In this chapter, I introduce three different types of AI-based moral enhancement proposals discussed in the literature – substitutive enhancement, value-driven enhancement, and value-open moral enhancement. I analyse them based on the following criteria: effectiveness, examining whether they bring about tangible moral changes; autonomy, assessing whether they infringe on human autonomy and agency; and developmental impact, considering whether they hinder the development of natural moral skills. This analysis demonstrates that no (...) single approach to AI enhancement can satisfy all proposed criteria, suggesting a need for pluralism in devising AI-based enhancement tools. The most advisable approach to AI-based enhancement is to explore and develop a variety of tools that cater to the diverse needs of users and address different weaknesses in moral decision-making. (shrink)

Some skeptics question the very possibility of moral bioenhancement by arguing that if we lack a widely acceptable notion of morality, we will not be able to accept the use of a biotechnological technique as a tool for moral bioenhancement. I will examine this skepticism and argue that the assessment of moral bioenhancement does not require such a notion of morality. In particular, I will demonstrate that this skepticism can be neutralized in the case of recent neurofeedback (...) techniques. This goal will be accomplished in four steps. First, I will draw an outline of the skepticism against the possibility of moral bioenhancement and point out that a long-lasting dispute among moral philosophers nourishes this skepticism. Second, I will survey recent neurofeedback techniques and outline their three features: the variety of the target human faculties, such as emotion, cognition, and behavior; the flexibility or personalizability of the target brain state; and the nonclinical application of neurofeedback techniques. Third, I will argue that, by virtue of these three unique features, neurofeedback techniques can be a tool for moral bioenhancement without adopting any specific notion of morality. Fourth, I will examine the advantages and threats that neurofeedback-based moral enhancement may have. Finally, I will conclude that neurofeedback-based moral enhancement can become a new and promising tool for moral bioenhancement and requires further ethical investigations on its unique features. (shrink)

Scientific progress in recent neurofeedback research may bring about a new type of moral neuroenhancement, namely, neurofeedback-based moral enhancement; however, this has yet to be examined thoroughly. This paper presents an ethical analysis of the possibility of neurofeedback-based moral enhancement and demonstrates that this type of moral enhancement sheds new light on the moral enhancement debate. First, I survey this debate and extract the typical structural flow of its arguments. (...) Second, by applying structure to the case of neurofeedback-based moral enhancement, I examine the ethical, legal, and social issues to show that this technique is unique and traditionalist, which makes it compatible with almost all our conservative notions, so that it, accordingly, can be seen as an ethically acceptable option. Third, by rejecting the premise in the moral enhancement debate that bio/neuro-enhancement has its unique ELSI that traditional methods would never create, I demonstrate that, by virtue of its traditional or conservative features, neurofeedback-based moral enhancement can be incorporated into the traditional moral education network. Finally, I conclude that, being a part of the traditional moral education network, neurofeedback-based moral enhancement can be a unique and ethically acceptable option of moral neuroenhancement. (shrink)

John Harris recently argues that the moral bioenhancement proposed by Persson and Savulescu can damage moral agency by depriving the recipients of their freedom to fall (freedom to make wrongful choices) and therefore should not be pursued. The link Harris makes between moral agency and the freedom to fall, however, implies that all forms of moral enhancement, including moral education, that aim to make the enhancement recipients less likely to “fall” are detrimental to (...) moral agency. In this paper, I present a new moral agency-based critique against the moral bioenhancement program envisaged by Persson and Savulescu. I argue that the irresistible influences exerted by the bioenhancement program harms our capabilities for conducting accurate self-reflection and forming decisions that truly express our will, which subsequently undermine our moral agency. (shrink)

In this article, I use science-fiction scenarios drawn from Dan Simmons’ “Hyperion Cantos” (Hyperion, The Fall of Hyperion, Endymion, The Rise of Endymion) to explore a cluster of issues related to the evolutionary history and neural bases of human moral cognition, and the moral desirability of improving our ability to make moral decisions by techniques of neuroengineering. I begin by sketching a picture of what recent research can teach us about the character of human moral psychology, (...) with a particular emphasis on highlighting the importance of our evolutionary background as social mammals. I then consider how the moral psychology of intelligent machines might differ from our own, and argue that the differences would depend on the extent to which their evolutionary background resembled our own. I offer two very different case studies—the “Technocore AIs” that have evolved from early, parasitic computer programs, and the mysterious “Shrike,” who travels backward through time. I close by looking at the character of Aenea, a messianic figure that is a joint descendant of humans and machines. I argue that while the sort of “moral enhancement” she represents is far beyond the scope of either contemporary neuroscience or artificial intelligence research, it nevertheless represents a worthwhile goal. (shrink)

