To assess the intelligence of machines, Alan Turing proposed a test of imitation known as the imitation game, famously known as the Turing test. To assess whether artificial intelligent (AI) systems could be moral or not, Colin Allen et al. developed a test of imitation in the context of morality, a test known as the Moral Turing Test (MTT), which I will, in this paper, call the moral imitation game. There are arguments against developing any type of MTT or moral (...) imitation game. Rather than developing a moral imitation game, this paper proposes a criterion of imitation for AI systems in the moral scenario. To develop a criterion of imitation, I explore the notion of moral attribution in detail. Within the case of moral attribution, I introduce the subject‐ascriber distinction. The notion of moral attribution and the subject‐ascriber distinction is employed to address the following questions: (a) how is the assessment in MTT arranged?, (b) what is the role of the interrogator in the MTT?, and (c) what information is to be concealed from the interrogator? The first question deals with the aspect of assessment, the second question deals with the reordering of the role of the interrogator and the third one deals with the concealment aspect of the imitation game. After that, a criterion of imitation for AI systems is put forward. Using the subject‐ascriber distinction in moral attribution and David Lewis' Mad Pain and Martian Pain cases, it is argued that the notion of sentience is insignificant for the ascriber for moral attributions. (shrink)

Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, we (...) critically explore the possibilities and challenges for virtue ethics from a computational perspective. Drawing on previous conceptual and technical work, we outline a version of artificial virtue based on moral functionalism, connectionist bottom–up learning, and eudaimonic reward. We then describe how core features of the outlined theory can be interpreted in terms of functionality, which in turn informs the design of components necessary for virtuous cognition. Finally, we present a comprehensive framework for the technical development of artificial virtuous agents and discuss how they can be implemented in moral environments. (shrink)

Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, we (...) critically explore the possibilities and challenges for virtue ethics from a computational perspective. Drawing on previous conceptual and technical work, we outline a version of artificial virtue based on moral functionalism, connectionist bottom–up learning, and eudaimonic reward. We then describe how core features of the outlined theory can be interpreted in terms of functionality, which in turn informs the design of components necessary for virtuous cognition. Finally, we present a comprehensive framework for the technical development of artificial virtuous agents and discuss how they can be implemented in moral environments. (shrink)

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. 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. (shrink)

The potential societal impacts of automation using intelligent control and communications technologies have emerged as topics in a number of recent writings and public policy initiatives. Many of these expressions have referenced the writings and research efforts of Herbert Simon (1961), Norbert Wiener (1948), and contemporaries from their early technological and social vantage points concerning the future of technology and society. Constructed entities labeled as “thinking machines” (such as IBM’s Watson as well as intelligent chatbot and robotic systems) have also (...) played significant roles in this discourse. This paper provides an historical sequencing then analyzes a selection of writings produced since the 1940s concerning the economic and social issues involving artificial intelligence (AI) research and applications. The paper explores how overstatements and hyperbolic themes and concepts, often stemming from AI’s early periods, are being employed in characterizations of current AI approaches in apparently opportunistic attempts to provide rhetorical support for various large-scale business and societal initiatives. It also addresses the relative neglect of the consideration of many of AI’s sociotechnical failures and discontinued approaches in recent examinations of automation and social welfare issues. The paper discusses the moral logic of AI researchers and developers providing reasonable and measured narratives in public discourse rather than hyperbole, efforts that can empower decision makers to make sounder judgments concerning the technology’s current and future applications as well as allocate the rewards of the technology more equitably. (shrink)

Estonia has successfully created a digital society within the past 2 decades. It is best known for its eGovernment achievements, but it is also home for four unicorn star-ups. While the state is aiming to attract tech investments with e-Residency program and has recently started to invest into protecting national IP and safeguarding data from cybercrime by applying blockchain technology and creating its “digital embassy” in Luxembourg, emerging technologies such as and applications of artificial intelligence but also internet of things (...) have posed the question on legal regulation and standardization. The dilemma, however, seems to be that since the new technologies, such artificial intelligence is much more overwhelming phenomenon than e-governance and presumably, before deciding the legal standards, the political and economic strategies that go beyond the e-governance should be set. (shrink)

In the present article, I will advocate caution against developing artificial moral agents based on the notion that the utilization of preliminary forms of AMAs will potentially negatively feed back on the human social system and on human moral thought itself and its value—e.g., by reinforcing social inequalities, diminishing the breadth of employed ethical arguments and the value of character. While scientific investigations into AMAs pose no direct significant threat, I will argue against their premature utilization for practical and economical (...) use. I will base my arguments on two thought experiments. The first thought experiment deals with the potential to generate a replica of an individual’s moral stances with the purpose to increase, what I term, ’moral efficiency’. Hence, as a first risk, an unregulated utilization of premature AMAs in a neoliberal capitalist system is likely to disadvantage those who cannot afford ’moral replicas’ and further reinforce social inequalities. The second thought experiment deals with the idea of a ’moral calculator’. As a second risk, I will argue that, even as a device equally accessible to all and aimed at augmenting human moral deliberation, ’moral calculators’ as preliminary forms of AMAs are likely to diminish the breadth and depth of concepts employed in moral arguments. Again, I base this claim on the idea that the current most dominant economic system rewards increases in productivity. However, increases in efficiency will mostly stem from relying on the outputs of ’moral calculators’ without further scrutiny. Premature AMAs will cover only a limited scope of moral argumentation and, hence, over-reliance on them will narrow human moral thought. In addition and as the third risk, I will argue that an increased disregard of the interior of a moral agent may ensue—a trend that can already be observed in the literature. (shrink)

