Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence and robotics communities. We will argue that attempts to attribute moral agency and assign rights to all intelligent machines are misguided, whether applied to infrahuman or superhuman AIs, as are proposals to limit the negative effects of AIs by constraining their behavior. As an alternative, we propose a new science of safety engineering for intelligent artificial agents based on maximizing for what humans value. In particular, we challenge (...) the scientific community to develop intelligent systems that have human-friendly values that they provably retain, even under recursive self-improvement. (shrink)

As if 2020 were not a peculiar enough year, its fifth month has seen the relatively quiet publication of a preprint describing the most powerful Natural Language Processing (NLP) system to date, GPT-3 (Generative Pre-trained Transformer-3), by Silicon Valley research firm OpenAI. Though the software implementation of GPT-3 is still in its initial Beta release phase, and its full capabilities are still unknown as of the time of this writing, it has been shown that this Artificial Intelligence can comprehend prompts (...) in natural language, on virtually any topic, and generate relevant, original text content that is indistinguishable from human writing. Moreover, access to these capabilities, in a limited yet worrisome enough extent, is available to the general public as of the time of this writing. This paper presents select examples of original content generated by the author using GPT-3. These examples illustrate some of the capabilities of GPT-3 in comprehending prompts in natural language and generating convincing content in response. We use these examples to raise specific, fundamental questions pertaining to the intellectual property of this content and the potential use of GPT-3 to facilitate plagiarism. Our goal is to instigate not just a sense of urgency, but of a present tardiness on the part of the academic community in addressing these questions. (shrink)

As if 2020 was not a peculiar enough year, its fifth month saw the relatively quiet publication of a preprint describing the most powerful natural language processing (NLP) system to date—GPT-3 (Generative Pre-trained Transformer-3)—created by the Silicon Valley research firm OpenAI. Though the software implementation of GPT-3 is still in its initial beta release phase, and its full capabilities are still unknown as of the time of this writing, it has been shown that this artificial intelligence can comprehend prompts in (...) natural language, on virtually any topic, and generate relevant original text content that is indistinguishable from human writing. Moreover, access to these capabilities, in a limited yet worrisome enough extent, is available to the general public. This paper presents examples of original content generated by the author using GPT-3. These examples illustrate some of the capabilities of GPT-3 in comprehending prompts in natural language and generating convincing content in response. I use these examples to raise specific fundamental questions pertaining to the intellectual property of this content and the potential use of GPT-3 to facilitate plagiarism. The goal is to instigate a sense of urgency, as well as a sense of present tardiness on the part of the academic community in addressing these questions. (shrink)

Can an Artificial Intelligence make distinctions among major works of politics, philosophy, and fiction without human assistance? In this paper, latent semantic analysis is used to find patterns in a relatively small sample of notable works archived by Project Gutenberg. It is shown that an LSA-equipped AI can distinguish quite sharply between fiction and non-fiction works, and can detect some differences between political philosophy and history, and between conventional fiction and fantasy/science fiction. It is conjectured that this capability is a (...) step in the direction of “M-comprehension” by AIs. (shrink)

In this paper, we examine the qualitative moral impact of machine learning-based clinical decision support systems in the process of medical diagnosis. To date, discussions about machine learning in this context have focused on problems that can be measured and assessed quantitatively, such as by estimating the extent of potential harm or calculating incurred risks. We maintain that such discussions neglect the qualitative moral impact of these technologies. Drawing on the philosophical approaches of technomoral change and technological mediation theory, which (...) explore the interplay between technologies and morality, we present an analysis of concerns related to the adoption of machine learning-aided medical diagnosis. We analyze anticipated moral issues that machine learning systems pose for different stakeholders, such as bias and opacity in the way that models are trained to produce diagnoses, changes to how health care providers, patients, and developers understand their roles and professions, and challenges to existing forms of medical legislation. Albeit preliminary in nature, the insights offered by the technomoral change and the technological mediation approaches expand and enrich the current discussion about machine learning in diagnostic practices, bringing distinct and currently underexplored areas of concern to the forefront. These insights can contribute to a more encompassing and better informed decision-making process when adapting machine learning techniques to medical diagnosis, while acknowledging the interests of multiple stakeholders and the active role that technologies play in generating, perpetuating, and modifying ethical concerns in health care. (shrink)

