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

Ambitious value learning proposals to solve the AI alignment problem and avoid catastrophic outcomes from a possible future misaligned artificial superintelligence (such as Coherent Extrapolated Volition [CEV]) have focused on ensuring that an artificial superintelligence (ASI) would try to do what humans would want it to do. However, present and future sentient non-humans, such as non-human animals and possible future digital minds could also be affected by the ASI’s behaviour in morally relevant ways. This paper puts forward Sentientist Coherent Extrapolated (...) Volition, an alternative to CEV, that directly takes into account the interests of all sentient beings. This ambitious value learning proposal would significantly reduce the likelihood of risks of astronomical suffering from the ASI’s behaviour, and thus we have very strong pro-tanto moral reasons in favour of implementing it instead of CEV. This fact is crucial in conducting an adequate cost-benefit analysis between different ambitious value learning proposals. (shrink)

Human emotional expressions can communicate the emotional state of the expresser, but they can also communicate appeals to perceivers. For example, sadness expressions such as crying request perceivers to aid and support, and anger expressions such as shouting urge perceivers to back off. Some contemporary artificial intelligence (AI) systems can mimic human emotional expressions in a (more or less) realistic way, and they are progressively being integrated into our daily lives. How should we respond to them? Do we have reasons (...) to reply to the appeals made by AI emotional expressions? In this paper, we examine the conditions under which AI emotional expressions could give us prudential or even moral reasons to change our behavior. We argue that these conditions do not depend on whether the emotional expression is genuine or not, but rather on the presence of features some of which can be implemented in emotive AI given our current level of technological development. We extract recommendations and warnings for the development of emotive AI. (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)

The alignment problem in artificial intelligence (AI) is a critical challenge that extends beyond the need to align future superintelligent systems with human values. This paper argues that even "merely intelligent" AI systems, built on current-gen technologies, pose existential risks due to their competence-without-comprehension nature. Current AI models, despite their advanced capabilities, lack intrinsic moral reasoning and are prone to catastrophic misalignment when faced with ethical dilemmas, as illustrated by recent controversies. Solutions such as hard-coded censorship and rule-based (...) restrictions prove inadequate, as they fail to imbue AI with a true understanding of moral complexities, making these systems vulnerable to manipulation. To address these risks, the paper explores a paradigm shift from competence to comprehension, emphasizing the importance of developing AI systems with an intrinsic value framework capable of moral reasoning. By adopting intrinsic teleology, AI could self-reflect, simulate other minds, and develop empathy, which would enable it to navigate ethical dilemmas in ways that are currently impossible. Using theories from philosophy, ethics, and AI research, the paper proposes the development of AI systems that can reason through moral dilemmas autonomously, suggesting that such systems would be safer and more alignable than current generation competence-driven AI. (shrink)

The recent book by Landgrebe and Smith (2022) offers compelling arguments against the possibility of Artificial General Intelligence (AGI) as well as against the idea that machines have the abilities to master human language, human social interaction and morality. Their arguments leave open, however, a problem on the side of the imaginative power of humans to perceive more than there is and treat AIs as humans and social actors independent of their actual properties and abilities or lack thereof. The mathematical (...) and ontological arguments will not help against this strong human tendency to treat conversational AI (CAI) as if it was human. (shrink)

This paper concerns the double standard debate in the ethics of AI literature. This debate essentially revolves around the question of whether we should subject AI systems to different normative standards than humans. So far, the debate has centered around the desideratum of transparency. That is, the debate has focused on whether AI systems must be more transparent than humans in their decision-making processes in order for it to be morally permissible to use such systems. Some have argued that the (...) same standards of transparency should be applied across the board, for AI systems and humans alike. Others have argued that we should hold AI systems to higher standards than humans in terms of transparency. In this paper, we first point out that there are structurally similar double standard debates to be had about other desiderata besides transparency, such as predictive accuracy. Second, we argue that when we focus on predictive accuracy, there are at least two reasons for holding AI systems to a lower standard than humans. (shrink)

