The aim of this exploratory paper is to review an under-appreciated parallel between group agency and artificial intelligence. As both phenomena involve non-human goal-directed agents that can make a difference to the social world, they raise some similar moral and regulatory challenges, which require us to rethink some of our anthropocentric moral assumptions. Are humans always responsible for those entities’ actions, or could the entities bear responsibility themselves? Could the entities engage in normative reasoning? Could they even have rights and (...) a moral status? I will tentatively defend the (increasingly widely held) view that, under certain conditions, artificial intelligent systems, like corporate entities, might qualify as responsible moral agents and as holders of limited rights and legal personhood. I will further suggest that regulators should permit the use of autonomous artificial systems in high-stakes settings only if they are engineered to function as moral (not just intentional) agents and/or there is some liability-transfer arrangement in place. I will finally raise the possibility that if artificial systems ever became phenomenally conscious, there might be a case for extending a stronger moral status to them, but argue that, as of now, this remains very hypothetical. (shrink)

Some authors have recently suggested that it is time to consider rights for robots. These suggestions are based on the claim that the question of robot rights should not depend on a standard set of conditions for ‘moral status’; but instead, the question is to be framed in a new way, by rejecting the is/ought distinction, making a relational turn, or assuming a methodological behaviourism. We try to clarify these suggestions and to show their highly problematic consequences. While we find (...) the suggestions ultimately unmotivated, the discussion shows that our epistemic condition with respect to the moral status of others does raise problems, and that the human tendency to empathise with things that do not have moral status should be taken seriously—we suggest that it produces a “derived moral status”. Finally, it turns out that there is typically no individual in real AI that could even be said to be the bearer of moral status. Overall, there is no reason to think that robot rights are an issue now. (shrink)

Most people who have considered the matter have concluded that machines cannot be moral agents. Responsibility for acting on the outputs of machines must always rest with a human being. A key problem for the ethical use of AI, then, is to ensure that it does not block the attribution of responsibility to humans or lead to individuals being unfairly held responsible for things over which they had no control. This is the “responsibility gap”. In this paper, we argue that (...) the claim that machines cannot be held responsible for their actions has unacknowledged implications for the conditions under which the outputs of AI can serve as reasons for belief. Following Robert Brandom, we argue that, because the assertion of a claim is an action, moral agency is a necessary condition for the giving and evaluating of reasons in discourse. Thus, the same considerations that suggest that machines cannot be held responsible for their actions suggest that they cannot be held to account for the epistemic value — or lack of value — of their outputs. If there is a responsibility gap, there is also a “testimony gap.” An under-recognised problem with the use of AI, then, is to ensure that it does not block the attribution of testimony to human beings or lead to individuals being held responsible for claims that they have not asserted. More generally, the “assertions” of machines are only capable of serving as justifications for belief or action where one or more people accept responsibility for them. (shrink)

Artificial agents create significant moral opportunities and challenges. Over the last two decades, discourse has largely focused on the concept of a ‘responsibility gap.’ We argue that this concept is incoherent, misguided, and diverts attention from the core issue of ‘control gaps.’ Control gaps arise when there is a discrepancy between the causal control an agent exercises and the moral control it should possess or emulate. Such gaps present moral risks, often leading to harm or ethical violations. We propose a (...) second-order ‘duty of moral control’ that mandates closing these gaps to reduce risks within acceptable moral limits. Our analysis encompasses both autonomous machines and collective agents, acknowledging their similarities and key differences in constitution and moral status. We suggest four methods to close control gaps: ensuring artificial agents attain moral agency, providing meaningful human control, implementing safety engineering, and employing social control. These methods aim to responsibly integrate artificial agents into society. We conclude that a realistic approach, which addresses the practical problems posed by control gaps, is essential. This approach provides solutions to manage the risks posed by artificial agents while maintaining acceptable moral standards, ensuring we responsibly harness their potential and address the ethical challenges they present. (shrink)

