This paper examines the role of machine functionalism, as one of the most popular positions within the philosophy of mind, in the context of the development of artificial intelligence. Our analysis starts from the idea that machine functionalism is a theory that is largely consistent with the principles behind the strong AI thesis. However, we will see that there is a convincing counter-argument against such claims, and we will problematize this issue. Also, by testing ChatGPT, as the (...) most popular publicly available AI tool, we will make an effort to figure out whether the strong AI thesis could currently even be considered a potentially sustainable principle. Since ChatGPT fails the Turing test our conclusion is that the strong AI thesis cannot be upheld even in principle, implying that the current state of this AI tool does not yet provide strong enough arguments in favor of machine functionalism. (shrink)

The advent of the intelligent robot has occupied a significant position in society over the past decades and has given rise to new issues in society. As we know, the primary aim of artificial intelligence or robotic research is not only to develop advanced programs to solve our problems but also to reproduce mental qualities in machines. The critical claim of artificial intelligence advocates is that there is no distinction between mind and machines and thus they argue that (...) there are possibilities for machine ethics, just as human ethics. Unlike computer ethics, which has traditionally focused on ethical issues surrounding human use of machines, AI or machine ethics is concerned with the behaviour of machines towards human users and perhaps other machines as well, and the ethicality of these interactions. The ultimate goal of machine ethics, according to the AI scientists, is to create a machine that itself follows an ideal ethical principle or a set of principles; that is to say, it is guided by this principle or these principles in decisions it makes about possible courses of action it could takea. Thus, machine ethics task of ensuring ethical behaviour of an artificial agent. Although, there are many philosophical issues related to artificial intelligence, but our attempt in this paper is to discuss, first, whether ethics is the sort of thing that can be computed. Second, if we are ascribing mind to machines, it gives rise to ethical issues regarding machines. And if we are not drawing the difference between mind and machines, we are not only redefining specifically human mind but also the society as a whole. Having a mind is, among other things, having the capacity to make voluntary decisions and actions. The notion of mind is central to our ethical thinking, and this is because the human mind is self-conscious, and this is a property that machines lack, as yet. (shrink)

This article identifies and examines a tension in mental health researchers’ growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research specifically, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data (...) points. The imperatives of the “participatory turn” in mental health research may be at odds with the (often unquestioned) assumptions and data collection methods of AI/ML approaches. This article aims to show why this is a problem and how it might be addressed. (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)

Policymakers are responsible for key decisions about political governance. Usually, they are selected or elected based on experience and then supported in their decision-making by the additional counsel of subject experts. Those satisfied with this system believe these individuals – generally speaking – will have the right intuitions about the best types of action. This is important because political decisions have ethical implications; they affect how we all live in society. Nevertheless, there is a wealth of research that cautions against (...) trusting human judgment as it can be severely flawed. This paper will look at the root causes of the most common errors of human judgment before arguing – contra the instincts of many – that future AI systems could take a range of political decisions more reliably. I will argue that, if/when engineers establish ethically robust systems, governments will have a moral obligation to refer to them as a part of decision-making. (shrink)

Our ability to locate moral responsibility is often thought to be a necessary condition for conducting morally permissible medical practice, engaging in a just war, and other high-stakes endeavors. Yet, with increasing reliance upon artificially intelligent systems, we may be facing a wideningresponsibility gap, which, some argue, cannot be bridged by traditional concepts of responsibility. How then, if at all, can we make use of crucial emerging technologies? According to Colin Allen and Wendell Wallach, the advent of so-called ‘artificial (...) moral agents’ (AMAs) is inevitable. Still, this notion may seem to push back the problem, leaving those who have an interest in developing autonomous technology with a dilemma. We may need to scale-back our efforts at deploying AMAs (or at least maintain human oversight); otherwise, we must rapidly and drastically update our moral and legal norms in a way that ensures responsibility for potentially avoidable harms. This paper invokes contemporary accounts of responsibility in order to show how artificially intelligent systems might be held responsible. Although many theorists are concerned enough to develop artificial conceptions ofagencyor to exploit our present inability to regulate valuable innovations, the proposal here highlights the importance of—and outlines a plausible foundation for—a workable notion ofartificial moral responsibility. (shrink)

This paper concerns top-down approaches in machine ethics. It is divided into three main parts. First, I briefly describe top-down design approaches, and in doing so I make clear what those approaches are committed to and what they involve when it comes to training an AI to behave ethically. In the second part, I formulate two underappreciated motivations for endorsing them, one relating to predictability of machine behavior and the other relating to scrutability of machine decision-making. (...) Finally, I present three major worries about such approaches, and I attempt to show that advocates of top-down approaches have some plausible avenues of response. I focus most of my attention on what I call the ‘technical manual objection’ to top-down approaches, inspired by the work of Annas (2004). In short, the idea is that top-down approaches treat ethical decision-making as being merely a matter of following some ethical instructions in the same way that one might follow some set of instructions contained in a technical manual (e.g., computer manual), and this invites sensible skepticism about the ethical wisdom of machines that have been trained on those approaches. I respond by claiming that the objection is successful only if it is understood as targeting machines that have certain kinds of goals, and it should not compel us to totally abandon top-down approaches. Such approaches could still be reasonably employed to design ethical AI that operate in contexts that include fairly noncontroversial answers to ethical questions. In fact, we should prefer top-down approaches when it comes to those types of context, or so I argue, due to the advantages I claim for them. (shrink)