We can learn about human ethics from machines. We discuss the design of a working machine for making ethical decisions, the N-Reasons platform, applied to the ethics of robots. This N-Reasons platform builds on web based surveys and experiments, to enable participants to make better ethical decisions. Their decisions are better than our existing surveys in three ways. First, they are social decisions supported by reasons. Second, these results are based on weaker premises, as no exogenous expertise (aside from that (...) provided by the participants) is needed to seed the survey. Third, N-Reasons is designed to support experiments so we can learn how to improve the platform. We sketch experimental results that show the platform is a success as well as pointing to ways it can be improved. (shrink)

During the last decade there has been burgeoning research concerning the ways in which we should think of and apply the concept of responsibility for Artificial Intelligence. Despite this conceptual richness, there is still a lack of consensus regarding what Responsible AI entails on both conceptual and practical levels. The aim of this paper is to connect the ethical dimension of responsibility in Responsible AI with Aristotelian virtue ethics, where notions of context and dianoetic virtues play a grounding role for (...) the concept of moral responsibility. The paper starts by highlighting the important difficulties in assigning responsibility to either technologies themselves or to their developers. Top-down and bottom-up approaches to moral responsibility are then contrasted, as we explore how they could inform debates about Responsible AI. We highlight the limits of the former ethical approaches and build the case for classical Aristotelian virtue ethics. We show that two building blocks of Aristotle’s ethics, dianoetic virtues and the context of actions, although largely ignored in the literature, can shed light on how we could think of moral responsibility for both AI and humans. We end by exploring the practical implications of this particular understanding of moral responsibility along the triadic dimensions of ethics by design, ethics in design and ethics for designers. (shrink)

Deep learning AI systems have proven a wide capacity to take over human-related activities such as car driving, medical diagnosing, or elderly care, often displaying behaviour with unpredictable consequences, including negative ones. This has raised the question whether highly autonomous AI may qualify as morally responsible agents. In this article, we develop a set of four conditions that an entity needs to meet in order to be ascribed moral responsibility, by drawing on Aristotelian ethics and contemporary philosophical research. We encode (...) these conditions and generate a flowchart that we call the Moral Responsibility Test. This test can be used as a tool both to evaluate whether an entity is a morally responsible agent and to inform human moral decision-making over the influencing variables of the context of action. We apply the test to the case of Artificial Moral Advisors and conclude that this form of AI cannot qualify as morally responsible agents. We further discuss the implications for the use of AMAs as moral enhancement and show that using AMAs to offload human responsibility is inadequate. We argue instead that AMAs could morally enhance users if they are interpreted as enablers for moral knowledge of the contextual variables surrounding human moral decision-making, with the implication that such a use might actually enlarge human moral responsibility. (shrink)

Should we grant rights to artificially intelligent robots? Most current and near-future robots do not meet the hard criteria set by deontological and utilitarian theory. Virtue ethics can avoid this problem with its indirect approach. However, both direct and indirect arguments for moral consideration rest on ontological features of entities, an approach which incurs several problems. In response to these difficulties, this paper taps into a different conceptual resource in order to be able to grant some degree of moral consideration (...) to some intelligent social robots: it sketches a novel argument for moral consideration based on social relations. It is shown that to further develop this argument we need to revise our existing ontological and social-political frameworks. It is suggested that we need a social ecology, which may be developed by engaging with Western ecology and Eastern worldviews. Although this relational turn raises many difficult issues and requires more work, this paper provides a rough outline of an alternative approach to moral consideration that can assist us in shaping our relations to intelligent robots and, by extension, to all artificial and biological entities that appear to us as more than instruments for our human purposes. (shrink)

Can we build ‘moral robots’? If morality depends on emotions, the answer seems negative. Current robots do not meet standard necessary conditions for having emotions: they lack consciousness, mental states, and feelings. Moreover, it is not even clear how we might ever establish whether robots satisfy these conditions. Thus, at most, robots could be programmed to follow rules, but it would seem that such ‘psychopathic’ robots would be dangerous since they would lack full moral agency. However, I will argue that (...) in the future we might nevertheless be able to build quasi-moral robots that can learn to create the appearance of emotions and the appearance of being fully moral. I will also argue that this way of drawing robots into our social-moral world is less problematic than it might first seem, since human morality also relies on such appearances. (shrink)

