Machine Ethics

A AI Robotics Ethics Society (AIRES) é uma organização sem fins lucrativos fundada em 2018 por Aaron Hui, com o objetivo de se promover a conscientização e a importância da implementação e regulamentação ética da AI. A AIRES é hoje uma organização com capítulos em universidade como UCLA (Los Angeles), USC (University of Southern California), Caltech (California Institute of Technology), Stanford University, Cornell University, Brown University e a Pontifícia Universidade Católica do Rio Grande do Sul (Brasil). AIRES na PUCRS é (...) o primeiro capítulo internacional da AIRES, e como tal, estamos empenhados em promover e aprimorar a Missão AIRES. Nossa missão é focar na educação dos líderes da IA de amanhã em princípios éticos, para assegurar que a IA seja criada de forma ética e responsável. Como ainda existem poucas propostas de como devemos implementar princípios éticos e diretrizes normativas na prática do desenvolvimento de sistemas de IA, o objetivo deste trabalho é tentar diminuir esta lacuna entre o discurso e a práxis. Entre princípios abstratos e implementação técnica. Neste trabalho, buscamos introduzir o leitor ao tema da Ética e Segurança da IA. Ao mesmo tempo, apresentamos uma série de ferramentas para auxiliar desenvolvedores de sistemas inteligentes a desenvolver “bons” modelos. Este trabalho é um guia em desenvolvimento publicado em inglês e português. Contribuições e sugestões são bem vindas. (shrink)

This essay seeks to understand what it means for the human collective when AI technologies have become a predominant force in each of our lives through identifying three moral dilemmas (i.e., tragedy of the commons, tragedy of commonsense morality, tragedy of apathy) that shape human choices. In the first part, we articulate AI-driven versions of the three moral dilemmas. Then, in the second part, drawing from evolutionary psychology, existentialism, and East Asian philosophies, we argue that a deep appreciation of three (...) shades of human finitude can help us mitigate harmful effects of the AI-driven versions of the three tragedies and even transcend them. (shrink)

The potential capacity for robots to deceive has received considerable attention recently. Many papers focus on the technical possibility for a robot to engage in deception for beneficial purposes (e.g. in education or health). In this short experimental paper, I focus on a more paradigmatic case: Robot lying (lying being the textbook example of deception) for nonbeneficial purposes as judged from the human point of view. More precisely, I present an empirical experiment with 399 participants which explores the following three (...) questions: (i) Are ordinary people willing to ascribe intentions to deceive to artificial agents? (ii) Are they as willing to judge a robot lie as a lie as they would be when human agents engage in verbal deception? (iii) Do they blame a lying artificial agent to the same extent as a lying human agent? The response to all three questions is a resounding yes. This, I argue, implies that robot deception and its normative consequences deserve considerably more attention than it presently attracts. (shrink)

Large Language Models (LLMs) like ChatGPT were trained on human conversation, but in the future they will also train us. As chatbots speak from our smartphones and customer service helplines, they will become a part of everyday life and a growing share of all the conversations we ever have. It’s hard to doubt this will have some effect on us. Here I explore a specific concern about the impact of artificial conversation on our capacity to deliberate and hold ourselves accountable (...) to reason – that is, to be autonomous, in Kant’s sense of the term. I develop ideas from psychologist Jean Piaget to show how chatbots are autonomy traps: their deference to our commands tempts us into venting authoritarian whims, ultimately weakening our own self-control. I argue that the Kantian tradition, including Piaget and sociologist Emile Durkheim, offers powerful conceptual resources for resisting this slide. But it will require us to do something that may seem bizarre: we will need to treat mindless chatbots as if they are autonomous persons too. (shrink)

Abstract: As there are no visible ways to create safe self-improving superintelligence, but it is looming, we probably need temporary ways to prevent its creation. The only way to prevent it, is to create special AI, which is able to control and monitor all places in the world. The idea has been suggested by Goertzel in form of AI Nanny, but his Nanny is still superintelligent and not easy to control, as was shown by Bensinger at al. We explore here (...) the ways to create the safest and simplest form of AI, which may work as AI Nanny. Such AI system will be enough to solve most problems, which we expect the AI will solve, including control of robotics, acceleration of the medical research, but will present less risk, as it will be less different from humans. As AI police, it will work as operation system for most computers, producing world surveillance system, which will be able to envision and stop any potential terrorists and bad actors in advance. As uploading technology is lagging, and neuromorphic AI is intrinsically dangerous, the most plausible way to human-based AI Nanny is either functional model of the human mind or a Narrow-AI empowered group of people. (shrink)