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

The value sensitive design (VSD) approach to designing transformative technologies for human values is taken as the object of study in this chapter. VSD has traditionally been conceptualized as another type of technology or instrumentally as a tool. The various parts of VSD’s principled approach would then aim to discern the various policy requirements that any given technological artifact under consideration would implicate. Yet, little to no consideration has been given to how laws, regulations, policies and social norms engage within (...) VSD practices. Similarly, how the interactive nature of the VSD approach can, in turn, influence those directives. This is exacerbated when we consider machine ethics policy that have global consequences outside their development spheres. What constructs and models will position AI designers to engage in policy concerns? How can the design of AI policy be integrated with technical design? How might VSD be used to develop AI policy? How might law, regulations, social norms, and other kinds of policy regarding AI systems be engaged within value sensitive design? This chapter takes the VSD as its starting point and aims to determine how laws, regulations and policies come to influence how value trade-offs can be managed within VSD practices. It shows that the iterative and interactional nature of VSD both permits and encourages existing policies to be integrated both early on and throughout the design process. The chapter concludes with some potential future research programs. (shrink)

Tonkens has issued a seemingly impossible challenge, to articulate a comprehensive ethical framework within which artificial moral agents satisfy a Kantian inspired recipe—"rational" and "free"—while also satisfying perceived prerogatives of machine ethicists to facilitate the creation of AMAs that are perfectly and not merely reliably ethical. Challenges for machine ethicists have also been presented by Anthony Beavers and Wendell Wallach. Beavers pushes for the reinvention of traditional ethics to avoid "ethical nihilism" due to the reduction of (...) morality to mechanical causation. Wallach pushes for redoubled efforts toward a comprehensive account of ethics to guide machine ethicists on the issue of artificial 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, or give up on the possibility and “muddle through” regardless. This series of papers pursues the first option, meets Tonkens' "challenge" and pursues Wallach's ends through Beavers’ proposed means, by "landscaping" traditional moral theory in resolution of a comprehensive account of moral agency. This first paper sets out the challenge and establishes the tradition that Kant had inherited from Aristotle, briefly entertains an Aristotelian AMA, fields objections, and ends with unanswered questions. The next paper in this series responds to the challenge in Kantian terms, and argues that a Kantian AMA is not only a possibility for Machine ethics research, but a necessary one. (shrink)

In this paper I provide an exposition and critique of Johnson and Noorman’s (2014) three conceptualizations of the agential roles artificial systems can play. I argue that two of these conceptions are unproblematic: that of causally efficacious agency and “acting for” or surrogate agency. Their third conception, that of “autonomous agency,” however, is one I have reservations about. The authors point out that there are two ways in which the term “autonomy” can be used: there is, firstly, the engineering (...) sense of the term, which simply refers to the ability of some system to act independently of substantive human control. Secondly, there is the moral sense of the term, which has traditionally grounded many notions of human mor-al responsibility. I argue that the continued usage of “autonomy” in discussions of artificial agency complicates matters unnecessarily. This occurs in two ways: firstly, the condition of autonomy, even in its engineering sense, fails to accurately describe the way “autonomous” systems are developed in practice. Secondly, the continued usage of autonomy in the moral sense introduces unnecessary meta-physical baggage form the free will debate into discussions about moral agency. In order to understand the debate surrounding autonomy, we would therefore first need to settle many seemingly intractable metaphysical questions regarding the existence of free will in human beings. (shrink)

I compare a ‘realist’ with a ‘social–relational’ perspective on our judgments of the moral status of artificial agents (AAs). I develop a realist position according to which the moral status of a being—particularly in relation to moral patiency attribution—is closely bound up with that being’s ability to experience states of conscious satisfaction or suffering (CSS). For a realist, both moral status and experiential capacity are objective properties of agents. A social relationist denies the existence of any such objective properties (...) in the case of either moral status or consciousness, suggesting that the determination of such properties rests solely upon social attribution or consensus. A wide variety of social interactions between us and various kinds of artificial agent will no doubt proliferate in future generations, and the social–relational view may well be right that the appearance of CSS features in such artificial beings will make moral role attribution socially prevalent in human–AA relations. But there is still the question of what actual CSS states a given AA is capable of undergoing, independently of the appearances. This is not just a matter of changes in the structure of social existence that seem inevitable as human–AA interaction becomes more prevalent. The social world is itself enabled and constrained by the physical world, and by the biological features of living social participants. Properties analogous to certain key features in biological CSS are what need to be present for nonbiological CSS. Working out the details of such features will be an objective scientific inquiry. (shrink)

I discuss the realizability and the ethical ramifications of Machine Ethics, from a number of different perspectives: I label these the anthropocentric, infocentric, biocentric and ecocentric perspectives. Each of these approaches takes a characteristic view of the position of humanity relative to other aspects of the designed and the natural worlds—or relative to the possibilities of ‘extra-human’ extensions to the ethical community. In the course of the discussion, a number of key issues emerge concerning the relation between technology (...) and ethics, and the nature of what it is to have moral status. Some radical challenges to certain technological presuppositions and ramifications of the infocentric approach will be discussed. Notwithstanding the obvious tensions between the infocentric perspective on one side and the biocentric and ecocentric perspectives on the other, we will see that there are also striking parallels in the way that each of these three approaches generates challenges to an anthropocentric ethical hegemony, and possible scope for some degree of convergence. (shrink)