In this article I discuss a recent proposal according to which human beings are in need of moral enhancement by novel biomedical means in order to reduce the risk of catastrophes that could threaten the very possibility of continued human existence on this planet. I raise two objections to this proposal. The first objection claims that the idea that human beings could be morally enhanced by altering our emotional psychological inclinations, such as altruism, is misguided. In the line (...) with Kantian understanding of morality I argue that our morality is based on rationality and not on inclinations. If we take this view of morality it becomes clear that the proposed enhancement by biomedical means cannot be moral enhancement. What is enhanced is emotional aspect of our character, not our morality. People enhanced in this way would not act on the basis of their deliberate choices but on basis of preprogramed psychological inclination. This would in turn undermine our basic moral concept of freedom and, thereby, of moral responsibility. The second objection to the proposal show how the idea that moral enhancement by biomedical means should be mandatory violates political freedom of citizens. Faced with the objection that moral enhancement by biomedical means could be necessary in order to prevent catastrophic destruction of environment, in the final part of this chapter I try to point to education and liberal democracy as the alternative and morally acceptable ways of changing our behaviour. (shrink)

Advocates of moral enhancement through pharmacological, genetic, or other direct interventions sometimes explicitly argue, or assume without argument, that traditional moral education and development is insufficient to bring about moral enhancement. Traditional moral education grounded in a Kohlbergian theory of moral development is indeed unsuitable for that task; however, the psychology of moral development and education has come a long way since then. Recent studies support the view that moral cognition is (...) a higher-order process, unified at a functional level, and that a specific moral faculty does not exist. It is more likely that moral cognition involves a number of different mechanisms, each connected to other cognitive and affective processes. Taking this evidence into account, we propose a novel, empirically informed approach to moral development and education, in children and adults, which is based on a cognitive-affective approach to moral dispositions. This is an interpretative approach that derives from the cognitive-affective personality system (Mischel and Shoda, 1995). This conception individuates moral dispositions by reference to the cognitive and affective processes that realise them. Conceived of in this way, moral dispositions influence an agent's behaviour when they interact with situational factors, such as mood or social context. Understanding moral dispositions in this way lays the groundwork for proposing a range of indirect methods of moral enhancement, techniques that promise similar results as direct interventions whilst posing fewer risks. (shrink)

This paper offers an overview of the prospects and ethics of using AI to achieve human enhancement, and more broadly what we call intellectual augmentation (IA). After explaining the central notions of human enhancement, IA, and AI, we discuss the state of the art in terms of the main technologies for IA, with or without brain-computer interfaces. Given this picture, we discuss potential ethical problems, namely inadequate performance, safety, coercion and manipulation, privacy, cognitive liberty, authenticity, and fairness in (...) more detail. We conclude that while there are very significant technical hurdles to real human enhancement through AI, and significant ethical problems, there are also significant benefits that may realistically be achieved in ways that are consonant with a rights-based ethics as well. We also highlight the specific concerns that apply particularly to applications of AI for "sheer" IA (more realistic in the near term), and to enhancement applications, respectively. (shrink)

This paper aims to clear up the epistemology of learning morality from Artificial Moral Advisors (AMAs). We start with a brief consideration of what counts as moral enhancement and consider the risk of deskilling raised by machines that offer moral advice. We then shift focus to the epistemology of moral advice and show when and under what conditions moral advice can lead to enhancement. We argue that people’s motivational dispositions are enhanced by inspiring (...) people to act morally, instead of merely telling them how to act. Drawing upon these insights, we claim that if AMAs are to genuinely enhance people morally, they should be designed as inspiration and not authority machines. In the final section, we evaluate existing AMA models to shed light on which holds the most promise for helping to make users better moral agents. (shrink)

Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and planetary (...) boundaries. It is evident that AI can function better when trained to mimic certain human mental processes. Based on insights from quantum mechanics and the informational entropy-based notion of value, we suggest AI developers can enhance the AI training processes' effectiveness and efficiency by creating and implementing parameter systems that are capable of effectively assigning probabilities to informational quanta. Such systems can help reduce entropy within the system, which lowers the energy required for data storage and processing while decreasing the likelihood of information loss during training. Successfully applying the concept of information entropy-based value in AI development will be crucial for advancing generative AI and achieving AGI in a sustainable manner. (shrink)