The advent of intelligent artificial systems has sparked a dispute about the question of who is responsible when such a system causes a harmful outcome. This paper champions the idea that this dispute should be approached as a conceptual engineering problem. Towards this claim, the paper first argues that the dispute about the responsibility gap problem is in part a conceptual dispute about the content of responsibility and related concepts. The paper then argues that the way forward is to evaluate (...) the conceptual choices we have, in the light of a systematic understanding of why the concept is important in the first place—in short, the way forward is to engage in conceptual engineering. The paper then illustrates what approaching the responsibility gap problem as a conceptual engineering problem looks like. It outlines argumentative pathways out of the responsibility gap problem and relates these to existing contributions to the dispute. (shrink)

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)

AI systems, like self-driving cars, healthcare robots, or Autonomous Weapon Systems, already play an increasingly important role in our lives and will do so to an even greater extent in the near future. This raises a fundamental philosophical question: who is morally responsible when such systems cause unjustified harm? In the paper, we argue for the admittedly surprising claim that some of these systems can themselves be morally responsible for their conduct in an important and everyday sense of the term—the (...) attributability sense. More specifically, relying on work by Nomy Arpaly and Timothy Schroeder (In Praise of Desire, OUP 2014), we propose that the behavior of these systems can manifest their ‘quality of will’ and thus be regarded as something they can be blameworthy for. We develop this position in detail, justify some of its crucial presuppositions, and defend it against potential objections. (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)

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

Most accounts of responsibility focus on one type of responsibility, moral responsibility, or address one particular aspect of moral responsibility such as agency. This article outlines a broader framework to think about responsibility that includes causal responsibility, relational responsibility, and what I call “narrative responsibility” as a form of “hermeneutic responsibility”, connects these notions of responsibility with different kinds of knowledge, disciplines, and perspectives on human being, and shows how this framework is helpful for mapping and analysing how artificial intelligence (...) (AI) challenges human responsibility and sense-making in various ways. Mobilizing recent hermeneutic approaches to technology, the article argues that next to, and interwoven with, other types of responsibility such as moral responsibility, we also have narrative and hermeneutic responsibility—in general and for technology. For example, it is our task as humans to make sense of, with and, if necessary, against AI. While from a posthumanist point of view, technologies also contribute to sense-making, humans are the experiencers and bearers of responsibility and always remain in charge when it comes to this hermeneutic responsibility. Facing and working with a world of data, correlations, and probabilities, we are nevertheless condemned to make sense. Moreover, this also has a normative, sometimes even political aspect: acknowledging and embracing our hermeneutic responsibility is important if we want to avoid that our stories are written elsewhere—through technology. (shrink)

While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...) robot blame, namely the folk's willingness to ascribe inculpating mental states or "mens rea" to robots. In a vignette-based experiment (N=513), we presented participants with a situation in which an agent knowingly runs the risk of bringing about substantial harm. We manipulated agent type (human v. group agent v. AI-driven robot) and outcome (neutral v. bad), and measured both moral judgment (wrongness of the action and blameworthiness of the agent) and mental states attributed to the agent (recklessness and the desire to inflict harm). We found that (i) judgments of wrongness and blame were relatively similar across agent types, possibly because (ii) attributions of mental states were, as suspected, similar across agent types. This raised the question - also explored in the experiment - whether people attribute knowledge and desire to robots in a merely metaphorical way (e.g., the robot "knew" rather than really knew). However, (iii), according to our data people were unwilling to downgrade to mens rea in a merely metaphorical sense when given the chance. Finally, (iv), we report a surprising and novel finding, which we call the inverse outcome effect on robot blame: People were less willing to blame artificial agents for bad outcomes than for neutral outcomes. This suggests that they are implicitly aware of the dangers of overattributing blame to robots when harm comes to pass, such as inappropriately letting the responsible human agent off the moral hook. (shrink)

