John Danaher

This chapter studies the future of retribution and, in particular, the role that robots will play in shaping that future. It begins by describing the _Bouphonia_ ritual, which speaks to two important features of the human condition: the enduring significance of practices of blame and punishment in human life, and the occasional absurdity of this desire. What happens when robots — or other sophisticated artificially intelligent (AI) machines — get embedded in our societies and have a part to play in criminal acts? Should they, like the knife in the _Bouphonia_ ritual, be blamed for their contribution? Or should something else happen, something a little more radical? The chapter makes the case for radicalism. In particular, it suggests that the rise of the robots should lead us to reconsider the wisdom of our traditional practices of punishment and blame.

It is now possible for AI systems to generate novel inventions without meaningful human direction and control. Should such inventions be patented? The prevailing consensus, confirmed in recent test cases and official guidance, is that patent law only covers inventions by natural persons (i.e., humans). This, however, sometimes creates an odd situation in which AI-generated inventions cannot be patented, nor can the humans responsible for those systems gain patent rights indirectly through the operation of the law. In this article, we argue against this prevailing consensus. We present five reasons for thinking that AI-generated inventions should be patentable and that AI systems should be legally recognized as inventors. In making this argument, we do not claim that modern AI systems have acquired some significant legal or moral status that is equivalent to humans. Our argument is more practical in nature. We argue that failing to recognize AI inventorship will have negative repercussions for economic development and innovation, at a time when AI assistance is needed.

Technology could be used to improve morality but it could do so in different ways. Some technologies could augment and enhance moral behaviour externally by using external cues and signals to push and pull us towards morally appropriate behaviours. Other technologies could enhance moral behaviour internally by directly altering the way in which the brain captures and processes morally salient information or initiates moral action. The question is whether there is any reason to prefer one method over the other? In this article, I argue that there is. Specifically, I argue that internal moral enhancement is likely to be preferable to external moral enhancement, when it comes to the legitimacy of political decision-making processes. In fact, I go further than this and argue that the increasingly dominant forms of external moral enhancement (algorithm-assisted enhancement) may already be posing a significant threat to political legitimacy, one that we should try to address. Consequently, research and development of internal moral enhancements should be prioritised as a political project.

Recent developments in AI and robotics enable people to create _personalised digital duplicates_ – these are artificial, at least partial, recreations or simulations of real people. The advent of such duplicates enables people to overcome their individual scarcity. But this comes at a cost. There is a common view among ethicists and value theorists suggesting that individual scarcity contributes to or heightens the value of a life or parts of a life. In this paper, we address this topic. We make five main points. First, that there is a plausible _prima facie_ case for the scarcity threat: AI may undermine the value of an individual human life by making us less scarce. Second, notwithstanding this prima facie threat, the role of scarcity in individual value is disputable and always exists in tension with the contrasting view that scarcity is a tragedy that limits our value. Third, there are two distinct forms of scarcity – instrumental and intrinsic – and they contribute to value in different ways. Fourth, digital duplication technology may undermine instrumental scarcity, to at least some extent, but the axiological consequences of this are highly variable. Fifth, digital duplication technology does not affect intrinsic scarcity, and may actually heighten it.

Considering public moral attitudes is a hallmark of the anticipatory governance of emerging biotechnologies, such as heritable human genome editing. However, such anticipatory governance often overlooks that future morality is open to change and that future generations may perform different moral assessments on the very biotechnologies we are trying to govern in the present. In this article, we identify an ’anticipatory gap’ that has not been sufficiently addressed in the discussion on the public governance of heritable genome editing, namely, uncertainty about the moral visions of future generations about the emerging applications that we are currently attempting to govern now. This paper motivates the relevance of this anticipatory gap, identifying the challenges it generates and offering various recommendations so that moral uncertainty does not lead to governance paralysis with regard to human germline genome editing.

The idea that technologies can change moral beliefs and practices is an old one. But how, exactly, does this happen? This paper builds on an emerging field of inquiry by developing a synoptic taxonomy of the mechanisms of techno-moral change. It argues that technology affects moral beliefs and practices in three main domains: decisional (how we make morally loaded decisions), relational (how we relate to others) and perceptual (how we perceive situations). It argues that across these three domains there are six primary mechanisms of techno-moral change: (i) adding options; (ii) changing decision-making costs; (iii) enabling new relationships; (iv) changing the burdens and expectations within relationships; (v) changing the balance of power in relationships; and (vi) changing perception (information, mental models and metaphors). The paper also discusses the layered, interactive and second-order effects of these mechanisms.