This chapter focuses on AI-based cognitive and perceptual enhancements. AI-based brain enhancements are already under development, and they may become commonplace over the next 30–50 years. We raise doubts concerning whether radical AI-based enhancements transhumanists advocate will accomplish the transhumanists goals of longevity, human flourishing, and intelligence enhancement. We urge that even if the technologies are medically safe and are not used as tools by surveillance capitalism or an authoritarian dictatorship, these enhancements may still fail to (...) do their job for philosophical reasons. In what follows, we explore one such concern, a problem that involves the nature of the self. We illustrate that the so called transhumanist efforts to “merge oneself with AI” could lead to perverse realizations of AI technology, such as the demise of the person who sought enhancement. And, in a positive vein, we offer ways to avoid this, at least within the context of one theory of the nature of personhood. (shrink)

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

Large Language Models (LLMs) are generative AI systems capable of producing original texts based on inputs about topic and style provided in the form of prompts or questions. The introduction of the outputs of these systems into human discursive practices poses unprecedented moral and political questions. The article articulates an analysis of the moral status of these systems and their interactions with human interlocutors based on the Habermasian theory of communicative action. The analysis explores, among other (...) things, Habermas's inquiries into the analogy between human minds and computers, and into the status of atypical participants in the linguistic community such as genetically modified subjects and animals. Major conclusions are the LLMs seem to qualify as authors that originally participate in discursive practices but do display only a structurally derivative form of communicative competence and fail to meet the status of communicative agents. In this sense, while the contribution of AI writing systems in public discourse and deliberation can support the process of mutual understanding within the community of speakers, the human actors involved in the development, use, and diffusion of these systems share a collective responsibility for the disclosure of AI authorship and verification and adjudication of validity claims. (shrink)

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

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)

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)

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)

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

With the increasing degrees A.I.s and machines are applied across different social contexts, the need for implementing ethics in A.I.s is pressing. In this paper, we argue for a pluralist hybrid model for the implementation of moral A.I.s. We first survey current approaches to moral A.I.s and their inherent limitations. Then we propose the pluralist hybrid approach and show how these limitations of moral A.I.s can be partly alleviated by the pluralist hybrid approach. The core ethical decision-making (...) capacity of an A.I. based on the pluralist hybrid approach consists of two systems. The first is a deterministic algorithm system that incorporates different moral rules for making explicit moral decisions. The second is a machine learning system that calculates the value of the variables required by the application of moral principles. The pluralist hybrid system is better than the existing proposals as (i) it better addresses the moral disagreement problem of the top-down approach by including different moral principles, while (ii) it reduces the opacity of ethical decision-making compared with a bottom-up system by implementing explicit moral principles for moral decision making. (shrink)

The AI Contribution Value System Argument proposes a framework in which AI-generated contributions are valued based on their societal impact rather than traditional monetary metrics. Traditional economic systems often fail to capture the enduring value of AI innovations, which can mitigate pressing global challenges. This argument introduces a contribution-based valuation model grounded in equity, inclusivity, and sustainability. By incorporating measurable metrics such as quality-adjusted life years (QALYs), emissions reduced, and innovations generated, this system ensures rewards align with tangible (...) societal benefits. It emphasizes the need for global collaboration, ethical safeguards, and adaptive frameworks to prevent monopolization and corruption. Through AI-enhanced transparency, blockchain-based trust mechanisms, and cross-border cooperation, the AI Contribution Value System offers a transformative approach to fostering sustainable and equitable innovation in the 21st century. (shrink)

[Note: articles 1-5 are in English; Intro, Discussion, and Conclusion are in Portuguese.] Responsibility practices that are part of our daily lives involve, among other things, standards about how one should praise, blame, or punish people for their actions, as well as particular acts that follow those standards to a greater or lesser extent. A classical question in philosophy asks whether human beings can actually be morally responsible for what they do. This dissertation argues that addressing this classical question is (...) insufficient if one wants the investigation of moral responsibility to serve the goal of improving ordinary responsibility practices. As an alternative, I offer directions for an interdisciplinary investigation that I take to be in a better position to promote that goal. My argument is developed in five articles and a discussion section. The first four articles describe limitations of skeptical views, which deny the existence of moral responsibility. The first article assesses a skeptical argument based on results from neuroscience that intends to show that there is no free will. I argue that a premise in the argument—which says that choices are determined by events in the brain—is not supported by the available results. The second article argues that, despite the fact that existent results do not show that choices are determined by brain events, further studies in neuroscience could in principle do that. The third article begins the discussion of limitations that concern the implementability of some of the changes in responsibility practices recommended in skeptical approaches. Specifically, I describe challenges that attempts to reduce the severity of legal punishment are likely to face due to psychological facts about belief in free will and desire to punish. The forth article presents results from an original experiment that sought to test a hypothesis about the workings of belief in free will and the desire to punish, namely the hypothesis that the desire to punish causally affects beliefs about free will. Results failed to support the hypothesis. Finally, the fifth article presents what I call the enhancement model, i.e., a proposal about how to structure an interdisciplinary investigation that can promote the enhancement of ordinary responsibility practices. The final discussion section shows how the enhancement model overcomes some of the limitations of recent discussions about the existence of moral responsibility, which includes not just the skeptical views considered in earlier articles, but also views that affirm the existence of moral responsibility and free will. The central claim of this dissertation, therefore, is that the investigation of moral responsibility can be rearranged so as to further the goal of improving ordinary responsibility practices. (shrink)