The purpose of this essay is to determine the domain of validity of the notions developed in Machine Ethics [ME]. To this aim, I analyse the epistemological and methodological presuppositions that lie at the root of such technological project. On this basis, I then try and develop the theoretical means to identify and deconstruct improper applications of these notions to objects that do not belong to the same epistemic context, focusing in particular on the extent to which ME (...) is supposed to feedback onto moral philosophy. By highlighting the inadequacy of many approaches to the supposed philosophical implications of ME, I wish to redirect attention to its actual scope and to stress its relevance for the social acceptance of autonomous technologies. The essay is structured as follows. After a brief introduction (§ 1), in § 2 I shed light upon the link between the current trend of robotic development toward greater degrees of autonomy and the corresponding need for artificial moral agents that fuels research in ME. I then present the epistemological profile of ME in § 3, focusing on its main component, i.e., the modelling of human moral agency in the language of robotics and computer science. In § 4 I deal with cases in which such model is brought to bear on human ethics and moral philosophy as well, whilst in § 5 I develop a criticism of this extension based on an account of the actual epistemological relations that obtain between philosophical and technological knowledge in the context of the ME project. In § 6 I discuss the role that the ordinary use of language plays in the process of extending machinerelated notions to other domains of knowledge and, finally, I clarify what the appropriate scope of machine ethics is notwithstanding its many utopian or dystopian misinterpretations. (shrink)

Virtue ethics seems to be a promising moral theory for understanding and interpreting the development and behavior of artificial moral agents. Virtuous artificial agents would blur traditional distinctions between different sorts of moral machines and could make a claim to membership in the moral community. Accordingly, we investigate the “machine question” by studying whether virtue or vice can be attributed to artificial intelligence; that is, are people willing to judge machines as possessing moral character? An (...) experiment describes situations where either human or AI agents engage in virtuous or vicious behavior and experiment participants then judge their level of virtue or vice. The scenarios represent different virtue ethics domains of truth, justice, fear, wealth, and honor. Quantitative and qualitative analyses show that moral attributions are weakened for AIs compared to humans, and the reasoning and explanations for the attributions are varied and more complex. On “relational” views of membership in the moral community, virtuous machines would indeed be included, even if they are indeed weakened. Hence, while our moral relationships with artificial agents may be of the same types, they may yet remain substantively different than our relationships to human beings. (shrink)

The rapid adoption and implementation of artificial intelligence in medicine creates an ontologically distinct situation from prior care models. There are both potential advantages and disadvantages with such technology in advancing the interests of patients, with resultant ontological and epistemic concerns for physicians and patients relating to the instatiation of AI as a dependent, semi- or fully-autonomous agent in the encounter. The concept of libertarian paternalism potentially exercised by AI (and those who control it) has created challenges to conventional (...) assessments of patient and physician autonomy. The unclear legal relationship between AI and its users cannot be settled presently, an progress in AI and its implementation in patient care will necessitate an iterative discourse to preserve humanitarian concerns in future models of care. This paper proposes that physicians should neither uncritically accept nor unreasonably resist developments in AI but must actively engage and contribute to the discourse, since AI will affect their roles and the nature of their work. One’s moral imaginative capacity must be engaged in the questions of beneficence, autonomy, and justice of AI and whether its integration in healthcare has the potential to augment or interfere with the ends of medical practice. (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 aim of this paper is to offer an analysis of the notion of artificial moral agent (AMA) and of its impact on human beings’ self-understanding as moral agents. Firstly, I introduce the topic by presenting what I call the Continuity Approach. Its main claim holds that AMAs and human moral agents exhibit no significant qualitative difference and, therefore, should be considered homogeneous entities. Secondly, I focus on the consequences this approach leads to. In order to do this I (...) take into consideration the work of Bostrom and Dietrich, who have radically assumed this viewpoint and thoroughly explored its implications. Thirdly, I present an alternative approach to AMAs—the Discontinuity Approach—which underscores an essential difference between human moral agents and AMAs by tackling the matter from another angle. In this section I concentrate on the work of Johnson and Bryson and I highlight the link between their claims and Heidegger’s and Jonas’s sug-gestions concerning the relationship between human beings and technological products. In conclusion I argue that, although the Continuity Approach turns out to be a necessary postulate to the machine ethics project, the Discontinuity Approach highlights a relevant distinction between AMAs and human moral agents. On this account, the Discontinuity Approach generates a clearer understanding of what AMAs are, of how we should face the moral issues they pose, and, finally, of the difference that separates machine ethics from moral philosophy. (shrink)

Since the automation revolution of our technological era, diverse machines or robots have gradually begun to reconfigure our lives. With this expansion, it seems that those machines are now faced with a new challenge: more autonomous decision-making involving life or death consequences. This paper explores the philosophical possibility of artificial moral agency through the following question: could a machine obtain the cognitive capacities needed to be a moral agent? In this regard, I propose to expose, under a normative-cognitive (...) perspective, the minimum criteria through which we could recognize an artificial entity as a genuine moral entity. Although my proposal should be considered from a reasonable level of abstraction, I will critically analyze and identify how an artificial agent could integrate those cognitive features. Finally, I intend to discuss their limitations or possibilities. (shrink)

In what ways should we include future humanoid robots, and other kinds of artificial agents, in our moral universe? We consider the Organic view, which maintains that artificial humanoid agents, based on current computational technologies, could not count as full-blooded moral agents, nor as appropriate targets of intrinsic moral concern. On this view, artificial humanoids lack certain key properties of biological organisms, which preclude them from having full moral status. Computationally controlled systems, however advanced in their cognitive (...) or informational capacities, are, it is proposed, unlikely to possess sentience and hence will fail to be able to exercise the kind of empathic rationality that is a prerequisite for being a moral agent. The organic view also argues that sentience and teleology require biologically based forms of self-organization and autonomous self-maintenance. The organic view may not be correct, but at least it needs to be taken seriously in the future development of the field of Machine Ethics. (shrink)

