The book addresses the broad issue of sustainability of our civilization and seeks to contribute to the ongoing discussion of what many see as its systemic crisis. There is a broad agreement that new creative ideas, initiatives, and solutions are essential for dealing with the current problems. However, despite this recognition, we still know very little about the process of creation and how it works. As a result, our civilization fails to harness the enormous creative potential of humanity. This failure, (...) the book argues, is the main source of our current problems—languishing economy, deteriorating environment, continued violence, the deficit of democracy, and the lack of new fundamental breakthroughs in science. It examines some of these problems and demonstrates the connection between them and our failure to embrace the process of creation. The book offers a perspective that sheds light on the process of creation. It pays special attention to the theoretical contributions of Jean Piaget and the ongoing discussions of knowledge production that help us understand better how the process of creation works. The central argument of the book is that in order to solve our current problems and ensure the sustainability of our civilization well into the future we must embrace the process of creation and make it the central organizing principle of our social practice. Finally, the book provides an outline of the principal changes that the adoption of the new social practice organized around the process of creation will involve. (shrink)

The book presents the case that cognitive science should turn its attention to developing theories of human cognition that cover the full range of human perceptual, cognitive, and action phenomena. Cognitive science has now produced a massive number of high-quality regularities with many microtheories that reveal important mechanisms. The need for integration is pressing and will continue to increase. Equally important, cognitive science now has the theoretical concepts and tools to support serious attempts at unified theories. The argument is made (...) entirely by presenting an exemplar unified theory of cognition both to show what a real unified theory would be like and to provide convincing evidence that such theories are feasible. The exemplar is SOAR, a cognitive architecture, which is realized as a software system. After a detailed discussion of the architecture and its properties, with its relation to the constraints on cognition in the real world and to existing ideas in cognitive science, SOAR is used as theory for a wide range of cognitive phenomena: immediate responses ; discrete motor skills ; memory and learning ; problem solving ; language ; and development. The treatments vary in depth and adequacy, but they clearly reveal a single, highly specific, operational theory that works over the entire range of human cognition, SOAR is presented as an exemplar unified theory, not as the sole candidate. Cognitive science is not ready yet for a single theory – there must be multiple attempts. But cognitive science must begin to work toward such unified theories. (shrink)

Exposing the chimpanzee to language training appears to enhance the animal's ability to perform some kinds of tasks but not others. The abilities that are enhanced involve abstract judgment, as in analogical reasoning, matching proportions of physically unlike exemplars, and completing incomplete representations of action. The abilities that do not improve concern the location of items in space and the inferences one might make in attempting to obtain them. Representing items in space and making inferences about them could be done (...) with an imaginal code, but representing relations and judging the relations between them, as in analogies, requires a more abstract code. Language training cannot instill such an abstract code, but for species that have the code to start with, it may enhance the animal's ability to use it. (shrink)

This paper puts forward a general framework for thought about human information processing. It is intended to avoid some of the problems of pipeline or stage models of function. At the same time it avoids the snare of supposing a welter of indefinitely many separate processes. The approach is not particularly original, but rather represents the common elements or presuppositions in a number of modern theories. These presuppositions are not usually explicit, however, and making them so reduces the danger of (...) slipping back into earlier modes of thought.The key point is to distinguish between persisting representations and the processes that translate one representation into another. Various classes or groups of persisting representations can be distinguished by the experimental treatments that interfere with them. In particular, there now seem to be several kinds of short-term or temporary storage, different from each other as well as from longterm memory; the translating processes also have several different modes or kinds. A particularly important aspect of the current position is that a model of this general type no longer requires some external agent to direct and control long sequences of behaviour. (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)