Philosophers increasingly argue that collective agents can be blameworthy for wrongdoing. Advocates tend to endorse functionalism, on which collectives are analogous to complicated robots. This is puzzling: we don’t hold robots blameworthy. I argue we don’t hold robots blameworthy because blameworthiness presupposes the capacity for a mental state I call ‘moral self-awareness’. This raises a new problem for collective blameworthiness: collectives seem to lack the capacity for moral self-awareness. I solve the problem by giving an account of how collectives have (...) this capacity. The trick is to take seriously individuals’ status as flesh-and-blood material constituents of collectives. The idea will be: under certain conditions that I specify, an individual can be the locus of a collective's moral self-awareness. The account provides general insights concerning collectives’ dependence on members, the boundaries of membership, and the locus of collectives’ phenomenology. (shrink)

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

Most accounts of responsibility focus on one type of responsibility, moral responsibility, or address one particular aspect of moral responsibility such as agency. This article outlines a broader framework to think about responsibility that includes causal responsibility, relational responsibility, and what I call “narrative responsibility” as a form of “hermeneutic responsibility”, connects these notions of responsibility with different kinds of knowledge, disciplines, and perspectives on human being, and shows how this framework is helpful for mapping and analysing how artificial intelligence (...) (AI) challenges human responsibility and sense-making in various ways. Mobilizing recent hermeneutic approaches to technology, the article argues that next to, and interwoven with, other types of responsibility such as moral responsibility, we also have narrative and hermeneutic responsibility—in general and for technology. For example, it is our task as humans to make sense of, with and, if necessary, against AI. While from a posthumanist point of view, technologies also contribute to sense-making, humans are the experiencers and bearers of responsibility and always remain in charge when it comes to this hermeneutic responsibility. Facing and working with a world of data, correlations, and probabilities, we are nevertheless condemned to make sense. Moreover, this also has a normative, sometimes even political aspect: acknowledging and embracing our hermeneutic responsibility is important if we want to avoid that our stories are written elsewhere—through technology. (shrink)

In the social epistemology of scientific knowledge, it is largely accepted that relationships of trust, not just reliance, are necessary in contemporary collaborative science characterised by relationships of opaque epistemic dependence. Such relationships of trust are taken to be possible only between agents who can be held accountable for their actions. But today, knowledge production in many fields makes use of AI applications that are epistemically opaque in an essential manner. This creates a problem for the social epistemology of scientific (...) knowledge, as scientists are now epistemically dependent on AI applications that are not agents, and therefore not appropriate candidates for trust. (shrink)

Robots are becoming more visible parts of our life, a situation which prompts questions about their place in our society. One group of issues that is widely discussed is connected with robots’ moral and legal status as well as their potential rights. The question of granting robots rights is polarizing. Some positions accept the possibility of granting them human rights whereas others reject the notion that robots can be considered potential rights holders. In this paper, I claim that robots will (...) never have all human rights, even if we accept that they are morally equal to humans. I focus on the role of embodiment in the content of the law. I claim that even relatively small differences in the ontologies of entities could lead to the need to create new sets of rights. I use the example of Neanderthals to illustrate that entities similar to us might have required different legal statuses. Then, I discuss the potential legal status of human-like robots. (shrink)

It is an increasingly popular view among philosophers that moral responsibility can, in principle, be attributed to unconscious autonomous agents. This trend is already remarkable in itself, but it is even more interesting that most proponents of this view provide more or less the same argument to support their position. I argue that as it stands, the Extension Argument, as I call it, is not sufficient to establish the thesis that unconscious autonomous agents can be morally responsible. I attempt to (...) show that the Extension Argument should overcome especially strong ethical considerations; moreover, its epistemological grounds are not too solid, partly because the justifications of its premises are in conflict. (shrink)

Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented programme typical to current scholarship that often views technology in instrumental terms. With this in mind, I problematise the concept of a technological subjectivity through an exploration of various aspects of ChatGPT in light of Foucault’s work, arguing that current systems lack (...) the reflexivity and self-formative characteristics inherent in the notion of the subject. By drawing upon a recent dialogue between Foucault and phenomenology, I suggest four techno-philosophical desiderata that would address the gaps in this search for a technological subjectivity: embodied self-care, embodied intentionality, imagination and reflexivity. Thus I propose that advanced AI be reconceptualised as a subject capable of “technical” self-crafting and reflexive self-conduct, opening new pathways to grasp the intertwinement of the human and the artificial. This reconceptualization holds the potential to render future AI technology more transparent and responsible in the circulation of knowledge, care and power. (shrink)