Our rapidly increasing reliance on frictionless AI interactions may increase cognitive and emotional distance, thereby letting our adaptive resilience slacken and our ethical virtues atrophy from disuse. Many trends already well underway involve the offloading of cognitive, emotional, and ethical labor to AI software in myriad social, civil, personal, and professional contexts. Gradually, we may lose the inclination and capacity to engage in critically reflective thought, making us more cognitively and emotionally vulnerable and thus more anxious and prone to manipulation (...) from false news, deceptive advertising, and political rhetoric. In this article, I consider the overarching features of this problem and provide a framework to help AI designers tackle it through system enhancements in smartphones and other products and services in the burgeoning internet of things (IoT) marketplace. The framework is informed by two ideas: psychologist Daniel Kahneman’s cognitive dual process theory and moral self-awareness theory, a four-level model of moral identity that I developed with Benjamin M. Cole. (shrink)

The history of humankind is full of examples that indicate a constant desire to make human beings more moral. Nowadays, technological breakthroughs might have a significant impact on our moral character and abilities. This is the case of Virtual Reality (VR) technologies. The aim of this paper is to consider the ethical aspects of the use of VR in enhancing empathy. First, we will offer an introduction to VR, explaining its fundamental features, devices and concepts. Then, we will (...) approach the characterization of VR as an “empathy machine,” showing why this medium has aroused so much interest and why, nevertheless, we do not believe it is the ideal way to enhance empathy. As an alternative, we will consider fostering empathy-related abilities through virtual embodiment in avatars. In the conclusion, however, we will, we will examine some of the serious concerns related to the ethical relevance of empathy and will defend the philosophical case for a reason-guided empathy, also suggesting specific guidelines for possible future developments of empathy enhancement projects through VR embodied experiences. (shrink)

This article presents a robust defense of the concept of “datafied enhancement” as a subset of human enhancement. Firstly, the author notes that the widespread development of ICT and AI technologies has made it possible to collect and analyze human biometric data, thus integrating data into the concept of embodiment. Secondly, the author explores the cultural and intellectual history of datafied enhancement, highlighting the significant role data has played in human evolution. Thirdly, the author examines the functional (...) classifications of datafied enhancement, arguing that conversational, wearable, ingestible, and embeddable technological devices can enhance individuals’ physical, cognitive, emotional, and moral capacities by collecting body data. Fourthly, the author underscores the importance of distinguishing datafied enhancement from dataism to avoid misconceptions. Finally, the author addresses potential ethical issues, such as data exclusivity, the uncontrollable data self, and privacy invasion. By acknowledging these risks, datafied enhancement can be guided to become a technology that respects human dignity and promotes the common good. (shrink)

Artificial intelligence (AI), blockchain, virtual and augmented reality, (semi-)autonomous ve- hicles, autoregulatory weapon systems, enhancement, reproductive technologies and human- oid robotics – these technologies (and many others) are no longer speculative visions of the future; they have already found their way into our lives or are on the verge of a breakthrough. These rapid technological developments awaken a need for orientation: what distinguishes hu- man from machine and human intelligence from artificial intelligence, how far should the body be allowed (...) to be changed and what are the dangers and opportunities presented by these technologies? Many of these questions are also addressed to theology. For example, questions about the image of humanity, the understanding of creation, the ethics of technological body interventions or the moral status of robots. What does theology have to say about these technological developments? It is the right time for theology to scientifically explore tech- nologization and AI and to formulate answers. As technology changes the various areas of human life, society and the world around us, the places and topics of theology are also undergoing transformation. Puzio, Anna: Theology Meets AI: Examining Perspectives, Tasks, and Theses on the Intersection of Technology and Religion. In: Puzio, Anna/Kunkel, Nicole/Klinge, Hendrik (Hg.): Alexa, How Do You Feel About Religion? Theological Approaches to Technology and Artificial Intelligence (Theology and AI 1). Darmstadt: wbg 2023, S. 29–41. DOI: 10.53186/1030373. (shrink)