My research into Virtual Reality technology and its central property of immersion has indicated that immersion in Virtual Reality (VR) electronic systems is a significant key to the understanding of contemporary culture as well as considerable aspects of previous culture as detected in the histories of philosophy and the visual arts. The fundamental change in aesthetic perception engendered by immersion, a perception which is connected to the ideal of total-immersion in virtual space, identifies certain shifts in ontology which are relevant (...) to a better understanding of the human being. This understanding was achieved through a broad inquiry into the histories of Virtual Reality, philosophy, and the visual arts and has lead to the formulation of an aesthetic theory of immersive consciousness indicative of immersive culture. The primary subject of this discourse is immersion then: an experience which will be identified within the dissertation as the indispensable characteristic of Virtual Reality. The understanding of immersion arrived at here will be used to fashion a synchronous theory of art particularly informed by encounters and concepts of immersion into virtuality. To sufficiently address this subject in a scholarly fashion, I have researched, found and accumulated aesthetic and philosophic examples of immersive tendencies, as found within the histories of art and philosophy, which subsequently contributed towards the articulation of what I have come to call immersive consciousness. As a result of formulating such an immersive consciousness, a good deal of the basis for the questioning of the Western ontological tradition has been found in the Western tradition itself when we look with new eyes and ask new uncertain questions. Moreover, this immersive consciousness will be used to propose some abstract questions encircling today's electronic-based culture. Through the structuring of the argument within the thesis - and overtly within the conclusion - I have articulated a non-teleological creative strategy which provides the basis for an unconstraining integration of noologies (ways of semblancing the thinking process). This strategy provides a means of exemplifying - and for honoring - various methods of thinking. This structuring strategy is consistent with the 'hacker ethic' as defined by Steven Levy, as a demand that access to computers - and anything which might teach us something about the way the world works - should be unlimited and total. To follow this strategy, this dissertation has set out to understand how topical conceptions of virtual immersion connect to pre-existing systems of thought as revealed in art as they have extended out of antecedent ontological self-understandings, historical human self-understandings which have evidenced themselves in the elaboration of technological objectives. To do this I have forged a certain rhizomatic paternity/maternity for Virtual Reality within this dissertation by joining choice immersive examples of simulacra technology into mental connections with the relevant examples culled from the histories of art, architecture, information-technology, sex, myth, space, consciousness and philosophy. (shrink)

The field of information technology is broadened up to the domain of ‘learning’ systems and cybernetics. In covering this extension of the field due recourse is made to the epistemological basis of theory construction. When so comprehended, information technology becomes a philosophical inquiry on a variety of social, scientific and technological issues. A new idea that we refer to as neuro-cybernetics is born. The term neuro-cybernetics is used to delineate the epistemological field of system and cybernetic study. The above-mentioned phenomenological (...) or the epistemic model of a cybernetic and system type is applied to flood control problem in Bangladesh. This example presents an application of the cybernetic model to a physico-human problem. This is the nature of socio-scientific system. In it, organically unifying relations occur between the environment and the human world, with the objective of controlling the perennial problem of floods by using interactive factors. (shrink)

Are minds really dynamical or are they really symbolic? Because minds are bundles of computations, and because computation is always a matter of interpretation of one system by another, minds are necessarily symbolic. Because minds, along with everything else in the universe, are physical, and insofar as the laws of physics are dynamical, minds are necessarily dynamical systems. Thus, the short answer to the opening question is “yes.” It makes sense to ask further whether some of the computations that constitute (...) a human mind are constrained by functional, algorithmic, or implementational factors to be essentially of the discrete symbolic variety (even if they supervene on an apparently continuous dynamical substrate). I suggest that here too the answer is “yes” and discuss the need for such discrete, symbolic cognitive computations in communication-related tasks. (shrink)

According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.