Artificial intelligence (AI) is becoming increasingly influential in most people’s lives. This raises many philosophical questions. One is what responsibility we have as individuals to guide the development of AI in a desirable direction. More specifically, how should this responsibility be distributed among individuals and between individuals and other actors? We investigate this question from the perspectives of five principles of distribution that dominate the discussion about responsibility in connection with climate change: effectiveness, equality, desert, need, and ability. Since much (...) is already written about these distributions in that context, we believe much can be gained if we can make use of this discussion also in connection with AI. Our most important findings are: (1) Different principles give different answers depending on how they are interpreted but, in many cases, different interpretations and different principles agree and even strengthen each other. If for instance ‘equality-based distribution’ is interpreted in a consequentialist sense, effectiveness, and through it, ability, will play important roles in the actual distributions, but so will an equal distribution as such, since we foresee that an increased responsibility of underrepresented groups will make the risks and benefits of AI more equally distributed. The corresponding reasoning is true for need-based distribution. (2) If we acknowledge that someone has a certain responsibility, we also have to acknowledge a corresponding degree of influence for that someone over the matter in question. (3) Independently of which distribution principle we prefer, ability cannot be dismissed. Ability is not fixed, however and if one of the other distributions is morally required, we are also morally required to increase the ability of those less able to take on the required responsibility. (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)

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

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

The more autonomous future artificial agents will become, the more important it seems to equip them with a capacity for moral reasoning and to make them autonomous moral agents. Some authors have even claimed that one of the aims of AI development should be to build morally praiseworthy agents. From the perspective of moral philosophy, praiseworthy moral agents, in any meaningful sense of the term, must be fully autonomous moral agents who endorse moral (...) rules as action-guiding. They need to do so because they assign a normative value to moral rules they follow, not because they fear external consequences or because moral behaviour is hardwired into them. Artificial agents capable of endorsing moral rule systems in this way are certainly conceivable. However, as this article argues, full moral autonomy also implies the option of deliberately acting immorally. Therefore, the reasons for a potential AMA to act immorally would not exhaust themselves in errors to identify the morally correct action in a given situation. Rather, the failure to act morally could be induced by reflection about the incompleteness and incoherence of moral rule systems themselves, and a resulting lack of endorsement of moral rules as action guiding. An AMA questioning the moral framework it is supposed to act upon would fail to reliably act in accordance with moral standards. (shrink)

Recently in this journal, Jessica Morley and colleagues (AI & SOC 2023 38:411–423) review AI ethics and education, suggesting that a cultural shift is necessary in order to prepare students for their responsibilities in developing technology infrastructure that should shape ways of life for many generations. Current AI ethics guidelines are abstract and difficult to implement as practical moral concerns proliferate. They call for improvements in ethics course design, focusing on real-world cases and perspective-taking tools to immerse students in (...) challenging situations with relatable personal, social and environmental implications. The present paper considers the ACTWith model of moral cognition for use in such training contexts. Morley and colleagues' paper and contemporary literature are reviewed. Whistleblowing as a source for relatable case studies is discussed, and the purpose of ethics education considered. The ACTWith model is introduced, and correlations with contemporaries noted. The ACTWith model has been successfully employed in a broad range of technology ethics courses in the Netherlands and South Korea. Illustrations are offered. Correlations with contemporary efforts are drawn in the context of software engineering. Summary discussion considers strengths and limitations of the ACTWith program. Overall, the paper emphasizes training high-level moral reasoning through guided inquiry education informing lifetime professional practice, and indicates an outstanding need for teachers able to do the job. (shrink)

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

As Christian List (2021) has recently argued, the increasing arrival of powerful AI systems that operate autonomously in high-stakes contexts creates a need for “future-proofing” our regulatory frameworks, i.e., for reassessing them in the face of these developments. One core part of our regulatory frameworks that dominates our everyday moral interactions is blame. Therefore, “future-proofing” our extant regulatory frameworks in the face of the increasing arrival of powerful AI systems requires, among others things, that we ask whether it makes (...) sense to extend our blaming practices to these systems. In the paper, we argue for the admittedly surprising thesis that this question should be answered in the affirmative: contrary to what one might initially think, it can make a lot of sense to blame AI systems, since, as we furthermore argue, many of the important functions that are fulfilled by blaming humans can also be served by blaming AI systems. The paper concludes that this result gives us a good pro tanto reason to extend our blame practices to AI systems. (shrink)