While today there is much discussion about the ethics of artificial intelligence, less work has been done on the philosophical nature of AI. Drawing on Bergson and Ricoeur, this paper proposes to use the concepts of time, process, and narrative to conceptualize AI and its normatively relevant impact on human lives and society. Distinguishing between a number of different ways in which AI and time are related, the paper explores what it means to understand AI as narrative, as (...) process, or as the emergent outcome of processes and narratives. It pays particular attention to what it calls the “narrator” and “time machine” roles of AI and the normative implications of these roles. It argues that AI processes and narratives shape our time and link past, present, and future in particular ways that are ethically and politically significant. (shrink)

The increasing workplace use of artificially intelligent (AI) technologies has implications for the experience of meaningful human work. Meaningful work refers to the perception that one’s work has worth, significance, or a higher purpose. The development and organisational deployment of AI is accelerating, but the ways in which this will support or diminish opportunities for meaningful work and the ethical implications of these changes remain under-explored. This conceptual paper is positioned at the intersection of the meaningful work and ethical AI (...) literatures and offers a detailed assessment of the ways in which the deployment of AI can enhance or diminish employees’ experiences of meaningful work. We first outline the nature of meaningful work and draw on philosophical and business ethics accounts to establish its ethical importance. We then explore the impacts of three paths of AI deployment (replacing some tasks, ‘tending the machine’, and amplifying human skills) across five dimensions constituting a holistic account of meaningful work, and finally assess the ethical implications. In doing so we help to contextualise the meaningful work literature for the era of AI, extend the ethical AI literature into the workplace, and conclude with a range of practical implications and future research directions. (shrink)

Artificial intelligence and robotics is pervasive in daily life and set to expand to new levels potentially replacing human decision-making and action. Self-driving cars, home and healthcare robots, and autonomous weapons are some examples. A distinction appears to be emerging between potentially benevolent civilian uses of the technology (eg unmanned aerial vehicles delivering medicines), and potentially malevolent military uses (eg lethal autonomous weapons killing human com- batants). Machine-mediated human interaction challenges the philosophical basis of human existence and ethical (...) conduct. Aside from technical challenges of ensuring ethical conduct in artificial intelligence and robotics, there are moral questions about the desirability of replacing human functions and the human mind with such technology. How will artificial intelligence and robotics engage in moral reasoning in order to act ethically? Is there a need for a new set of moral rules? What happens to human interaction when it is mediated by technology? Should such technology be used to end human life? Who bears responsibility for wrongdoing or harmful conduct by artificial intelligence and robotics? -/- Whilst Kant may be familiar to international lawyers for setting restraints on the use of force and rules for perpetual peace, his foundational work on ethics provides an inclusive moral philosophy for assessing ethical conduct of individuals and states and, thus, is relevant to discussions on the use and development of artificial intelligence and robotics. His philosophy is inclusive because it incorporates justifications for morals and legitimate responses to immoral conduct, and applies to all human agents irrespective of whether they are wrongdoers, unlawful combatants, or unjust enemies. Humans are at the centre of rational thinking, action, and norm-creation so that the rationale for restraints on methods and means of warfare, for example, is based on preserving human dignity as well as ensuring conditions for perpetual peace among states. Unlike utilitarian arguments which favour use of autonomous weapons on the basis of cost-benefit reasoning or the potential to save lives, Kantian ethics establish non-consequentialist and deontological rules which are good in themselves to follow and not dependent on expediency or achieving a greater public good. -/- Kantian ethics make two distinct contributions to the debate. First, they provide a human-centric ethical framework whereby human exist- ence and capacity are at the centre of a norm-creating moral philosophy guiding our understanding of moral conduct. Second, the ultimate aim of Kantian ethics is practical philosophy that is relevant and applicable to achieving moral conduct. -/- I will seek to address the moral questions outlined above by exploring how core elements of Kantian ethics relate to use of artificial intelli- gence and robotics in the civilian and military spheres. Section 2 sets out and examines core elements of Kantian ethics: the categorical imperative; autonomy of the will; rational beings and rational thinking capacity; and human dignity and humanity as an end in itself. Sections 3-7 consider how these core elements apply to artificial intelligence and robotics with discussion of fully autonomous and human-machine rule-generating approaches; types of moral reasoning; the difference be- tween ‘human will’ and ‘machine will’; and respecting human dignity. (shrink)

The article examines the challenges involved in the process of developing artificial ethical agents. The process involves the creators or designing professionals, the procedures to develop an ethical agent and the artificial systems. There are two possibilities available to create artificial ethical agents: (a) programming ethical guidance in the artificial Intelligence (AI)-equipped machines and/or (b) allowing AI-equipped machines to learn ethical decision-making by observing humans. However, it is difficult to fulfil these possibilities due to the subjective (...) nature of ethical decision-making. The challenge related to the developers is that they themselves lack training in ethical skills. The creators who develop an artificial ethical agent should be able to foresee the ethical issues and have knowledge about ethical decision-making to improve the ethical use of AI-equipped machines. The suggestion is that the focus should be on training professionals involved in the process of developing these artificial systems in ethics rather than developing artificial ethical agents and thereby attributing ethical agency to it. (shrink)

The article examines the challenges involved in the process of developing artificial ethical agents. The process involves the creators or designing professionals, the procedures to develop an ethical agent and the artificial systems. There are two possibilities available to create artificial ethical agents: (a) programming ethical guidance in the artificial Intelligence (AI)-equipped machines and/or (b) allowing AI-equipped machines to learn ethical decision-making by observing humans. However, it is difficult to fulfil these possibilities due to the subjective (...) nature of ethical decision-making. The challenge related to the developers is that they themselves lack training in ethical skills. The creators who develop an artificial ethical agent should be able to foresee the ethical issues and have knowledge about ethical decision-making to improve the ethical use of AI-equipped machines. The suggestion is that the focus should be on training professionals involved in the process of developing these artificial systems in ethics rather than developing artificial ethical agents and thereby attributing ethical agency to it. (shrink)

