are given an extended discussion especially in the second book of New Essays on Human Understanding (1704, published 1765), written partly at the same time as some of the correspondence and unpublished related material. I will first give an overview of Leibniz's position concerning the spiritual machine or automaton in the New System and then go on to explore the three moral themes one by one, as they feature in the subsequent correspondence and in the New Essays. I will show that the three topics are essential to the function of the spiritual machine – to Sophie Charlotte Leibniz wrote: "...let us say that everything in bodies happens mechanically, or in accordance with laws of motion, and that everything in the soul happens morally, or in accordance with perceived good or evil." There are many texts that anticipate the views in the New System (notably the unpublished memoir De Affectibus of 1679) and Leibniz continued to discuss its themes later on (in addition to correpondence, for example, in Theodicy of 1710 and Monadology and Principles of Nature and Grace of 1714). Here I focus on the short-term development of Leibniz's views on the topic (around 1695-1705), but I argue that his basic view of the spiritual machine did not change much after finishing the dialogue with Locke in 1704. (shrink)

The creation of artificial moral systems requires us to make difficult choices about which of varying human value sets should be instantiated. The industry-standard approach is to seek and encode moral consensus. Here we argue, based on evidence from empirical psychology, that encoding current moral consensus risks reinforcing current norms, and thus inhibiting moral progress. However, so do efforts to encode progressive norms. Machine ethics is thus caught between a rock and a hard place. The problem (...) is particularly acute when progress beyond prevailing moral norms is particularly urgent, as is currently the case due to the inadequacy of prevailing moral norms in the face of the climate and ecological crisis. (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)

Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which they (...) are presumptuous. After elaborating this moral concern, I explore the possibility that carefully procuring the training data for image recognition systems could ensure that the systems avoid the problem. The lesson of this paper extends beyond just the particular case of image recognition systems and the challenge of responsibly identifying a person’s intentions. Reflection on this particular case demonstrates the importance (as well as the difficulty) of evaluating machine learning systems and their training data from the standpoint of moral considerations that are not encompassed by ordinary assessments of predictive accuracy. (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)

According to the most popular theories of intentionality, a family of theories we will refer to as “functional intentionality,” a machine can have genuine intentional states so long as it has functionally characterizable mental states that are causally hooked up to the world in the right way. This paper considers a detailed description of a robot that seems to meet the conditions of functional intentionality, but which falls victim to what I call “the composition problem.” One obvious way to escape (...) the problem (arguably, the only way) is if the robot can be shown to be a moral patient – to deserve a particular moral status. If so, it isn’t clear how functional intentionality could remain plausible (something like “phenomenal intentionality” would be required). Finally, while it would have seemed that a reasonable strategy for establishing the moral status of intelligent machines would be to demonstrate that the machine possessed genuine intentionality, the composition argument suggests that the order of precedence is reversed: The machine must first be shown to possess a particular moral status before it is a candidate for having genuine intentionality. (shrink)

In this paper, I argue that Consequentialism represents a kind of ethical theory that is the most plausible to serve as a basis for a machine ethic. First, I outline the concept of an artificial moral agent and the essential properties of Consequentialism. Then, I present a scenario involving autonomous vehicles to illustrate how the features of Consequentialism inform agent action. Thirdly, an alternative Deontological approach will be evaluated and the problem of moral conflict discussed. Finally, two bottom-up (...) approaches to the development of machine ethics are presented and briefly challenged. (shrink)

This paper addresses a question about the moral status of Artificial Intelligence (AI): will AIs ever become moral patients? I argue that, while it is in principle possible for an intelligent machine to be a moral patient, there is no good reason to believe this will in fact happen. I start from the plausible assumption that traditional artifacts do not meet a minimal necessary condition of moral patiency: having a good of one's own. I then argue (...) that intelligent machines are no different from traditional artifacts in this respect. To make this argument, I examine the feature of AIs that enables them to improve their intelligence, i.e., machine learning. I argue that there is no reason to believe that future advances in machine learning will take AIs closer to having a good of their own. I thus argue that concerns about the moral status of future AIs are unwarranted. Nothing about the nature of intelligent machines makes them a better candidate for acquiring moral patiency than the traditional artifacts whose moral status does not concern us. (shrink)

