Online research in philosophy

Machine consciousness exists already in organic systems and it is only a matter of time -- and some agreement -- before it will be realised in reverse-engineered organic systems and forward- engineered inorganic systems. The agreement must be over the preconditions that must first be met if the enterprise is to be successful, and it is these preconditions, for instance, being a socially-embedded, structurally-coupled and dynamic, goal-directed entity that organises its perceptual input and enacts its world through the application of both a cognitive and kinaesthetic imagination, that I shall concentrate on presenting in this paper. It will become clear that these preconditions will present engineers with a tall order, but not, I will argue, an impossible one. After all, we might agree with Freeman and Núñez's claim that the machine metaphor has restricted the expectations of the cognitive sciences (Freeman & Núñez, 1999); but it is a double-edged sword, since our limited expectations about machines also narrow the potential of our cognitive science.

There is quite a bit of disagreement in cognitive science regarding the role that consciousness and control play in explanations of how people do what they do. The purpose of the present paper is to do the following: (1) examine the theoretical choice points that have lead theorists to conflicting positions, (2) examine the philosophical and empirical problems different theories encounter as they address the issue of conscious agency, and (3) provide an integrative framework (Wild Systems Theory) that addresses these problems and potentially naturalizes conscious agency. It does so by grounding conscious and control in the notion of self-sustaining energy-transformation systems (i.e., living systems), versus computational or self- organizing systems, as is the case in information processing theory and dynamical systems theory, respectively. Given its assertion that content (and consciousness) emerges in self-sustaining systems, Wild Systems Theory may also provide a sound theoretical basis for a science of consciousness in general.

The complex systems approach to cognitive science invites a new understanding of extended cognitive systems. According to this understanding, extended cognitive systems are heterogenous, composed of brain, body, and niche, non-linearly coupled to one another. In our previous work, we have argued that this view of cognitive systems, as non-linearly coupled brain-body-niche systems, promises conceptual and methodological advances on a series of traditional philosophical problems concerning cognition, reductionism, and consciousness. In this paper, we discuss agency and intentional action in light of this view of cognition.

In previous publications I have argued that much scientific activity should be thought of as involving the operation of distributed cognitive systems. Since these contributions to the cognitive study of science appear in venues not necessarily frequented by philosophers of science, I begin with a brief introduction to the notion of a distributed cognitive system. I then describe what I take to be an exemplary case of a scientific distributed cognitive system, the Hubble Space Telescope (HST). I do not here reargue the case for conceiving of systems like the HST as distributed cognitive systems. Rather, I examine a question that arises once one has adopted the perspective of distributed cognitive systems, namely, the role of agency in a distributed cognitive system. Here I argue, contrary to several advocates of distributed cognitive systems, that we should regard the human components of distributed cognitive systems as the only sources of agency within such systems. In particular, we should not extend notions of agency to such systems as a whole.

The complex systems approach to cognitive science invites a new understanding of extended cognitive systems. According to this understanding, extended cognitive systems are heterogenous, composed of brain, body, and niche, non-linearly coupled to one another. This view of cognitive systems, as non-linearly coupled brain–body–niche systems, promises conceptual and methodological advances. In this article we focus on two of these. First, the fundamental interdependence among brain, body, and niche makes it possible to explain extended cognition without invoking representations or computation. Second, cognition and conscious experience can be understood as a single phenomenon, eliminating fruitless philosophical discussion of qualia and the so-called hard problem of consciousness. What we call “extended phenomenological-cognitive systems” are relational and dynamical entities, with interactions among heterogeneous parts at multiple spatial and temporal scales.

While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems.

While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems.

From the perspective of cognitive science, it is illuminating to think of much contemporary scienti?c research as taking place in distributed cognitive systems. This is particularly true of large-scale experimental and observational systems such as the Hubble Telescope. Clark, Hutchins, Knorr-Cetina, and Latour insist or imply such a move requires expanding our notions of knowledge, mind, and even consciousness. Whether this is correct seems to me not a straightforward factual question. Rather, the issue seems to be how best to develop a theoretical understanding of such systems appropriate to the study of science and technology. I argue that there is no need to attribute to such systems as a whole any form of cognitive agency. We can well understand the importance of such systems while restricting agency to the human components. The implication is that we think of these large-scale distributed cognitive systems not so much as uni?ed wholes, but as hybrid systems including both physical artifacts and ordinary humans.

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness. To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST). A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems.

There is quite a bit of disagreement in cognitive science regarding the role that consciousness and control play in explanations of how people do what they do. The purpose of the present paper is to do the following: (1) examine the theoretical choice points that have lead theorists to conflicting positions, (2) examine the philosophical and empirical problems different theories encounter as they address the issue of conscious agency, and (3) provide an integrative framework (Wild Systems Theory) that addresses these problems and potentially naturalizes conscious agency. It does so by grounding conscious and control in the notion of self-sustaining energy-transformation systems (i.e., living systems), versus computational or self- organizing systems, as is the case in information processing theory and dynamical systems theory, respectively. Given its assertion that content (and consciousness) emerges in self-sustaining systems, Wild Systems Theory may also provide a sound theoretical basis for a science of consciousness in general.