The aim of this thesis is to advance a philosophically justifiable account of Artificial Moral Agency (AMA). Concerns about the moral status of Artificial Intelligence (AI) traditionally turn on questions of whether these systems are deserving of moral concern (i.e. if they are moral patients) or whether they can be sources of moral action (i.e. if they are moral agents). On the Organic View of Ethical Status, being a moral patient is a necessary condition for an entity to (...) qualify as a moral agent. This view claims that because artificial agents (AAs) lack sentience, they cannot be proper subjects of moral concern and hence cannot be considered to be moral agents. I raise conceptual and epistemic issues with regards to the sense of sentience employed on this view, and I argue that the Organic View does not succeed in showing that machines cannot be moral patients. Nevertheless, irrespective of this failure, I also argue that the entire project is misdirected in that moral patiency need not be a necessary condition for moral agency. Moreover, I claim that whereas machines may conceivably be moral patients in the future, there is a strong case to be made that they are (or will very soon be) moral agents. Whereas it is often argued that machines cannot be agents simpliciter, let alone moral agents, I claim that this argument is predicated on a conception of agency that makes unwarranted metaphysical assumptions even in the case of human agents. Once I have established the shortcomings of this “standard account”, I move to elaborate on other, more plausible, conceptions of agency, on which some machines clearly qualify as agents. Nevertheless, the argument is still often made that while some machines may be agents, they cannot be moral agents, given their ostensible lack of the requisite phenomenal states. Against this thesis, I argue that the requirement of internal states for moral agency is philosophically unsound, as it runs up against the problem of other minds. In place of such intentional accounts of moral agency, I provide a functionalist alternative, which makes conceptual room for the existence of AMAs. The implications of this thesis are that at some point in the future we may be faced with situations for which no human being is morally responsible, but a machine may be. Moreover, this responsibility holds, I claim, independently of whether the agent in question is “punishable” or not. (shrink)

This paper explores and ultimately affirms the surprising claim that artificial intelligence (AI) can become part of the person, in a robust sense, and examines three ethical and legal implications. The argument is based on a rich, legally inspired conception of persons as free and independent rightholders and objects of heightened protection, but it is construed so broadly that it should also apply to mainstream philosophical conceptions of personhood. The claim is exemplified by a specific technology, devices that connect (...) human brains with computers and operate by AI-algorithms. Under philosophically reasonable and empirically realistic conditions, these devices and the AI running them become parts of the person, in the same way as arms, hearts, or mental capacities are. This transformation shall be called empersonification. It has normative and especially legal consequences because people have broader and stronger duties regarding other persons (and parts of them) than regarding things. Three consequences with practical implications are: (i) AI-devices cease to exist as independent legal entities and come to enjoy the special legal protection of persons; (ii) therefore, third parties such as manufacturers or authors of software lose (intellectual) property rights in device and software; (iii) persons become responsible for the outputs of the empersonified AI-devices to the same degree that they are for desires or intentions arising from the depths of their unconscious. More generally, empersonification marks a new step in the long history of human–machine interaction that deserves critical ethical reflection and calls for a stronger value-aligned development of these technologies. (shrink)

The ethical issues related to the possible future creation of machines with general intellectual capabilities far outstripping those of humans are quite distinct from any ethical problems arising in current automation and information systems. Such superintelligence would not be just another technological development; it would be the most important invention ever made, and would lead to explosive progress in all scientific and technological fields, as the superintelligence would conduct research with superhuman efficiency. To the extent that ethics is a (...) cognitive pursuit, a superintelligence could also easily surpass humans in the quality of its moral thinking. However, it would be up to the designers of the superintelligence to specify its original motivations. Since the superintelligence may become unstoppably powerful because of its intellectual superiority and the technologies it could develop, it is crucial that it be provided with human-friendly motivations. This paper surveys some of the unique ethical issues in creating superintelligence, and discusses what motivations we ought to give a superintelligence, and introduces some cost-benefit considerations relating to whether the development of superintelligent machines ought to be accelerated or retarded. (shrink)

This paper explores and ultimately affirms the surprising claim that artificial intelligence (AI) can become part of the person, in a robust sense, and examines three ethical and legal implications. The argument is based on a rich, legally inspired conception of persons as free and independent rightholders and objects of heightened protection, but it is construed so broadly that it should also apply to mainstream philosophical conceptions of personhood. The claim is exemplified by a specific technology, devices that connect (...) human brains with computers and operate by AI-algorithms. Under philosophically reasonable and empirically realistic conditions, these devices and the AI running them become parts of the person, in the same way as arms, hearts, or mental capacities are. This transformation shall be called empersonification. It has normative and especially legal consequences because people have broader and stronger duties regarding other persons (and parts of them) than regarding things. Three consequences with practical implications are: (i) AI-devices cease to exist as independent legal entities and come to enjoy the special legal protection of persons; (ii) therefore, third parties such as manufacturers or authors of software lose (intellectual) property rights in device and software; (iii) persons become responsible for the outputs of the empersonified AI-devices to the same degree that they are for desires or intentions arising from the depths of their unconscious. More generally, empersonification marks a new step in the long history of human–machine interaction that deserves critical ethical reflection and calls for a stronger value-aligned development of these technologies. (shrink)