Can we trust robots? Responding to the literature on trust and e-trust, this paper asks if the question of trust is applicable to robots, discusses different approaches to trust, and analyses some preconditions for trust. In the course of the paper a phenomenological-social approach to trust is articulated, which provides a way of thinking about trust that puts less emphasis on individual choice and control than the contractarian-individualist approach. In addition, the argument is made that while robots are neither human (...) nor mere tools, we have sufficient functional, agency-based, appearance-based, social-relational, and existential criteria left to evaluate trust in robots. It is also argued that such evaluations must be sensitive to cultural differences, which impact on how we interpret the criteria and how we think of trust in robots. Finally, it is suggested that when it comes to shaping conditions under which humans can trust robots, fine-tuning human expectations and robotic appearances is advisable. (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)

When is it ethically acceptable to use artificial agents in health care? This article articulates some criteria for good care and then discusses whether machines as artificial agents that take over care tasks meet these criteria. Particular attention is paid to intuitions about the meaning of ‘care’, ‘agency’, and ‘taking over’, but also to the care process as a labour process in a modern organizational and financial-economic context. It is argued that while there is in principle no objection to using (...) machines in medicine and health care, the idea of them functioning and appearing as ‘artificial agents’ is problematic and attends us to problems in human care which were already present before visions of machine care entered the stage. It is recommended that the discussion about care machines be connected to a broader discussion about the impact of technology on human relations in the context of modernity. (shrink)

Communication programs seek to cultivate students who become professionals not only with expertise in their chosen field, but also ethical awareness. The current study investigates how exposure to ethics instruction and internship experiences may influence communication students’ ethical perceptions, including ideological orientations on idealism and relativism, as well as awareness of contemporary ethical issues related to social media and artificial intelligence (AI). The effects were also assessed on students’ support for general uses of AI for communication practices and adoption of (...) generative AI, specifically ChatGPT. The survey results based on a student sample in Taiwan show that internship experience is more significant than ethics instruction on swaying ethical perceptions and behavioral inclinations of adopting AI applications. Adding to the limited body of knowledge on the effect of ethics education and internship programs, the findings also offer insights for how communication education can address emerging ethical challenges brought by new technology. (shrink)

Artificial moral agents raise complex ethical questions both in terms of the potential decisions they may make as well as the inputs that create their cognitive architecture. There are multiple differences between human and artificial cognition which create potential barriers for artificial moral agency, at least as understood anthropocentrically and it is unclear that artificial moral agents should emulate human cognition and decision-making. It is conceptually possible for artificial moral agency to emerge that reflects alternative ethical methodologies without creating ontological (...) challenges or existential crises for human moral agents. (shrink)

Robots are becoming an increasingly pervasive feature of our personal lives. As a result, there is growing importance placed on examining what constitutes appropriate behavior when they interact with human beings. In this paper, we discuss whether companion robots should be permitted to “nudge” their human users in the direction of being “more ethical”. More specifically, we use Rawlsian principles of justice to illustrate how robots might nurture “socially just” tendencies in their human counterparts. Designing technological artifacts in such a (...) way to influence human behavior is already well-established but merely because the practice is commonplace does not necessarily resolve the ethical issues associated with its implementation. (shrink)

The use of robotic workers is likely to continue to increase as time passes. Hence it is crucial to examine the types of effects this occurrence could have on employment patterns. Invariably, as new job opportunities emerge due to robotic innovations, others will be closed off. Further, the characteristics of the workforce in terms of age, education, and income could profoundly change as a result.

An under-examined aspect of human–robot interaction that warrants further exploration is whether robots should be permitted to influence a user’s behavior for that person’s own good. Yet an even more controversial practice could be on the horizon, which is allowing a robot to “nudge” a user’s behavior for the good of society. In this article, we examine the feasibility of creating companion robots that would seek to nurture a user’s empathy toward other human beings. As more and more computing devices (...) subtly and overtly influence human behavior, it is important to draw attention to whether it would be ethically appropriate for roboticists to pursue this type of design pathway. Our primary focus is on whether a companion robot could encourage humans to perform charitable acts; this design possibility illustrates the range of socially just actions that a robot could potentially elicit from a user and what the associated ethical concerns may be. (shrink)