¿Puede la inteligencia artificial (IA) hacernos más morales o ayudarnos a tomar decisiones más éticas? El libro Más (que) humanos. Biotecnología, inteligencia artificial y ética de la mejora, editado por Francisco Lara y Julian Savulescu (2021), puede inspirarnos filosóficamente sobre este debate contemporáneo. En esta nota crítica, contextualizo la aportación general del volumen y analizo los dos últimos capítulos de Monasterio-Astobiza y de Lara y Deckers, quienes argumentan a favor del uso de la IA para hacernos mejores agentes morales. El (...) objetivo es ampliar y matizar críticamente algunas cuestiones clave sobre cómo la IA puede asistirnos para tomar decisiones más éticas. (shrink)

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

Autonomy has been central to moral and political philosophy for millenia, and has been positioned as a critical aspect of both justice and wellbeing. Research in psychology supports this position, providing empirical evidence that autonomy is critical to motivation, personal growth and psychological wellness. Responsible AI will require an understanding of, and ability to effectively design for, human autonomy (rather than just machine autonomy) if it is to genuinely benefit humanity. Yet the effects on human autonomy of digital experiences (...) are neither straightforward nor consistent, and are complicated by commercial interests and tensions around compulsive overuse. This multi-layered reality requires an analysis that is itself multidimensional and that takes into account human experience at various levels of resolution. We borrow from HCI and psychological research to apply a model (“METUX”) that identifies six distinct spheres of technology experience. We demonstrate the value of the model for understanding human autonomy in a technology ethics context at multiple levels by applying it to the real-world case study of an AI-enhanced video recommender system. In the process we argue for the following three claims: 1) There are autonomy-related consequences to algorithms representing the interests of third parties, and they are not impartial and rational extensions of the self, as is often perceived; 2) Designing for autonomy is an ethical imperative critical to the future design of responsible AI; and 3) Autonomy-support must be analysed from at least six spheres of experience in order to approriately capture contradictory and downstream effects. (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)

Erick J. Ramirez, Miles Elliott and Per‑Erik Milam (2021) have recently claimed that using Virtual Reality (VR) as an educational nudge to promote empathy is unethical. These authors argue that the influence exerted on the participant through virtual simulation is based on the deception of making them believe that they are someone else when this is impossible. This makes the use of VR for empathy enhancement a manipulative strategy in itself. In this article, we show that Ramirez et (...) al.’s ethical rejection of empathy enhancement through VR is based on confusion. First, we show that this misunderstanding stems from the conception of empathy-enhancing simulations solely as failed attempts at “being someone else,” along with ignoring the crucial difference between the psychological perspective-taking processes of imagine-other and imagine-self. Then, having overcome that misconception, we argue that the ethical misgivings about the use of VR to promote empathy should disappear and that these projects have greater potential for behavioural change than purely sympathy-focused interventions. (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)

We routinely take diminished capacity as diminishing moral responsibility (as in the case of immaturity, senility, or particular mental impairments). The prospect of enhanced capacity therefore poses immediate questions with regard to moral responsibility. Of particular interest are those capacities that might allow us to better avoid serious harms or wrongdoing. We can consider questions of responsibility with regards to enhancement at various removes. In the first instance: where such (safe and effective) interventions exist, do we have (...) an obligation to undergo such enhancement? Secondly: once enhanced, would the ambit of our responsibility therefore increase? Some philosophers have argued that enhanced capacities potentially generate “hyperresponsibility.” Hyperresponsible people would be held to a different and higher moral standard than those of us with more ordinary human capacities, and are liable to be more blameworthy for wrongdoing than ordinary agents. This chapter discusses the implications of enhancement for three central views of responsibility, namely: capacity-based, control-based and revelation-based views. Debates around moral responsibility have primarily concerned diminished capacities; as such the prospect of enhancement introduces new terrain—and potentially new fault-lines and complexities—in which to interrogate our theoretical conceptions of the foundations (and limits) of moral responsibility. (shrink)

Emotion detection and management have emerged as pivotal areas in humancomputer interaction, offering potential applications in healthcare, entertainment, and customer service. This study explores the use of deep learning (DL) models to enhance emotion recognition accuracy and enable effective emotion regulation mechanisms. By leveraging large datasets of facial expressions, voice tones, and physiological signals, we train deep neural networks to recognize a wide array of emotions with high precision. The proposed system integrates emotion recognition with adaptive management strategies that provide (...) personalized feedback and interventions based on detected emotional states. Our approach surpasses traditional machine learning methods, demonstrating superior performance in real-time applications. We also explore the ethical implications and challenges associated with deploying such systems, particularly regarding privacy concerns and the potential for misuse. Through extensive experiments, our model achieved an average accuracy rate of 92%, highlighting its robustness across different environments and user demographics. This research not only contributes to the growing field of affective computing but also lays the groundwork for future developments in emotionally intelligent systems. (shrink)

