The Limits of Machine Ethics

Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence/robotics communities. We will argue that the attempts to allow machines to make ethical decisions or to have rights are misguided. Instead we propose a new science of safety engineering for intelligent artificial agents. In particular we issue a challenge to the scientific community to develop intelligent systems capable of proving that they are in fact safe even under recursive self-improvement. The last decade has seen a boom of new subfields of computer science concerned with development of ethics in machines. Machine ethics [5, 6, 32, 29, 40], computer ethics [28], robot ethics [37, 38, 27], ethicALife [42], machine morals [44], cyborg ethics [43], computational ethics [36], roboethics [41], robot rights [21], and artificial morals [3] are just some of the proposals meant to address society's concerns with safety of ever more advanced machines [39]. Unfortunately the perceived abundance of research in intelligent machine safety is misleading. The great majority of published papers are purely philosophical in nature and do little more than reiterate the need for machine ethics and argue about which set of moral convictions would be the right ones to implement in our artificial progeny (Kantian [33], Utilitarian [20], Jewish [34], etc.). However, since ethical norms are not universal, a " correct " ethical code could never be selected over others to the satisfaction of humanity as a whole.

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.

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.

EthicAI=Labs, 2022

This article addresses the "ethical turn" in the studies of AI which is framed by the discourses of the so-called "empirical turn" (Verbeek). In this context, the main research goal in the field of AI ethics is implementing ethical principles within machines considered as growing increasingly autonomous in their agency. Outlined are the ethical theories and design approaches to achieving this goal as well as some of the technical and conceptual challenges faced by the AI researchers. However, in discussing the question of implementing ethical restrictions in machines to prevent them from harming humankind and better serve its pursuit of happiness, an ethical contradiction arises (Gunkel, 2020: 547). If we want to speak of ethics, shouldn’t we begin to consider artificial system’s rights and not only their obligations? This understanding dissolves the power relationship between humans and machines discussed above. And finally, this article points to a fundamental limitation of AI ethics research in that the existing discourses rather serve as “a tool for policy making” without any ambition of radically questioning the framework (ontological, metaphysical, transcendental or politico-economic), which provides the conditions of innovation and existence of technologies as such.

Belgian/Netherlands Artificial Intelligence Conference, 2012

With the increasing dependence on autonomous operating agents and robots the need for ethical machine behavior rises. This paper presents a moral reasoner that combines connectionism, utilitarianism and ethical theory about moral duties. The moral decision-making matches the analysis of expert ethicists in the health domain. This may be useful in many applications, especially where machines interact with humans in a medical context. Additionally, when connected to a cognitive model of emotional intelligence and affective decision making, it can be explored how moral decision making impacts affective behavior.

2020

Abstracts for the Second Workshop on Implementing Machine Ethics

2009 AAAI Fall Symposium Series, 2009

As machines become more intelligent and take on more responsibilities, their decision-making capabilities must be informed and constrained by a coherent, integrated moral/ethical structure with no internal inconsistencies for everyone's safety and well-being. Unfortunately, no such structure is currently agreed upon to exist. We propose to solve this problem by a) drawing upon experimental evidence and lessons learned from evolution and economics to show that morality is actually objective and derivable from first principles; b) presenting a coherent, integrated, platonic ethical system with no internal inconsistencies that flows naturally from a single high-level logically-derived Kantian imperative to low-level reflexive "rules of thumb" that match current human sensibilities; and c) suggesting a biologically-inspired architecture which supports and enforces this system which can be relatively easily implemented.

arXiv (Cornell University), 2022

The 4th Industrial Revolution is the culmination of the digital age. Nowadays, technologies such as robotics, nanotechnology, genetics, and artificial intelligence promise to transform our world and the way we live. Artificial Intelligence Ethics and Safety is an emerging research field that has been gaining popularity in recent years. Several private, public and non-governmental organizations have published guidelines proposing ethical principles for regulating the use and development of autonomous intelligent systems. Meta-analyses of the AI Ethics research field point to convergence on certain principles that supposedly govern the AI industry. However, little is known about the effectiveness of this form of "Ethics." In this paper, we would like to conduct a critical analysis of the current state of AI Ethics and suggest that this form of governance based on principled ethical guidelines is not sufficient to norm the AI industry and its developers. We believe that drastic changes are necessary, both in the training processes of professionals in the fields related to the development of software and intelligent systems and in the increased regulation of these professionals and their industry. To this end, we suggest that law should benefit from recent contributions from bioethics, to make the contributions of AI ethics to governance explicit in legal terms.

2020

The impending highly automated and autonomous systems enabled by artificial intelligence (AI) bring with them new challenges and risks. Placing too much trust in, or misusing, machines that make decisions is risky, and the legalities are complex in terms of liability and responsibility. Autonomous systems can be grouped into three broad categories: technical systems that make decisions in "no win" hazardous situations (vehicles in traffic, collaborating robots); decision support systems in governance applications (administration, government, court, staff acquisition, etc.), which may lead to unfair decisions for humans and society; and systems that are open to deliberate misuse by providing information that can't be proven to be true or fake, potentially influencing elections, public opinion or legal processes to an extent unknown before. These risks cannot be easily countered by conventional methods. We give an overview of the potential and risks afforded by this tech...

IEEE Robotics & Automation Magazine, 2011

A pproaches to programming ethical behavior for computer systems face challenges that are both technical and philosophical in nature. In response, an incrementalist account of machine ethics is developed: a successive adaptation of programmed constraints to new, morally relevant abilities in computers. This approach allows progress under conditions of limited knowledge in both ethics and computer systems engineering and suggests reasons that we can circumvent broader philosophical questions about computer intelligence and autonomy.