Why should moral philosophers, moral psychologists, and machine ethicists care about computational complexity? Debates on whether artificial intelligence (AI) can or should be used to solve problems in ethical domains have mainly been driven by what AI can or cannot do in terms of human capacities. In this paper, we tackle the problem from the other end by exploring what kind of moral machines are possible based on what computational systems can or cannot do. To do (...) so, we analyze normative ethics through the lens of computational complexity. First, we introduce computational complexity for the uninitiated reader and discuss how the complexity of ethical problems can be framed within Marr’s three levels of analysis. We then study a range of ethical problems based on consequentialism, deontology, and virtue ethics, with the aim of elucidating the complexity associated with the problems themselves (e.g., due to combinatorics, uncertainty, strategic dynamics), the computational methods employed (e.g., probability, logic, learning), and the available resources (e.g., time, knowledge, learning). The results indicate that most problems the normative frameworks pose lead to tractability issues in every category analyzed. Our investigation also provides several insights about the computational nature of normative ethics, including the differences between rule- and outcome-based moral strategies, and the implementation-variance with regard to moral resources. We then discuss the consequences complexity results have for the prospect of moral machines in virtue of the trade-off between optimality and efficiency. Finally, we elucidate how computational complexity can be used to inform both philosophical and cognitive-psychological research on human morality by advancing the moral tractability thesis. (shrink)

Many policies and ethical guidelines recommend developing “trustworthy AI”. We argue that developing morally trustworthy AI is not only unethical, as it promotes trust in an entity that cannot be trustworthy, but it is also unnecessary for optimal calibration. Instead, we show that reliability, exclusive of moral trust, entails the appropriate normative constraints that enable optimal calibration and mitigate the vulnerability that arises in high-stakes hybrid decision-making environments, without also demanding, as moral trust would, the anthropomorphization of AI (...) and thus epistemically dubious behavior. The normative demands of reliability for inter-agential action are argued to be met by an analogue to procedural metacognitive competence (i.e., the ability to evaluate the quality of one’s own informational states to regulate subsequent action). Drawing on recent empirical findings that suggest providing reliability scores (e.g., F1-scores) to human decision-makers improves calibration in the AI system, we argue that reliability scores provide a good index of competence and enable humans to determine how much they wish to rely on the system. (shrink)

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)

I propose a framework, derived from moral theory, for assessing the moral status of intelligent machines. Using this framework, I claim that some current and foreseeable intelligent machines have approximately as much moral status as plants, trees, and other environmental entities. This claim raises the question: what obligations could a moral agent (e.g., a normal adult human) have toward an intelligent machine? I propose that the threshold for any moral obligation should be the (...) "functional morality" of Wallach and Allen [20], while the upper limit of our obligations should not exceed the upper limit of our obligations toward plants, trees, and other environmental entities. (shrink)

In this paper, I set out a new Kantian approach to resolving conflicts between moral obligations for highly autonomous machine agents. First, I argue that efforts to build explicitly moral autonomous machine agents should focus on what Kant refers to as duties of right, which are duties that everyone could accept, rather than on duties of virtue (or “ethics”), which are subject to dispute in particular cases. “Moral” machines must first be rightful machines, I argue. (...) I then show how this shift in focus from ethics to a standard of public right resolves the conflicts in what is known as the "trolley problem" for autonomous ma-chine agents. Finally, I consider how a deontic logic suitable for capturing duties of right might meet Kant’s requirement that rightfully enforceable obligations be consistent in a system of equal freedom under universal law. (shrink)

Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.

In, “The Turing Triage Test”, published in Ethics and Information Technology, I described a hypothetical scenario, modelled on the famous Turing Test for machine intelligence, which might serve as means of testing whether or not machines had achieved the moral standing of people. In this paper, I: (1) explain why the Turing Triage Test is of vital interest in the context of contemporary debates about the ethics of AI; (2) address some issues that complexify the application of this (...) test; and, (3) in doing so, defend a way of thinking about the question of the moral standing of intelligent machines, which takes the idea of “seriousness” seriously. This last objective is, in fact, my primary one and is motivated by the sense that, to date, much of the “philosophy” of AI has suffered from a profound failure to properly distinguish between things that we can say and things that we can really mean. (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)