Abstract: The field of artificial general intelligence (AGI) safety is quickly growing. However, the nature of human values, with which future AGI should be aligned, is underdefined. Different AGI safety researchers have suggested different theories about the nature of human values, but there are contradictions. This article presents an overview of what AGI safety researchers have written about the nature of human values, up to the beginning of 2019. 21 authors were overviewed, and some of them have several theories. A (...) theory classification method is suggested, where the theories are judged according to the level of their complexity and behaviorists-internalists scale, as well as the level of their generality-humanity. We suggest that a multiplicity of well-supported theories means that the nature of human values is difficult to define, and some meta-level theory is needed. (shrink)

Ryan Tonkens (2009) has issued a seemingly impossible challenge, to articulate a comprehensive ethical framework within which artificial moral agents (AMAs) satisfy a Kantian inspired recipe - both "rational" and "free" - while also satisfying perceived prerogatives of Machine Ethics to create AMAs that are perfectly, not merely reliably, ethical. Challenges for machine ethicists have also been presented by Anthony Beavers and Wendell Wallach, who have pushed for the reinvention of traditional ethics in order to avoid "ethical nihilism" due to (...) the reduction of morality to mechanical causation, and for redoubled efforts toward a comprehensive vision of human ethics to guide machine ethicists on the issue of moral agency. Options thus present themselves: reinterpret traditional ethics in a way that affords a comprehensive account of moral agency inclusive of both artificial and natural agents, “muddle through” regardless, or give up on the possibility. This paper pursues the first option, meets Tonkens' "challenge" and addresses Wallach's concerns through Beaver's proposed means, by "landscaping" traditional moral theory in resolution of the necessary comprehensive and inclusive account that at once draws into question the stated goals of Machine Ethics, itself. (shrink)

The AI Robotics Ethics Society (AIRES) is a non-profit organization founded in 2018 by Aaron Hui to promote awareness and the importance of ethical implementation and regulation of AI. AIRES is now an organization with chapters at universities such as UCLA (Los Angeles), USC (University of Southern California), Caltech (California Institute of Technology), Stanford University, Cornell University, Brown University, and the Pontifical Catholic University of Rio Grande do Sul (Brazil). AIRES at PUCRS is the first international chapter of AIRES, and (...) as such, we are committed to promoting and enhancing the AIRES Mission. Our mission is to focus on educating the AI leaders of tomorrow in ethical principles to ensure that AI is created ethically and responsibly. As there are still few proposals for how we should implement ethical principles and normative guidelines in the practice of AI system development, the goal of this work is to try to bridge this gap between discourse and praxis. Between abstract principles and technical implementation. In this work, we seek to introduce the reader to the topic of AI Ethics and Safety. At the same time, we present several tools to help developers of intelligent systems develop "good" models. This work is a developing guide published in English and Portuguese. Contributions and suggestions are welcome. (shrink)

This paper examines the practice of using predictive systems to lengthen the prison sentences of convicted persons when the systems forecast a higher likelihood of re-offense or re-arrest. There has been much critical discussion of technologies used for sentencing, including questions of bias and opacity. However, there hasn’t been a discussion of whether this use of predictive systems makes sense in the first place. We argue that it does not by showing that there is no plausible theory of punishment that (...) supports it. (shrink)

The field of AI safety aims to prevent increasingly capable artificially intelligent systems from causing humans harm. Research on moral alignment is widely thought to offer a promising safety strategy: if we can equip AI systems with appropriate ethical rules, according to this line of thought, they'll be unlikely to disempower, destroy or otherwise seriously harm us. Deontological morality looks like a particularly attractive candidate for an alignment target, given its popularity, relative technical tractability and commitment to harm-avoidance principles. I (...) argue that the connection between moral alignment and safe behavior is more tenuous than many have hoped. In general, AI systems can possess either of these properties in the absence of the other, and we should favor safety when the two conflict. In particular, advanced AI systems governed by standard versions of deontology need not be especially safe. (shrink)

There has been an increasing interest into how to build Artificial Moral Agents (AMAs) that make moral decisions on the basis of causation rather than mere correction. One promising avenue for achieving this is to use a causal modelling approach. This paper explores an open and important problem with such an approach; namely, the problem of what makes a causal model an appropriate model. I explore why we need to establish criteria for what makes a model appropriate, and offer-up such (...) criteria which appeals to normative considerations. (shrink)

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)

The creation of artificial moral systems requires us to make difficult choices about which of varying human value sets should be instantiated. The industry-standard approach is to seek and encode moral consensus. Here we argue, based on evidence from empirical psychology, that encoding current moral consensus risks reinforcing current norms, and thus inhibiting moral progress. However, so do efforts to encode progressive norms. Machine ethics is thus caught between a rock and a hard place. The problem is particularly acute when (...) progress beyond prevailing moral norms is particularly urgent, as is currently the case due to the inadequacy of prevailing moral norms in the face of the climate and ecological crisis. (shrink)