BackgroundHealthcare providers have to make ethically complex clinical decisions which may be a source of stress. Researchers have recently introduced Artificial Intelligence (AI)-based applications to assist in clinical ethical decision-making. However, the use of such tools is controversial. This review aims to provide a comprehensive overview of the reasons given in the academic literature for and against their use.MethodsPubMed, Web of Science, Philpapers.org and Google Scholar were searched for all relevant publications. The resulting set of publications was title and (...) abstract screened according to defined inclusion and exclusion criteria, resulting in 44 papers whose full texts were analysed using the Kuckartz method of qualitative text analysis.ResultsArtificial Intelligence might increase patient autonomy by improving the accuracy of predictions and allowing patients to receive their preferred treatment. It is thought to increase beneficence by providing reliable information, thereby, supporting surrogate decision-making. Some authors fear that reducing ethical decision-making to statistical correlations may limit autonomy. Others argue that AI may not be able to replicate the process of ethical deliberation because it lacks human characteristics. Concerns have been raised about issues of justice, as AI may replicate existing biases in the decision-making process.ConclusionsThe prospective benefits of using AI in clinical ethical decision-making are manifold, but its development and use should be undertaken carefully to avoid ethical pitfalls. Several issues that are central to the discussion of Clinical Decision Support Systems, such as justice, explicability or human–machine interaction, have been neglected in the debate on AI for clinical ethics so far.Trial registrationThis review is registered at Open Science Framework (https://osf.io/wvcs9). (shrink)

Can machine intelligence do clinical ethics? And if so, would applying it to actual medical cases be desirable? In a recent target article (Meier et al. 2022), we described the piloting of our advisory algorithm METHAD. Here, we reply to commentaries published in response to our project. The commentaries fall into two broad categories: concrete criticism that concerns the development of METHAD; and the more general question as to whether one should employ decision-support systems of this kind—the debate (...) we set out to ignite with our target article. (shrink)

One of the main difficulties in assessing artificial intelligence (AI) is the tendency for people to anthropomorphise it. This becomes particularly problematic when we attach human moral activities to AI. For example, the European Commission’s High-level Expert Group on AI (HLEG) have adopted the position that we should establish a relationship of trust with AI and should cultivate trustworthy AI (HLEG AI Ethics guidelines for trustworthy AI, 2019, p. 35). Trust is one of the most important and defining (...) activities in human relationships, so proposing that AI should be trusted, is a very serious claim. This paper will show that AI cannot be something that has the capacity to be trusted according to the most prevalent definitions of trust because it does not possess emotive states or can be held responsible for their actions—requirements of the affective and normative accounts of trust. While AI meets all of the requirements of the rational account of trust, it will be shown that this is not actually a type of trust at all, but is instead, a form of reliance. Ultimately, even complex machines such as AI should not be viewed as trustworthy as this undermines the value of interpersonal trust, anthropomorphises AI, and diverts responsibility from those developing and using them. (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)

Digital phenotyping is the term given to the capturing and use of user log data from health and wellbeing technologies used in apps and cloud-based services. This paper explores ethical issues in making use of digital phenotype data in the arena of digital health interventions. Products and services based on digital wellbeing technologies typically include mobile device apps as well as browser-based apps to a lesser extent, and can include telephony-based services, text-based chatbots, and voice-activated chatbots. Many of these digital (...) products and services are simultaneously available across many channels in order to maximize availability for users. Digital wellbeing technologies offer useful methods for real-time data capture of the interactions of users with the products and services. It is possible to design what data are recorded, how and where it may be stored, and, crucially, how it can be analyzed to reveal individual or collective usage patterns. The paper also examines digital phenotyping workflows, before enumerating the ethical concerns pertaining to different types of digital phenotype data, highlighting ethical considerations for collection, storage, and use of the data. A case study of a digital health app is used to illustrate the ethical issues. The case study explores the issues from a perspective of data prospecting and subsequent machine learning. The ethical use of machine learning and artificial intelligence on digital phenotype data and the broader issues in democratizing machine learning and artificial intelligence for digital phenotype data are then explored in detail. (shrink)

This Article explores the possibility of having ethical artificial intelligence. It argues that we face a dilemma in trying to develop artificial intelligence that is ethical: either we have to be able to codify ethics as a set of rules or we have to value a machine’s ability to make ethical mistakes so that it can learn ethics like children do. Neither path seems very promising, though perhaps by thinking about the difficulties with each we (...) may come to a better understanding of artificial intelligence and ourselves. (shrink)

Recent advancements in AI have prompted a large number of AI ethics guidelines published by governments and nonprofits. While many of these papers propose concrete or seemingly applicable ideas, few philosophically sound proposals are made. In particular, we observe that the line of questioning has often not been examined critically and underlying conceptual problems not always dealt with at the root. In this paper, we investigate the nature of ethical AI systems and what their moral status might be by (...) first turning to the notions of moral agency and patience. We find that their explication would come at a too high cost which is why we, second, articulate a different approach that avoids vague and ambiguous concepts or the problem of other minds. Third, we explore the impact of our philosophical and conceptual analysis on the regulatory landscape, make this link explicit, and finally propose a set of promising policy steps. (shrink)

In his famous 1950 paper where he presents what became the benchmark for success in artificial intelligence, Turing notes that "at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted" (Turing 1950, 442). Kurzweil (1990) suggests that Turing's prediction was correct, even if no machine has yet to pass the Turing Test. In the wake (...) of the computer revolution, research in artificial intelligence and cognitive science has pushed in the direction of interpreting "thinking" as some sort of computational process. On this understanding, thinking is something computers (in principle) and humans (in practice) can both do. It is difficult to say precisely when in history the meaning of the term "thinking" headed in this direction. Signs are already present in the mechanistic and mathematical tendencies of the early Modern period, and maybe even glimmers are apparent in the ancient Greeks themselves. But over the long haul, we somehow now consider "thinking" as separate from the categories of "thoughtfulness" (in the general sense of wondering about things), "insight" and "wisdom." Intelligent machines are all around us, and the world is populated with smart cars, smart phones and even smart (robotic) appliances. But, though my cell phone might be smart, I do not take that to mean that it is thoughtful, insightful or wise. So, what has become of these latter categories? They seem to be bygones left behind by scientific and computational conceptions of thinking and knowledge that no longer have much use for them. In 2000, Allen, Varner and Zinser addressed the possibility of a Moral Turing Test (MTT) to judge the success of an automated moral agent (AMA), a theme that is repeated in Wallach and Allen (2009).. (shrink)