Table of Contents Foreword .................................................................................................... ......................................... xiv Preface .................................................................................................... .............................................. xv Acknowledgment .................................................................................................... .......................... xxiii Section 1 On the Cusp: Critical Appraisals of a Growing Dependency on Intelligent Machines Chapter 1 Algorithms versus Hive Minds and the Fate of Democracy ................................................................... 1 Rick Searle, IEET, USA Chapter 2 We Can Make Anything: Should We? .................................................................................................. 15 Chris Bateman, University of Bolton, UK Chapter 3 Grounding Machine Ethics within the Natural System ........................................................................ 30 Jared Gassen, JMG Advising, USA Nak Young Seong, Independent Scholar, (...) South Korea Section 2 From the Outside In: Intelligent Machine Technologies as a Window on Human Morality both as Evolved and as Evident in Internet Discourse, Today Chapter 4 The Emergence of Arti cial Autonomy: A View from the Foothills of a Challenging Climb ............. 51 Fernando da Costa Cardoso, Universidade Nova de Lisboa, Portugal Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Chapter 5 Semantic Analysis of Bloggers Experiences as a Knowledge Source of Average Human Morality .... 73 Rafal Rzepka, Hokkaido University, Japan Kenji Araki, Hokkaido University, Japan Section 3 From the Inside Out: The Ethics of Human Enhancement from Moral Perception to Competition in the Workplace Chapter 6 Machine Ethics Interfaces: An Ethics of Perception of Nanocognition ............................................... 97 Melanie Swan, Kingston University, UK Chapter 7 Ethical Concerns in Human Enhancement: Advantages in Corporate/Organizational Settings ......... 124 Ben Tran, Alliant International University, USA Section 4 From Far to Near and Near to Far: The Ethics of Distancing Technologies in Education and Warfare Chapter 8 Responsibility and War Machines: Toward a Forward-Looking and Functional Account ................. 152 Jai Galliott, Macquarie University, Australia Chapter 9 Ethical Responsibilities of Preserving Academicians in an Age of Mechanized Learning: Balancing the Demands of Educating at Capacity and Preserving Human Interactivity ................... 166 James E. Willis III, Indiana University, USA Viktoria Alane Strunk, Independent Scholar, USA Section 5 Wrapping Things Up, then Unwrapping Them Again: Integral Visions of Morality in a Technological World, Over Evolutionary Time, with Revolutionary Means, and with Open Questions about the Final Purpose of It All Chapter 10 Bridging Two Realms of Machine Ethics ........................................................................................... 197 Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Ari Saptawijaya, Universidade Nova de Lisboa, Portugal & Universitas Indonesia, Indonesia Chapter 11 Robots in Warfare and the Occultation of the Existential Nature of Violence ................................... 225 Rick Searle, IEET, USA Chapter 12 Self-Referential Complex Systems and Aristotle’s Four Causes ........................................................ 239 Aleksandar Malecic, University of Nis, Serbia Related References .................................................................................................... ........................ 261 Compilation of References .................................................................................................... ........... 292 About the Contributors .................................................................................................... ................ 325 Index .................................................................................................... ............................................... 329 . (shrink)

This paper focuses on the research field of machine ethics and how it relates to a technological singularity—a hypothesized, futuristic event where artificial machines will have greater-than-human-level intelligence. One problem related to the singularity centers on the issue of whether human values and norms would survive such an event. To somehow ensure this, a number of artificial intelligence researchers have opted to focus on the development of artificial moral agents, which refers to machines capable of moral (...) reasoning, judgment, and decision-making. To date, different frameworks on how to arrive at these agents have been put forward. However, there seems to be no hard consensus as to which framework would likely yield a positive result. With the body of work that they have contributed in the study of moral agency, philosophers may contribute to the growing literature on artificial moral agency. While doing so, they could also think about how the said concept could affect other important philosophical concepts. (shrink)

Abstract: Artificial Morality is a new, emerging interdisciplinary field that centres around the idea of creating artificial moral agents, or AMAs, by implementing moral competence in artificial systems. AMAs are ought to be autonomous agents capable of socially correct judgements and ethically functional behaviour. This request for moral machines comes from the changes in everyday practice, where artificial systems are being frequently used in a variety of situations from home help and elderly care purposes to banking (...) and court algorithms. It is therefore important to create reliable and responsible machines based on the same ethical principles that society demands from people. New challenges in creating such agents appear. There are philosophical questions about a machine’s potential to be an agent, or mora l agent, in the first place. Then comes the problem of social acceptance of such machines, regardless of their theoretic agency status. As a result of efforts to resolve this problem, there are insinuations of needed additional psychological (emotional and cogn itive) competence in cold moral machines. What makes this endeavour of developing AMAs even harder is the complexity of the technical, engineering aspect of their creation. Implementation approaches such as top- down, bottom-up and hybrid approach aim to find the best way of developing fully moral agents, but they encounter their own problems throughout this effort. (shrink)

A prominent objection to non-cognitive moral bio-enhancements is that they would compromise the recipient’s ‘freedom to fall’. I begin by discussing some ambiguities in this objection, before outlining an Aristotelian reading of it. I suggest that this reading may help to forestall Persson and Savulescu’s ‘God-Machine’ criticism; however, I suggest that the objection still faces the problem of explaining why the value of moral conformity is insufficient to outweigh the value of the freedom to fall itself. I also (...) question whether the objection is compatible with Neil Levy’s parity principle. Accordingly, I go on to consider an alternative relational freedom-based objection to NCMBEs that aims to explain the fundamental moral importance of the freedom that NCMBEs would violate. I argue that although this strategy might allow the critic of NCMBEs to bypass a powerful criticism of Harris’ objection, it also weakens the freedom-based objection’s compatibility with the parity principle. (shrink)

This paper delves into the use of machine learning-based systems in decision-making processes and its implications for moral responsibility as traditionally defined. It focuses on the emergence of responsibility gaps and examines proposed strategies to address them. The paper aims to provide an introductory and comprehensive overview of the ongoing debate surrounding moral responsibility in automated decision-making. By thoroughly examining these issues, we seek to contribute to a deeper understanding of the implications of AI integration in society.