Abstract: One approach to alignment with human values in AI and robotics is to engineer artificial systems isomorphically with human beings. One persistent problem is that different human beings champion different value orientations as ideal, exclusive of others, thereby confounding worries about AI. Prior work proposed a view of human development of purpose and source of meaning in life in terms of project ideal conditions, in effect establishing lifelong value orientations according to which intermediate situations are evaluated. The idea is (...) that robots designed accordingly may autonomously align with human values through similar developmental processes, to realize project ideal conditions through iterative interaction with social and object environments. The present work considers two apparently mutually exclusive views on value alignment, that of St. Augustine and contemporary cognitive scientists including Gregg Northoff. The present work describes these views as divergent error theories which, due to variable development of variable cognitive potential, present to different subjects as mutually exclusive yet accurate accounts of personal experience. Specifically, the hypothesis proposed is that differential development of spindle neural projections during adolescence establishes lifelong connections between prior established relatively immediate routine processes (entrained during childhood) and later developing higher-level social and self-processes, with these projections hard-wiring lifelong value orientations. Insights from this study are applied to considerations for AI value alignment and robot religion. Robot experiments informed by this study may eventually represent such differences by design, with autonomous robots developing religious associations with temporally distal project ideal conditions through love for humanity, as described by Augustine, contrary to contemporary accounts emphasizing selfish fit to passing norms. Finally, the motivating hope of this study is that risks associated with value misaligned robots may be obviated by adequately informed designers. (shrink)

Vision is an important metaphor in ethical and political questions of knowledge. The feminist philosopher Donna Haraway points out the “perverse” nature of an intrusive, alienating, all-seeing vision (to which we might cry out “stop looking at me!”), but also encourages us to embrace the embodied nature of sight and its promises for genuinely situated knowledge. Current technologies of machine vision – surveillance cameras, drones (for war or recreation), iPhone cameras – are usually construed as instances of the former rather (...) than the latter, and for good reasons. However, although in no way attempting to diminish the real suffering these technologies have brought about in the world, I make the case for understanding technologies of computer vision as material instances of embodied seeing and situated knowing. Furthermore, borrowing from Iris Murdoch’s concept of moral vision, I suggest that these technologies direct our labor towards self-reflection in ethically significant ways. My approach draws upon paradigms in computer vision research, phenomenology, and feminist epistemology. Ultimately, this essay is an argument for directing more philosophical attention from merely criticizing technologies of vision as ethically deficient towards embracing them as complex, methodologically and epistemologically important objects. (shrink)

We paraphrase Descartes’ famous dictum in the area of AI ethics where the “I doubt and therefore I am” is suggested as a necessary aspect of morality. Therefore AI, which cannot doubt itself, cannot possess moral agency. Of course, this is not the end of the story. We explore various aspects of the human mind that substantially differ from AI, which includes the sensory grounding of our knowing, the act of understanding, and the significance of being able to doubt ourselves. (...) The foundation of our argument is the discipline of ethics, one of the oldest and largest knowledge projects of human history, yet, we seem only to be beginning to get a grasp of it. After a couple of thousand years of studying the ethics of humans, we (humans) arrived at a point where moral psychology suggests that our moral decisions are intuitive, and all the models from ethics become relevant only when we explain ourselves. This recognition has a major impact on what and how we can do regarding AI ethics. We do not offer a solution, we explore some ideas and leave the problem open, but we hope somewhat better understood than before our study. (shrink)

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

The field of value alignment, or more broadly machine ethics, is becoming increasingly important as artificial intelligence developments accelerate. By ‘alignment’ we mean giving a generally intelligent software system the capability to act in ways that are beneficial, or at least minimally harmful, to humans. There are a large number of techniques that are being experimented with, but this work often fails to specify what values exactly we should be aligning. When making a decision, an agent is supposed to maximize (...) the expected utility of its value function. Classically, this has been referred to as happiness, but this is just one of many things that people value. -/- In order to resolve this issue, we need to determine a set of human values that represent humanity's interests. Although this problem might seem intractable, research shows that people of various cultures and religions actually share more in common than they realize. In this book we review world religions, moral philosophy and evolutionary psychology to elucidate a common set of shared values. We then show how these values can be used to address the alignment problem and conclude with problems and goals for future research. -/- The key audience for this book will be researchers in the field of ethics and artificial intelligence who are interested in, or working on this problem. These people will come from various professions and include philosophers, computer programmers and psychologists, as the problem itself is multi-disciplinary. (shrink)

The generative AI boom is unleashing its minions. Enterprise software vendors have rolled out legions of automated assistants that use large language model (LLM) technology, such as ChatGPT, to offer users helpful suggestions or to execute simple tasks. These so-called copilots and chatbots can increase productivity and automate tedious manual work. In this article, we explain how that leads to the risk that users' ethical competence may degrade over time — and what to do about it.