In this paper I argue, contrary to recent literature, that it is unethical to create artificial agents possessing human-level intelligence that are programmed to be human beings’ obedient servants. In developing the argument, I concede that there are possible scenarios in which building such artificial servants is, on net, beneficial. I also concede that, on some conceptions of autonomy, it is possible to build human-level AI servants that will enjoy full-blown autonomy. Nonetheless, the main thrust of my argument is that, (...) in building such artificial agents, their creators cannot help but evince an objectionable attitude akin to the Aristotelian vice of manipulativeness. (shrink)

In this paper, we ask how ‘cognitive extenders’, based on AI technology, affect their users’ status as moral agents and the moral evaluation of their actions. We study how ‘AI-extenders’ can either enhance or diminish their users’ moral agency. On the one hand, they can broaden the scope of agential features and on the other hand, they can undermine the agent’s autonomy and lead to decreased responsibility. Our focus is on moral agency and responsibility of the AI-extended human being as (...) a hybrid, coupled system. Assuming standard conditions for responsible agency, we will look at specific cases where the extender would make a difference to the agent’s moral status. The thought-experimental extenders we are dealing with are enabled by already existing technologies. The obvious motivation behind the exercise is that these devices might be useful for people suffering from psychiatric conditions complicating the expression of their moral agency. We analyze the moral status of AI-extended agents as coupled systems and argue that the functioning of an AI-extender can make a difference to an agent’s fitness to be held morally responsible. This should be considered in the responsible design and development of AI-extenders. (shrink)

Despite the moral underpinnings of Karl Popper’s philosophy, he has not presented a well-established moral theory for critical rationalism (CR). This paper addresses the ontological status of _moral agents_ as part of a research program for developing a moral theory for CR. It argues that moral agents are _selves_ who have achieved the cognitive capacity of _personhood_ through an evolutionary scenario and interaction with the environment. This proposal draws on Popper’s theory of the self and his theory of three worlds, (...) which offer both epistemological and ontological insights into the emergence and evolution of _moral agents_. The paper also discusses some of the consequences of this proposal for the _objectivity_ and _criticizability_ of moral judgments and the moral agency of artificial intelligence. It concludes by suggesting some directions for future research on the epistemological and ontological problems of ethics in CR. (shrink)

Would a political system where the governance was overseen by an algorithmic system be legitimate? The intuitive answer seems to be no. This paper considers the philosophical effort to justify this intuition that argue for algocracy, a rule by algorithms, being illegitimate. Taking as the paradigmatic example the anti-algocratic argument from Danaher that attempts to ground algocratic illegitimacy in the opacity of algocratic decision-making, it is argued that the argument oversimplfies the matters. Opacity can delegitimise—but not simpliciter. It delegitimises because (...) of the presence of certain downstream violations of obligations and rights of the public that result from the opaque governance. Algocratic decision-makers, however, seem not to be subjects to these normative constraints in the relevant sense. The paper therefore argues that the standards of legitimacy that have been deployed for or against different kinds of human governance do not apply to the algorithmic decision-making systems with quite the same force. New avenues for rooting the illegitimacy of algocratic decision-makers have to be developed. (shrink)

In this paper, I will argue that the responsibility gap arising from new AI systems is reducible to the problem of many hands and collective agency. Systematic analysis of the agential dimension of AI will lead me to outline a disjunctive between the two problems. Either we reduce individual responsibility gaps to the many hands, or we abandon the individual dimension and accept the possibility of responsible collective agencies. Depending on which conception of AI agency we begin with, the responsibility (...) gap will boil down to one of these two moral problems. Moreover, I will adduce that this conclusion reveals an underlying weakness in AI ethics: the lack of attention to the question of the disciplinary boundaries of AI ethics. This absence has made it difficult to identify the specifics of the responsibility gap arising from new AI systems as compared to the responsibility gaps of other applied ethics. Lastly, I will be concerned with outlining these specific aspects. (shrink)