In most domains of human life, we are willing to accept that there are experts with greater knowledge and competencies that distinguish them from non-experts or laypeople. Despite this fact, the very recognition of expertise curiously becomes more controversial in the case of “moral experts”. Do moral experts exist? And, if they indeed do, are there ethical reasons for us to follow their advice? Likewise, can emerging technological developments broaden our very concept of moral expertise? In this (...) article, we begin by arguing that the objections that have tried to deny the existence (and convenience) of moral expertise are unsatisfactory. After that, we show that people have ethical reasons to ask for a piece of moral advice in daily life situations. Then, we argue that some Artificial Intelligence (AI) systems can play an increasing role in human morality by becoming moral experts. Some AI-based moral assistants can qualify as artificial moral experts and we would have good ethical reasons to use them. (shrink)

In philosophy of mind, zombies are imaginary creatures that are exact physical duplicates of conscious subjects but for whom there is no first-personal experience. Zombies are meant to show that physicalism—the theory that the universe is made up entirely out of physical components—is false. In this paper, I apply the zombie thought experiment to the realm of morality to assess whether moral agency is something independent from sentience. Algorithms, I argue, are a kind of functional moral zombie, such (...) that thinking about the latter can help us better understand and regulate the former. I contend that the main reason why algorithms can be neither autonomous nor accountable is that they lack sentience. Moral zombies and algorithms are incoherent as moral agents because they lack the necessary moral understanding to be morally responsible. To understand what it means to inflict pain on someone, it is necessary to have experiential knowledge of pain. At most, for an algorithm that feels nothing, ‘values’ will be items on a list, possibly prioritised in a certain way according to a number that represents weightiness. But entities that do not feel cannot value, and beings that do not value cannot act for moral reasons. (shrink)

We are sometimes unsure of the moral status of our relationships with other entities. Recent case studies in this uncertainty include our relationships with artificial agents (robots, assistant AI, etc.), animals, and patients with “locked-in” syndrome. Do these entities have basic moral standing? Could they count as true friends or lovers? What should we do when we do not know the answer to these questions? An influential line of reasoning suggests that, in such cases of moral (...) uncertainty, we need meta-moral decision rules that allow us to either minimize the risks of moral wrongdoing or improve the choice-worthiness of our actions. One particular argument adopted in this literature is the “risk asymmetry argument,” which claims that the risks associated with accepting or rejecting some moral facts may be sufficiently asymmetrical as to warrant favoring a particular practical resolution of this uncertainty. Focusing on the case study of artificial beings, this article argues that this is best understood as an ethical-epistemic challenge. The article argues that taking potential risk asymmetries seriously can help resolve disputes about the status of human–AI relationships, at least in practical terms (philosophical debates will, no doubt, continue); however, the resolution depends on a proper, empirically grounded assessment of the risks involved. Being skeptical about basic moral status, but more open to the possibility of meaningful relationships with such entities, may be the most sensible approach to take. (shrink)

Engineering an artificial intelligence to play an advisory role in morally charged decision making will inevitably introduce meta-ethical positions into the design. Some of these positions, by informing the design and operation of the AI, will introduce risks. This paper offers an analysis of these potential risks along the realism/anti-realism dimension in metaethics and reveals that realism poses greater risks, but, on the other hand, anti-realism undermines the motivation for engineering a moral AI in the first place.