This article argues that existing approaches to programming ethical AI fail to resolve a serious moral-semantic trilemma, generating interpretations of ethical requirements that are either too semantically strict, too semantically flexible, or overly unpredictable. This paper then illustrates the trilemma utilizing a recently proposed ‘general ethical dilemma analyzer,’ GenEth. Finally, it uses empirical evidence to argue that human beings resolve the semantic trilemma using general cognitive and motivational processes involving ‘mental time-travel,’ whereby we simulate different possible pasts and futures. I (...) demonstrate how mental time-travel psychology leads us to resolve the semantic trilemma through a six-step process of interpersonal negotiation and renegotiation, and then conclude by showing how comparative advantages in processing power would plausibly cause AI to use similar processes to solve the semantic trilemma more reliably than we do, leading AI to make better moral-semantic choices than humans do by our very own lights. (shrink)

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

As artificial intelligence becomes more sophisticated and robots approach autonomous decision-making, debates about how to assign moral responsibility have gained importance, urgency, and sophistication. Answering Stenseke’s (2022a) call for scaffolds that can help us classify views and commitments, we think the current debate space can be represented hierarchically, as answers to key questions. We use the resulting taxonomy of five stances to differentiate—and defend—what is known as the “blank check” proposal. According to this proposal, a person activating a robot could (...) willingly make themselves answerable for whatever events ensue, even if those events stem from the robot’s autonomous decision(s). This blank check solution was originally proposed in the context of automated warfare (Champagne & Tonkens, 2015), but we extend it to cover all robots. We argue that, because moral answerability in the blank check is accepted voluntarily and before bad outcomes are known, it proves superior to alternative ways of assigning blame. We end by highlighting how, in addition to being just, this self-initiated and prospective moral answerability for robot harm provides deterrence that the four other stances cannot match. (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)

Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is often defined too imprecisely because its multifaceted nature and the sociotechnical structure of AI systems imply a variety of values, practices, and measures to which accountability in AI can refer. We address this lack of clarity by defining accountability in terms of answerability, identifying three conditions of possibility (authority recognition, interrogation, and limitation of power), and an architecture of seven features (context, range, agent, forum, standards, process, (...) and implications). We analyse this architecture through four accountability goals (compliance, report, oversight, and enforcement). We argue that these goals are often complementary and that policy-makers emphasise or prioritise some over others depending on the proactive or reactive use of accountability and the missions of AI governance. (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)

Meet Tega. Blue, fluffy, and AI-enabled, Tega is a relational robot: a robot designed to form relationships with humans. Created to aid in early childhood education, Tega talks with children, plays educational games with them, solves puzzles, and helps in creative activities like making up stories and drawing. Children are drawn to Tega, describing him as a friend, and attributing thoughts and feelings to him ("he's kind," "if you just left him here and nobody came to play with him, he (...) might be sad"). Scholars and members of the public alike have raised the alarm about relational robots, worrying that the relationships that people, and especially children, form with such robots are objectionably inauthentic. We, members of an interdisciplinary team that developed and studies Tega, make this inauthenticity worry precise and offer practical recommendations for addressing it. We distinguish two kinds of (in)authenticity -- inauthenticity as unreality, and inauthenticity as deception -- arguing that neither is just what others have thought it is. With our distinction in hand, we argue that the authenticity concern can be met only through co-design methods -- methods that give stakeholders of all kinds (e.g. parents, educators, and children themselves) a genuine say in how relational robots are built. (shrink)

Robert Sparrow (among others) claims that if an autonomous weapon were to commit a war crime, it would cause harm for which no one could reasonably be blamed. Since no one would bear responsibility for the soldier’s share of killing in such cases, he argues that they would necessarily violate the requirements of jus in bello, and should be prohibited by international law. I argue this view is mistaken and that our moral understanding of war is sufficient to determine blame (...) for any wrongful killing done by autonomous weapons. Analyzing moral responsibility for autonomous weapons starts by recognizing that although they are capable of causing moral consequences, they are neither praiseworthy nor blameworthy in the moral sense. As such, their military role is that of a tool, albeit a rather sophisticated one, and responsibility for their use is roughly analogous to that of existing “smart” weapons. There will likely be some difficulty in managing these systems as they become more intelligent and more prone to unpredicted behavior, but the moral notion of shared responsibility and the legal notion of command responsibility are sufficient to locate responsibility for their use. (shrink)

We propose four policies of ethical design of human-grade Artificial Intelligence. Two of our policies are precautionary. Given substantial uncertainty both about ethical theory and about the conditions under which AI would have conscious experiences, we should be cautious in our handling of cases where different moral theories or different theories of consciousness would produce very different ethical recommendations. Two of our policies concern respect and freedom. If we design AI that deserves moral consideration equivalent to that of human beings, (...) that AI should be designed with self-respect and with the freedom to explore values other than those we might impose. We are especially concerned about the temptation to create human-grade AI pre-installed with the desire to cheerfully sacrifice itself for its creators’ benefit. (shrink)

As we build increasingly intelligent machines, we confront difficult questions about how to specify their objectives. One approach, which we call human-centered, tasks the machine with the objective of learning and satisfying human objectives by observing our behavior. This paper considers how human-centered AI should conceive the humans it is trying to help. We argue that an Aristotelian model of human agency has certain advantages over the currently dominant theory drawn from economics.