As biological organisms, we age and, eventually, die. However, age’s deteriorating effects may not be universal. Some theoretical entities, due to their synthetic composition, could exist independently from aging—artificial general intelligence (AGI). With adequate resource access, an AGI could theoretically be ageless and would be, in some sense, immortal. Yet, this need not be inevitable. Designers could imbue AGIs with artificial mortality via an internal shut-off point. The question, though, is, should they? Should researchers curtail an AGI’s potentially endless lifespan (...) by deliberately making it mortal? It is this question that this article explores. First, it considers what type of AGI is under discussion before outlining how such beings could be ageless. Then, after clarifying the type of immortality under discussion and arguing that imbuing an AGI with synthetic aging would be person-affecting, the article explores four core conundrums: (i) deliberately causing a morally significant being’s death; (ii) immortality’s associated harms; (iii) concerns about immortality’s unequal assignment; and (iv) the danger of immortal AGI overlords. The article concludes that while prudence requires we create an aging AGI, in the face of the material harm such an action would constitute, this is an insufficient reason to justify doing so. (shrink)

The aim of this chapter is to explore the safety value of implementing Asimov’s Laws of Robotics as a future general framework that humans should obey. Asimov formulated laws to make explicit the safeguards of the robots in his stories: (1) A robot may not injure or harm a human being or, through inaction, allow a human being to come to harm; (2) A robot must obey the orders given to it by human beings except where such orders would conflict (...) with the First Law; (3) A robot must protect its own existence as long as such protection does not conflict with the First or Second Law. In Asimov’s stories, it is always assumed that the laws are built into the robots to govern the behaviour of the robots. As his stories clearly demonstrate, the Laws can be ambiguous. Moreover, the laws are not very specific. General rules as a guide for robot behaviour may not be a very good method to achieve robot safety – if we expect the robots to follow them. But would it work for humans? In this chapter, we ask whether it would make as much, or more, sense to implement the laws in human legislation with the purpose of governing the behaviour of people or companies that develop, build, market or use AI, embodied in robots or in the form of software, now and in the future. (shrink)

Raul Hakli & Pekka Mäkelä (2016, 2019) make a popular assumption in machine ethics explicit by arguing that artificial agents cannot be responsible because they are designed. Designed agents, they think, are analogous to manipulated humans and therefore not meaningfully in control of their actions. Contrary to this, I argue that under all mainstream theories of responsibility, designed agents can be responsible. To do so, I identify the closest parallel discussion in the literature on responsibility and free will, which concerns (...) ‘design cases’. Design cases are theoretical examples of agents that appear to lack responsibility because they were designed, philosophers use these cases to explore the relationship between design and responsibility. This paper presents several replies to design cases from the responsibility literature and uses those replies to situate the corresponding positions on the design and responsibility of artificial agents in machine ethics. I argue that each reply can support the design of responsible agents. However, each reply also entails different levels of severity in the constraints for the design of responsible agents. I offer a brief discussion of the nature of those constraints, highlighting the challenges respective to each reply. I conclude that designing responsible agents is possible, with the caveat that the difficulty of doing so will vary according to one’s favoured reply to design cases. (shrink)

The advent of ChatGPT, and the subsequent rapid improvement in the performance of what has become known as Generative AI, has led to many pundits declaring that AI will revolutionize education, as well as work, in the future. In this paper, we argue that enthusiasm for the use of AI in tertiary education is misplaced. A proper understanding of the nature of the outputs of AI suggests that it would be profoundly misguided to replace human teachers with AI, while the (...) history of automation in other settings suggests that it is naïve to think that AI can be developed to assist human teachers without replacing them. The dream that AI could teach students effectively neglects the importance of ‘learning how’ in order to ‘learn that’, that teachers are also role models, and the social nature of education. To the extent that students need to learn how to use AI, they should do so in specialized study skills units. Rather than creating a market for dodgy educational AI by lowering their ambitions about what they can offer, universities should invest in smaller class sizes and teachers who are passionate about their disciplines. To flourish in the future, just as much as they do today, societies will need people who have learned to think and not—or not just—intelligent machines. (shrink)

