Andy Clark and his Critics

In this volume, a range of high-profile researchers in philosophy of mind, philosophy of cognitive science, and empirical cognitive science, critically engage with Clark's work across the themes of: Extended, Embodied, Embedded, Enactive, and Affective Minds; Natural Born Cyborgs; and Perception, Action, and Prediction. Daniel Dennett provides a foreword on the significance of Clark's work, and Clark replies to each section of the book, thus advancing current literature with original contributions that will form the basis for new discussions, debates and directions in the discipline

‘The Action of the Brain’. Machine Models and Adaptive Functions in Turing and Ashby

Given the personal acquaintance between Alan M. Turing and W. Ross Ashby and the partial proximity of their research fields, a comparative view of Turing’s and Ashby’s work on modelling “the action of the brain” (letter from Turing to Ashby, 1946) will help to shed light on the seemingly strict symbolic/embodied dichotomy: While it is clear that Turing was committed to formal, computational and Ashby to material, analogue methods of modelling, there is no straightforward mapping of these approaches onto symbol-based AI and embodiment-centered views respectively. Instead, it will be demonstrated that both approaches, starting from a formal core, were at least partly concerned with biological and embodied phenomena, albeit in revealingly distinct ways

"Consciousness". Selected Bibliography 1970 - 2001

This is a bibliography of books and articles on consciousness in philosophy, cognitive science, and neuroscience over the last 30 years. There are three main sections, devoted to monographs, edited collections of papers, and articles. The first two of these sections are each divided into three subsections containing books in each of the main areas of research. The third section is divided into 12 subsections, with 10 subject headings for philosophical articles along with two additional subsections for articles in cognitive science and neuroscience. Of course the division is somewhat arbitrary, but I hope that it makes the bibliography easier to use. This bibliography has first been compiled by Thomas Metzinger and David Chalmers to appear in print in two philosophical anthologies on conscious experience (Metzinger 1995a, b). From 1995 onwards it has been continuously updated by Thomas Metzinger, and now is freely available as a PDF-, RTF-, or HTML-file. This bibliography mainly attempts to cover the Anglo-Saxon and German debates, in a non-annotated, fully formatted way that makes it easy to "cut and paste" from the original file. To a certain degree this bibliography also contains items in other languages than English and German - all submissions in other languages are welcome. Last update of current version: July 13th, 2001

Can biological quantum networks solve NP-hard problems?

There is a widespread view that the human brain is so complex that it cannot be efficiently simulated by universal Turing machines. During the last decades the question has therefore been raised whether we need to consider quantum effects to explain the imagined cognitive power of a conscious mind. This paper presents a personal view of several fields of philosophy and computational neurobiology in an attempt to suggest a realistic picture of how the brain might work as a basis for perception, consciousness and cognition. The purpose is to be able to identify and evaluate instances where quantum effects might play a significant role in cognitive processes. Not surprisingly, the conclusion is that quantum-enhanced cognition and intelligence are very unlikely to be found in biological brains. Quantum effects may certainly influence the functionality of various components and signalling pathways at the molecular level in the brain network, like ion ports, synapses, sensors, and enzymes. This might evidently influence the functionality of some nodes and perhaps even the overall intelligence of the brain network, but hardly give it any dramatically enhanced functionality. So, the conclusion is that biological quantum networks can only approximately solve small instances of NP-hard problems. On the other hand, artificial intelligence and machine learning implemented in complex dynamical systems based on genuine quantum networks can certainly be expected to show enhanced performance and quantum advantage compared with classical networks. Nevertheless, even quantum networks can only be expected to efficiently solve NP-hard problems approximately. In the end it is a question of precision - Nature is approximate.Comment: 38 page