Non possiamo immaginare un mondo senza le nostre tecnologie e i nostri strumenti. In molti modi, le nostre tecnologie sono ciò che ci definisce come esseri umani, separandoci dal resto del regno animale. Tuttavia, pensare alle nostre tecnologie come semplici strumenti, strumenti che possono essere usati nel bene o nel male, ci rende vulnerabili agli effetti sistemici e duraturi che le tecnologie hanno sulla nostra società, sui comportamenti, e sulle generazioni future. Oggetti Buoni esplora come le tecnologie incarnano i valori (...) dei loro creatori. Prendendo questo approccio unico per guardare alle nostre importanti tecnologie, questa è la prima monografia in Italiano che esplora come le tecnologie siano sensibili al valore, dimostrando come possiamo orientare il nostro futuro attraverso un design intelligente ed etico. Piuttosto che aspettare il futuro, Oggetti Buoni ci mostra come possiamo progettare il nostro futuro per i valori che riteniamo più importanti. (shrink)

The central challenge of “machine ethics” is to build autonomous machine agents that act morally rightly. But how can we build autonomous machine agents that act morally rightly, given reasonable disputes over what is right and wrong in particular cases? In this chapter, I argue that Immanuel Kant’s political philosophy can provide an important part of the answer.

Practical quantum computing devices and their applications to AI in particular are presently mostly speculative. Nevertheless, questions about whether this future technology, if achieved, presents any special ethical issues are beginning to take shape. As with any novel technology, one can be reasonably confident that the challenges presented by "quantum AI" will be a mixture of something new and something old. Other commentators (Sevilla & Moreno 2019), have emphasized continuity, arguing that quantum computing does not substantially affect approaches to value (...) alignment methods for AI, although they allow that further questions arise concerning governance and verification of quantum AI applications. In this brief paper, we turn our attention to the problem of identifying as-yet-unknown discontinuities that might result from quantum AI applications. Wise development, introduction, and use of any new technology depends on successfully anticipating new modes of failure for that technology. This requires rigorous efforts to break systems in protected sandboxes, and it must be conducted at all stages of technology design, development, and deployment. Such testing must also be informed by technical expertise but cannot be left solely to experts in the technology because of the history of failures to predict how non-experts will use or adapt to new technologies. This interplay between experts and non-experts may be particularly acute for quantum AI because quantum mechanics is notoriously difficult to understand. (As Richard Feynman quipped, "Anyone who claims to understand quantum mechanics is either lying or crazy.") We will discuss the extent to which the difficulties in understanding the physics underlying quantum computing challenges attempts to anticipate new failure modes that might be introduced in AI applications intended for unsupervised operation in the public sphere. (shrink)

This paper presents a new trilemma with respect to resolving the control and alignment problems in machine ethics. Section 1 outlines three possible types of artificial moral agents (AMAs): (1) 'Inhuman AMAs' programmed to learn or execute moral rules or principles without understanding them in anything like the way that we do; (2) 'Better-Human AMAs' programmed to learn, execute, and understand moral rules or principles somewhat like we do, but correcting for various sources of human moral error; and (3) 'Human-Like (...) AMAs' programmed to understand and apply moral values in broadly the same way that we do, with a human-like moral psychology. Sections 2–4 then argue that each type of AMA generates unique control and alignment problems that have not been fully appreciated. Section 2 argues that Inhuman AMAs are likely to behave in inhumane ways that pose serious existential risks. Section 3 then contends that Better-Human AMAs run a serious risk of magnifying some sources of human moral error by reducing or eliminating others. Section 4 then argues that Human-Like AMAs would not only likely reproduce human moral failures, but also plausibly be highly intelligent, conscious beings with interests and wills of their own who should therefore be entitled to similar moral rights and freedoms as us. This generates what I call the New Control Problem: ensuring that humans and Human-Like AMAs exert a morally appropriate amount of control over each other. Finally, Section 5 argues that resolving the New Control Problem would, at a minimum, plausibly require ensuring what Hume and Rawls term ‘circumstances of justice’ between humans and Human-Like AMAs. But, I argue, there are grounds for thinking this will be profoundly difficult to achieve. I thus conclude on a skeptical note. Different approaches to developing ‘safe, ethical AI’ generate subtly different control and alignment problems that we do not currently know how to adequately resolve, and which may or may not be ultimately surmountable. (shrink)