Breast cancer is the leading cause of death among women with cancer. Computer-aided diagnosis is an efficient method for assisting medical experts in early diagnosis, improving the chance of recovery. Employing artificial intelligence (AI) in the medical area is very crucial due to the sensitivity of this field. This means that the low accuracy of the classification methods used for cancer detection is a critical issue. This problem is accentuated when it comes to blurry mammogram images. In this paper, convolutional (...) neural networks (CNNs) are employed to present the traditional convolutional neural network (TCNN) and supported convolutional neural network (SCNN) approaches. The TCNN and SCNN approaches contribute by overcoming the shift and scaling problems included in blurry mammogram images. In addition, the flipped rotation-based approach (FRbA) is proposed to enhance the accuracy of the prediction process (classification of the type of cancerous mass) by taking into account the different directions of the cancerous mass to extract effective features to form the map of the tumour. The proposed approaches are implemented on the MIAS medical dataset using 200 mammogram breast images. Compared to similar approaches based on KNN and RF, the proposed approaches show better performance in terms of accuracy, sensitivity, spasticity, precision, recall, time of performance, and quality of image metrics. (shrink)

The exponential growth of data storage requirements has become a pressing challenge in hybrid cloud environments, necessitating efficient data deduplication methods. This research proposes a novel Smart Deduplication Framework (SDF) designed to identify and eliminate redundant data, thus optimizing storage usage and improving data retrieval speeds. The framework leverages a hybrid cloud architecture, combining the scalability of public clouds with the security of private clouds. By employing a combination of client-side hashing, metadata indexing, and machine learning-based duplicate detection, the (...) framework achieves significant storage savings without compromising data integrity. Real-time testing on a hybrid cloud setup demonstrated a 65% reduction in storage needs and a 40% improvement in data retrieval times. Additionally, the system employs blockchain for immutable logging of deduplication activities, enhancing transparency and traceability. This study concludes with an evaluation of the deduplication framework's impact on cost efficiency, system performance, and potential scalability. Future enhancements aim to integrate multi-cloud interoperability and advanced compression algorithms to further refine storage management. (shrink)

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

Artificial Intelligence (AI) is a technology that enables machines or computer systems to perform tasks that usually require human intelligence. AI systems can understand and interpret information, make decisions, and solve problems based on patterns and data. They can also improve their performance over time by learning from their experiences. AI is used in various applications, such as enhancing knowledge and understanding, helping as voice assistants, aiding in image recognition, facilitating self-driving cars, and helping diagnose diseases. The appropriate usage (...) of AI can help in the promotion of Sikhism. However, awareness of the pitfalls of using AI for religious purposes is essential. So, we must use AI with caution in spiritual matters. (shrink)

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

Sports physicians are continuously confronted with new biotechnological innovations. This applies not only to doping in sports, but to all kinds of so-called enhancement methods. One fundamental problem regarding the sports physician's self-image consists in a blurred distinction between therapeutic treatment and non-therapeutic performance enhancement. After a brief inventory of the sports physician's work environment I reject as insufficient the attempts to resolve the conflict of the sports physician by making it a classificatory problem. Followed by a critical (...) assessment of some ideas from the US President's Council on Bioethics, the formulation of ethical codes and attempts regarding a moral topography, it is argued that the sports physician's conflict cannot be resolved by the distinction between therapy and enhancement. Instead, we also have to consider the possibility that the therapy-based paradigm of medicine cannot do justice to the challenges of the continuously increasing technical manipulability of the human body and even our cognitive functions as well. At the same time we should not adhere to transhumanist ideas, because non-therapeutic interventions require clear criteria. Based on assistive technologies an alternative framework can be sketched that allows for the integration of therapeutic and non-therapeutic purposes. After a thorough definition of standards and criteria, the role of the sports physician might be defined as that of an assistant for enhancement. Yet the process of defining such an alternative framework is a societal and political task that cannot be accomplished by the sports physicians themselves. Until these questions are answered sports physicians continue to find themselves in a structural dilemma that they partially can come to terms with through personal integrity. (shrink)