Recent literature on the role of pictorial representation in the life sciences has focused on the relationship between detailed representations of empirical data and more abstract, formal representations of theory. The standard argument is that in both a historical and epistemic sense, this relationship is a directional one: beginning with raw, unmediated images and moving towards diagrams that are more interpreted and more theoretically rich. Using the neural network diagrams of Warren McCulloch and Walter Pitts as a case study, I (...) argue that while in the empirical sciences, pictorial representation tends to move from data to theory, in areas of the life sciences that are predominantly theoretical, when abstraction occurs at the outset, the relationship between detail and abstraction in pictorial representations can be of a different character. (shrink)

This paper offers an introduction to the philosophy and science of embodied learning, conceived as both the stabilizing and expansionary process that sustains order and novelty within learners’ worlds enacted through observing and describing. Embodied learning acknowledges stability and change as the purposeful conjoined characteristics that sustain learners. It is, in many respects, a composite theory that represents work from various disciplines. This ‘naturalized epistemology’ conceives a world of fact inevitably imbued with the values that our own structural histories guarantee (...) us observers, whether acknowledged or not within our reflective awareness. These values, however, are not simple sets of preferences, for they are constituted in our individual learning histories that, for good or bad, influence the course of future learning. This conservational element of our condition is only half the story, however. The more radical aspect resides in the expansionary capacity of embodied observers to change, to enact worlds that are not pre‐given but, rather, brought forth by learners as observers and describers. Furthermore, embodied learning seeks a grounding for understanding in the often‐unexplored epistemological terrain between positivist absolutism or its mirrored polar opposite, postmodern nihilism. Its epistemological stance derives from its ontology, which is grounded in the profound obviousness that ‘everything said is said by someone’. (shrink)

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions. # 2004 Elsevier Ltd. All rights reserved.

The approach the majority of neuroscientists take to the question of how consciousness is generated, it is probably fair to say, is to ignore it. Although there are active research programs looking at correlates of consciousness, and explorations of informational properties of what might be relevant neural ensembles, the tacitly implied mechanism of consciousness in these approaches is that it somehow just happens. This reliance on a “magical emergence” of consciousness does not address the “objectively unreasonable” proposition that elements that (...) have no attributes or properties that can be said to relate to consciousness somehow aggregate to produce it. Neuroscience has furnished evidence that neurons are fundamental to consciousness; at the fine and gross scale, aspects of our conscious experience depend on specific patterns of neural activity – in some way, the connectivity of neurons computes the features of our experience. So how do we get from knowing that some specific configurations of cells produce consciousness to understanding why this would be the case? Behind the voltages and currents electrophysiologists measure is a staggeringly complex system of electromagnetic fields – these are the fundamental physics of neurons and glia in the brain. The brain is entirely made of electromagnetism phenomena from the level of the atoms up. The EM field literally manifests the computations, or signaling, or information processing/activities performed by connected cellular ensembles that generate a 1st-person perspective. An investigation into the EM field at the cellular scale provides the possibility of identifying the outward signs of a mechanism in fundamental terms, as opposed to merely describing the correlates of our mental abstractions of it. (shrink)

By the late 1990s, several converging trends in economics, psychology, and neuroscience had set the stage for the birth of a new scientific field known as “neuroeconomics”. Without the availability of an extensive variety of experimental designs for dealing with individual and social decision-making provided by experimental economics and psychology, many neuroeconomics studies could not have been developed. At the same time, without the significant progress made in neuroscience for grasping and understanding brain functioning, neuroeconomics would have never seen the (...) light of day. The paper is an overview of the main significant advances in the knowledge of brain functioning by neuroscience that have contributed to the emergence of neuroeconomics and its rise over the past two decades. These advances are grouped over three non-independent topics referred to as the “emo-rational” brain, “social” brain, and “computational” brain. For each topic, it emphasizes findings considered as critical to the birth and development of neuroeconomics while highlighting some of prominent questions about which knowledge should be improved by future research. In parallel, it shows that the boundaries between neuroeconomics and several recent sub-fields of cognitive neuroscience, such as affective, social, and more generally, decision neuroscience, are rather porous. (shrink)