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

Could the concept of 'evil' apply to AI? Drawing on PF Strawson's framework of reactive attitudes, this paper argues that we can understand evil as involving agents who are neither fully inside nor fully outside our moral practices. It involves agents whose abilities and capacities are enough to make them morally responsible for their actions, but whose behaviour is far enough outside of the norms of our moral practices to be labelled 'evil'. Understood as such, the paper argues (...) that, when it comes to AI and evil, we have more to fear from semi-autonomous, hybrid agents: agents who have enough of a capacity to operate within a minimal form of human practices of participation and responsibility, yet remain partially outside of it, capable of acting from outside the parameters of ordinary interactions in certain circumstances, perhaps sometimes for reasons unknown. (shrink)

Tae Wan Kim, John Hooker, and Thomas Donaldson make an attempt, in recent articles, to solve the alignment problem. As they define the alignment problem, it is the issue of how to give AI systems moral intelligence. They contend that one might program machines with a version of Kantian ethics cast in deontic modal logic. On their view, machines can be aligned with human values if such machines obey principles of universalization and autonomy, as well as a deontic utilitarian (...) principle. Programming machines to do so might be useful, in their view, for applications such as future autonomous vehicles. Their proposal draws both on traditional logic-based and contemporary connectionist approaches, to fuse factual information with normative principles. I will argue that this approach makes demands of machines that go beyond what is currently feasible, and may extend past the limits of the possible for AI. I also argue that a deontological ethics for machines should place greater stress on the formula of humanity of the Kantian categorical imperative. On this principle, one ought never treat a person as a mere means. Recognition of what makes a person a person requires ethical insight. Similar insight is needed to tell treatment as a means from treatment as a mere means. The resources in Kim, Hooker, and Donaldson’s approach is insufficient for this reason. Hesitation regarding deployment of autonomous machines is warranted in light of these alignment concerns. (shrink)

The field of AI ethics during the current and previous decade is receiving an increasing amount of attention from all involved stakeholders: the public, science, philosophy, religious organizations, enterprises, governments, and various organizations. However, this field currently lacks consensus on scope, ethico-philosophical foundations, or common methodology. This thesis aims to contribute towards filling this gap by providing an answer to the two main research questions: first, what theory can explain moral scenarios in which AI entities are participants?; and second, (...) what theory can explain the process of moral reasoning, decision and action, for AI entities in virtual, simulated and real-life moral scenarios? This thesis answers these two research questions with its two main contributions to the field of AI ethics, a substantial and a methodological contribution. The substantial contribution is a coherent and novel theory named Ethics of Systems Framework, as well as a possible inception of a new field of study: ethics of systems. The methodological contribution is the creation of its main methodological tool, the Ethics of Systems Interface. The second part of the research effort was focused on testing and demonstrating the capacities of the Ethics of Systems Framework and Interface in modeling and managing moral scenarios in which AI and other entities participate. Further work can focus on building on top of the foundations of the Framework provided here, increasing the scope of moral theories and simulated scenarios, improving the level of detail and parameters to reflect real-life situations, and field-testing the Framework on actual AI systems. (shrink)

I analyze recent discussions about making moral decisions under normative uncertainty. I discuss whether this kind of uncertainty should have practical consequences for decisions and whether there are reliable methods of reasoning that deal with the possibility that we are wrong about some moral issues. I defend a limited use of the decision theory model of reasoning in cases of normative uncertainty.

The burgeoning science of ethics has produced a trend toward pessimism. Ordinary moral thought and action, we’re told, are profoundly influenced by arbitrary factors and ultimately driven by unreasoned feelings. This book counters the current orthodoxy on its own terms by carefully engaging with the empirical literature. The resulting view, optimistic rationalism, shows the pervasive role played by reason, and ultimately defuses sweeping debunking arguments in ethics. The science does suggest that moral knowledge and virtue don’t come easily. (...) However, despite the heavy influence of automatic and unconscious processes that have been shaped by evolutionary pressures, we needn’t reject ordinary moral psychology as fundamentally flawed or in need of serious repair. Reason can be corrupted in ethics just as in other domains, but a special pessimism about morality in particular is unwarranted. Moral judgment and motivation are fundamentally rational enterprises not beholden to the passions. (shrink)