Human-centered explainable AI (HCXAI) advocates for the integration of social aspects into AI explanations. Central to the HCXAI discourse is the Social Transparency (ST) framework, which aims to make the socio-organizational context of AI systems accessible to their users. In this work, we suggest extending the ST framework to address the risks of social misattributions in Large Language Models (LLMs), particularly in sensitive areas like mental health. In fact LLMs, which are remarkably capable of simulating roles and personas, may lead (...) to mismatches between designers' intentions and users' perceptions of social attributes, risking to promote emotional manipulation and dangerous behaviors, cases of epistemic injustice, and unwarranted trust. To address these issues, we propose enhancing the ST framework with a fifth 'W-question' to clarify the specific social attributions assigned to LLMs by its designers and users. This addition aims to bridge the gap between LLM capabilities and user perceptions, promoting the ethically responsible development and use of LLM-based technology. (shrink)

Most Enlightenment thinkers believed that the World’s order (as ultimately based on divine laws) is good and thus every gain of knowledge will have good consequences. Scientific process was assumed to entail moral progress. In fact some moral progress did occur in the Western civilization and science contributed to it, but it is widely incommensurate with the progress of science. The Enlightenment’s concept of a concerted scientific and moral progress proved largely wrong for several reasons. (1) (...) Public morality and science evolve largely independently and may either enhance or inhibit each other. (2) There are no objective values to be read in the World’s order and simply followed. Instead, our real, subjective values and the moral systems they fuel have all been generated and shaped by evolution rather than designed to be universally good, and thus ought to be managed rather than simply followed. (3) Our evolved morality is flawed, deficient, prone to doctrinal manipulation and refractory to progress. (4) The majority of people show metaethical incompetence in failing to take a reasoned critical stand toward the principles and assumptions of received morals. This makes moral progress largely dependent on those who reach metaethical competence by transcending the conventional stages of moral development. (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)

Rapid advances in AI-based automation have led to a number of existential and economic concerns. In particular, as automating technologies develop enhanced competency they seem to threaten the values associated with meaningful work. In this article, we focus on one such value: the value of achievement. We argue that achievement is a key part of what makes work meaningful and that advances in AI and automation give rise to a number achievement gaps in the workplace. This could limit people’s (...) ability to participate in meaningful forms of work. Achievement gaps are interesting, in part, because they are the inverse of the (negative) responsibility gaps already widely discussed in the literature on AI ethics. Having described and explained the problem of achievement gaps, the article concludes by identifying four possible policy responses to the problem. (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)

With the proliferation of sophisticated cyber threats, traditional malware detection techniques are becoming inadequate to ensure robust cybersecurity. This study explores the integration of deep learning (DL) techniques into malware detection systems to enhance their accuracy, scalability, and adaptability. By leveraging convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers, this research presents an intelligent malware detection framework capable of identifying both known and zero-day threats. The methodology involves feature extraction from static, dynamic, and hybrid malware datasets, followed by (...) training DL models to classify malicious and benign software with high precision. A robust experimental setup evaluates the framework using benchmark malware datasets, yielding a 96% detection accuracy and demonstrating resilience against adversarial attacks. Real-time analysis capabilities further improve response times, reducing the risk of potential damage. The study also incorporates visualization tools to provide interpretable insights into model decisions, enhancing transparency for cybersecurity practitioners. Concluding with a discussion on the challenges and future prospects, this research paves the way for scalable, AI-driven solutions to combat evolving cyber threats. (shrink)

In this paper, I examine why moral exemplars are useful and even necessary in moral education despite several critiques from researchers and educators. To support my point, I review recent AI research demonstrating that exemplar-based learning is superior to rule-based learning in model performance in training neural networks, such as large language models. I particularly focus on why education aiming at promoting the development of multifaceted moral functioning can be done effectively by using exemplars, which (...) is similar to exemplar-based learning in AI model training. Furthermore, I discuss the potential limitations and issues related to exemplar-applied moral education with findings from recent studies in AI research raising concerns about model biases and toxic outcomes. I attempt to propose ways to address the concerns regarding employing moral exemplars as well. As remedies, I suggest that autonomy-supporting deliberative and reflective learning processes should be utilized. Furthermore, based on the discussion, I examine how macroscopic socio-cultural aspects influence the effectiveness of exemplar-applied moral education. Suggestions for moral educators and future directions for research in moral education are briefly discussed. (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 purpose of this paper is to unveil the incompleteness of John Harris' view that parents have a moral obligation to genetically enhance their unborn children. Specifically, here two main conclusions are proposed: (1) at present there exist insufficient empirical data for determining whether prenatal genetic enhancement (PGE) is a moral obligation on prospective parents. Although the purpose of PGE research would be to determine the extent to which PGE is safe and effective, the task of determining (...) the veracity of Harris' premises is impossible to achieve without begging the question; we would be forced to assume the moral permissibility of PGE in order to generate the data that are required for determining its moral standing. So, given this empirical blindness, consequence-based normative frameworks like that of Harris cannot determine the moral standing of PGE, but merely push the question of the moral standing of PGE back a step, without offering any plausible and morally endorsable recourse for how to answer it; (2) even if PGE research were legal, which it is not, parents nevertheless have good reason not to consent to it for their children, especially as participants in the first wave(s) of such research. (shrink)