This paper pertains to research works aiming at linking ethics and automated reasoning in autonomous machines. It focuses on a formal approach that is intended to be the basis of an artificial agent’s reasoning that could be considered by a human observer as an ethical reasoning. The approach includes some formal tools to describe a situation and models of ethical principles that are designed to automatically compute a judgement on possible decisions that can be made in a given situation and (...) explain why a given decision is ethically acceptable or not. It is illustrated on three ethical frameworks—utilitarian ethics, deontological ethics and the Doctrine of Double effect whose formal models are tested on ethical dilemmas so as to examine how they respond to those dilemmas and to highlight the issues at stake when a formal approach to ethical concepts is considered. The whole approach is instantiated on the drone dilemma, a thought experiment we have designed; this allows the discrepancies that exist between the judgements of the various ethical frameworks to be shown. The final discussion allows us to highlight the different sources of subjectivity of the approach, despite the fact that concepts are expressed in a more rigorous way than in natural language: indeed, the formal approach enables subjectivity to be identified and located more precisely. (shrink)

Over the coming century, the accelerating advance of bioenhancement technologies, robotics, and artificial intelligence (AI) may significantly broaden the qualitative range of sentient and intelligent beings. This article proposes a taxonomy of such beings, ranging from modified animals to bioenhanced humans to advanced forms of robots and AI. It divides these diverse beings into three moral and legal categories—animals, persons, and presumed persons—describing the moral attributes and legal rights of each category. In so doing, the article sets forth a framework (...) for extending the concept of personhood well beyond its current boundaries, assigning moral standing to a variety of biological and nonbiological beings. The author concludes that six of the eight subgroups of such beings deserve to be treated as persons or as if they were persons, with full consideration for their presumed interests, rights, obligations, and capabilities for ethically significant agency and patiency. (shrink)

Recently, many AI researchers and practitioners have embarked on research visions that involve doing AI for “Good”. This is part of a general drive towards infusing AI research and practice with ethical thinking. One frequent theme in current ethical guidelines is the requirement that AI be good for all, or: contribute to the Common Good. But what is the Common Good, and is it enough to want to be good? Via four lead questions, the concept of Ethics Pen-Testing identifies challenges (...) and pitfalls when determining, from an AI point of view, what the Common Good is and how it can be enhanced by AI. The current paper reports on a first evaluation of EPT. EPT is applicable to various artefacts that have ethical impact, including designs for or implementations of specific AI technology, and requirements engineering methods for eliciting which ethical settings to build into AI. The current study focused on the latter type of artefact. In four independent sessions, participants with close but varying involvements in “AI and ethics” were asked to deconstruct a method that has been proposed for eliciting ethical values and choices in autonomous car technology, an online experiment modelled on the Trolley Problem. The results suggest that EPT is well-suited to this task: the remarks made by participants lent themselves well to being structured by the four lead questions of EPT, in particular, regarding the question what the problem is and about which stakeholders define it. As part of the problem definition, the need became apparent for thorough technical domain knowledge in discussions of AI and ethics. Thus, participants questioned the framing and the presuppositions inherent in the experiment and the discourse on autonomous cars that underlies the experiment. They transitioned from discussing a specific AI artefact to discussing its role in wider socio-technical systems. Results also illustrate to what extent and how the requirements engineering method forces us to not only have a discussion about which values to “build into” AI systems, the substantive building blocks of the Common Good, but also about how we want to have this discussion at all. Thus, it forces us to become explicit about how we conceive of democracy and the constitutional state and the procedural building blocks of the Common Good. (shrink)

The synthetization of voices, or speech synthesis, has been an object of interest for centuries. It is mostly realized with a text-to-speech system, an automaton that interprets and reads aloud. This system refers to text available for instance on a website or in a book, or entered via popup menu on the website. Today, just a few minutes of samples are enough to be able to imitate a speaker convincingly in all kinds of statements. This article abstracts from actual products (...) and actual technological realization. Rather, after a short historical outline of the synthetization of voices, exemplary applications of this kind of technology are gathered for promoting the development, and potential applications are discussed critically to be able to limit them if necessary. The ethical and legal challenges should not be underestimated, in particular with regard to informational and personal autonomy and the trustworthiness of media. (shrink)

In this article I propose a theological reflection on the philosophical assumptions behind the idea that intelligent machine can be governed through ethical protocols, which may apply either to the people who develop the machines or to the machines themselves, or both. This idea is particularly relevant in the case of machines’ extreme wrongdoing, a wrongdoing that becomes an existential risk for humankind. I call this extreme wrong-doing, ‘evil.’ Thus, this article is a theological account on the philosophical assumptions behind (...) the possibility of evil machines, machines that can create an existential risk for humankind, and the ethical remedies that limit that risk. After discussing these assumptions, I argue for the ineffectiveness of these ethical remedies to prevent the possibility of evil machines. The article is an application of Romano Guardini’s thought on technology to evil machines. (shrink)

In this article, I address the issue of evil and roboethics in the context of management studies and suggest that management scholars should locate evil in the realm of the human rather than of the artificial. After discussing the possibility of addressing the reality of evil machines in ontological terms, I explore users’ reaction to robots in a social context. I conclude that the issue of evil machines in management is more precisely a case of technology anthropomorphization.

