There is a long-standing debate regarding the nature of the relationship between emotions and consciousness. Majority of existing computational models of emotions largely avoid the issue, and generally do not explicitly address distinctions between the conscious and the unconscious components of emotions. This paper highlights the importance of developing an adequately differentiated vocabulary describing the mental states of interest, and their features and components, for the development of computational models of the relationships between emotions and consciousness. We discuss current psychological (...) theories of emotion, highlighting specific points in the affective processes where links exist with consciousness, and possible roles played by each. We discuss examples of models that are beginning to address components of the interface between emotions and consciousness: models of social emotions, requiring explicit representations of the self; models of affective biases on attention; models of emotion and metacognition; and models of emotion regulation. We conclude with a discussion of some of the challenges associated with modeling mental states whose core distinguishing characteristic is an awareness of affective feelings, and highlight the importance of integrating the diverse approaches to emotion research and modeling currently existing within psychology and neuroscience. (shrink)

A great deal of effort has been, and continues to be, devoted to developing consciousness artificially (A small selection of the many authors writing in this area includes: Cotterill (J Conscious Stud 2:290–311, 1995 , 1998 ), Haikonen ( 2003 ), Aleksander and Dunmall (J Conscious Stud 10:7–18, 2003 ), Sloman ( 2004 , 2005 ), Aleksander ( 2005 ), Holland and Knight ( 2006 ), and Chella and Manzotti ( 2007 )), and yet a similar amount of effort has (...) gone in to demonstrating the infeasibility of the whole enterprise (Most notably: Dreyfus ( 1972/1979 , 1992 , 1998 ), Searle ( 1980 ), Harnad (J Conscious Stud 10:67–75, 2003 ), and Sternberg ( 2007 ), but there are a great many others). My concern in this paper is to steer some navigable channel between the two positions, laying out the necessary pre-conditions for consciousness in an artificial system, and concentrating on what needs to hold for the system to perform as a human being or other phenomenally conscious agent in an intersubjectively-demanding social and moral environment. By adopting a thick notion of embodiment—one that is bound up with the concepts of the lived body and autopoiesis (Maturana and Varela 1980 ; Varela et al. 2003 ; and Ziemke 2003 , 2007a , J Conscious Stud 14(7):167–179, 2007b )—I will argue that machine phenomenology is only possible within an embodied distributed system that possesses a richly affective musculature and a nervous system such that it can, through action and repetition, develop its tactile-kinaesthetic memory, individual kinaesthetic melodies pertaining to habitual practices, and an anticipatory enactive kinaesthetic imagination. Without these capacities the system would remain unconscious, unaware of itself embodied within a world. Finally, and following on from Damasio’s ( 1991 , 1994 , 1999 , 2003 ) claims for the necessity of pre-reflective conscious, emotional, bodily responses for the development of an organism’s core and extended consciousness, I will argue that without these capacities any agent would be incapable of developing the sorts of somatic markers or saliency tags that enable affective reactions, and which are indispensable for effective decision-making and subsequent survival. My position, as presented here, remains agnostic about whether or not the creation of artificial consciousness is an attainable goal. (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)

A brain model based on glial-neuronal interactions is proposed. Glial-neuronal synaptic units are interpreted as elementary reflection mechanisms, called proemial synapses. In glial networks (syncytia), cyclic intentional programs are generated, interpreted as auto-reflective intentional programming. Both types of reflection mechanisms are formally described and may be implementable in a robot brain. Based on the logic of acceptance and rejection, the robot is capable of rejecting irrelevant environmental information, showing at least a "touch" of subjective behavior. Since reflective intentional programming generates (...) both relevant and irrelevant structures already within the brain, ontological gaps arise which must be integrated. In the human brain, the act of self-reference may exert a holistic function enabling self-consciousness. However, since the act of self-reference is a mysterious function not experimentally testable in brain research, it cannot be implemented in a robot brain. Therefore, the creation of self-conscious robots may never be possible. Finally, some philosophical implications are discussed. (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)

Machine consciousness is not only a technological challenge, but a new way to approach scientific and theoretical issues which have not yet received a satisfactory solution from AI and robotics. We outline the foundations and the objectives of machine consciousness from the standpoint of building a conscious robot.