The field of mindfulness and the emerging science of heroism have a common interest in the causes and conditions of selfless altruism though up to this point there has been little cross-pollination. However, there is increasing evidence that mindfulness training delivers heroically relevant qualities such as increased attentional functioning, enhanced primary sensory awareness, greater conflict monitoring, increased cognitive control, reduced fear response, and an increase in loving kindness and self-sacrificing behaviors. Predicated on the notion of a “no self,” traditional mindfulness (...) and its focus on enlightenment and selfless service may in fact be ideally suited to the development of the elusive “trait” (predictable) versus “state” (intermittent) heroic character. Interweaving observations and questions drawn from the science of heroism, the article explores the relevant theory, practices, and scientific outcomes of mindfulness. It finds that there is evidence that heroically relevant qualities are trainable with the suite of mindfulness techniques and that an enduring experience of selflessness and service of others (the enlightened hero) may well be within the grasp of the serious practitioner. (shrink)

This dissertation consists of five chapters, each written as independent research papers that are unified by an overarching concern regarding information privacy and machine learning-based artificial intelligence (AI). This dissertation addresses the issues concerning privacy and AI by responding to the following three main research questions (RQs): RQ1. ‘How does an AI system affect privacy?’; RQ2. ‘How effectively does the General Data Protection Regulation (GDPR) assess and address privacy issues concerning both individuals and groups?’; and RQ3. ‘How can the (...) value of privacy be embedded into systems?’ -/- To respond to the RQs, this dissertation adopts the privacy impact assessment (PIA) as the overall methodology. A PIA encompasses three distinct stages; the first, the analytical stage, concerns the analysis of how AI (particularly focusing on inference as a process that includes inferred information, AI models’ performance, and accessing information uncovered by AI models) impacts privacy. Second, the legal assessment stage concerns whether AI that processes personal information and develops models complies with the GDPR. Finally, the design requirements stage features proposals for design requirements for systems aimed at protecting privacy. Accordingly, this dissertation is structured in three parts, each corresponding to a specific stage of a PIA and responding to one of the RQs. -/- Part I, which addresses the first stage of the PIA, comprises three chapters that altogether respond to RQ1. Chapter 2 analyses how AI impacts the descriptive aspect of privacy; this part argues that AI challenges the current definitions of privacy and that the ‘source control’ and ‘actual access’ definitions of privacy, once revised in the face of counter-examples involving inferred information, converge. Chapter 3, which considers how AI impacts the normative aspect of privacy, particularly the value of privacy, argues that AI affects the social value of privacy, which depends on trust, as this dimension of privacy is constituted when AI models perform accurately. Chapter 4 examines how AI impacts the normative aspect of privacy, particularly the right to privacy, and it argues that, although accessing information uncovered by AI models raises concerns about the privacy of algorithmically designed groups, the right to privacy cannot be recognised for such groups. This is the disruptive feature of AI that has led to consideration of new approaches other than the traditional one, which involves recognising the right to privacy, to protect the privacy of these groups. Instead of recognising the right to privacy for algorithmically designed groups, this chapter suggests taking a moral principle for the moral obligation of protecting vulnerable groups within an ethics of vulnerability. -/- Part II concerns the second stage of the PIA and consists of one chapter that responds to RQ2. Chapter 5, in addition to evaluating whether AI that processes personal information and develops models complies with the GDPR, also assesses whether the GDPR adequately addresses the privacy issues raised by AI. It specifically focuses on group privacy and argues that GDPR has limitations in protecting the privacy of algorithmically designed groups and that the privacy of such vulnerable entities must be considered in the context of privacy and data protection. -/- Part III, which is related to the third stage of the PIA, also consists of one chapter that responds to RQ3. Chapter 6 proposes design requirements to protect privacy by integrating privacy into systems and argues that privacy is instrumentally valuable for the sake of autonomy. Accordingly, to embed the value of privacy into systems, design requirements are articulated through the translation of norms that promote and protect autonomy. (shrink)