A common style of argument in the literature on free will and moral responsibility is the Manipulation Argument. These tend to begin with a case of an agent in a deterministic universe who is manipulated, say, via brain surgery, into performing some action. Intuitively, this agent is not responsible for that action. Yet, since there is no relevant difference, with respect to whether an agent is responsible, between the manipulated agent and a typical agent in a deterministic universe, responsibility (...) is not compatible with the truth of determinism. In response, some theorists have argued that there is a relevant difference, and have developed two sorts of accounts of that difference: bypassing views, and manipulator-focused views. Manipulator-focused views suggest that the difference concerns the presence of a manipulator, whereas bypassing views suggest that the relevant difference concerns the fact that the action issues from attitudes that the manipulated agent acquired in a way that bypassed her capacities for control over her mental life. One sort of case used to decide between these sorts of accounts is a case of machine induction, which is just like a manipulation case, yet the change in the agent is the result of some natural force. Against the received view, Xiaofei Liu argues that such cases pose problems for bypassing views, and favor manipulator-focused views instead. This paper addresses Liu’s arguments, as well as a variety of cases, concluding that cases of machine induction do not provide motivation for a bypassing theorist to adopt a manipulator-focused view. (shrink)

Helen Frowe (2006/2010) contends that there is a substantial moral difference between killing and letting die, arguing that in Michael Tooley's infamous machine case it is morally wrong to flip a coin to determine who lives or dies. Here I argue that Frowe fails to show that killing and letting die are morally inequivalent. However, I believe that she has succeeded in showing that it is wrong to press the button in Tooley's case, where pressing the button will change (...) who lives and dies. I argue that because killing and letting die are morally equivalent we have no reason to press the button in the machine case. Pressing the button in this case is morally wrong because there is no reason to do it; to press the button is to treat matters of life and death irreverently. (shrink)

The chief themes of this discussion are as follows. First, we need a theory of the grounds of moral status that could guide practical considerations regarding how to treat the wide range of potentially conscious entities with which we are acquainted – injured humans, cerebral organoids, chimeras, artificially intelligent machines, and non-human animals. I offer an account of phenomenal value that focuses on the structure and sophistication of phenomenally conscious states at a time and over time in the (...) mental lives of conscious subjects. Second, we need to map a theory of moral status onto practical considerations. I prefer the precautionary framework proposed by many, and fruitfully precisified recently by Birch. I have suggested that in addition to further discussion surrounding the evidential bar for attributing consciousness to different types of entities, more discussion is needed regarding how value and moral status may vary across different entity-types, and regarding the sources of value in an entity’s mental life. (shrink)

Ex Machina is a 2014 science-fiction film written and directed by Alex Garland, centered around the creation of a human-like artificial intelligence (AI) named Ava. The plot focuses on testing Ava for consciousness by offering a unique reinterpretation of the Turing Test. The film offers an excellent thought experiment demonstrating the consequences of various approaches to a potentially conscious AI. In this paper, I will argue that intelligence testing has significant epistemological shortcomings that necessitate an ethical approach not reliant on (...) ontological commitments. As such, we should be prepared to treat AI as though it is a living being that is deserving of corresponding moral obligations. For a sufficiently human-like AI, such as Ava, I will argue that socio-relational ethics is the best starting point in order to nurture the machine towards ethical proclivities, as evident by the consequences of the characters’ behavior throughout the film. I conclude that intelligence testing is an insufficient determinant of machine ethics, that the project of machine ethics should focus as much on how we treat AI as how AI treats us, and that from a consequentialist perspective it is better to treat machines ethically before they gain consciousness rather than after. (shrink)

The Morality First strategy for developing AI systems that can represent and respond to human values aims to first develop systems that can represent and respond to moral values. I argue that Morality First and other X-First views are unmotivated. Moreover, according to some widely accepted philosophical views about value, these strategies are positively distorting. The natural alternative, according to which no domain of value comes “first” introduces a new set of challenges and highlights an important but otherwise obscured (...) problem for e-AI developers. (shrink)