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

Ethics plays a key role in the normative analysis of the impacts of technology. We know that computers in general and the processing of data, the use of artificial intelligence, and the combination of computers and/or artificial intelligence with robotics are all associated with ethically relevant implications for individuals, groups, and society. In this article, we argue that while all technologies are ethically relevant, there is no need to create a separate ‘ethics of X’ or ‘X ethics’ for each and every subtype of technology or technological property—e.g. computer ethics, AI ethics, data ethics, information ethics, robot ethics, and machine ethics. Specific technologies might have specific impacts, but we argue that they are often sufficiently covered and understood through already established higher-level domains of ethics. Furthermore, the proliferation of tech ethics is problematic because (a) the conceptual boundaries between the subfields are not well-defined, (b) it leads to a duplication of effort and constant reinventing the wheel, and (c) there is danger that participants overlook or ignore more fundamental ethical insights and truths. The key to avoiding such outcomes lies in a taking the discipline of ethics seriously, and we consequently begin with a brief description of what ethics is, before presenting the main forms of technology related ethics. Through this process, we develop a hierarchy of technology ethics, which can be used by developers and engineers, researchers, or regulators who seek an understanding of the ethical implications of technology. We close by deducing two principles for positioning ethical analysis which will, in combination with the hierarchy, promote the leveraging of existing knowledge and help us to avoid an exaggerated proliferation of tech ethics.

Technologies can have profound effects on social moral systems. Is there any way to systematically investigate and anticipate these potential effects? This paper aims to contribute to this emerging field on inquiry through a case study method. It focuses on two core human values—truth and trust—describes their structural properties and conceptualisations, and then considers various mechanisms through which technology is changing and can change our perspective on those values. In brief, the paper argues that technology is transforming these values by changing the costs/benefits of accessing them; allowing us to substitute those values for other, closely-related ones; increasing their perceived scarcity/abundance; and disrupting traditional value-gatekeepers. This has implications for how we study other, technologically-mediated, value changes.

What is techno-optimism and how can it be defended? Although techno-optimist views are widely espoused and critiqued, there have been few attempts to systematically analyse what it means to be a techno-optimist and how one might defend this view. This paper attempts to address this oversight by providing a comprehensive analysis and evaluation of techno-optimism. It is argued that techno-optimism is a pluralistic stance that comes in weak and strong forms. These vary along a number of key dimensions but each shares the view that technology plays a key role in ensuring that the good prevails over the bad. Whatever its strength, to defend this stance, one must flesh out an argument with four key premises. Each of these premises is highly controversial and can be subjected to a number of critiques. The paper discusses five such critiques in detail. The paper also considers possible responses from the techno-optimist. Finally, it is concluded that although strong forms of techno-optimism are not intellectually defensible, a modest, agency-based version of techno-optimism may be defensible.

There is a concern that the widespread deployment of autonomous machines will open up a number of ‘responsibility gaps’ throughout society. Various articulations of such techno-responsibility gaps have been proposed over the years, along with several potential solutions. Most of these solutions focus on ‘plugging’ or ‘dissolving’ the gaps. This paper offers an alternative perspective. It argues that techno-responsibility gaps are, sometimes, to be welcomed and that one of the advantages of autonomous machines is that they enable us to embrace certain kinds of responsibility gap. The argument is based on the idea that human morality is often tragic. We frequently confront situations in which competing moral considerations pull in different directions and it is impossible to perfectly balance these considerations. This heightens the burden of responsibility associated with our choices. We cope with the tragedy of moral choice in different ways. Sometimes we delude ourselves into thinking the choices we make were not tragic ; sometimes we delegate the tragic choice to others ; sometimes we make the choice ourselves and bear the psychological consequences. Each of these strategies has its benefits and costs. One potential advantage of autonomous machines is that they enable a reduced cost form of delegation. However, we only gain the advantage of this reduced cost if we accept that some techno-responsibility gaps are virtuous.

A concise but informative overview of AI ethics and policy. Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring homeowners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, and voters in liberal democracies? Authored by experts in fields ranging from computer science and law to philosophy and cognitive science, this book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues such as transparency, bias, liability, privacy, and regulation. Both business and government have integrated algorithmic decision support systems into their daily operations, and the book explores the implications for our lives as citizens. For example, do we take it on faith that a machine knows best in approving a patient's health insurance claim or a defendant's request for bail? What is the potential for manipulation by targeted political ads? How can the processes behind these technically sophisticated tools ever be transparent? The book discusses such issues as statistical definitions of fairness, legal and moral responsibility, the role of humans in machine learning decision systems, “nudging” algorithms and anonymized data, the effect of automation on the workplace, and AI as both regulatory tool and target.

This chapter addresses the growing problem of unwanted sexual interactions in virtual environments. It reviews the available evidence regarding the prevalence and severity of this problem. It then argues that due to the potential harms of such interactions, as well as their nonconsensual nature, there is a good prima facie argument for viewing them as serious moral wrongs. Does this prima facie argument hold up to scrutiny? After considering three major objections – the ‘it’s not real’ objection; the ‘it’s just a game’ objection; and the ‘unrestricted consent’ objection – this chapter argues that it does. The chapter closes by reviewing some of the policy options available to us in addressing the problem of virtual sexual assault.