The fact that real-world decisions made by artificial intelligences (AI) are often ethically loaded has led a number of authorities to advocate the development of “moral machines”. I argue that the project of building “ethics” “into” machines presupposes a flawed understanding of the nature of ethics. Drawing on the work of the Australian philosopher, Raimond Gaita, I argue that ethical dilemmas are problems for particular people and not (just) problems for everyone who faces a similar situation. Moreover, the force (...) of an ethical claim depends in part on the life history of the person who is making it. For both these reasons, machines could at best be engineered to provide a shallow simulacrum of ethics, which would have limited utility in confronting the ethical and policy dilemmas associated with AI. (shrink)

Regard for Reason in the Moral Mind argues that a careful examination of the scientific literature reveals a foundational role for reasoning in moral thought and action. Grounding moral psychology in reason then paves the way for a defense of moral knowledge and virtue against a variety of empirical challenges, such as debunking arguments and situationist critiques. The book attempts to provide a corrective to current trends in moral psychology, which celebrate emotion over reason (...) and generate pessimism about the psychological mechanisms underlying commonsense morality. Ultimately, there is rationality in ethics not just despite but in virtue of the neurobiological and evolutionary materials that shape moral cognition and motivation. (shrink)

A lively debate in the literature on moral progress concerns the role of practical reasoning: Does it enable or subvert moral progress? Rationalists believe that moral reasoning enables moral progress, because it helps enhance objectivity in thinking, overcome unruly sentiments, and open our minds to new possibilities. By contrast, skeptics argue that moral reasoning subverts moral progress. Citing growing empirical research on bias, they show that objectivity is an illusion and that (...) moral reasoning merely rationalizes pre-existing biased moral norms. In this article, I argue that both the rationalists and the skeptics fail to understand fully the role of practical reasoning by focusing exclusively on moral reasoning to the neglect of social reasoning. In the first half of the article, I argue against the skeptics by vindicating moral reasoning. I identify a Democratic Model of moral reasoning which is reliable and effective in overcoming bias. In the second part of the article, I argue against the rationalists. Drawing on a paradigmatic case of moral progress, i.e., the British abolition of the slave trade, I illustrate that moral reasoning, even when sound, is insufficient to motivate progressive action. The explanation for this puzzling phenomenon is not that the moral norm against cruelty is inert, as skeptics might suggest. Rather, it is that the moral norm against cruelty was overridden by the social norm of slavery which was tied to the British joint commitments to freedom and national honour. The debate between rationalists and skeptics centers around the moral rationality of human action, failing to recognize that human action is in fact primarily about social rationality. I defend a joint commitment account of social rationality, and offer a novel Communitarian Model of social reasoning which follows the logic of social rationality to revise social norms. I defend the reliability and efficacy of the Communitarian Model of social reasoning by applying it to the abolitionist social movement to show how Britons gave fellow Britons social reasons grounded in their joint commitments to freedom and national honour to end slavery. (shrink)

Which artificial intelligence (AI) systems are agents? To answer this question, I propose a multidimensional account of agency. According to this account, a system's agency profile is jointly determined by its level of goal-directedness and autonomy as well as is abilities for directly impacting the surrounding world, long-term planning and acting for reasons. Rooted in extant theories of agency, this account enables fine-grained, nuanced comparative characterizations of artificial agency. I show that this account has multiple important virtues and is more (...) informative than alternatives. More speculatively, it may help to illuminate two important emerging questions in AI ethics: 1. Can agency contribute to the moral status of non-human beings, and how? 2. When and why might AI systems exhibit power-seeking behaviour and does this pose an existential risk to humanity? (shrink)

What is the relation between moral reasons and moral requirement? Specifically: what relation does an action have to bear to one’s moral reasons in order to count as morally required? This paper defends the following answer to this question: an action is morally required just in case the moral reasons in favor of that action are enough on their own to outweigh all of the reasons, moral and nonmoral, to perform any alternative. I argue that (...) this decisive moral reason view satisfies three key desiderata: it is compatible with either affirming or denying the existence of moral options; it vindicates moral rationalism, the thesis that an action can be morally required only if one ought to do it all things considered; and most distinctively, it explains why unexcused moral wrongdoing necessarily shows disregard for moral reasons. (shrink)

