This paper is a review of the work that has been carried out on machine consciousness. A clear overview of this diverse field is achieved by breaking machine consciousness down into four different areas, which are used to understand its aims, discuss its relationship with other subjects and outline the work that has been carried out so far. The criticisms that have been made against machine consciousness are also covered, along with its potential benefits, and the work that has been (...) done on analysing systems for signs of consciousness. Some of the social and ethical issues raised by machine consciousness are examined at the end of the paper. (shrink)

Can machines be conscious and what would be the ethical implications? This article gives an overview of current robotics approaches toward machine consciousness and considers factors that hamper an understanding of machine consciousness. After addressing the epistemological question of how we would know whether a machine is conscious and discussing potential advantages of potential future machine consciousness, it outlines the role of consciousness for ascribing moral status. As machine consciousness would most probably differ considerably from human consciousness, several complex questions (...) must be addressed, including what forms of machine consciousness would be morally relevant forms of consciousness, and what the ethical implications of morally relevant forms of machine consciousness would be. While admittedly part of this reflection is speculative in nature, it clearly underlines the need for a detailed conceptual analysis of the concept of artificial consciousness and stresses the imperative to avoid building machines with morally relevant forms of consciousness. The article ends with some suggestions for potential future regulation of machine consciousness. (shrink)

Deep learning AI systems have proven a wide capacity to take over human-related activities such as car driving, medical diagnosing, or elderly care, often displaying behaviour with unpredictable consequences, including negative ones. This has raised the question whether highly autonomous AI may qualify as morally responsible agents. In this article, we develop a set of four conditions that an entity needs to meet in order to be ascribed moral responsibility, by drawing on Aristotelian ethics and contemporary philosophical research. We encode (...) these conditions and generate a flowchart that we call the Moral Responsibility Test. This test can be used as a tool both to evaluate whether an entity is a morally responsible agent and to inform human moral decision-making over the influencing variables of the context of action. We apply the test to the case of Artificial Moral Advisors and conclude that this form of AI cannot qualify as morally responsible agents. We further discuss the implications for the use of AMAs as moral enhancement and show that using AMAs to offload human responsibility is inadequate. We argue instead that AMAs could morally enhance users if they are interpreted as enablers for moral knowledge of the contextual variables surrounding human moral decision-making, with the implication that such a use might actually enlarge human moral responsibility. (shrink)

During the last decade there has been burgeoning research concerning the ways in which we should think of and apply the concept of responsibility for Artificial Intelligence. Despite this conceptual richness, there is still a lack of consensus regarding what Responsible AI entails on both conceptual and practical levels. The aim of this paper is to connect the ethical dimension of responsibility in Responsible AI with Aristotelian virtue ethics, where notions of context and dianoetic virtues play a grounding role for (...) the concept of moral responsibility. The paper starts by highlighting the important difficulties in assigning responsibility to either technologies themselves or to their developers. Top-down and bottom-up approaches to moral responsibility are then contrasted, as we explore how they could inform debates about Responsible AI. We highlight the limits of the former ethical approaches and build the case for classical Aristotelian virtue ethics. We show that two building blocks of Aristotle’s ethics, dianoetic virtues and the context of actions, although largely ignored in the literature, can shed light on how we could think of moral responsibility for both AI and humans. We end by exploring the practical implications of this particular understanding of moral responsibility along the triadic dimensions of ethics by design, ethics in design and ethics for designers. (shrink)

Domesticated animals need to be treated as fellow citizens: only if we conceive of domesticated animals as full members of our political communities can we do justice to their moral standing—or so Sue Donaldson and Will Kymlicka argue in their widely discussed book Zoopolis. In this contribution, we pursue two objectives. Firstly, we reject Donaldson and Kymlicka’s appeal for animal citizenship. We do so by submitting that instead of paying due heed to their moral status, regarding animals as citizens misinterprets (...) their moral qualities and thus risks treating them unjustly. Secondly, we suggest that Donaldson and Kymlicka’s reinforced focus on membership should draw our attention to the moral standing of a further ‘species’, namely robots. Developments within artificial intelligence have advanced rapidly in recent years. With robots’ gaining ever greater capacities and abilities, we need to ask urgent questions about the moral ramifications of these technical advances. (shrink)

This third paper locates the synthetic neurorobotics research reviewed in the second paper in terms of themes introduced in the first paper. It begins with biological non-reductionism as understood by Searle. It emphasizes the role of synthetic neurorobotics studies in accessing the dynamic structure essential to consciousness with a focus on system criticality and self, develops a distinction between simulated and formal consciousness based on this emphasis, reviews Tani and colleagues' work in light of this distinction, and ends by forecasting (...) the increasing importance of synthetic neurorobotics studies for cognitive science and philosophy of mind going forward, finally in regards to most- and myth-consciousness. (shrink)

