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)

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)

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

This essay addresses the other side of the robot ethics debate, taking up and investigating the question “Can and should robots have rights?” The examination of this subject proceeds by way of three steps or movements. We begin by looking at and analyzing the form of the question itself. There is an important philosophical difference between the two modal verbs that organize the inquiry—can and should. This difference has considerable history behind it that influences what is asked about and how. (...) Second, capitalizing on this verbal distinction, it is possible to identify four modalities concerning social robots and the question of rights. The second section will identify and critically assess these four modalities as they have been deployed and developed in the current literature. Finally, we will conclude by proposing another alternative, a way of thinking otherwise that effectively challenges the existing rules of the game and provides for other ways of theorizing moral standing that can scale to the unique challenges and opportunities that are confronted in the face of social robots. (shrink)

The question of whether AI systems such as robots can or should be afforded moral agency or patiency is not one amenable either to discovery or simple reasoning, because we as societies constantly reconstruct our artefacts, including our ethical systems. Consequently, the place of AI systems in society is a matter of normative, not descriptive ethics. Here I start from a functionalist assumption, that ethics is the set of behaviour that maintains a society. This assumption allows me to exploit the (...) theoretical biology of sociality and autonomy to explain our moral intuitions. From this grounding I extend to consider possible ethics for maintaining either human- or of artefact-centred societies. I conclude that while constructing AI systems as either moral agents or patients is possible, neither is desirable. In particular, I argue that we are unlikely to construct a coherent ethics in which it it is ethical to afford AI moral subjectivity. We are therefore obliged not to build AI we are obliged to. (shrink)

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

There is widespread agreement that there should be a principle requiring that artificial intelligence be ‘explicable’. Microsoft, Google, the World Economic Forum, the draft AI ethics guidelines for the EU commission, etc. all include a principle for AI that falls under the umbrella of ‘explicability’. Roughly, the principle states that “for AI to promote and not constrain human autonomy, our ‘decision about who should decide’ must be informed by knowledge of how AI would act instead of us” :689–707, 2018). There (...) is a strong intuition that if an algorithm decides, for example, whether to give someone a loan, then that algorithm should be explicable. I argue here, however, that such a principle is misdirected. The property of requiring explicability should attach to a particular action or decision rather than the entity making that decision. It is the context and the potential harm resulting from decisions that drive the moral need for explicability—not the process by which decisions are reached. Related to this is the fact that AI is used for many low-risk purposes for which it would be unnecessary to require that it be explicable. A principle requiring explicability would prevent us from reaping the benefits of AI used in these situations. Finally, the explanations given by explicable AI are only fruitful if we already know which considerations are acceptable for the decision at hand. If we already have these considerations, then there is no need to use contemporary AI algorithms because standard automation would be available. In other words, a principle of explicability for AI makes the use of AI redundant. (shrink)

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

The question whether AI systems have agency is gaining increasing importance in discussions of responsibility for AI behavior. This paper argues that an approach to artificial agency needs to be teleological, and consider the role of human goals in particular if it is to adequately address the issue of responsibility. I will defend the view that while AI systems can be viewed as autonomous in the sense of identifying or pursuing goals, they rely on human goals and other values incorporated (...) into their design, and are, as such, dependent on human agents. As a consequence, AI systems cannot be held morally responsible, and responsibility attributions should take into account normative and social aspects involved in the design and deployment of the said AI. My argument falls in line with approaches critical of attributing moral agency to artificial agents, but draws from the philosophy of action, highlighting further philosophical underpinnings of current debates on artificial agency. (shrink)

There are various philosophical approaches and theories describing the intimate relation people have to artifacts. In this paper, I explore the relation between two such theories, namely distributed cognition and distributed morality theory. I point out a number of similarities and differences in these views regarding the ontological status they attribute to artifacts and the larger systems they are part of. Having evaluated and compared these views, I continue by focussing on the way cognitive artifacts are used in moral practice. (...) I specifically conceptualise how such artifacts (a) scaffold and extend moral reasoning and decision-making processes, (b) have a certain moral status which is contingent on their cognitive status, and (c) whether responsibility can be attributed to distributed systems. This paper is primarily written for those interested in the intersection of cognitive and moral theory as it relates to artifacts, but also for those independently interested in philosophical debates in extended and distributed cognition and ethics of (cognitive) technology. (shrink)