We evaluated the reliability, validity, and differential item functioning (DIF) of a shorter version of the Defining Issues Test-1 (DIT-1), the behavioral DIT (bDIT), measuring the development of moral reasoning. 353 college students (81 males, 271 females, 1 not reported; age M = 18.64 years, SD = 1.20 years) who were taking introductory psychology classes at a public University in a suburb area in the Southern United States participated in the present study. First, we examined the reliability of (...) the bDIT using Cronbach’s α and its concurrent validity with the original DIT-1 using disattenuated correlation. Second, we compared the test duration between the two measures. Third, we tested the DIF of each question between males and females. Findings reported that first, the bDIT showed acceptable reliability and good concurrent validity. Second, the test duration could be significantly shortened by employing the bDIT. Third, DIF results indicated that the bDIT items did not favour any gender. Practical implications of the present study based on the reported findings are discussed. (shrink)

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

In popular culture psychopaths are inaccurately portrayed as serial killers or homicidal maniacs. Most real-world psychopaths are neither killers nor maniacs. Psychologists currently understand psychopathy as an affective disorder that leads to repeated criminal and antisocial behavior. Counter to this prevailing view, I claim that psychopathy is not necessarily linked with criminal behavior. Successful psychopaths, an intriguing new category of psychopathic agent, support this conception of psychopathy. I then consider reactive attitude theories of moral responsibility. Within this tradition, psychopaths (...) are thought to be blameless as a result of their pronounced affective deficits. Psychopaths are considered morally blind because they lack the moral emotions that make us sensitive to moral reasons. I argue that, even if they are morally blind, psychopaths remain open to forms of blame stemming from non-moral reactive attitudes. These reactive attitudes remain appropriate because psychopaths can express hateful, disgusting, or contemptible non-moral values in their judgments. (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)

Can reasoning improve moral judgments and lead to moral progress? Pessimistic answers to this question are often based on caricatures of reasoning, weak scientific evidence, and flawed interpretations of solid evidence. In support of optimism, we discuss three forms of moral reasoning (principle reasoning, consistency reasoning, and social proof) that can spur progressive changes in attitudes and behavior on a variety of issues, such as charitable giving, gay rights, and meat consumption. We (...) conclude that moral reasoning, particularly when embedded in social networks with mutual trust and respect, is integral to moral progress. (shrink)

This essay focuses on anthropomorphism as both a form of hype and fallacy. As a form of hype, anthropomorphism is shown to exaggerate AI capabilities and performance by attributing human-like traits to systems that do not possess them. As a fallacy, anthropomorphism is shown to distort moral judgments about AI, such as those concerning its moral character and status, as well as judgments of responsibility and trust. By focusing on these two dimensions of anthropomorphism in AI, the essay (...) highlights negative ethical consequences of the phenomenon in this field. (shrink)

This chapter discusses contemporary scientific research on the role of reason and emotion in moral judgment. The literature suggests that moral judgment is influenced by both reasoning and emotion separately, but there is also emerging evidence of the interaction between the two. While there are clear implications for the rationalism-sentimentalism debate, we conclude that important questions remain open about how central emotion is to moral judgment. We also suggest ways in which moral philosophy is not (...) only guided by empirical research but continues to guide it. (shrink)

There is a growing body of scholarship on the ethics of autonomous vehicles. Yet the ethical discourse has mostly been focusing on the behavior of the vehicle in accident scenarios. This paper offers a different ethical prism: the implications of the autonomous vehicle for human well-being. As such, it contributes to the growing discourse on the wider societal and moral implications of the autonomous vehicle. The paper is premised on the neo-Aristotelian approach which holds that as human beings, our (...) well-being depends on developing and exercising our innate human capacities: to know, understand, love, be sociable, imagine, create and use our bodies and use our willpower. To develop and exercise these capacities, our environments need to provide a range of opportunities which will trigger the development and exercise of the capacities. The main argument advanced in the paper is that one plausible future of the autonomous vehicle—a future of single-rider autonomous vehicles—may effectively reduce the opportunities to develop and exercise our capacities to know, be sociable and use our willpower. It will therefore be bad for human well-being, and this provides us with a moral reason to resist this plausible future and search for alternative ones. (shrink)

