The Machine Question AI Ethics and Moral Responsibility

Minds and Machines, 2017

Conatus

At the turn of the 21st century, Susan Leigh Anderson and Michael Anderson conceived and introduced the Machine Ethics research program, that aimed to highlight the requirements under which autonomous artificial intelligence (AI) systems could demonstrate ethical behavior guided by moral values, and at the same time to show that these values, as well as ethics in general, can be representable and computable. Today, the interaction between humans and AI entities is already part of our everyday lives; in the near future it is expected to play a key role in scientific research, medical practice, public administration, education and other fields of civic life. In view of this, the debate over the ethical behavior of machines is more crucial than ever and the search for answers, directions and regulations is imperative at an academic, institutional as well as at a technical level. Our discussion with the two inspirers and originators of Machine Ethics highlights the epistemological, meta...

2012

One of the enduring concerns of moral philosophy is deciding who or what is deserving of ethical consideration. Much recent attention has been devoted to the "animal question"--consideration of the moral status of nonhuman animals. In this book, David Gunkel takes up the "machine question": whether and to what extent intelligent and autonomous machines of our own making can be considered to have legitimate moral responsibilities and any legitimate claim to moral consideration. The machine question poses a fundamental challenge to moral thinking, questioning the traditional philosophical conceptualization of technology as a tool or instrument to be used by human agents. Gunkel begins by addressing the question of machine moral agency: whether a machine might be considered a legitimate moral agent that could be held responsible for decisions and actions. He then approaches the machine question from the other side, considering whether a machine might be a moral patient due legitimate moral consideration. Finally, Gunkel considers some recent innovations in moral philosophy and critical theory that complicate the machine question, deconstructing the binary agent–patient opposition itself. Technological advances may prompt us to wonder if the science fiction of computers and robots whose actions affect their human companions (think of HAL in 2001: A Space Odyssey) could become science fact. Gunkel's argument promises to influence future considerations of ethics, ourselves, and the other entities who inhabit this world.

We address problems in machine ethics dealt with using computational techniques. Our research has focused on Computational Logic, particularly Logic Programming, and its appropriateness to model morality, namely moral permissibility, its justification, and the dual-process of moral judgments regarding the realm of the individual. In the collective realm, we, using Evolutionary Game Theory in populations of individuals, have studied norms and morality emergence computationally. These, to start with, are not equipped with much cognitive capability, and simply act from a predetermined set of actions. Our research shows that the introduction of cognitive capabilities, such as intention recognition, commitment, and apology, separately and jointly, reinforce the emergence of cooperation in populations, comparatively to their absence. Bridging such capabilities between the two realms helps understand the emergent ethical behavior of agents in groups, and implements them not just in simulations, but in the world of future robots and their swarms. Evolutionary Anthropology provides teachings.

AI & SOCIETY, 2017

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 (AI) 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 take. 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.

Machine ethics are quickly becoming an important part of artificial intelligence research. We argue that attempts to attribute moral agency to intelligent machines are misguided, whether applied to infrahuman or superhuman AIs. Humanity should not put its future in the hands of the machines that do not do exactly what we want them to, since we will not be able to take power back. In general, a machine should never be in a position to make any non-trivial ethical or moral judgments concerning people unless we are confident, preferably with mathematical certainty, that these judgments are what we truly consider ethical.

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-"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 in order 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 establishes the challenge and sets out the tradition in terms of which an adequate solution should be assessed. The next paper in this series responds to the challenge in Kantian terms, and shows that a Kantian AMA is not only a possibility for Machine ethics research, but a necessary one.

Philosophy & Technology, 2013

A key distinction in ethics is between members and non-members of the moral community. Over time our notion of this community has expanded as we have moved from a rationality criterion to a sentience criterion for membership. I argue that a sentience criterion is insufficient to accommodate all members of the moral community; the true underlying criterion can be understood in terms of whether a being has interests. This may be extended to conscious, self-aware machines, as well as to any autonomous intelligent machines. Such machines exhibit an ability to formulate desires for the course of their own existence; this gives them basic moral standing. While not all machines display autonomy, those which do must be treated as moral patients; to ignore their claims to moral recognition is to repeat past errors. I thus urge moral generosity with respect to the ethical claims of intelligent machines.

Research into the ethics of artificial intelligence is often categorized into two subareas-robot ethics and machine ethics. Many of the definitions and classifications of the subject matter of these subfields, as found in the literature, are conflated, which I seek to rectify. In this essay, I infer that using the term 'machine ethics' is too broad and glosses over issues that the term computational ethics best describes. I show that the subject of inquiry of computational ethics is of great value and indeed is an important frontier in developing ethical artificial intelligence systems (AIS). I also show that computational is a distinct, often neglected field in the ethics of AI. In contrast to much of the literature, I argue that the appellation 'machine ethics' does not sufficiently capture the entire project of embedding ethics into AI/S and hence the need for computational ethics. This essay is unique for two reasons; first, it offers a philosophical analysis of the subject of computational ethics that is not found in the literature. Second, it offers a finely grained analysis that shows the thematic distinction among robot ethics, machine ethics and computational ethics.

Religions

Machine Ethics has established itself as a new discipline that studies how to endow autonomous devices with ethical behavior. This paper provides a general framework for classifying the different approaches that are currently being explored in the field of machine ethics and introduces considerations that are missing from the current debate. In particular, law-based codes implemented as external filters for action-which we have named filtered decision making-are proposed as the basis for future developments. The emergence of values as guides for action is discussed, and personal language -together with subjectivity-are indicated as necessary conditions for this development. Last, utilitarian approaches are studied and the importance of objective expression as a requisite for their implementation is stressed. Only values expressed by the programmer in a public language-that is, separate of subjective considerations-can be evolved in a learning machine, therefore establishing the limits of present-day machine ethics.