Great technological advances in such areas as computer science, artificial intelligence, and robotics have brought the advent of artificially intelligent robots within our reach within the next century. Against this background, the interdisciplinary field of machine ethics is concerned with the vital issue of making robots “ethical” and examining the moral status of autonomous robots that are capable of moral reasoning and decision-making. The existence of such robots will deeply reshape our socio-political life. This paper focuses on whether such highly (...) advanced yet artificially intelligent beings will deserve moral protection once they become capable of moral reasoning and decision-making. I argue that we are obligated to grant them moral rights once they have become full ethical agents, i.e., subjects of morality. I present four related arguments in support of this claim and thereafter examine four main objections to the idea of ascribing moral rights to artificial intelligent robots. (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)

When a computer system causes harm, who is responsible? This question has renewed significance given the proliferation of autonomous systems enabled by modern artificial intelligence techniques. At the root of this problem is a philosophical difficulty known in the literature as the responsibility gap. That is to say, because of the causal distance between the designers of autonomous systems and the eventual outcomes of those systems, the dilution of agency within the large and complex teams that design autonomous systems, and (...) the impossibility of fully predicting how autonomous systems will behave once deployed, determining who is morally responsible for harms caused by autonomous systems is unclear at a conceptual level. I review past work on this topic, criticizing prior works for suggesting workarounds rather than philosophical answers to the conceptual problem presented by the responsibility gap. The view I develop, drawing on my earlier work on vicarious moral responsibility, explains why computing professionals are ethically required to take responsibility for the systems they design, despite not being blameworthy for the harms these systems may cause. (shrink)

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

As robots are deployed in a widening range of situations, it is necessary to develop a clearer position about whether or not they can be trusted to make good moral decisions. In this paper, we take a realistic look at recent attempts to program and to train robots to develop some form of moral competence. Examples of implemented robot behaviours that have been described as 'ethical', or 'minimally ethical' are considered, although they are found to only operate in quite constrained (...) and limited application domains. There is a general recognition that current robots cannot be described as full moral agents, but it is less clear whether will always be the case. Concerns are raised about the insufficiently justified use of terms such as 'moral' and 'ethical' to describe the behaviours of robots that are often more related to safety considerations than to moral ones. Given the current state of the art, two possible responses are identified. The first involves continued efforts to develop robots that are capable of ethical behaviour. The second is to argue against, and to attempt to avoid, placing robots in situations that demand moral competence and an understanding of the surrounding social situation. There is something to be gained from both responses, but it is argued here that the second is the more responsible choice. (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)

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

This paper aims to highlight the life of computer technologies to understand what kind of ‘technological intentionality’ is present in computers based upon the phenomenological elements constituting the objects in general. Such a study can better explain the effects of new digital technologies on our society and highlight the role of digital technologies by focusing on their activities. Even if Husserlian phenomenology rarely talks about technologies, some of its aspects can be used to address the actions performed by the digital (...) technologies by focusing on the objects’ inner ‘life’ thanks to the analysis of passive synthesis and phenomenological horizons in the objects. These elements can be used in computer technologies to show how digital objects are ‘alive.’ This paper focuses on programs developed through high-order languages like C++ and unsupervised learning techniques like ‘Generative Adversarial Model.’ The phenomenological analysis reveals the computer’s autonomy within the programming stages. At the same time, the conceptual inquiry into the digital system’s learning ability shows the alive and changeable nature of the technological object itself. (shrink)

That the successful development of fully autonomous artificial moral agents (AMAs) is imminent is becoming the received view within artificial intelligence research and robotics. The discipline of Machines Ethics, whose mandate is to create such ethical robots, is consequently gaining momentum. Although it is often asked whether a given moral framework can be implemented into machines, it is never asked whether it should be. This paper articulates a pressing challenge for Machine Ethics: To identify an ethical framework that is both (...) implementable into machines and whose tenets permit the creation of such AMAs in the first place. Without consistency between ethics and engineering, the resulting AMAs would not be genuine ethical robots, and hence the discipline of Machine Ethics would be a failure in this regard. Here this challenge is articulated through a critical analysis of the development of Kantian AMAs, as one of the leading contenders for being the ethic that can be implemented into machines. In the end, however, the development of Kantian artificial moral machines is found to be anti-Kantian. The upshot of all this is that machine ethicists need to look elsewhere for an ethic to implement into their machines. (shrink)