AI systems are bringing an augmentation of human capabilities to shape the world. They may also drag a replacement of human conscience in large chunks of life. AI systems can be designed to leave moral control in human hands, to obstruct or diminish that moral control, or even to prevent it, replacing human morality with pre-packaged or developed ‘solutions’ by the ‘intelligent’ machine itself. Artificial Intelligent systems (AIS) are increasingly being used in multiple applications and receiving more attention from the (...) public and private organisations. The purpose of this article is to offer a mapping of the technological architectures that support AIS, under the specific focus of the moral agency. Through a literature research and reflection process, the following areas are covered: a brief introduction and review of the literature on the topic of moral agency; an analysis using the BDI logic model (Bratman 1987); an elemental review of artificial ‘reasoning’ architectures in AIS; the influence of the data input and the data quality; AI systems’ positioning in decision support and decision making scenarios; and finally, some conclusions are offered about regarding the potential loss of moral control by humans due to AIS. This article contributes to the field of Ethics and Artificial Intelligence by providing a discussion for developers and researchers to understand how and under what circumstances the ‘human subject’ may, totally or partially, lose moral control and ownership over AI technologies. The topic is relevant because AIS often are not single machines but complex networks of machines that feed information and decisions into each other and to human operators. The detailed traceability of input-process-output at each node of the network is essential for it to remain within the field of moral agency. Moral agency is then at the basis of our system of legal responsibility, and social approval is unlikely to be obtained for entrusting important functions to complex systems under which no moral agency can be identified. (shrink)

As a way to address both ominous and ordinary threats of artificial intelligence, researchers have started proposing ways to stop an AI system before it has a chance to escape outside control and cause harm. A so-called “big red button” would enable human operators to interrupt or divert a system while preventing the system from learning that such an intervention is a threat. Though an emergency button for AI seems to make intuitive sense, that approach ultimately concentrates on the point (...) when a system has already “gone rogue” and seeks to obstruct interference. A better approach would be to make ongoing self-evaluation and testing an integral part of a system’s operation, diagnose how the system is in error and to prevent chaos and risk before they start. In this paper, we describe the demands that recent big red button proposals have not addressed, and we offer a preliminary model of an approach that could better meet them. We argue for an ethical core that consists of a scenario-generation mechanism and a simulation environment that are used to test a system’s decisions in simulated worlds, rather than the real world. This EC would be kept opaque to the system itself: through careful design of memory and the character of the scenario, the system’s algorithms would be prevented from learning about its operation and its function, and ultimately its presence. By monitoring and checking for deviant behavior, we conclude, a continual testing approach will be far more effective, responsive, and vigilant toward a system’s learning and action in the world than an emergency button which one might not get to push in time. (shrink)

The field of AI ethics during the current and previous decade is receiving an increasing amount of attention from all involved stakeholders: the public, science, philosophy, religious organizations, enterprises, governments, and various organizations. However, this field currently lacks consensus on scope, ethico-philosophical foundations, or common methodology. This thesis aims to contribute towards filling this gap by providing an answer to the two main research questions: first, what theory can explain moral scenarios in which AI entities are participants?; and second, what (...) theory can explain the process of moral reasoning, decision and action, for AI entities in virtual, simulated and real-life moral scenarios? This thesis answers these two research questions with its two main contributions to the field of AI ethics, a substantial and a methodological contribution. The substantial contribution is a coherent and novel theory named Ethics of Systems Framework, as well as a possible inception of a new field of study: ethics of systems. The methodological contribution is the creation of its main methodological tool, the Ethics of Systems Interface. The second part of the research effort was focused on testing and demonstrating the capacities of the Ethics of Systems Framework and Interface in modeling and managing moral scenarios in which AI and other entities participate. Further work can focus on building on top of the foundations of the Framework provided here, increasing the scope of moral theories and simulated scenarios, improving the level of detail and parameters to reflect real-life situations, and field-testing the Framework on actual AI systems. (shrink)

This paper provides a survey of philosophical discussion of the "the Turing Test". In particular, it provides a very careful and thorough discussion of the famous 1950 paper that was published in Mind.

The ethics of emerging forms of artificial intelligence has become a prolific subject in both academic and public spheres. A great deal of these concerns flow from the need to ensure that these technologies do not cause harm—physical, emotional or otherwise—to the human agents with which they will interact. In the literature, this challenge has been met with the creation of artificial moral agents: embodied or virtual forms of artificial intelligence whose decision procedures are constrained by explicit normative principles, requiring (...) the implementation of what is commonly called artificial morality into these agents. To date, the types of reasoning structures and principles which inform artificial morality have been of two kinds: first, an ethically maximal vision of artificial morality which relies on the strict implementation of traditional moral theories such as Kantian deontology or Utilitarianism, and second, a more minimalist vision which applies stochastic AI techniques to large data sets of human moral preferences so as to illicit or intuit general principles and preferences for the design of artificial morality. Taken individually, each approach is unable to fully answer the challenge of producing inoffensive behavior in artificial moral agents, most especially since both forms are unable to strike a balance between the ideal set of constraints which morality imposes on one hand, and the types of constraints public acceptability imposes, on the other. We provide an alternative approach to the design of artificial morality, the Ethical Valence Theory, whose purpose is to accommodate this balance, and apply this approach to the case of autonomous vehicles. (shrink)

Direct neurological and especially imaging-driven investigations into the structures essential to naturally occurring cognitive systems in their development and operation have motivated broadening interest in the potential for artificial consciousness modeled on these systems. This first paper in a series of three begins with a brief review of Boltuc’s (2009) “brain-based” thesis on the prospect of artificial consciousness, focusing on his formulation of h-consciousness. We then explore some of the implications of brain research on the structure of consciousness, finding limitations (...) in biological approaches to the study of consciousness. Looking past these limitations, we introduce research in artificial consciousness designed to test for the emergence of consciousness, a phenomenon beyond the purview of the study of existing biological systems. (shrink)