The Development of an Evaluation Framework for eGovernment Systems

This paper is a positioning paper which outlines a proposal for engaging in the evaluation of eGovernment systems. The primary purpose of our proposed research is to develop, apply, test, and disseminate an evaluation framework which can support continuous, adaptable, and reflective evaluation of eGovernment systems. The theoretical bases for the methodology will be the Information Systems (IS), Soft Systems Methodology, SSM (Checkland and Scholes, 1990) which provides the platform for the analyses of the ‘soft’ aspects (e.g. human, political, cultural and organisational factors) and the Hard Systems Methodology (HSM) which provides methods and tools for quantitative measures and analyses of the system. A further three interrelated bases are: Reflective Practice, Organisational Learning (OL), and Information and Knowledge Management (IKM). Some of the key underlying principles to a successful evaluation framework are good data collection and analyses methods, an evaluative reflective practice approach whichentails the complete process of identification and analysis of strengths and problems, followed by rigorous testing, implementation, and revision of solutions. Such a cycle encourages organisational learning and promotes continuous improvement to both the evaluation framework and system. Additionally, it aims to cultivate an organisational culture that supports evaluation through reflection, continuous learning, and knowledge management which facilitates knowledge creation, capture, sharing, application and dissemination

Conversation with Robert Brandom

In this broad interview Robert Brandom talks about many themes concerning his work and about his career and education. Brandom reconstructs the main debts that he owes to colleagues and teachers, especially Wilfrid Sellars, Richard Rorty, and David Lewis, and talks about the projects he’s currently working on. He also talks about contemporary and classical pragmatism, and of the importance of classical thinkers like Kant and Hegel for contemporary debates. Other themes go deeper into the principal topics of his theoretical work – in particular, his later understanding of expressivism, his take on the debate between representationalists and anti-representationalists in semantics, the main open problems for his wide inferentialist project, and his methodological preference for the normative vocabulary in his account of discursive practice. Finally, Brandom touches on the epistemic role of perception and on his views about the importance of the phenomenological aspects of perceptual experience

Take another little piece of my heart: a note on bridging cognition and emotions

Science urges philosophy to be more empirical and philosophy urges science to be more reflective. This markedly occurred along the “discovery of the artificial” (CORDESCHI 2002): in the early days of Cybernetics and Artificial Intelligence (AI) researchers aimed at making machines more cognizant while setting up a framework to better understand human intelligence. By and large, those genuine goals still hold today, whereas AI has become more concerned with specific aspects of intelligence, such as (machine) learning, reasoning, vision, and action. As a matter of fact, the field suffers from a chasm between two formerly integrated aspects. One is the engineering endeavour involving the development of tools, e.g., autonomous systems for driving cars as well as software for semantic information retrieval. The other is the philosophical debate that tries to answer questions concerning the nature of intelligence. Bridging these two levels can indeed be crucial in developing a deeper understanding of minds. An opportunity might be offered by the cogent theme of emotions. Traditionally, computer science, psychological and philosophical research have been compelled to investigate mental processes that do not involve mood, emotions and feelings, in spite of Simon’s early caveat (SIMON 1967) that a general theory of cognition must incorporate the influences of emotion. Given recent neurobiological findings and technological advances, the time is ripe to seriously weigh this promising, albeit controversial, opportunity

Philosophical foundations of neuroscience in organizational research : functional and nonfunctional approaches

Neuroscience offers a unique opportunity to elucidate the role of mental phenomena, including consciousness. However the place of such phenomena in explanations of human behavior is controversial. For example, consciousness has been construed in varied and conflicting forms, making it difficult to represent it in meaningful ways without committing researchers to one species of consciousness or another, with vastly different implications for hypothesis development, methods of study, and interpretation of findings. We explore the conceptual foundations of different explications of consciousness and consider alternative ways for studying its role in research. In the end, although no approach is flawless or dominates all others in every way, we are convinced that any viable approach must take into account, if not privilege, the self in the sense of representing the subjective, first-person process of self as observer and knower of one’s own actions and history, and the feelings and meanings attached to these. The most promising frameworks in this regard are likely to be some variant of nonreductive monism, or perhaps a kind of naturalistic dualism that remains yet to be developed coherently