For an artificial agent to be morally praiseworthy, its rules for behaviour and the mechanisms for supplying those rules must not be supplied entirely by external humans. Such systems are a substantial departure from current technologies and theory, and are a low prospect. With foreseeable technologies, an artificial agent will carry zero responsibility for its behavior and humans will retain full responsibility.

Philosophers of information, according to Luciano Floridi (The philosophy of information. Oxford University Press, Oxford, 2010, p 32), study how information should be “adequately created, processed, managed, and used.” A small number of epistemologists have employed the concept of information as a cornerstone of their theoretical framework. How this concept can be used to make sense of seemingly intractable epistemological problems, however, has not been widely explored. This paper examines Fred Dretske’s information-based epistemology, in particular his response to radical epistemological (...) skepticism. We discuss the relationship between information, evidence and knowledge in relation to the problem of skepticism and the options available to an information-based epistemology for dealing with it. (shrink)

This paper tries to understand the phenomenon that humans are able to empathize with robots and the intuition that there might be something wrong with “abusing” robots by discussing the question regarding the moral standing of robots. After a review of some relevant work in empirical psychology and a discussion of the ethics of empathizing with robots, a philosophical argument concerning the moral standing of robots is made that questions distant and uncritical moral reasoning about entities’ properties and that recommends (...) first trying to understand the issue by means of philosophical and artistic work that shows how ethics is always relational and historical, and that highlights the importance of language and appearance in moral reasoning and moral psychology. It is concluded that attention to relationality and to verbal and non-verbal languages of suffering is key to understand the phenomenon under investigation, and that in robot ethics we need less certainty and more caution and patience when it comes to thinking about moral standing. (shrink)

With Artificial Intelligence entering our lives in novel ways—both known and unknown to us—there is both the enhancement of existing ethical issues associated with AI as well as the rise of new ethical issues. There is much focus on opening up the ‘black box’ of modern machine-learning algorithms to understand the reasoning behind their decisions—especially morally salient decisions. However, some applications of AI which are no doubt beneficial to society rely upon these black boxes. Rather than requiring algorithms to be (...) transparent we should focus on constraining AI and those machines powered by AI within microenvironments—both physical and virtual—which allow these machines to realize their function whilst preventing harm to humans. In the field of robotics this is called ‘envelopment’. However, to put an ‘envelope’ around AI-powered machines we need to know some basic things about them which we are often in the dark about. The properties we need to know are the: training data, inputs, functions, outputs, and boundaries. This knowledge is a necessary first step towards the envelopment of AI-powered machines. It is only with this knowledge that we can responsibly regulate, use, and live in a world populated by these machines. (shrink)

Determining the agency-status of machines and AI has never been more pressing. As we progress into a future where humans and machines more closely co-exist, understanding hallmark features of agency affords us the ability to develop policy and narratives which cater to both humans and machines. This paper maintains that decision-making processes largely underpin agential action, and that in most instances, these processes yield good results in terms of making good choices. However, in some instances, when faced with two (or (...) more) choices, an agent may find themselves with equal reasons to choose either - thus being presented with a tie. This paper argues that in the event of a tie, the ability to create a voluntarist reason is a hallmark feature of agency, and second, that AI, through current tie-breaking mechanisms does not have this ability, and thus fails at this particular feature of agency. (shrink)