Artificial Life has two goals. One attempts to describe fundamental qualities of living systems through agent based computer models. And the second studies whether or not we can artificially create living things in computational mediums that can be realized either, virtually in software, or through biotechnology. The study of ALife has recently branched into two further subdivisions, one is “dry” ALife, which is the study of living systems “in silico” through the use of computer simulations, and the other is (...) “wet” ALife that uses biological material to realize what has only been simulated on computers, effectively wet ALife uses biological material as a kind of computer. This is challenging to the field of computer ethics as it points towards a future in which computer and bioethics might have shared concerns. The emerging studies into wet ALife are likely to provide strong empirical evidence for ALife’s most challenging hypothesis: that life is a certain set of computable functions that can be duplicated in any medium. I believe this will propel ALife into the midst of the mother of all cultural battles that has been gathering around the emergence of biotechnology. Philosophers need to pay close attention to this debate and can serve a vital role in clarifying and resolving the dispute. But even if ALife is merely a computer modeling technique that sheds light on living systems, it still has a number of significant ethical implications such as its use in the modeling of moral and ethical systems, as well as in the creation of artificial moral agents. (shrink)

The present paper uses a Flourishing Ethics analysis to address the question of which ethical values and principles should be “instilled” into artificially intelligent agents. This is an urgent question that is still being asked seven decades after philosopher/scientist Norbert Wiener first asked it. An answer is developed by assuming that human flourishing is the central ethical value, which other ethical values, and related principles, can be used to defend and advance. The upshot is that Flourishing Ethics can (...) provide a common underlying ethical foundation for a wide diversity of cultures and communities around the globe; and the members of each specific culture or community can add their own specific cultural values—ones which they treasure, and which help them to make sense of their moral lives. (shrink)

Full ectogenesis as the complete externalization of human reproduction by bypassing the bodily processes of gestation and childbirth can be considered the culmination of genetic and reproductive technologies. Despite its still being a hypothetical scenario, it has been discussed for decades as the ultimate means to liberate women from their reproductive tasks in society and hence finally end fundamental gender injustices generally. In the debate about the application of artificial wombs to achieve gender equality, one aspect is barely mentioned (...) but is of crucial relevance from a medical‐ethical perspective: whether and how could full ectogenesis be justified as a proper use of medicine? After characterizing the technology as a special form of human enhancement and as an extension of medical practice that goes beyond the traditional field of medicine, this paper critically assesses the theoretical possibilities of legitimizing this extension. We identify two ways of justification: either one argues that ectogenesis fulfils a proper goal of medicine (a justification we call pathologization), or one argues that the application of ectogenesis achieves a non‐medical goal (which we call medicalization). Because it is important from a medical‐ethical point of view to avoid an inappropriate instrumentalization or misuse of medicine and thus an undue medicalization of non‐medical problems, a set of necessary conditions has to be met. It is doubtful whether full ectogenesis for non‐medical purposes could fulfil these conditions. Rather, its comprehensive usage could be seen as a revolutionary modification of what it means to be human. (shrink)

Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence and robotics communities. We will argue that attempts to attribute moral agency and assign rights to all intelligent machines are misguided, whether applied to infrahuman or superhuman AIs, as are proposals to limit the negative effects of AIs by constraining their behavior. As an alternative, we propose a new science of safety engineering for intelligent artificial agents based on maximizing for what humans value. (...) In particular, we challenge the scientific community to develop intelligent systems that have human-friendly values that they provably retain, even under recursive self-improvement. (shrink)

The debate over the ethical repercussions of Artificial Intelligence (AI) cannot disregard the “sum total of ideas that bring into evidence a system of ethical reference that justifies that profound dimension of technology as a central element in the attainment of a ‘finalized’ perfection of man”(Galvan 2001). This implies an analysis of the ancient processes that might help to understand the complexities of contemporary society and the new challenges posed to human development. Being at the core of the dichotomy (...) between the human and the machine, biometrics will be central to the analysis carried out in this paper. Its measurement of physiological characteristics and behavioural patterns has politico-philosophical and legal consequences in terms of recognition and personal identity, as the use of artificial intelligence has shown. In information society, customs and traditions, cultural and communication processes, language and the self-determination of the individual have gradually acquired a stretched dimension that has led to a re-definition of the social structures within which the exchange of knowledge and data takes place, with AI-based technological devices playing a key role in such a scenario. The issue of biometric identity becomes highly complex when combined with the potential of digital services, as it is at this level that it shows the large number of interconnections deriving from social and political choices. The benefits of increased interconnection are limited by the risk of intrusion into the (social, personal or private) human sphere, which might pose a threat to both the physical, biological body, with its related freedoms (habeas corpus), and the digital body, in its multiple forms and media representations (habeas data). (shrink)

In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. -/- As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical (...) class='Hi'>ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? -/- The essays in this collection by researchers from both humanities and science describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility, and accurately modeling essential physician-machine-patient relationships. -/- This collection is the first book to address these 21st-century concerns. (shrink)

When we think about “machines”, or “robots”, or “AI”, what comes to our minds is generally an extension of our common relationship with objects in our humane and mundane world: there is a clear distinction between the subject, “we”, and the object. Upon review of some of the most important literary trends of the last centuries, this article invites us to consider the prevalence of this classical ontological division, taking into consideration examples such as Frankenstein, the “brain in a vat” (...) thought experiment, and the last advances towards the reality of “cyborg” beings. The question behind the article bring us to consider to what extent an absolute division between us and machines is still a thing in our days. (shrink)