In this paper Sullins argues that in certain circumstances robots can be seen as real moral agents. A distinction is made between persons and moral agents such that, it is not necessary for a robot to have personhood in order to be a moral agent. I detail three requirements for a robot to be seen as a moral agent. The first is achieved when the robot is significantly autonomous from any programmers or operators of the machine. (...) The second is when one can analyze or explain the robot's behavior only by ascribing to it some predisposition or 'intention' to do good or harm. And finally, robot moral agency requires the robot to behave in a way that shows and understanding of responsibility to some other moral agent. Robots with all of these criteria will have moral rights as well as responsibilities regardless of their status as persons. (shrink)

This paper discusses the philosophical issues pertaining to Kantian moral agency and artificial intelligence. Here, our objective is to offer a comprehensive analysis of Kantian ethics to elucidate the non-feasibility of Kantian machines. Meanwhile, the possibility of Kantian machines seems to contend with the genuine human Kantian agency. We argue that in machine morality, ‘duty’ should be performed with ‘freedom of will’ and ‘happiness’ because Kant narrated the human tendency of evaluating our ‘natural necessity’ through ‘happiness’ as (...) the end. Lastly, we argue that the Kantian ‘freedom of will’ and ‘faculty of choice’ do not belong to any deterministic model of ‘agency’ as these are sacrosanct systems. The conclusion narrates the non-feasibility of Kantian AI agents from the genuine Kantian ethical outset, offering a utility-based Kantian ethical performer instead. (shrink)

In this paper, we defend three claims about what it will take for an AI system to be a basic moral patient to whom we can owe duties of non-maleficence not to harm her and duties of beneficence to benefit her: (1) Moral patients are mental patients; (2) Mental patients are true intentional systems; and (3) True intentional systems are systematically flexible. We suggest that we should be particularly alert to the possibility of such systematically flexible true intentional (...) systems developing in the areas of exploratory robots and artificial personal assistants. Finally, we argue that in light of our failure to respect the well-being of existing biological moral patients and worries about our limited resources, there are compelling moral reasons to treat artificial moral patiency as something to be avoided at least for now. (shrink)

This article focuses on a particular issue under machine ethics—that is, the nature of Artificial Moral Agents. Machine ethics is a branch of artificial intelligence that looks into the moral status of artificial agents. Artificial moral agents, on the other hand, are artificial autonomous agents that possess moral value, as well as certain rights and responsibilities. This paper demonstrates that attempts to fully develop a theory that could possibly account for the nature of Artificial Moral (...) Agents may consider certain philosophical ideas, like the standard characterizations of agency, rational agency, moral agency, and artificial agency. At the very least, the said philosophical concepts may be treated as signposts for further research on how to truly account for the nature of Artificial Moral Agents. (shrink)

Recommender systems are artificial intelligence technologies, deployed by online platforms, that model our individual preferences and direct our attention to content we’re likely to engage with. As the digital world has become increasingly saturated with information, we’ve become ever more reliant on these tools to efficiently allocate our attention. And our reliance on algorithmic recommendation may, in turn, reshape us as moral agents. While recommender systems could in principle enhance our moral agency by enabling us to cut through (...) the information saturation of the internet and focus on things that matter, as they’re currently designed and implemented they’re apt to interfere with our ability to attend appropriately to morally relevant factors. In order to analyze the distinctive moral problems algorithmic recommendation poses, we develop a framework for the ethics of attention and an account of judicious attention allocation as a moral skill. We then discuss empirical evidence suggesting that attentional moral skill can be thwarted and undermined in various ways by algorithmic recommendation and related affordances of online platforms, as well as economic and technical considerations that support this concern. Finally, we consider how emerging technologies might overcome the problems we identify. (shrink)