Contemporary medical diagnostics has a dynamic moral landscape, which includes a variety of agents, factors, and components. A significant part of this landscape is composed of information technologies that play a vital role in doctors’ decision-making. This paper focuses on the so-called Intelligent Decision-Support System that is widely implemented in the domain of contemporary medical diagnosis. The purpose of this article is twofold. First, I will show that the IDSS may be considered a moral agent in the practice of medicine (...) today. To develop this idea I will introduce the approach to artificial agency provided by Luciano Floridi. Simultaneously, I will situate this approach in the context of contemporary discussions regarding the nature of artificial agency. It is argued here that the IDSS possesses a specific sort of agency, includes several agent features (e.g. autonomy, interactivity, adaptability), and hence, performs an autonomous behavior, which may have a substantial moral impact on the patient’s well-being. It follows that, through the technology of artificial neural networks combined with ‘deep learning’ mechanisms, the IDSS tool achieves a specific sort of independence (autonomy) and may possess a certain type of moral agency. Second, I will provide a conceptual framework for the ethical evaluation of the moral impact that the IDSS may have on the doctor’s decision-making and, consequently, on the patient’s wellbeing. This framework is the Object-Oriented Model of Moral Action developed by Luciano Floridi. Although this model appears in many contemporary discussions in the field of information and computer ethics, it has not yet been applied to the medical domain. This paper addresses this gap and seeks to reveal the hidden potentialities of the OOP model for the field of medical diagnosis. (shrink)

The growing prominence of computers in contemporary life, often seemingly with minds of their own, invites rethinking the question of moral responsibility. If the moral responsibility for an act lies with the subject that carried it out, it follows that different concepts of the subject generate different views of moral responsibility. Some recent theorists have argued that actions are produced by composite, fluid subjects understood as extended agencies (cyborgs, actor networks). This view of the subject contrasts with methodological individualism: the (...) idea that actions are produced only by human individuals. This essay compares two views of responsibility: moral individualism (the ethical twin of methodological individualism), and joint responsibility (associated with extended agency theory). It develops a view of what joint responsibility might look like, and considers the advantages it might bring relative to moral individualism as well as the objections that are sure to be raised against it. (shrink)

Among ethicists and engineers within robotics there is an ongoing discussion as to whether ethical robots are possible or even desirable. We answer both of these questions in the positive, based on an extensive literature study of existing arguments. Our contribution consists in bringing together and reinterpreting pieces of information from a variety of sources. One of the conclusions drawn is that artifactual morality must come in degrees and depend on the level of agency, autonomy and intelligence of the machine. (...) Moral concerns for agents such as intelligent search machines are relatively simple, while highly intelligent and autonomous artifacts with significant impact and complex modes of agency must be equipped with more advanced ethical capabilities. Systems like cognitive robots are being developed that are expected to become part of our everyday lives in future decades. Thus, it is necessary to ensure that their behaviour is adequate. In an analogy with artificial intelligence, which is the ability of a machine to perform activities that would require intelligence in humans, artificial morality is considered to be the ability of a machine to perform activities that would require morality in humans. The capacity for artificial (artifactual) morality, such as artifactual agency, artifactual responsibility, artificial intentions, artificial (synthetic) emotions, etc., come in varying degrees and depend on the type of agent. As an illustration, we address the assurance of safety in modern High Reliability Organizations through responsibility distribution. In the same way that the concept of agency is generalized in the case of artificial agents, the concept of moral agency, including responsibility, is generalized too. We propose to look at artificial moral agents as having functional responsibilities within a network of distributed responsibilities in a socio-technological system. This does not take away the responsibilities of the other stakeholders in the system, but facilitates an understanding and regulation of such networks. It should be pointed out that the process of development must assume an evolutionary form with a number of iterations because the emergent properties of artifacts must be tested in real world situations with agents of increasing intelligence and moral competence. We see this paper as a contribution to the macro-level Requirement Engineering through discussion and analysis of general requirements for design of ethical robots. (shrink)

As artificial intelligence (AI) continues to proliferate into every area of modern life, there is no doubt that society has to think deeply about the potential impact, whether negative or positive, that it will have. Whilst scholars recognise that AI can usher in a new era of personal, social and economic prosperity, they also warn of the potential for it to be misused towards the detriment of society. Deliberate strategies are therefore required to ensure that AI can be safely integrated (...) into society in a manner that would maximise the good for as many people as possible, whilst minimising the bad. One of the most urgent societal expectations of artificial agents is the need for them to behave in a manner that is morally relevant, i.e. to become artificial moral agents (AMAs). In this article, I will argue that exemplarism, an ethical theory based on virtue ethics, can be employed in the building of computationally rational AMAs with weak machine ethics. I further argue that three features of exemplarism, namely grounding in moral exemplars, meeting community expectations and practical simplicity, are crucial to its uniqueness and suitability for application in building AMAs that fit the ethos of AI4SG. (shrink)