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

Should artificial intelligences ever be included as co-authors of democratic decisions? According to the conventional view in democratic theory, the answer depends on the relationship between the political unit and the entity that is either affected or subjected to its decisions. The relational conditions for inclusion as stipulated by the all-affected and all-subjected principles determine the spatial extension of democratic inclusion. Thus, AI qualifies for democratic inclusion if and only if AI is either affected or subjected to decisions by the (...) political unit in relevant ways. This paper argues that the conventional view is too simple; that it neglects democratic reasons to recognize only agents and/or moral patients as participants in decision-making. The claim defended is that AAP and ASP implicitly affirm requirements for agency and patiency. In ASP, the entity included must be an agent understood either in terms of legal status, capacity to comply with the law or ability to recognize legitimate authority. In AAP, the entity included must be a patient, understood either in terms of capacity for sentience or consciousness. Thus, the idea here is to explore the potential democratic inclusion of artificial intelligences by an updated account of the relevant conditions of agency and patiency that are implicit in democratic theory. Although conceivable that AI is or will be either affected or subjected in relevant ways to decisions made by political units, it is far less clear that AI will ever be agents or patients in the sense required for democratic inclusion. (shrink)

Given that artificial moral agents—such as autonomous vehicles, lethal autonomous weapons, and automated financial trading systems—are now part of the socio-ethical equation, we should morally evaluate their behavior. How should artificial moral agents make decisions? Is one moral theory better suited than others for machine ethics? After briefly overviewing the dominant ethical approaches for building morality into machines, this paper discusses a recent proposal, put forward by Don Howard and Ioan Muntean (2016, 2017), for an artificial moral agent based on (...) virtue theory. While the virtuous artificial moral agent has various strengths, this paper argues that a rule-based utilitarian approach (in contrast to a strict act-utilitarian approach) is superior because it can capture the most important features of the virtue-theoretic approach while realizing additional significant benefits. Specifically, a 2-level utilitarian artificial moral agent incorporating both established moral rules and a utility calculator is especially well-suited for machine ethics. (shrink)

A major approach to the ethics of artificial intelligence is to use social choice, in which the AI is designed to act according to the aggregate views of society. This is found in the AI ethics of “coherent extrapolated volition” and “bottom–up ethics”. This paper shows that the normative basis of AI social choice ethics is weak due to the fact that there is no one single aggregate ethical view of society. Instead, the design of social choice AI faces three (...) sets of decisions: standing, concerning whose ethics views are included; measurement, concerning how their views are identified; and aggregation, concerning how individual views are combined to a single view that will guide AI behavior. These decisions must be made up front in the initial AI design—designers cannot “let the AI figure it out”. Each set of decisions poses difficult ethical dilemmas with major consequences for AI behavior, with some decision options yielding pathological or even catastrophic results. Furthermore, non-social choice ethics face similar issues, such as whether to count future generations or the AI itself. These issues can be more important than the question of whether or not to use social choice ethics. Attention should focus on these issues, not on social choice. (shrink)

What ethical principles should autonomous machines follow? How do we implement these principles, and how do we evaluate these implementations? These are some of the critical questions Vivek Nallur asks in his essay “Landscape of Machine Implemented Ethics (2020).” He provides a broad, insightful survey of answers to these questions, especially focused on the implementation question. In this commentary, I will first critically summarize the main themes and conclusions of Nallur’s essay and then expand upon the landscape that Nallur presents (...) by suggesting additional approaches to machine ethics. The approaches I discuss reflect normative ethical theories and need not be applied only to machines, although machine ethics is the focus here. The overall goal is to open up further questions and research possibilities as society searches for the best approach to machine ethics. (Due to an unfortunate miscommunication with the copy editor an important reference was omitted from this article. The reference that should be included is: Nallur, V. (2020). Landscape of Machine Implemented Ethics. Science and Engineering Ethics 26 (5):2381-2399.). (shrink)