Artificial Intelligence (AI) Agents are often compared to psychopaths in popular news articles. The headlines are ‘eye-catching’, but the questions of what this analogy means or why it matters are hardly answered. The aim of this paper is to take this popular analogy ‘seriously’. By that, I mean two things. First, I aim to explore the scope of this analogy, i.e. to identify and analyse the shared properties of AI agents and psychopaths, namely, their lack of moral emotions and their (...) capacity for instrumental rationality. Second, I aim to examine the impact of the analogy. I argue that both agents, as ‘amoral calculators’, present the perfect candidates to revisit two long-standing debates on moral and criminal responsibility, regarding the necessity of moral emotions for ‘moral-agent-capacity responsibility’ and the necessity of ‘moral-agent-capacity responsibility’ for criminal responsibility. Finally, cross-examining the debates on the moral and criminal responsibility of psychopaths and AI agents is instructive and revealing. Instructive since the moral and legal treatment of psychopaths can be telling about the future treatment of AI agents (and vice versa) and revealing since it makes explicit our often-implicit philosophical commitments on the criteria of moral agency and the overarching purpose of criminal law. (shrink)

According to some philosophers, if moral agency is understood in behaviourist terms, robots could become moral agents that are as good as or even better than humans. Given the behaviourist conception, it is natural to think that there is no interesting moral difference between robots and humans in terms of moral agency (call it the _equivalence thesis_). However, such moral differences exist: based on Strawson’s account of participant reactive attitude and Scanlon’s relational account of blame, I argue that a distinct (...) kind of reason available to humans—call it _human-relative reason_—is not available to robots. The difference in moral reason entails that sometimes an action is morally permissible for humans, but not for robots. Therefore, when developing moral robots, we cannot consider only what humans can or cannot do. I use examples of paternalism to illustrate my argument. (shrink)

This extended abstract summarises some of the basic points of AI ethics and policy as they present themselves now. We explain the notion of AI, the main ethical issues in AI and the main policy aims and means.

Jotta olisimme moraalisesti vastuussa teoistamme, meidän on kyettävä muodostamaan käsityksiä oikeasta ja väärästä ja toimimaan ainakin jossain määrin niiden mukaisesti. Jos olemme täysivaltaisia moraalitoimijoita, myös ymmärrämme miksi jotkin teot ovat väärin, ja kykenemme siten joustavasti mukauttamaan toimintaamme eri tilanteisiin. Esitän, ettei näköpiirissä ole tekoälyjärjestelmiä, jotka kykenisivät aidosti välittämään oikein tekemisestä tai ymmärtämään moraalin vaatimuksia, koska nämä kyvyt vaativat kokemustietoisuutta ja kokonaisvaltaista arvostelukykyä. Emme siten voi sysätä koneille vastuuta teoistaan. Meidän on sen sijaan pyrittävä rakentamaan keinotekoisia oikeintekijöitä - järjestelmiä, jotka eivät (...) ole moraalitoimijoita, mutta kuitenkin toimivat likipitäen siten kuin me itse parhaimmillamme tekisimme. (shrink)

The aim of this paper is to better qualify the problem of online trust. The problem of online trust is that of evaluating whether online environments have the proper design to enable trust. This paper tries to better qualify this problem by showing that there is no unique answer, but only conditional considerations that depend on the conception of trust assumed and the features that are included in the environments themselves. In fact, the major issue concerning traditional debates surrounding online (...) trust is that those debates focus on specific definitions of trust and specific online environments. Ordinarily, a definition of trust is assumed and then environmental conditions necessary for trust are evaluated with respect to such specific definition. However, this _modus operandi_ fails to appreciate that trust is a rich concept, with a multitude of meanings and that there is still no strict consensus on which meaning shall be taken as the proper one. Moreover, the fact that online environments are constantly evolving and that new design features might be implemented in them is completely ignored. In this paper, the richness of the philosophical discussions about trust is brought into the analysis of online trust. I first provide a set of conditions that depend on the definition of trust that can be assumed and then discuss those conditions with respect to the design of online environments in order to determine whether they can enable (and under which circumstances) trust. (shrink)