Intelligent algorithms together with various machine learning techniques hold a dominant position among major challenges for contemporary value sensitive design. Self-learning capabilities of current AI applications blur the causal link between programmer and computer behavior. This creates a vital challenge for the design, development and implementation of digital technologies nowadays. This paper seeks to provide an account of this challenge. The main question that shapes the current analysis is the following: What conceptual tools can be developed within the value sensitive (...) design school of thought for evaluating machine learning algorithms where the causal relation between designers and the behavior of their computer systems has been eroded? The answer to this question will be provided through two levels of investigation within the value sensitive design methodology. The first level is conceptual. Within the conceptual level, we will introduce the notion of computer intentionality and will show how this term may be used for solving an issue of non-causal relation between designer and computer system. The second level of investigation is technical. At this level the emphasis will be given to machine learning algorithms. (shrink)

Can computer systems ever be considered moral agents? This paper considers two factors that are explored in the recent philosophical literature. First, there are the important domains in which computers are allowed to act, made possible by their greater functional capacities. Second, there is the claim that these functional capacities appear to embody relevant human abilities, such as autonomy and responsibility. I argue that neither the first (Domain-Function) factor nor the second (Simulacrum) factor gets at the central issue in the (...) case for computer moral agency: whether they can have the kinds of intentional states that cause their decisions and actions. I give an account that builds on traditional action theory and allows us to conceive of computers as genuine moral agents in virtue of their own causally efficacious intentional states. These states can cause harm or benefit to moral patients, but do not depend on computer consciousness or intelligence. (shrink)

There has been much debate whether computers can be responsible. This question is usually discussed in terms of personhood and personal characteristics, which a computer may or may not possess. If a computer fulfils the conditions required for agency or personhood, then it can be responsible; otherwise not. This paper suggests a different approach. An analysis of the concept of responsibility shows that it is a social construct of ascription which is only viable in certain social contexts and which serves (...) particular social aims. If this is the main aspect of responsibility then the question whether computers can be responsible no longer hinges on the difficult problem of agency but on the possibly simpler question whether responsibility ascriptions to computers can fulfil social goals. The suggested solution to the question whether computers can be subjects of responsibility is the introduction of a new concept, called “quasi-responsibility” which will emphasise the social aim of responsibility ascription and which can be applied to computers. (shrink)

The UK Government’s Code of Conduct for data-driven health and care technologies, specifically artificial intelligence -driven technologies, comprises 10 principles that outline a gold-standard of ethical conduct for AI developers and implementers within the National Health Service. Considering the importance of trust in medicine, in this essay I aim to evaluate the conceptualisation of trust within this piece of ethical governance. I examine the Code of Conduct, specifically Principle 7, and extract two positions: a principle of rationally justified trust that (...) posits trust should be made on sound epistemological bases and a principle of value-based trust that views trust in an all-things-considered manner. I argue rationally justified trust is largely infeasible in trusting AI due to AI’s complexity and inexplicability. Contrarily, I show how value-based trust is more feasible as it is intuitively used by individuals. Furthermore, it better complies with Principle 1. I therefore conclude this essay by suggesting the Code of Conduct to hold the principle of value-based trust more explicitly. (shrink)

Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more “explainable” by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, (...) or data-related issues, we focus on the very conceptual underpinnings of the design decisions made by developers and other stakeholders during the lifecycle of a machine learning project. For instance, the design and development of an app to track snoring to detect possible health risks presuppose some picture or another of “health”, which is a key notion that conceptually underpins the project. We take it as a premise that these key concepts are necessarily present during design and development, albeit perhaps tacitly. We argue that by providing “justificatory explanations” about how the team understands the relevant key concepts behind its design decisions, interested parties could gain valuable insights and make better sense of the workings and outcomes of systems. Using the concept of “health”, we illustrate how a particular understanding of it might influence decisions during the design and development stages of a machine learning project, and how making this explicit by incorporating it into ex-post explanations might increase the explanatory and justificatory power of these explanations. We posit that a greater conceptual awareness of the key concepts that underpin design and development decisions may be beneficial to any attempt to develop explainability methods. We recommend that “justificatory explanations” are provided as technical documentation. These are declarative statements that contain at its simplest: (1) a high-level account of the understanding of the relevant key concepts a team possess related to a project’s main domain, (2) how these understandings drive decision-making during the life-cycle stages, and (3) it gives reasons (which could be implicit in the account) that the person or persons doing the explanation consider to have plausible justificatory power for the decisions that were made during the project. (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)