There is a death by suicide in the world every 40 seconds, and suicide is the second leading cause of death for 15–29-year-olds. Experts say that one of the best ways to prevent suicide is for those in distress to hear from people who care about them. Facebook is in a unique position—through its support for networks and friendships on the site—to help connect a person in these difficult situations with people who can support them. Connecting people with the resources (...) they need is part of Facebook’s ongoing efforts to help build a safe community inside and outside of Facebook. This article provides a brief overview of how Facebook’s work to develop suicide prevention tools started and evolved, and the ethical considerations which surfaced during the process in the form of concrete product decisions around the implementation of these tools. This article is structured into three sections. Section 1 reviews what has been done in this space and lists and briefly describes other suicide prevention apps and tools. Section 2 describes Facebook’s overall approach to suicide prevention. Here, we’ll delve first into how that approach originated and how it was influenced by the external community’s proactive interactions with Facebook, highlighting our unique position to help address the problem. Afterwards, we’ll explain how that approach evolved, describing its various stages and iterations: understanding, reactive reporting, queue prioritization, and proactive reporting. This section describes the tools and resources Facebook has developed for people who may be at risk. Particular attention is devoted to the use of ArtificiaI Intelligence and Machine Learning to detect posts or live videos where someone might be expressing thoughts of suicide. Section 3 will elaborate on the ethical questions addressed when developing our approach and when making concrete product decisions to implement our suicide prevention tools. In this last section, we’ll expound the competing values and interests that were at stake during the product development process, and how we reached ethical balances between them. (shrink)

Emotions play a significant role in human relations, decision-making, and the motivation to act on those decisions. There are ongoing attempts to use artificial intelligence (AI) to read human emotions, and to predict human behavior or actions that may follow those emotions. However, a person’s emotions cannot be easily identified, measured, and evaluated by others, including automated machines and algorithms run by AI. The ethics of emotional AI is under research and this study has examined the emotional variables (...) as well as the perception of emotional AI in two large random groups of college students in an international university in Japan, with a heavy representation of Japanese, Indonesian, Korean, Chinese, Thai, Vietnamese, and other Asian nationalities. Surveys with multiple close-ended questions and an open-ended essay question regarding emotional AI were administered for quantitative and qualitative analysis, respectively. The results demonstrate how ethically questionable results may be obtained through affective computing and by searching for correlations in a variety of factors in collected data to classify individuals into certain categories and thus aggravate bias and discrimination. Nevertheless, the qualitative study of students’ essays shows a rather optimistic view over the use of emotional AI, which helps underscore the need to increase awareness about the ethical pitfalls of AI technologies in the complex field of human emotions. (shrink)

An Artificial Intelligence algorithm trained on data that reflect racial biases may yield racially biased outputs, even if the algorithm on its own is unbiased. For example, algorithms used to schedule medical appointments in the USA predict that Black patients are at a higher risk of no-show than non-Black patients, though technically accurate given existing data that prediction results in Black patients being overwhelmingly scheduled in appointment slots that cause longer wait times than non-Black patients. This perpetuates racial inequity, (...) in this case lesser access to medical care. This gives rise to one type of Accuracy-Fairness trade-off: preserve the efficiency offered by using AI to schedule appointments or discard that efficiency in order to avoid perpetuating ethno-racial disparities. Similar trade-offs arise in a range of AI applications including others in medicine, as well as in education, judicial systems, and public security, among others. This article presents a framework for addressing such trade-offs where Machine Learning and Optimization components of the algorithm are decoupled. Applied to medical appointment scheduling, our framework articulates four approaches intervening in different ways on different components of the algorithm. Each yields specific results, in one case preserving accuracy comparable to the current state-of-the-art while eliminating the disparity. (shrink)

Machine ethics is the field that strives to develop ‘artificial moral agents’ (AMAs), artificial systems that can autonomously make moral decisions. Some authors have questioned the feasibility of machine ethics, by questioning whether artificial systems can possess moral competence, or the capacity to reach morally right decisions in various situations. This paper explores this question by drawing on the work of several moral philosophers (McDowell, Wiggins, Hampshire, and Nussbaum) who have characterised moral competence (...) in a manner inspired by Aristotle. Although disparate in many ways, these philosophers all emphasise what may be called ‘moral sensitivity’ as a precondition for moral competence. Moral sensitivity is the uncodified, practical skill to recognise, in a range of situations, which features of the situations are morally relevant, and how they are relevant. This paper argues that the main types of AMAs currently proposed are incapable of full moral sensitivity. First, top-down AMAs that proceed from fixed rule-sets are too rigid to respond appropriately to the wide range of qualitatively unique factors that moral sensitivity gives access to. Second, bottom-up AMAs that learn moral behaviour from examples are at risk of generalising from these examples in undesirable ways, as they lack embedding in what Wittgenstein calls a ‘form of life’, which allows humans to appropriately learn from moral examples. The paper concludes that AMAs are unlikely to possess full moral competence, but closes by suggesting that they may still be feasible in restricted domains of public morality, where moral sensitivity plays a smaller role. (shrink)

We human beings do have the power to modify our deep structure, through drugs and surgery. But we cannot yet use this power with enough precision to make deep changes to our neural structure without high risk of death or disability. There are two reasons why we find ourselves in this position. First, our instruments of self-modification are crude. Second, we have very limited knowledge about where and how to apply our instruments to get specific desirable effects. For the same (...) reason, we don't even have good knowledge about what effects are physically possible. (shrink)