It is commonly assumed that a virtual life would be less meaningful (perhaps even meaningless). As virtual reality technologies develop and become more integrated into our everyday lives, this poses a challenge for those that care about meaning in life. In this chapter, it is argued that the common assumption about meaninglessness and virtuality is mistaken. After clarifying the distinction between two different visions of virtual reality, four arguments are presented for thinking that meaning is possible in virtual reality. Following this, four objections are discussed and rebutted. The chapter concludes that we can be cautiously optimistic about the possibility of meaning in virtual worlds.

Henry Shevlin’s paper—“How could we know when a robot was a moral patient?” – argues that we should recognize robots and artificial intelligence (AI) as psychological moral patients if they are cognitively equivalent to other beings that we already recognize as psychological moral patients (i.e., humans and, at least some, animals). In defending this cognitive equivalence strategy, Shevlin draws inspiration from the “behavioral equivalence” strategy that I have defended in previous work but argues that it is flawed in crucial respects. Unfortunately—and I guess this is hardly surprising—I cannot bring myself to agree that the cognitive equivalence strategy is the superior one. In this article, I try to explain why in three steps. First, I clarify the nature of the question that I take both myself and Shevlin to be answering. Second, I clear up some potential confusions about the behavioral equivalence strategy, addressing some other recent criticisms of it. Third, I will explain why I still favor the behavioral equivalence strategy over the cognitive equivalence one.

We are living in an algorithmic age where mathematics and computer science are coming together in powerful new ways to influence, shape and guide our behaviour and the governance of our societies. As these algorithmic governance structures proliferate, it is vital that we ensure their effectiveness and legitimacy. That is, we need to ensure that they are an effective means for achieving a legitimate policy goal that are also procedurally fair, open and unbiased. But how can we ensure that algorithmic governance structures are both? This article shares the results of a collective intelligence workshop that addressed exactly this question. The workshop brought together a multidisciplinary group of scholars to consider barriers to legitimate and effective algorithmic governance and the research methods needed to address the nature and impact of specific barriers. An interactive management workshop technique was used to harness the collective intelligence of this multidisciplinary group. This method enabled participants to produce a framework and research agenda for those who are concerned about algorithmic governance. We outline this research agenda below, providing a detailed map of key research themes, questions and methods that our workshop felt ought to be pursued. This builds upon existing work on research agendas for critical algorithm studies in a unique way through the method of collective intelligence.

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

Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims to: (i) defend the need for a novel conceptual model for understanding the systemic legal disruption caused by new technologies such as AI; (ii) to situate this model in relation to preceding debates about the interaction of regulation with new technologies (particularly the ‘cyberlaw’ and ‘robolaw’ debates); and (iii) to set out a detailed model for understanding the legal disruption precipitated by AI, examining both pathways stemming from new affordances that can give rise to a regulatory ‘disruptive moment’, as well as the Legal Development, Displacement or Destruction that can ensue. The article proposes that this model of legal disruption can be broadly generalisable to understanding the legal effects and challenges of other emerging technologies.

The idea that humans should abandon their individuality and use technology to bind themselves together into hivemind societies seems both farfetched and frightening – something that is redolent of the worst dystopias from science fiction. In this article, we argue that these common reactions to the ideal of a hivemind society are mistaken. The idea that humans could form hiveminds is sufficiently plausible for its axiological consequences to be taken seriously. Furthermore, far from being a dystopian nightmare, the hivemind society could be desirable and could enable a form of sentient flourishing. Consequently, we should not be so quick to deny it. We provide two arguments in support of this claim – the axiological openness argument and the desirability argument – and then defend it against three major objections.

Human values seem to vary across time and space. What implications does this have for the future of human value? Will our human and (perhaps) post-human offspring have very different values from our own? Can we study the future of human values in an insightful and systematic way? This article makes three contributions to the debate about the future of human values. First, it argues that the systematic study of future values is both necessary in and of itself and an important complement to other future-oriented inquiries. Second, it sets out a methodology and a set of methods for undertaking this study. Third, it gives a practical illustration of what this ‘axiological futurism’ might look like by developing a model of the axiological possibility space that humans are likely to navigate over the coming decades.

Can human life have value in a world in which humans are rendered obsolete by technological advances? This article answers this question by developing an extended analysis of the axiological impact of human obsolescence. In doing so, it makes four main arguments. First, it argues that human obsolescence is a complex phenomenon that can take on at least four distinct forms. Second, it argues that one of these forms of obsolescence is not a coherent concept and hence not a plausible threat to human well-being. Third, it argues that existing fears of technologically-induced human obsolescence are less compelling than they first appear. Fourth, it argues that there are two reasons for embracing a world of widespread, technologically-induced human obsolescence.