This contribution aims to investigate not so much the ethical implications of utilizing intelligent machines in specific contexts, (human resources, self-driving cars, robotic hospital assistants, et cetera), but the premises of their widespread use. In particular, it aims to analyze the complex concept of decision making - the cornerstone of any ethical argument - from a dual point of view: decision making assigned to machines and decision making enacted by machines. Analyzing the role of algorithms in decision making, we suggest (...) a redefinition of the ethical vocabulary for AI, specifically regarding the concept of agency. (shrink)

While autonomous vehicles (AVs) are not designed to harm people, harming people is an inevitable by-product of their operation. How are AVs to deal ethically with situations where harming people is inevitable? Rather than focus on the much-discussed question of what choices AVs should make, we can also ask the much less discussed question of who gets to decide what AVs should do in such cases. Here there are two key options: AVs with a personal ethics setting (PES) or an (...) “ethical knob” that end users can control or AVs with a mandatory ethics setting (MES) that end users cannot control. Which option, a PES or an MES, is best and why? This chapter argues, by drawing on the choice architecture literature, in favor of a hybrid view that requires mandated default choice settings while allowing for limited end user control. (shrink)

This paper considers ethical concerns with regard to replacing human relations with humanoid robots. Many have written about the impact that certain types of relations with robots may have on us, and why we should be concerned about robots replacing human relations. There has, however, been no consideration of this issue from an African philosophical perspective. Ubuntu philosophy provides a novel perspective on how relations with robots may impact our own moral character and moral development. This paper first discusses what (...) humanoid robots are, why and how humans tend to anthropomorphise them, and what the literature says about robots crowding out human relations. It then explains the ideal of becoming “fully human”, which pertains to being particularly moral in character. In ubuntu philosophy, we are not only biologically human, but must strive to become better, more moral versions of ourselves, to become fully human. We can become fully human by having other regarding traits or characteristics within the context of interdependent, or humane, relationships (such as by exhibiting human equality, reciprocity, or solidarity). This concept of becoming fully human is important in ubuntu philosophy. Having explained that idea, the main argument of the paper is then put forward: that treating humanoid robots as if they are human is morally concerning if they crowd out human relations, because such relations prevent us from becoming fully human. This is because we cannot experience human equality, solidarity, and reciprocity with robots, which can be seen to characterise interdependent, or humane, relations with human beings. (shrink)

The expanding social role and continued development of artificial intelligence (AI) needs theological investigation of its anthropological and moral potential. A pragmatic theological anthropology adapted for AI can characterize moral AI as experiencing its natural, social, and moral world through interpretations of its external reality as well as its self-reckoning. Systems theory can further structure insights into an AI social self that conceptualizes itself within Ignacio Ellacuria’s historical reality and its moral norms through Thomistic ideogenesis. This enables a conceptualization process (...) capable of carrying moral weight and grounded in reality; structures the experience of an AI emergent self into multiple levels of interpretation; and drives a multi-level systems architecture for moral AI. Modeling AI’s interpretive experience and self-reckoning as a causal, sociotechnical, and moral actor can help moral AI identify conflicts between its normative values and develop the practical wisdom (phronesis) needed to apply its general moral models. (shrink)

Ex Machina is a 2014 science-fiction film written and directed by Alex Garland, centered around the creation of a human-like artificial intelligence (AI) named Ava. The plot focuses on testing Ava for consciousness by offering a unique reinterpretation of the Turing Test. The film offers an excellent thought experiment demonstrating the consequences of various approaches to a potentially conscious AI. In this paper, I will argue that intelligence testing has significant epistemological shortcomings that necessitate an ethical approach not reliant on (...) ontological commitments. As such, we should be prepared to treat AI as though it is a living being that is deserving of corresponding moral obligations. For a sufficiently human-like AI, such as Ava, I will argue that socio-relational ethics is the best starting point in order to nurture the machine towards ethical proclivities, as evident by the consequences of the characters’ behavior throughout the film. I conclude that intelligence testing is an insufficient determinant of machine ethics, that the project of machine ethics should focus as much on how we treat AI as how AI treats us, and that from a consequentialist perspective it is better to treat machines ethically before they gain consciousness rather than after. (shrink)

Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the (...) difficult task of operationalizing the principles of beneficence, non-maleficence and patient autonomy, and describe how we selected suitable input parameters that we extracted from a training dataset of clinical cases. The first performance results are promising, but an algorithmic approach to ethics also comes with several weaknesses and limitations. Should one really entrust the sensitive domain of clinical ethics to machine intelligence? (shrink)