Can nonhuman animals and artificial intelligence (AI) entities be attributed moral agency? The general assumption in the philosophical literature is that moral agency applies exclusively to humans since they alone possess free will or capacities required for deliberate reflection. Consequently, only humans have been taken to be eligible for ascriptions of moral responsibility in terms of, for instance, blame or praise, moral criticism, or attributions of vice and virtue. Animals and machines may cause harm, but they cannot be appropriately ascribed (...) moral responsibility for their behavior. This thesis challenges the conventional paradigm by proposing an alternative approach where moral agency is conceived as the competence to participate in moral responsibility practices. By shifting focus from intra-individual to contextual and socially situated features, this practice-focused approach appears to make the attribution of moral agency to nonhuman animals and AI entities more plausible than commonly assumed. Moreover, considering the current and potential future prevalence of nonhuman animals and AI entities in everyday settings and social contexts, a potential extension of moral agency to such entities could very well transform our social, moral, and legal practices. Hence, this thesis proposes that the attribution or withholding of moral agency to different entities should be carefully evaluated, considering the potential normative implications. (shrink)

Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented programme typical to current scholarship that often views technology in instrumental terms. With this in mind, I problematise the concept of a technological subjectivity through an exploration of various aspects of ChatGPT in light of Foucault’s work, arguing that current systems lack (...) the reflexivity and self-formative characteristics inherent in the notion of the subject. By drawing upon a recent dialogue between Foucault and phenomenology, I suggest four techno-philosophical desiderata that would address the gaps in this search for a technological subjectivity: embodied self-care, embodied intentionality, imagination and reflexivity. Thus I propose that advanced AI be reconceptualised as a subject capable of “technical” self-crafting and reflexive self-conduct, opening new pathways to grasp the intertwinement of the human and the artificial. This reconceptualisation holds the potential to render future AI technology more transparent and responsible in the circulation of knowledge, care and power. (shrink)

I develop an account of the nature of improvisation, as a distinctive form of temporally extended agency. In contrast to the standard view, which says that agents perform extended actions by means of planning them in advance, I argue that improvising involves planning one’s actions contemporaneously with their performance, or equivalently, planning these actions after one has already begun performing them. >> Improvisation is psychologically distinctive because it involves the adoption of backward-looking intentions, or retroplans, which represent the actions that (...) an agent has already performed as to-have-been performed under new descriptions, in relation to how these actions constitute parts of the larger action into which they are subsequently improvisationally incorporated. >> Improvisation is metaphysically distinctive because it involves exercising a special kind of diachronic agential control over the temporally extended action that one is performing. By means of continuing to act, as guided by a holistic improvised plan with backward-looking components, one can genuinely incorporate one’s previously-performed actions into a larger temporal whole, and thereby retroactively determine that these actions were (intentionally) performed under new descriptions. This is possible because of the temporally emergent metaphysical nature of the action-types that are improvisable. >> Improvisation is normatively distinctive because it enables new possibilities for temporally extended action, such as flexibly responding to unpredictable information in the course of acting and the retainment of a distinctive kind of self-curiosity during action. The progressive temporal structure of improvisation also raises a number of distinctive deliberative constraints that can be fruitfully modelled in general terms. >> Finally, improvisation is existentially distinctive, in the sense that an agent’s entire life can be understood as one grand-scale improvisational performance, where they gain existential unity and responsibility for the entire shape and meaning of their life by means of the successful improvisation of a self-constituting project over the course of their existence. Applying the account of the nature of improvisation at the level of a whole human life enables us to improv(is)e on existing existentialist and narrativist treatments of meaningful unity in life, and also to give a novel, systematic account of a series of existential crises and challenges. (shrink)