By following the arguments developed by Vygotsky and employing the cultural-historical activity theory (CHAT) in addition to dialectical logic, this paper attempts to investigate the interaction between psychology and artificial intelligence (AI) to confront the epistemological and methodological challenges encountered in AI research. The paper proposes that AI is facing an epistemological and methodological crisis inherited from psychology based on dualist ontology. The roots of this crisis lie in the duality between rationalism and objectivism or in the mind-body rupture that (...) has governed the production of scientific thought and the proliferation of approaches. In addition, by highlighting the sociohistorical conditions of AI, this paper investigates the historical characteristics of the shift of the crisis from psychology to AI. Additionally, we examine the epistemological and methodological roots of the main challenges encountered in AI research by noting that empiricism is the dominant tendency in the field. Empiricism gives rise to methodological and practical challenges, including challenges related to the emergence of meaning, abstraction, generalization, the emergence of symbols, concept formation, functional reflection of reality, and the emergence of higher psychological functions. Furthermore, through discussing attempts to formalize dialectical logic, the paper, based on contradiction formation, proposes a qualitative epistemological, methodological, and formal alternative by using a preliminary algorithmic model that grasps the formation of meaning as an essential ability for the qualitative reflection of reality and the emergence of other mental functions. (shrink)

Theories of cognition and theories of social practices and institutions have often each separately acknowledged the relevance of the other; but seldom have there been consistent and sustained attempts to synthesize these two areas within one explanatory framework. This is precisely what my dissertation aims to remedy. I propose that certain recent developments and themes in philosophy of mind and cognitive science, when understood in the right way, can explain the emergence and dynamics of social practices and institutions. Likewise, the (...) view I construct explains how social practices and institutions shape the character of cognition of their constituent agents. Moreover, I explain both cognitive and social agency under the single explanatory framework provided by Dynamic Systems Theory. Drawing upon the phenomenological tradition, "embodied, "extended", "embedded", "enactive", and "ecological" approaches to cognition, as well as the conceptual resources of Dynamic Systems Theory, I construct a theory of agency that sees cognitive and social agents as far-from-equilibrium, open, recursively self-maintenant dynamic systems. Depending on the specifics of concrete circumstances, such systems, which I call "Dynamic Embodied Agents", may develop and possess emergent capacities for error-detection, flexible learning, normative behavior, representation, self-reflection, various modes of pattern-recognition, a temporal sense of self, and even moral responsibility. Some such systems are also sensitive to perceived social influences ; while reciprocally constituting and causally affecting them. (shrink)

Adopting the notion of “pragmatic information” as interpreted by Roederer and granted that understanding arises from genuine information processing, I show that Searle’s “Chinese Room Argument” in rejecting the thesis of Strong Artificial Intelligence and his responses to critics are sound and acceptable. The paper is a safe and secure translation of Searle’s argument into a language of information. According to the notion of information that I adopt, information and information processing are exclusive attributes of biological and artificial systems. However, (...) I will show that information-theoretically, biological brains are fundamentally different from their artificial simulations. I will argue that only biological systems, or their duplicates, are genuine information processing systems and thus capable of understanding Chinese. “Understanding”, in my proposal, denotes “phenomenal consciousness” in the context of Chalmers’ thesis of naturalistic dualism. (shrink)

Eliminative functionalism is the view that mental attributes, of humans and other machines, consist ultimately in behavioural abilities or dispositions. Hence, ‘Strong AI’: if a machine consistently acts as if it were fully conscious, then conscious it is. From these assumptions, optimistic futurists have derived a variety of remarkable visions of our ‘post-human’ future; from widely-recognised ‘robot rights’ to ‘mind uploading’, immortality, ‘apotheosis’ and beyond. It is argued here, however, that eliminative functionalism is false; for at least on our present (...) knowledge, the subjectively qualitative characteristics of conscious experience are neither deducible from, nor logically required to generate, the performance of any sort of overtly ‘intelligent’, or indeed, characteristically human behaviour. Thus, a machine could easily be designed to report awareness of phenomenal qualities, without necessarily possessing them; and Alan Turing’s ‘Imitation Game’ test for artificial thinking is unable to determine whether or not a machine is sentient. An alternative test is proposed, in which the machine is asked phenomenological questions under conditions designed to detect any form of cheating—whilst also, potentially revealing evidence for the occurrence of genuine qualitative experience. (shrink)