Autonomous and automatic weapons would be fire and forget: you activate them, and they decide who, when and how to kill; or they kill at a later time a target you’ve selected earlier. Some argue that this sort of killing is always wrong. If killing is to be done, it should be done only under direct human control. (E.g., Mary Ellen O’Connell, Peter Asaro, Christof Heyns.) I argue that there are surprisingly many kinds of situation where this is false and (...) where the use of Automated Weapons Systems would in fact be morally required. These include cases where a) once one has activated a weapon expected then to behave lethally, it would be appropriate to let it continue because this is part of a plan whose goodness one was best positioned to evaluate before activating the weapon; b) one expects better long-term consequences from allowing it to continue; c) allowing it to continue would express a decision you made to be resolute, a decision that could not have advantaged you had it not been true that you would carry through with it; d) the weapon is mechanically not recallable, so that, to not allow it to carry through, you would have had to refrain from activating it in the first place, something you expected would have disastrous consequences; e) you must deputize necessary killings to autonomous machines in order to protect yourself from guilt you shouldn’t have to bear; f) it would be morally better for the burden of responsibility for the killing to be shared among several agents, and the agents deputizing killing to machines can do this, especially where it’s not predictable which machine will be successful; g) a killing would be morally better done with elements of randomness and lack of deliberation, and a (relatively stupid) machine could do this where a person could not; h) the machine would be acting as a Doomsday Device, so that it could not have had its hoped for deterrent effect had you not ensured that you would be unable to recall it if enemy action activated it; i) letting it carry through is a necessary part of its own learning process, and you expect that this learning will have salutary effects later on; j) human intervention in the machine’s operation would disastrously impair its precision, or its speed and efficiency; k) using non-automated methods would require human resources you just don’t have in a task that nevertheless must be done (e.g., using land-mines to protect remote installations); l) the weapon has such horrible and indiscriminate power that it is doubtful whether it could be actually used in ways compatible with International Humanitarian Law and the Laws of War, which require that weapons be used only in ways respecting distinctness, necessity and proportionality, but its threat of use could respect these principles in affording deterrence provided human error cannot lead to their accidental deployment, this requiring that they be controlled by carefully designed autonomous and automatic systems. I then consider objections based on conceptions of human dignity and find that very often dignity too is best served by autonomous machine killing. Examples include saving your village by activating a robot to kill invading enemies who would inflict great indignity on your village, using a suicide robot to save yourself from a less dignified death at enemy hands, using a robotic drone to kill someone otherwise not accessible in order to restore dignity to someone this person killed and to his family, and using a robot to kill someone who needs killing, but the killing of whom by a human executioner would soil the executioner’s dignity. I conclude that what matters in rightful killing isn’t necessarily that it be under the direct control of a human, but that it be under the control of morality; and that could sometimes require use of an autonomous or automated device. (This paper was formerly called "Fire and Forget: A Defense of the Use of Autonomous Weapons in War" on Philpapers; the current title is the title of the published version.). (shrink)

One of the predominant debates in AI Ethics is the worry and necessity to create fair, transparent and accountable algorithms that do not perpetuate current social inequities. I offer a critical analysis of Reuben Binns’s argument in which he suggests using public reason to address the potential bias of the outcomes of machine learning algorithms. In contrast to him, I argue that ultimately what is needed is not public reason per se, but an audit of the implicit moral assumptions (...) of societies within which algorithms are built and applied. Public justification is appealing since it offers us the possibility to align the decision-making outcomes of the algorithm with the core moral values of stakeholders within a constitutional democratic society. My concern is that the common moral principles that form the foundation of public reason are not necessarily neutral, as they still express specific moral ideals and normative standards even if there is moral agreement by society as a whole, or among different stakeholders within society. Appealing to such normative standards may thus still lead to algorithmic outcomes being biased as common moral values may very well still be discriminatory even though they are formed from a consensus, and even if public reason is applied as a kind of filter for potential algorithmic outcomes. Hence, I argue that these implicit moral norms within society that we take as a given in public reasoning, need to be audited from generation to generation in order to effectively mitigate potential algorithmic bias. (shrink)

This article analyzes emerging artificial intelligence (AI)-enhanced lie detection systems from ethical and human resource (HR) management perspectives. I show how these AI enhancements transform lie detection, followed with analyses as to how the changes can lead to moral problems. Specifically, I examine how these applications of AI introduce human rights issues of fairness, mental privacy, and bias and outline the implications of these changes for HR management. The changes that AI is making to lie detection are altering the (...) roles of human test administrators and human subjects, adding machine learning-based AI agents to the situation and establishing invasive data collection processes as well as introducing certain biases in results. I project that the potentials for pervasive and continuous lie detection initiatives (“truth machines”) are substantial, displacing human-centered efforts to establish trust and foster integrity in organizations. I argue that if it is possible for HR managers to do so, they should cease using technologically-based lie detection systems entirely and work to foster trust and accountability on a human scale. However, if these AI-enhanced technologies are put into place by organizations by law, agency mandate, or other compulsory measures, care should be taken that the impacts of the technologies on human rights and wellbeing are considered. The article explores how AI can displace the human agent in some aspects of lie detection and credibility assessment scenarios, expanding the prospects for inscrutable, “black box” processes and novel physiological constructs (such as “biomarkers of deceit”) that may increase the potential for such human rights concerns as fairness, mental privacy, and bias. Employee interactions with autonomous lie detection systems rather with than human beings who administer specific tests can reframe organizational processes and rules concerning the assessment of personal honesty and integrity. The dystopian projection of organizational life in which analyses and judgments of the honesty of one’s utterances are made automatically and in conjunction with one’s personal profile provides unsettling prospects for the autonomy of self-representation. (shrink)