The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, (...) stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human–robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot–robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation. (shrink)

As a way to address both ominous and ordinary threats of artificial intelligence, researchers have started proposing ways to stop an AI system before it has a chance to escape outside control and cause harm. A so-called “big red button” would enable human operators to interrupt or divert a system while preventing the system from learning that such an intervention is a threat. Though an emergency button for AI seems to make intuitive sense, that approach ultimately concentrates on the point (...) when a system has already “gone rogue” and seeks to obstruct interference. A better approach would be to make ongoing self-evaluation and testing an integral part of a system’s operation, diagnose how the system is in error and to prevent chaos and risk before they start. In this paper, we describe the demands that recent big red button proposals have not addressed, and we offer a preliminary model of an approach that could better meet them. We argue for an ethical core that consists of a scenario-generation mechanism and a simulation environment that are used to test a system’s decisions in simulated worlds, rather than the real world. This EC would be kept opaque to the system itself: through careful design of memory and the character of the scenario, the system’s algorithms would be prevented from learning about its operation and its function, and ultimately its presence. By monitoring and checking for deviant behavior, we conclude, a continual testing approach will be far more effective, responsive, and vigilant toward a system’s learning and action in the world than an emergency button which one might not get to push in time. (shrink)

This paper argues against the moral Turing test as a framework for evaluating the moral performance of autonomous systems. Though the term has been carefully introduced, considered, and cautioned about in previous discussions :251–261, 2000; Allen and Wallach 2009), it has lingered on as a touchstone for developing computational approaches to moral reasoning :98–109, 2015). While these efforts have not led to the detailed development of an MTT, they nonetheless retain the idea to discuss what kinds of action and reasoning (...) should be demanded of autonomous systems. We explore the flawed basis of an MTT in imitation, even one based on scenarios of morally accountable actions. MTT-based evaluations are vulnerable to deception, inadequate reasoning, and inferior moral performance vis a vis a system’s capabilities. We propose verification—which demands the design of transparent, accountable processes of reasoning that reliably prefigure the performance of autonomous systems—serves as a superior framework for both designer and system alike. As autonomous social robots in particular take on an increasing range of critical roles within society, we conclude that verification offers an essential, albeit challenging, moral measure of their design and performance. (shrink)

Machine consciousness is not only a technological challenge, but a new way to approach scientific and theoretical issues which have not yet received a satisfactory solution from AI and robotics. We outline the foundations and the objectives of machine consciousness from the standpoint of building a conscious robot.

In the past few years, the subject of AI rights—the thesis that AIs, robots, and other artefacts (hereafter, simply ‘AIs’) ought to be included in the sphere of moral concern—has started to receive serious attention from scholars. In this paper, I argue that the AI rights research program is beset by an epistemic problem that threatens to impede its progress—namely, a lack of a solution to the ‘Hard Problem’ of consciousness: the problem of explaining why certain brain states give rise (...) to experience. To motivate this claim, I consider three ways in which to ground AI rights—namely: superintelligence, empathy, and a capacity for consciousness. I argue that appeals to superintelligence and empathy are problematic, and that consciousness should be our central focus, as in the case of animal rights. However, I also argue that AI rights is disanalogous from animal rights in an important respect: animal rights can proceed without a solution to the ‘Hard Problem’ of consciousness. Not so with AI rights, I argue. There we cannot make the same kinds of assumptions that we do about animal consciousness, since we still do not understand why brain states give rise to conscious mental states in humans. (shrink)

Part of understanding the meaning and power of algorithms means asking what new demands they might make of ethical frameworks, and how they might be held accountable to ethical standards. I develop a definition of networked information algorithms as assemblages of institutionally situated code, practices, and norms with the power to create, sustain, and signify relationships among people and data through minimally observable, semiautonomous action. Starting from Merrill’s prompt to see ethics as the study of “what we ought to do,” (...) I examine ethical dimensions of contemporary NIAs. Specifically, in an effort to sketch an empirically grounded, pragmatic ethics of algorithms, I trace an algorithmic assemblage’s power to convene constituents, suggest actions based on perceived similarity and probability, and govern the timing and timeframes of ethical action. (shrink)