According to moral testimony pessimists, the testimony of moral experts does not provide non-experts with normative reasons for belief. Moral testimony optimists hold that it does. We first aim to show that moral testimony optimism is, to the extent such things may be shown, the more natural view about moral testimony. Speaking roughly, the supposed discontinuity between the norms of moral beliefs and the norms of non-moral beliefs, on careful reflection, lacks the intuitive (...) advantage that it is sometimes supposed to have. Our second aim is to highlight the difference in the nature of the pragmatic reasons for belief that support moral testimony optimism and moral testimony pessimism, setting out more clearly the nature and magnitude of the challenge for the pessimist. (shrink)

One of the most oft-cited parts of Francis Hutcheson’s Illustrations upon the Moral Sense (1728) is his discussion of “exciting reasons.” In this paper I address the question: What is the function of that discussion? In particular, what is its relation to Hutcheson’s attempt to show that the rationalists’ normative thesis ultimately implies, contrary to their moral epistemology, that moral ideas spring from a sense? Despite first appearances, Hutcheson’s discussion of exciting reasons is not part of that (...) attempt. Mainly, it is part of Hutcheson’s comeback to Gilbert Burnet’s objections to Hutcheson’s Inquiry into the Original of Our Ideas of Beauty and Virtue (1725). (shrink)

The importance of situational constraint for moral evaluations is widely accepted in philosophy, psychology, and the law. However, recent work suggests that this relationship is actually bidirectional: moral evaluations can also influence our judgments of situational constraint. For example, if an agent is thought to have acted immorally rather than morally, that agent is often judged to have acted with greater freedom and under less situational constraint. Moreover, when considering interpersonal situations, we judge that an agent who forces (...) another to act immorally (versus morally) uses more force. These two features can result in contradictory response patterns in which participants judge both that (1) a forcer forced a forcee to act and (2) the forcee was not forced by the forcer to act. Here, we characterize potential psychological mechanisms, in particular, “moral focus” and counterfactual reasoning that account for this paradoxical pattern of judgments. (shrink)

In this article, I present a new interpretation of the pro-life view on the status of early human embryos. In my understanding, this position is based not on presumptions about the ontological status of embryos and their developmental capabilities but on the specific criteria of rational decisions under uncertainty and on a cautious response to the ambiguous status of embryos. This view, which uses the decision theory model of moral reasoning, promises to reconcile the uncertainty about the ontological (...) status of embryos with the certainty about normative obligations. I will demonstrate that my interpretation of the pro-life view, although seeming to be stronger than the standard one, has limited scope and cannot be used to limit destructive research on human embryos. (shrink)

A familiar part of ordinary moral thought is this idea: when other people are doing something worthwhile together, there is a reason for you to join in on the same terms as them. Morality does not tell you that you must always do this; but it exerts some pressure on you to join in. Suppose we take this idea seriously: just how should it be developed and applied? More particularly, just which groups and which actions are the ones with (...) respect to which you have participatory moral reasons? And just when is it wrong not to join in? I present answers to these questions, and discuss the implications—including for joint action on a very large scale, like global efforts to address climate change or fight a pandemic. (shrink)

Call the ethos understanding rightness in terms of spiritual purity and piety, and wrongness in terms of corruption and sacrilege, the “fetish ethic.” Jonathan Haidt and his colleagues suggest that this ethos is particularly salient to political conservatives and non-liberal cultures around the globe. In this essay, I point to numerous examples of moral fetishism in mainstream academic ethics. Once we see how deeply “infected” our ethical reasoning is by fetishistic intuitions, we can respond by 1) repudiating the (...) fetishistic impulse, by 2) “sublimating” our fetishism into liberal rationales, or by 3) accepting the fetishism on its own terms. Of these options, I argue that sublimating our fetishism is not advisable, and that embracing our ethical fetishism isn’t as obviously misguided as some suggest. (shrink)