Vision is an important metaphor in ethical and political questions of knowledge. The feminist philosopher Donna Haraway points out the “perverse” nature of an intrusive, alienating, all-seeing vision (to which we might cry out “stop looking at me!”), but also encourages us to embrace the embodied nature of sight and its promises for genuinely situated knowledge. Current technologies of machine vision – surveillance cameras, drones (for war or recreation), iPhone cameras – are usually construed as instances of the former rather (...) than the latter, and for good reasons. However, although in no way attempting to diminish the real suffering these technologies have brought about in the world, I make the case for understanding technologies of computer vision as material instances of embodied seeing and situated knowing. Furthermore, borrowing from Iris Murdoch’s concept of moral vision, I suggest that these technologies direct our labor towards self-reflection in ethically significant ways. My approach draws upon paradigms in computer vision research, phenomenology, and feminist epistemology. Ultimately, this essay is an argument for directing more philosophical attention from merely criticizing technologies of vision as ethically deficient towards embracing them as complex, methodologically and epistemologically important objects. (shrink)

It is indubitable that machines with artificial intelligence (AI) will be an essential component in humans’ quest to become a spacefaring civilization. Most would agree that long-distance space travel and the colonization of Mars will not be possible without adequately developed AI. Machines with AI have a normative function, but some argue that it can also be evaluated from the perspective of ethical norms. This essay is based on the assumption that machine ethics is an essential philosophical perspective (...) in realizing the aim of humanity becoming a spacefaring civilization. In this essay, I explore two questions in the field of machine ethics, that I believe to be relevant to the role AI will play in long-distance space travel. The first is, should moral theory be extended to include machines with AI, and second, can machines be fully ethical agents? In this essay, I define AI and then discuss the difference between implicit, explicit and full ethical agents in relation to machines with AI. I then present the argument that the inclusion of moral theory is essential in the development of machines with AI. Without an adequate inclusion of moral theory in the design of AI it may pose an existential threat to humanity, especially in the development of super-intelligent machines. I also highlight that conceptual clarity is essential in the field of machine ethics and the choice of the conceptual foundation that informs AI research and development has ethical implications, especially in the case of super-intelligent machines. This essay is an exploratory and speculative philosophical analysis of certain aspects of machine ethics relevant to long-distance space travel and does not attempt to provide definitive answers to the questions posed in the essay, but instead aims to bring attention to what I deem important considerations. (shrink)

This paper presents a new trilemma with respect to resolving the control and alignment problems in machine ethics. Section 1 outlines three possible types of artificial moral agents (AMAs): (1) 'Inhuman AMAs' programmed to learn or execute moral rules or principles without understanding them in anything like the way that we do; (2) 'Better-Human AMAs' programmed to learn, execute, and understand moral rules or principles somewhat like we do, but correcting for various sources of human moral (...) error; and (3) 'Human-Like AMAs' programmed to understand and apply moral values in broadly the same way that we do, with a human-like moral psychology. Sections 2–4 then argue that each type of AMA generates unique control and alignment problems that have not been fully appreciated. Section 2 argues that Inhuman AMAs are likely to behave in inhumane ways that pose serious existential risks. Section 3 then contends that Better-Human AMAs run a serious risk of magnifying some sources of human moral error by reducing or eliminating others. Section 4 then argues that Human-Like AMAs would not only likely reproduce human moral failures, but also plausibly be highly intelligent, conscious beings with interests and wills of their own who should therefore be entitled to similar moral rights and freedoms as us. This generates what I call the New Control Problem: ensuring that humans and Human-Like AMAs exert a morally appropriate amount of control over each other. Finally, Section 5 argues that resolving the New Control Problem would, at a minimum, plausibly require ensuring what Hume and Rawls term ‘circumstances of justice’ between humans and Human-Like AMAs. But, I argue, there are grounds for thinking this will be profoundly difficult to achieve. I thus conclude on a skeptical note. Different approaches to developing ‘safe, ethical AI’ generate subtly different control and alignment problems that we do not currently know how to adequately resolve, and which may or may not be ultimately surmountable. (shrink)

The ultimate goal of research into computational intelligence is the construction of a fully embodied and fully autonomous artificial agent. This ultimate artificial agent must not only be able to act, but it must be able to act morally. In order to realize this goal, a number of challenges must be met, and a number of questions must be answered, the upshot being that, in doing so, the form of agency to which we must aim in developing artificial agents comes (...) into focus. This chapter explores these issues, and from its results details a novel approach to meeting the given conditions in a simple architecture of information processing. (shrink)