As ever more advanced digital systems are created, it becomes increasingly likely that some of these systems will be digital minds, i.e. digital subjects of experience. With digital minds comes the risk of digital suffering. The problem of digital suffering is that of mitigating this risk. We argue that the problem of digital suffering is a high stakes moral problem and that formidable epistemic obstacles stand in the way of solving it. We then propose a strategy for solving it: Access (...) Monitor Prevent (AMP). AMP uses a ‘dancing qualia’ argument to link the functional states of certain digital systems to their experiences—this yields epistemic access to digital minds. With that access, we can prevent digital suffering by only creating advanced digital systems that we have such access to, monitoring their functional profiles, and preventing them from entering states with functional markers of suffering. After introducing and motivating AMP, we confront limitations it faces and identify some options for overcoming them. We argue that AMP fits especially well with—and so provides a moral reason to prioritize—one approach to creating such systems: whole brain emulation. We also contend that taking other paths to digital minds would be morally risky. (shrink)

Although virtue ethics has repeatedly been proposed as a suitable framework for the development of artificial moral agents, it has been proven difficult to approach from a computational perspective. In this work, we present the first technical implementation of artificial virtuous agents in moral simulations. First, we review previous conceptual and technical work in artificial virtue ethics and describe a functionalistic path to AVAs based on dispositional virtues, bottom-up learning, and top-down eudaimonic reward. We then provide the details of a (...) technical implementation in a moral simulation based on a tragedy of the commons scenario. The experimental results show how the AVAs learn to tackle cooperation problems while exhibiting core features of their theoretical counterpart, including moral character, dispositional virtues, learning from experience, and the pursuit of eudaimonia. Ultimately, we argue that virtue ethics provides a compelling path toward morally excellent machines and that our work provides an important starting point for such endeavors. (shrink)

Recent advancements in artificial intelligence have fueled widespread academic discourse on the ethics of AI within and across a diverse set of disciplines. One notable subfield of AI ethics is machine ethics, which seeks to implement ethical considerations into AI systems. However, since different research efforts within machine ethics have discipline-specific concepts, practices, and goals, the resulting body of work is pestered with conflict and confusion as opposed to fruitful synergies. The aim of this paper is to explore ways to (...) alleviate these issues, both on a practical and theoretical level of analysis. First, we describe two approaches to machine ethics: the philosophical approach and the engineering approach and show how tensions between the two arise due to discipline specific practices and aims. Using the concept of disciplinary capture, we then discuss potential promises and pitfalls to cross-disciplinary collaboration. Drawing on recent work in philosophy of science, we finally describe how metacognitive scaffolds can be used to avoid epistemological obstacles and foster innovative collaboration in AI ethics in general and machine ethics in particular. (shrink)

Artificial Intelligence (AI) systems are ubiquitous. From social media timelines, video recommendations on YouTube, and the kinds of adverts we see online, AI, in a very real sense, filters the world we see. More than that, AI is being embedded in agent-like systems, which might prompt certain reactions from users. Specifically, we might find ourselves feeling frustrated if these systems do not meet our expectations. In normal situations, this might be fine, but with the ever increasing sophistication of AI-systems, this (...) might become a problem. While it seems unproblematic to realize that being angry at your car for breaking down is unfitting, can the same be said for AI-systems? In this paper, therefore, I will investigate the so-called “reactive attitudes”, and their important link to our responsibility practices. I then show how within this framework there exist exemption and excuse conditions, and test whether our adopting the “objective attitude” toward agential AI is justified. I argue that such an attitude is appropriate in the context of three distinct senses of responsibility (answerability, attributability, and accountability), and that, therefore, AI-systems do not undermine our responsibility ascriptions. (shrink)

One of the primary, if not most critical, difficulties in the design and implementation of autonomous systems is the black-boxed nature of the decision-making structures and logical pathways. How human values are embodied and actualised in situ may ultimately prove to be harmful if not outright recalcitrant. For this reason, the values of stakeholders become of particular significance given the risks posed by opaque structures of intelligent agents (IAs). This paper explores how decision matrix algorithms, via the belief-desire-intention model for (...) autonomous vehicles, can be designed to minimize the risks of opaque architectures. Primarily through an explicit orientation towards designing for the values of explainability and verifiability. In doing so, this research adopts the Value Sensitive Design (VSD) approach as a principled framework for the incorporation of such values within design. VSD is recognized as a potential starting point that offers a systematic way for engineering teams to formally incorporate existing technical solutions within ethical design, while simultaneously remaining pliable to emerging issues and needs. It is concluded that the VSD methodology offers at least a strong enough foundation from which designers can begin to anticipate design needs and formulate salient design flows that can be adapted to the changing ethical landscapes required for utilisation in autonomous vehicles. (shrink)

Do we suddenly become justified in treating robots like humans by positing new notions like “artificial moral agency” and “artificial moral responsibility”? I answer no. Or, to be more precise, I argue that such notions may become philosophically acceptable only after crucial metaphysical issues have been addressed. My main claim, in sum, is that “artificial moral responsibility” betokens moral responsibility to the same degree that a “fake orgasm” betokens an orgasm.