Keskustelu tekoälyn soveltamiseen liittyvistä eettisistä ja poliittisista kysymyksistä käy juuri nyt kuumana. Emme halua tässä puheenvuorossa osallistua keskusteluun tarttumalla johonkin tiettyyn eettiseen ongelmaan. Sen sijaan pyrimme sanomaan jotain itsekeskustelusta ja sen vaikeudesta. Haluamme kiinnittää huomiota siihen, kuinka erilaiset ihmismielen ajattelutaipumukset ja virhepäätelmät voivat huomaamattamme vaikuttaa tapaamme hahmottaa ja ymmärtää tekoälyä ja siihen liittyviä eettisiä kysymyksiä. Kun ymmärrämme paremmin sen, kuinka hankalaa näiden kysymysten hahmottaminen arkisen mielemme kategorioilla oikein on, ja kun tunnistamme tästä syntyvät virhepäätelmät ja ajattelun vääristymät, kykenemme entistä korkeatasoisempaan (...) eettiseen arviointiin tekoälyyn liittyvissä kysymyksissä. Tarkoituksemme ei ole tarkastella loogisiavirhepäätelmiä, jotka rikkovat formaalin modus tollensin tai modus ponensin sääntöjä. Sen sijaan esittelemme empiirisiä tutkimustuloksia, jotka havainnollistavat ihmismielen taipumustatehdä systemaattisia virhearviointeja erilaisissa tilanteissa. (shrink)

In this paper, I add to the recent flurry of research concerning the moral patiency of artificial beings. Focusing on David Gunkel's adaptation of Levinas, I identify and argue that the Relationist's extrinsic case-by-case approach of ascribing artificial moral status fails on two accounts. Firstly, despite Gunkel's effort to avoid anthropocentrism, I argue that Relationism is, itself, anthropocentric in virtue of how its case-by-case approach is, necessarily, assessed from a human perspective. Secondly I, in light of interpreting Gunkel's Relationism as (...) a case-by-case approach, reiterate that it cannot give sufficient action guidance. (shrink)

This thesis aims to establish the possibility of, and a pathway to, artificial moral agents. Artificial moral agents are argued to be of value not just for their practical performance, but because they offer a non-human perspective that can be used to make human theories more objective. The thesis works to a definition of moral agency, arguing that moral agents need to be intentional, morally reasons-responsive, and autonomous, but not necessarily conscious. Then, applying this to artificial agents, it draws on (...) literature from moral epistemology and responsibility to argue that artificial agents normally fail to meet these criteria because they are not simultaneously morally reasons-responsive and autonomous. Following this, it argues that the most promising means of developing artificial moral agents is for artificial agents to evolve into moral agents. Even if not moral agents precisely, the evolutionary development suggested seems likely to produce autonomous artificial agents that respond to some moral reasons, which would still offer the desired non-human perspective. (shrink)

The aim of this chapter is to explore the safety value of implementing Asimov’s Laws of Robotics as a future general framework that humans should obey. Asimov formulated laws to make explicit the safeguards of the robots in his stories: (1) A robot may not injure or harm a human being or, through inaction, allow a human being to come to harm; (2) A robot must obey the orders given to it by human beings except where such orders would conflict (...) with the First Law; (3) A robot must protect its own existence as long as such protection does not conflict with the First or Second Law. In Asimov’s stories, it is always assumed that the laws are built into the robots to govern the behaviour of the robots. As his stories clearly demonstrate, the Laws can be ambiguous. Moreover, the laws are not very specific. General rules as a guide for robot behaviour may not be a very good method to achieve robot safety – if we expect the robots to follow them. But would it work for humans? In this chapter, we ask whether it would make as much, or more, sense to implement the laws in human legislation with the purpose of governing the behaviour of people or companies that develop, build, market or use AI, embodied in robots or in the form of software, now and in the future. (shrink)