The development of machine learning and deep learning (DL) in the field of AI (artificial intelligence) is the direct result of the advancement of nano-electronics. Machine learning is a function that provides the system with the capacity to learn from data without being programmed explicitly. It is basically a mathematical and probabilistic model. DL is part of machine learning methods based on artificial neural networks, simply called neural networks (NNs), as they are inspired by the biological NNs that constitute organic (...) brains. Despite its similarity to biological organs such as human brains, major problems arise in trying to attribute moral responsibility to autonomic systems based on hardware including nano-electronic devices, which are sought to replace humans (moral agents) in the context of AI. It is suggested that the required emotional environment which enables actions according to reasons in humans is not witnessed at AI devices. Though AI technology raises an enticing resemblance to human actions, this resemblance is to be considered with a skeptical eye. It is because actions are associated with reasons while causes are connected to operations. Human agents are capable of acting upon their reasons, while AI devices are limited only to operations as they are conditioned by their programming, which is considered as an embodiment of some causes. As moral responsibility goes hand in hand with the capacity to act (according to reasons), attributing moral responsibility to AI devices is revealed to be but a misleading metaphor. (shrink)

The central challenge of “machine ethics” is to build autonomous machine agents that act morally rightly. But how can we build autonomous machine agents that act morally rightly, given reasonable disputes over what is right and wrong in particular cases? In this chapter, I argue that Immanuel Kant’s political philosophy can provide an important part of the answer.

Some physicians, in their care of patients at risk of misusing opioids, use machine learning (ML)-based prediction drug monitoring programmes (PDMPs) to guide their decision making in the prescription of opioids. This can cause a conflict: a PDMP Score can indicate a patient is at a high risk of opioid abuse while a patient expressly reports oppositely. The prescriber is then left to balance the credibility and trust of the patient with the PDMP Score. Pozzi1 argues that a prescriber who (...) downgrades the credibility of a patient’s testimony based on a low PDMP Score is epistemically and morally unjustified and contributes to a form of testimonial injustice. This results in patients being silenced, excluded from decision-making processes and subjected to structural injustices. Additionally, the use of ML systems in medical practices raises concerns about perpetuating existing inequalities, overestimating their capabilities and displacing human authority. However, almost the very same critiques apply to human-based systems. Formalisation, ML systems included, should instead be viewed positively,2 and precisely as a powerful means to begin eroding these and other problems in ethically sensitive domains. In this case, the epistemic virtues of formalisation include promoting transparency, consistency and replicability in decision making. Rigorous ML systems can also help ensure that models …. (shrink)

Since the automation revolution of our technological era, diverse machines or robots have gradually begun to reconfigure our lives. With this expansion, it seems that those machines are now faced with a new challenge: more autonomous decision-making involving life or death consequences. This paper explores the philosophical possibility of artificial moral agency through the following question: could a machine obtain the cognitive capacities needed to be a moral agent? In this regard, I propose to expose, under (...) a normative-cognitive perspective, the minimum criteria through which we could recognize an artificial entity as a genuine moral entity. Although my proposal should be considered from a reasonable level of abstraction, I will critically analyze and identify how an artificial agent could integrate those cognitive features. Finally, I intend to discuss their limitations or possibilities. (shrink)

Artificial agents (AAs), particularly but not only those in Cyberspace, extend the class of entities that can be involved in moral situations. For they can be conceived of as moral patients (as entities that can be acted upon for good or evil) and also as moral agents (as entities that can perform actions, again for good or evil). In this paper, we clarify the concept of agent and go on to separate the concerns of morality and responsibility (...) of agents (most interestingly for us, of AAs). We conclude that there is substantial and important scope, particularly in Computer Ethics, for the concept of moral agent not necessarily exhibiting free will, mental states or responsibility. This complements the more traditional approach, common at least since Montaigne and Descartes, which considers whether or not (artificial) agents have mental states, feelings, emotions and so on. By focussing directly on mind-less morality we are able to avoid that question and also many of the concerns of Artificial Intelligence. A vital component in our approach is the Method of Abstraction for analysing the level of abstraction (LoA) at which an agent is considered to act. The LoA is determined by the way in which one chooses to describe, analyse and discuss a system and its context. The Method of Abstraction is explained in terms of an interface or set of features or observables at a given LoA. Agenthood, and in particular moral agenthood, depends on a LoA. Our guidelines for agenthood are: interactivity (response to stimulus by change of state), autonomy (ability to change state without stimulus) and adaptability (ability to change the transition rules by which state is changed) at a given LoA. Morality may be thought of as a threshold defined on the observables in the interface determining the LoA under consideration. An agent is morally good if its actions all respect that threshold; and it is morally evil if some action violates it. That view is particularly informative when the agent constitutes a software or digital system, and the observables are numerical. Finally we review the consequences for Computer Ethics of our approach. In conclusion, this approach facilitates the discussion of the morality of agents not only in Cyberspace but also in the biosphere, where animals can be considered moral agents without their having to display free will, emotions or mental states, and in social contexts, where systems like organizations can play the role of moral agents. The primary cost of this facility is the extension of the class of agents and moral agents to embrace AAs. (shrink)