Rather than assume a unitary cybernetics, I ask how its disunity mattered to the history of the human sciences in the United States from about 1940 to 1980. I compare the work of four prominent social scientists – Herbert Simon, George Miller, Karl Deutsch, and Talcott Parsons – who created cybernetic models in psychology, economics, political science, and sociology with the work of anthropologist Gregory Bateson, and relate their interpretations of cybernetics to those of such well-known cyberneticians as Norbert Wiener, (...) Warren McCulloch, W. Ross Ashby, and Heinz von Foerster. I argue that viewing cybernetics through the lens of disunity – asking what was at stake in choosing a specific cybernetic model – shows the complexity of the relationship between first-order cybernetics and the postwar human sciences, and helps us rethink the history of second-order cybernetics. (shrink)

Część II pracy objaśnia molekularne podłoże pamięci w oparciu o założenia Neuro-Elektro- Dynamiki postulowanej przez Aura i Yoga. Wskazano na biofizyczne mechanizmy generacji wspomnień, refleksji i odczuć dzięki efatycznym sprzężeniom synaptycznym, spełniającym wymagania indukowania impresjonów Vadakkana. Wykazano, że działanie mechanizmu selekcyjnego WTA może być dobrym modelem opisującym funkcję przełączania uwagi. Wskazano na relacje między pamięcią roboczą, krótkoterminową i trwałą i ich spójność z molekularnymi procesami zapamiętywania i rozpoznawania wzorców. Wskazano, że trwała pamięć epizodyczna wymaga konwersji sekwencji czasowych sygnałów bottom-up do (...) rozkładu przestrzennego tworzącego impresjony dynamiczne. Odwrotna transformacja tych impresjonów umożliwia przypominanie epizodów z przeszłości. Omówiono znaczenie wrodzonych struktur sieci neuronowych zapewniających dziedziczenie zachowań instynktownych. Struktury te nie wykluczają zachowania plastyczności umysłu umożliwiającej efektywne uczenie. (shrink)

Many years after the publication of “A Logical Calculus of the Ideas Immanent in Nervous Activity,” Warren McCulloch gave Walter Pitts credit for contributing his knowledge of modular mathematics to their joint project. In 1941 I presented my notions on the flow of information through ranks of neurons to Rashevsky’s seminar in the Committee on Mathematical Biology of the University of Chicago and met Walter Pitts, who then was about seventeen years old. He was working on a mathematical theory of (...) learning and I was much impressed. He was interested in problems of circularity, how to handle regenerative nervous activity in closed loops....For two years Walter and I worked on these problems whose solution depended upon modular mathematics of which I knew nothing, but Walter did.. In this paper, we will fill in some of the details regarding Pitts’s interest in problems of circularity, regenerative activity in closed loops of neurons, and modular mathematics, and the way in which they relate to “A Logical Calculus.”. (shrink)

The question posed is whether the optimization methods of calculus that are often used in social and scientific analyses offer an appropriate analytical approach to analyze problems that are immersed in systemic complexity and its consequences. This paper refers to the portfolio of such complex problems belonging to social and scientific forces. We refer to such a complex combination by the term ‘socio-scientific’. In the study of socio-scientific complexity, dynamic preferences, intricate decisions, and uncertain behavior, endogenous relations and systemic perturbations (...) abound. The arguments presented in this paper establish that the methodological approach of optimization and steady-state equilibrium turns out to be nicety rather than objectivity in the presence of complexity. Complex situations of the socio-scientific universe cause perturbations in the variables; there explaining complexity formed by the social embedding of variables. Indeed, human individuals, institutions and governments, and society at large are complex interrelated entities. Therefore, complex interrelations caused by social embedding remain submerged in social perturbations. However, interactions arising from social embedding also generate endogenous and complex relations. The contribution of this paper is in the area of endogenous learning in the wellbeing objective criterion function. The interrelationships between the emergent cognitive variables now cause interactive embedding, complexity, and social perturbations. Yet such perturbations are not altogether uncontrollable. They can be and need to be controlled for the purposes of social explanation—hence demanding predictability—even as the complex nature of evolutionary systemic learning proceeds. The controllability problem of extreme perturbations leads us to formalize a mathematical methodology to study controllable perturbations while avoiding extreme forms of perturbations in socio-scientific theory. (shrink)