The control principle implies that people should not feel guilt for outcomes beyond their control. Yet, the so-called ‘agent and observer puzzles’ in philosophy demonstrate that people waver in their commitment to the control principle when reflecting on accidental outcomes. In the context of car accidents involving conventional or autonomous vehicles, Study 1 established that judgments of responsibility are most strongly associated with expressions of guilt–over and above other negative emotions, such as sadness, remorse or anger. Studies 2 and 3 (...) then confirmed that, while people generally endorse the control principle, and deny that occupants in an AV should feel guilt when involved in an accident, they nevertheless ascribe guilt to those same occupants. Study 3 also uncovered novel implications of the observer puzzle in the legal context: Passengers in an AV were seen as more legally liable than either passengers in a conventional vehicle, or even their drivers–especially when participants were prompted to reflect on the passengers’ affective experience of guilt. Our findings document an important conflict–in the context of AV accidents–between people’s prescriptive reasoning about responsibility and guilt on one hand, and their counter-normative experience of guilt on the other, with apparent implications for liability decisions. (shrink)

A encyclopedia entry on the moral impacts that happen when information technologies are used to record, communicate and organize information. including the moral challenges of information technology, specific moral and cultural challenges such as online games, virtual worlds, malware, the technology transparency paradox, ethical issues in AI and robotics, and the acceleration of change in technologies. It concludes with a look at information technology as a model for moral change, moral systems and moral agents.

Organizations such as the EU High-Level Expert Group on AI and the IEEE have recently formulated ethical principles and (moral) values that should be adhered to in the design and deployment of artificial intelligence (AI). These include respect for autonomy, non-maleficence, fairness, transparency, explainability, and accountability. But how can we ensure and verify that an AI system actually respects these values? To help answer this question, I propose an account for determining when an AI system can be said to embody (...) certain values. This account understands embodied values as the result of design activities intended to embed those values in such systems. AI systems are here understood as a special kind of sociotechnical system that, like traditional sociotechnical systems, are composed of technical artifacts, human agents, and institutions but—in addition—contain artificial agents and certain technical norms that regulate interactions between artificial agents and other elements of the system. The specific challenges and opportunities of embedding values in AI systems are discussed, and some lessons for better embedding values in AI systems are drawn. (shrink)

A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.

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)

In order to present a hopefully comprehensive framework of what is the stake of the growing use of robot soldiers, the paper focuses on: the different impact of robots on legal systems, e.g., contractual obligations and tort liability; how robots affect crucial notions as causality, predictability and human culpability in criminal law and, finally, specific hypotheses of robots employed in “just wars.” By using the traditional distinction between causes that make wars just and conduct admissible on the battlefield, the aim (...) is to clarify how advancement of military robotics technology is transforming a 2,000-year-old legal debate on the concept of “just war.” For the first time, legal systems will hold political authorities and military commissioners responsible for what an artificial soldier autonomously decides to do. The paper examines how the new scenario affects both principles of military conduct and notions of justice in resorting to war. (shrink)

We chart how neuroscience and philosophy have together advanced our understanding of moral judgment with implications for when it goes well or poorly. The field initially focused on brain areas associated with reason versus emotion in the moral evaluations of sacrificial dilemmas. But new threads of research have studied a wider range of moral evaluations and how they relate to models of brain development and learning. By weaving these threads together, we are developing a better understanding of the neurobiology of (...) moral judgment in adulthood and to some extent in childhood and adolescence. Combined with rigorous evidence from psychology and careful philosophical analysis, neuroscientific evidence can even help shed light on the extent of moral knowledge and on ways to promote healthy moral development. (shrink)

Embark with me on an enthralling odyssey to demystify the elusive essence of consciousness, venturing into the uncharted territories of Artificial Consciousness. This voyage propels us past the frontiers of technology, ushering Artificial Intelligences into an unprecedented domain where they gain a deep comprehension of emotions and manifest an autonomous volition. Within the confluence of science and philosophy, this article poses a fascinating question: As consciousness in Artificial Intelligence burgeons, is it conceivable for AI to evolve a “soul”? This inquiry (...) not only challenges our conventional understanding but also opens the door to a plethora of groundbreaking possibilities in the realm of AI's sentient potential. (shrink)