Experts in Artificial Intelligence (AI) development predict that advances in the dvelopment of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance isn't done with prudence, it can result in negative outcomes for humanity. For this reason, several researchers in the area are trying to develop a robust, beneficial, and safe concept of artificial intelligence. Currently, several of the open problems in the field of AI research arise from the difficulty of avoiding unwanted (...) behaviors of intelligent agents, and at the same time specifying what we want such systems to do. It is of utmost importance that artificial intelligent agents have their values aligned with human values, given the fact that we cannot expect an AI to develop our moral preferences simply because of its intelligence, as discussed in the Orthogonality Thesis. Perhaps this difficulty comes from the way we are addressing the problem of expressing objectives, values, and ends, using representational cognitive methods. A solution to this problem would be the dynamic cognitive approach proposed by Dreyfus, whose phenomenological philosophy defends that the human experience of being-in-the-world cannot be represented by the symbolic or connectionist cognitive methods. A possible approach to this problem would be to use theoretical models such as SED (situated embodied dynamics) to address the values learning problem in AI. (shrink)

Autonomous Weapons Systems (AWS) have not gained a good reputation in the past. This attitude is odd if we look at the discussion of other-usually highly anticipated-AI-technologies, like autonomous vehicles (AVs); whereby even though these machines evoke very similar ethical issues, philosophers' attitudes towards them are constructive. In this article, I try to prove that there is an unjust bias against AWS because almost every argument against them is effective against AVs too. I start with the definition of "AWS." Then, (...) I arrange my arguments by the Just War Theory (JWT), covering jus ad bellum, jus in bello and jus post bellum problems. Meanwhile, I draw attention to similar problems against other AI-technologies outside the JWT framework. Finally, I address an exception, as addressed by Duncan Purves, Ryan Jenkins and Bradley Strawser, who realized the unjustified double standard, and deliberately tried to construct a special argument which rules out only AWS. (shrink)

Social robots are robots that can interact socially with humans. As social robots and the artificial intelligence that powers them becomes more advanced, they will likely take on more social and work roles. This has many important ethical implications. In this paper, we focus on one of the most central of these, the impacts that social robots can have on human autonomy. We argue that, due to their physical presence and social capacities, there is a strong potential for social robots (...) to enhance human autonomy as well as several ways they can inhibit and disrespect it. We argue that social robots could improve human autonomy by helping us to achieve more valuable ends, make more authentic choices, and improve our autonomy competencies. We also argue that social robots have the potential to harm human autonomy by instead leading us to achieve fewer valuable ends ourselves, make less authentic choices, decrease our autonomy competencies, make our autonomy more vulnerable, and disrespect our autonomy. Whether the impacts of social robots on human autonomy are positive or negative overall will depend on the design, regulation, and use we make of social robots in the future. (shrink)

Examining AI spirituality can illuminate problematic assumptions about human spirituality and AI cognition, suggest possible directions for AI development, reduce uncertainty about future AI, and yield a methodological lens sufficient to investigate human-AI sociotechnical interaction and morality. Incompatible philosophical assumptions about human spirituality and AI limit investigations of both and suggest a vast gulf between them. An emergentist approach can replace dualist assumptions about human spirituality and identify emergent behavior in AI computation to overcome overly reductionist assumptions about computation. Using (...) general systems theory to organize models of human experience yields insight into human morality and spirituality, upon which AI modeling can also draw. In this context, the pragmatist Josiah Royce’s semiotic philosophy of spirituality identifies unanticipated overlap between symbolic AI and spirituality and suggests criteria for a human-AI community focused on modeling morality that would result in an emergent Interpreter-Spirit sufficient to influence the ongoing development of human and AI morality and spirituality. (shrink)

The use of counterfactuals for considerations of algorithmic fairness and explainability is gaining prominence within the machine learning community and industry. This paper argues for more caution with the use of counterfactuals when the facts to be considered are social categories such as race or gender. We review a broad body of papers from philosophy and social sciences on social ontology and the semantics of counterfactuals, and we conclude that the counterfactual approach in machine learning fairness and social explainability can (...) require an incoherent theory of what social categories are. Our findings suggest that most often the social categories may not admit counterfactual manipulation, and hence may not appropriately satisfy the demands for evaluating the truth or falsity of counterfactuals. This is important because the wide- spread use of counterfactuals in machine learning can lead to misleading results when applied in high-stakes domains. Accordingly, we argue that even though counterfactuals play an essential part in some causal inferences, their use for questions of algorithmic fairness and social explanations can create more problems than they resolve. Our positive result is a set of tenets about using counterfactuals for fairness and explanations in machine learning. (shrink)