Central to the ethical concerns raised by the prospect of increasingly autonomous military robots are issues of responsibility. In this paper we examine different conceptions of autonomy within the discourse on these robots to bring into focus what is at stake when it comes to the autonomous nature of military robots. We argue that due to the metaphorical use of the concept of autonomy, the autonomy of robots is often treated as a black box in discussions about autonomous military robots. (...) When the black box is opened up and we see how autonomy is understood and ‘made’ by those involved in the design and development of robots, the responsibility questions change significantly. (shrink)

In this paper, I will identify two problems of trust in an AI-relevant context: a theoretical problem and a practical one. I will identify and address a number of skeptical challenges to an AI-relevant theory of trust. In addition, I will identify what I shall term the ‘scope challenge’, which I take to hold for any AI-relevant theory of trust that purports to be representationally adequate to the multifarious forms of trust and AI. Thereafter, I will suggest how trust-engineering, a (...) position that is intermediate between the modified pure rational-choice account and an account that gives rise to trustworthy AI, might allow us to address the practical problem of trust, before identifying and critically evaluating two candidate trust-engineering approaches. (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)

The current research aims to answer the following question: “who will be held responsible for harm involving an artificial intelligence system?” Drawing upon the literature on moral judgments, we assert that when people perceive an AI system’s action as causing harm to others, they will assign blame to different entity groups involved in an AI’s life cycle, including the company, the developer team, and even the AI system itself, especially when such harm is perceived to be intentional. Drawing upon the (...) theory of mind perception, we hypothesized that two dimensions of mind: perceived agency—attributing intention, reasoning, pursuing goals, and communicating to AI, and perceived experience—attributing emotional states, such as feeling pain and pleasure, personality, and consciousness to AI—mediated the relationship between perceived intentional harm and blame judgments toward AI. We also predicted that people are likely to attribute higher mind characteristics to AI when harm is perceived to be directed to humans than when it is perceived to be directed to non-humans. We tested our research model in three experiments. In all experiments, we found that perceived intentional harm led to blame judgments toward AI. In two experiments, we found perceived experience, not agency, mediated the relationship between perceived intentional harm and blame judgments. We also found that companies and developers were held responsible for moral violations involving AI, with developers received the most blame among the entities involved. Our third experiment reconciles the findings by showing that perceived intentional harm directed to a non-human entity did not lead to increased attributions of mind to AI. These findings have implications for theory and practice concerning unethical outcomes and behavior associated with AI use. (shrink)

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

Are trust relationships involving humans and artificial agents possible? This controversial question has become a hotly debated topic in the emerging field of machine ethics. Employing a model of trust advanced by Buechner and Tavani :39–51, 2011), I argue that the “short answer” to this question is yes. However, I also argue that a more complete and nuanced answer will require us to articulate the various levels of trust that are also possible in environments comprising both human agents and AAs. (...) In defending this view, I show how James Moor’s model for distinguishing four levels of ethical agents in the context of machine ethics :18–21, 2006) can help us to develop a framework that differentiates four levels of trust. Via a series of hypothetical scenarios, I illustrate each level of trust involved in HA–AA relationships. Finally, I argue that these levels of trust reflect three key factors or variables: the level of autonomy of the individual AAs involved, the degree of risk/vulnerability on the part of the HAs who place their trust in the AAs, and the kind of interactions that occur between the HAs and AAs in the trust environments. (shrink)