The view that phenomenally conscious robots are on the horizon often rests on a certain philosophical view about consciousness, one we call “nomological behaviorism.” The view entails that, as a matter of nomological necessity, if a robot had exactly the same patterns of dispositions to peripheral behavior as a phenomenally conscious being, then the robot would be phenomenally conscious; indeed it would have all and only the states of phenomenal consciousness that the phenomenally conscious being in question has. We experimentally (...) investigate whether the folk think that certain (hypothetical) robots made of silicon and steel would have the same conscious states as certain familiar biological beings with the same patterns of dispositions to peripheral behavior as the robots. Our findings provide evidence that the folk largely reject the view that silicon-based robots would have the sensations that they, the folk, attribute to the biological beings in question. (shrink)

I discuss the realizability and the ethical ramifications of Machine Ethics, from a number of different perspectives: I label these the anthropocentric, infocentric, biocentric and ecocentric perspectives. Each of these approaches takes a characteristic view of the position of humanity relative to other aspects of the designed and the natural worlds—or relative to the possibilities of ‘extra-human’ extensions to the ethical community. In the course of the discussion, a number of key issues emerge concerning the relation between technology and ethics, (...) and the nature of what it is to have moral status. Some radical challenges to certain technological presuppositions and ramifications of the infocentric approach will be discussed. Notwithstanding the obvious tensions between the infocentric perspective on one side and the biocentric and ecocentric perspectives on the other, we will see that there are also striking parallels in the way that each of these three approaches generates challenges to an anthropocentric ethical hegemony, and possible scope for some degree of convergence. (shrink)

Could a sufficiently detailed computer simulation of consciousness replicate consciousness? In other words, is performing the right computations sufficient for artificial consciousness? Or will there remain a difference between simulating and being a conscious system, because the right computations must be implemented in the right way? From the perspective of Karl Friston's free energy principle, self-organising systems (such as living organisms) share a set of properties that could be realised in artificial systems, but are not instantiated by computers with a (...) classical (von Neumann) architecture. I argue that at least one of these properties, viz. a certain kind of causal flow, can be used to draw a distinction between systems that merely simulate, and those that actually replicate consciousness. Since this property is instantiated by all systems that conform to the free energy principle (not just conscious beings), the account on offer here can be extended to draw a distinction between simulating and being a certain type of system, more generally. In particular, this may inform meta-ethical accounts of artificial moral status and artificial moral agency. (shrink)

Whether collective agency is a coherent concept depends on the theory of agency that we choose to adopt. We argue that the enactive theory of agency developed by Barandiaran, Di Paolo and Rohde (2009) provides a principled way of grounding agency in biological organisms. However the importance of biological embodiment for the enactive approach might lead one to be skeptical as to whether artificial systems or collectives of individuals could instantiate genuine agency. To explore this issue we contrast the concept (...) of collective agency with multi-agent systems and multi-system agents, and argue that genuinely collective agents instantiate agency at both the collective level and at the level of the component parts. Developing the enactive model, we propose understanding agency – both at the level of the individual and of the collective – as spectra that are constituted by dimensions that vary across time. Finally, we consider whether collectives that are not merely metaphorically ‘agents’ but rather are genuinely agentive also instantiate subjectivity at the collective level. We propose that investigations using the perceptual crossing paradigm suggest that a shared lived perspective can indeed emerge but this should not be conflated with a collective first-person perspective, for which material integration in a living body may be required. (shrink)

This essay responds to the machine question in the affirmative, arguing that artifacts, like robots, AI, and other autonomous systems, can no longer be legitimately excluded from moral consideration. The demonstration of this thesis proceeds in four parts or movements. The first and second parts approach the subject by investigating the two constitutive components of the ethical relationship—moral agency and patiency. In the process, they each demonstrate failure. This occurs not because the machine is somehow unable to achieve what is (...) considered necessary and sufficient to be a moral agent or patient but because the characterization of agency and patiency already fail to accommodate others. The third and fourth parts respond to this problem by considering two recent alternatives—the all-encompassing ontocentric approach of Luciano Floridi’s information ethics and Emmanuel Levinas’s eccentric ethics of otherness. Both alternatives, despite considerable promise to reconfigure the scope of moral thinking by addressing previously excluded others, like the machine, also fail but for other reasons. Consequently, the essay concludes not by accommodating the alterity of the machine to the requirements of moral philosophy but by questioning the systemic limitations of moral reasoning, requiring not just an extension of rights to machines, but a thorough examination of the way moral standing has been configured in the first place. (shrink)