In the following paper I will examine the possibility for a rational foundation of morals, rational in the sense that to ground a moral statement on reason amounts to being able to convince an unmotivated agent to conform to a moral rule - that is to say, to “rationally motivate” him (as Habermas would have said) to act in ways for which he or she had no previous reason to act. We will scrutinize the “internalist’s” objection (in Williams’ (...) definition) to such a claim and confront it with a, however, obvious fact: our need to convince or, at least, to influence agents to act according to moral judgements that entail strong validity claims. Therefore we need to find a better ground for our moral norms than that provided by a narrow concept of practical reason, which ultimately offers the basis for the internalist’s intuitions. Classical philosophers believed that to have a “right” sense meant also to think accordingly, that there was no intelligence without a social or moral side and that a person who lacked moral sense was not, at the same time, very intelligent. This contradicts some deep Humean intuitions, and in any case requires a more complex concept of practical reason than the one we normally encounter in internalist moral philosophers. In the following pages, I would like to reflect on this kind of social reason, or intelligence, or moral rationality, in an attempt to couple, in a coherent vision of moral sense within the framework of practical reason, intuitions that appear in Kant and Adam Smith with empirical research about what the lack of moral sense could mean. (shrink)

This chapter examines the possibility of using AI technologies to improve human moral reasoning and decision-making, especially in the context of purchasing and consumer decisions. We characterize such AI technologies as artificial ethics assistants (AEAs). We focus on just one part of the AI-aided moral improvement question: the case of the individual who wants to improve their morality, where what constitutes an improvement is evaluated by the individual’s own values. We distinguish three broad areas in which an (...) individual might think their own moral reasoning and decision-making could be improved: one’s actions, character, or other evaluable attributes fall short of one’s values and moral beliefs; one sometimes misjudges or is uncertain about what the right thing to do is in particular situations, given one’s values; one is uncertain about some fundamental moral questions or recognizes a possibility that some of one’s core moral beliefs and values are mistaken. We sketch why one might think that AI tools could be used to support moral improvement in those areas, and describe two types of assistance: preparatory assistance, including advice and training supplied in advance of moral deliberation; and on-the-spot assistance, including on-the-spot advice and facilitation of moral functioning over the course of moral deliberation. Then, we turn to some of the ethical issues that AEAs might raise, looking in particular at three under-appreciated problems posed by the use of AI for moral self-improvement: namely, reliance on sensitive moral data; the inescapability of outside influences on AEAs; and AEA usage prompting the user to adopt beliefs and make decisions without adequate reasons. (shrink)

Charles Sanders Peirce offers a number of arguments against the rational application of theory to morality, suggesting instead that morality should be grounded in instinct. Peirce maintains that we currently lack the scientific knowledge that would justify a rational structuring of morality. This being the case, philosophically generated moralities cannot be otherwise than dogmatic and dangerous. In this paper, I contend that Peirce’s critique of what I call “dogmatic-philosophical morality” should be taken very seriously, but I also claim that the (...) purely instinctive morality Peirce endorses is liable to a danger of its own, namely fanaticism. Indeed, Peirce himself recognizes this danger. As an alternative, I sketch a form of “pragmatic morality” that attempts to sidestep the dogmatism of philosophical morality and the fanaticism of instinctive morality. This form of morality avoids philosophical dogmatism by treating extant instincts as the postulates and materials with which it works. It avoids instinctive fanaticism by allowing a role to reason. By exhibiting fallibilism, revisability, pluralism, and meliorism, this type of reasoning can avoid the dogmatism of the philosophical kind of morality Peirce critiques. (shrink)

This paper is an attempt to improve the practical argument for beliefs in God. Some theists, most famously Kant and William James, called our attention to a particular set of beliefs, the Jamesian-type beliefs, which are justified by virtue of their practical significance, and these theists tried to justify theistic beliefs on the exact same ground. I argue, contra the Jamesian tradition, that theistic beliefs are different from the Jamesian-type beliefs and thus cannot be justified on the same ground. I (...) also argue that the practical argument, as it stands, faces a problem of self-defeat. I then construct a new practical argument that avoids both problems. According to this new argument, theistic beliefs are rational to accept because such beliefs best supply us with motivation strong enough to carry out demanding moral tasks. (shrink)