The UK Government’s Code of Conduct for data-driven health and care technologies, specifically artificial intelligence -driven technologies, comprises 10 principles that outline a gold-standard of ethical conduct for AI developers and implementers within the National Health Service. Considering the importance of trust in medicine, in this essay I aim to evaluate the conceptualisation of trust within this piece of ethical governance. I examine the Code of Conduct, specifically Principle 7, and extract two positions: a principle of rationally justified trust that (...) posits trust should be made on sound epistemological bases and a principle of value-based trust that views trust in an all-things-considered manner. I argue rationally justified trust is largely infeasible in trusting AI due to AI’s complexity and inexplicability. Contrarily, I show how value-based trust is more feasible as it is intuitively used by individuals. Furthermore, it better complies with Principle 1. I therefore conclude this essay by suggesting the Code of Conduct to hold the principle of value-based trust more explicitly. (shrink)

Following the social conception of moral agency, this paper claims that many beings commonly exempted from moral responsibility, like young children, adults with late-stage dementia, and nonhuman animals, may nevertheless qualify as participants in moral responsibility practices. Blame and other moral responsibility responses are understood according to the communicative emotion account of the reactive attitudes. To blame someone means having an emotion episode that acts as a vehicle for conveying a particular moral content. Therefore, moral agency is argued to be (...) manifested in communicative exchanges between a claimant and a defendant. While many human and nonhuman agents are justifiably exempted from ascriptions of moral responsibility, this does not necessarily exclude such agents from the community of moral agents altogether. Toddlers and dogs, for instance, seem capable of other-directed reactive attitudes, like resentment, and could, therefore, qualify as participants in moral responsibility practices with respect to the claimant position. Therefore, we may have reason to adopt a distinct claimant-directed participant stance to some beings, even if they fail to qualify as apt targets of blame. This expanded theoretical room for moral agency is argued to make explicit further normative considerations. (shrink)

In this article, a concise argument for computational rationality as a basis for artificial moral agency is advanced. Some ethicists have long argued that rational agents can become artificial moral agents. However, most of their views have come from purely philosophical perspectives, thus making it difficult to transfer their arguments to a scientific and analytical frame of reference. The result has been a disintegrated approach to the conceptualisation and design of artificial moral agents. In this article, I make the argument (...) for computational rationality as an integrative element that effectively combines the philosophical and computational aspects of artificial moral agency. This logically leads to a philosophically coherent and scientifically consistent model for building artificial moral agents. Besides providing a possible answer to the question of how to build artificial moral agents, this model also invites sound debate from multiple disciplines, which should help to advance the field of machine ethics forward. (shrink)

A traditional problem of ethics in mathematics is the denial of social responsibility. Pure mathematics is viewed as neutral and value free, and therefore free of ethical responsibility. Applications of mathematics are seen as employing a neutral set of tools which, of themselves, are free from social responsibility. However, mathematicians are convinced they know what constitutes good mathematics. Furthermore many pure mathematicians are committed to purism, the ideology that values purity above applications in mathematics, and some historical reasons for this (...) are discussed. MacIntyre’s virtue ethics accommodates both the good mathematician and the ethics of the social practice of mathematics. It demonstrates that purism is compatible with acknowledging the social responsibility of mathematics. Four aspects of this responsibility are mentioned, two concerning the impact of mathematics via education, and two concerning explicit and implicit applications of mathematics. The last of these opens up the performativity of mathematical and measurement applications in society, which change the very processes they are supposed to measure. Although these applications are not explored in detail, they illustrate the importance of considering the ethics and social responsibility of mathematics in society. MacIntyre’s virtue theory opens a broad approach to the controversial topic of the ethics of mathematics encompassing purism, and absolutist and social constructivist philosophies of mathematics, but still enabling ethical critiques of the impact of mathematics on society. (shrink)

Despite resistance from various societal actors, the development and deployment of lethal autonomous weaponry to warzones is perhaps likely, considering the perceived operational and ethical advantage such weapons are purported to bring. In this paper, it is argued that the deployment of truly autonomous weaponry presents an ethical danger by calling into question the ability of such weapons to abide by the Laws of War. This is done by noting the resonances between battlefield target identification and the process of ontic-ontological (...) investigation detailed in Martin Heidegger’s Being and Time, before arguing that the nature of lethal autonomous weaponry precludes them from being able to engage in such investigations—a key requisite for abiding by the relevant legislation that governs battlefield conduct. (shrink)