"The Emperor's New Mind" by Roger Penrose has received a great deal of both praise and criticism. This review discusses philosophical aspects of the book that form an attack on the "strong" AI thesis. Eight different versions of this thesis are distinguished, and sources of ambiguity diagnosed, including different requirements for relationships between program and behaviour. Excessively strong versions attacked by Penrose (and Searle) are not worth defending or attacking, whereas weaker versions remain problematic. Penrose (like Searle) regards the notion (...) of an algorithm as central to AI, whereas it is argued here that for the purpose of explaining mental capabilities the architecture of an intelligent system is more important than the concept of an algorithm, using the premise that what makes something intelligent is not what it does but how it does it. What needs to be explained is also unclear: Penrose thinks we all know what consciousness is and claims that the ability to judge Go "del's formula to be true depends on it. He also suggests that quantum phenomena underly consciousness. This is rebutted by arguing that our existing concept of "consciousness" is too vague and muddled to be of use in science. This and related concepts will gradually be replaced by a more powerful theory-based taxonomy of types of mental states and processes. The central argument offered by Penrose against the strong AI thesis depends on a tempting but unjustified interpretation of Goedel's incompleteness theorem. Some critics are shown to have missed the point of his argument. A stronger criticism is mounted, and the relevance of mathematical Platonism analysed. Architectural requirements for intelligence are discussed and differences between serial and parallel implementations analysed. (shrink)

My work in the philosophy of mind developed out of my early work in the philosophy of language, especially the theory of speech acts, Most of my work in the philosophy of mind has been concerned with the topics of intent ion ality and its structure, particularly the intentionality of perception and action and the relation of the intentionality of the mind to the intentionality of language. I have also written extensively on cognitive science (see cognitive psychology), especially on the (...) limitations Of the COMPUTATIONAL MODEL of the mind. Other work has concerned the mind‐body problem, the nature and structure of consciousness, the relation of consciousness to unconsciousness, the proper form of explanation in the social sciences and in the explanation of human behaviour generally, and the background of intentionality. I can only discuss a small number of these topics in this article, so I will confine myself to four of the most controversial areas. (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

Extract from Hofstadter's revew in Bulletin of American Mathematical Society : http://www.ams.org/journals/bull/1980-02-02/S0273-0979-1980-14752-7/S0273-0979-1980-14752-7.pdf -/- "Aaron Sloman is a man who is convinced that most philosophers and many other students of mind are in dire need of being convinced that there has been a revolution in that field happening right under their noses, and that they had better quickly inform themselves. The revolution is called "Artificial Intelligence" (Al)-and Sloman attempts to impart to others the "enlighten- ment" which he clearly regrets not having (...) experienced earlier himself. Being somewhat of a convert, Sloman is a zealous campaigner for his point of view. Now a Reader in Cognitive Science at Sussex, he began his academic career in more orthodox philosophy and, by exposure to linguistics and AI, came to feel that all approaches to mind which ignore AI are missing the boat. I agree with him, and I am glad that he has written this provocative book. The tone of Sloman's book can be gotten across by this quotation (p. 5): "I am prepared to go so far as to say that within a few years, if there remain any philosophers who are not familiar with some of the main developments in artificial intelligence, it will be fair to accuse them of professional incom- petence, and that to teach courses in philosophy of mind, epistemology, aesthetics, philosophy of science, philosophy of language, ethics, metaphysics, and other main areas of philosophy, without discussing the relevant aspects of artificial intelligence will be as irresponsible as giving a degree course in physics which includes no quantum theory." -/- (The author now regrets the extreme polemical tone of the book.). (shrink)

One of the most important and influential philosophers of the last 30 years, John Searle has been concerned throughout his career with a single overarching question: how can we have a unified and theoretically satisfactory account of ourselves and of our relations to other people and to the natural world? In other words, how can we reconcile our common-sense conception of ourselves as conscious, free, mindful, rational agents in a world that we believe comprises brute, unconscious, mindless, meaningless, mute physical (...) particles in fields of force? The essays in this collection are all related to the broad overarching issue that unites the diverse strands of Searle's work. Gathering in an accessible manner essays available only in relatively obscure books and journals, this collection will be of particular value to professionals and upper-level students in philosophy as well as to Searle's more extended audience in such fields as psychology and linguistics. (shrink)

It has long been one of the most fundamental problems of philosophy, and it is now, John Searle writes, "the most important problem in the biological sciences": What is consciousness? Is my inner awareness of myself something separate from my body? In what began as a series of essays in The New York Review of Books, John Searle evaluates the positions on consciousness of such well-known scientists and philosophers as Francis Crick, Gerald Edelman, Roger Penrose, Daniel Dennett, David Chalmers, and (...) Israel Rosenfield. He challenges claims that the mind works like a computer, and that brain functions can be reproduced by computer programs. With a sharp eye for confusion and contradiction, he points out which avenues of current research are most likely to come up with a biological examination of how conscious states are caused by the brain. Only when we understand how the brain works will we solve the mystery of consciousness, and only then will we begin to understand issues ranging from artificial intelligence to our very nature as human beings. (shrink)

This book provides a sustained and penetrating critique of a wide range of views in modern cognitive science and philosophy of the mind, from Turing's famous test for intelligence in machines to recent work in computational linguistic theory. While discussing many of the key arguments and topics, the authors also develop a distinctive analytic approach. Drawing on the methods of conceptual analysis first elaborated by Wittgenstein and Ryle, the authors seek to show that these methods still have a great deal (...) to offer in the field of the cognitive theory and the philosophy of mind, providing a powerful alternative to many of the positions put forward in the contemporary literature. Amoung the many issues discussed in the book are the following: the Cartesian roots of modern conceptions of mind; Searle's 'Chinese Room' thought experiment; Fodor's 'language of thought' hypothesis; the place of 'folk psychology' in cognitivist thought; and the question of whether any machine may be said to 'think' or 'understand' in the ordinary senses of these words. Wide ranging, up-to-date and forcefully argued, this book represents a major intervention in contemporary debates about the status of cognitive science an the nature of mind. It will be of particular interest to students and scholars in philosophy, psychology, linguistics and computing sciences. (shrink)

Advancing our understanding of one of the most influential 20th-century philosophers, Robert Vinten brings together an international line up of scholars to consider the relevance of Ludwig Wittgenstein's ideas to the cognitive science of religion. Wittgenstein's claims ranged from the rejection of the idea that psychology is a 'young science' in comparison to physics to challenges to scientistic and intellectualist accounts of religion in the work of past anthropologists. Chapters explore whether these remarks about psychology and religion undermine the frameworks (...) and practices of cognitive scientists of religion. Employing philosophical tools as well as drawing on case studies, contributions not only illuminate psychological experiments, anthropological observations and neurophysical research relevant to understanding religious phenomena, they allow cognitive scientists to either heed or clarify their position in relation to Wittgenstein's objections. By developing and responding to his criticisms, Wittgenstein and the Cognitive Science of Religion offers novel perspectives on his philosophy in relation to religion, human nature, and the mind. Contents: Introduction (Robert Vinten); Ch.1: 'Wittgenstein, Concepts, and Human Nature' (Roger Trigg); Ch.2: 'On Truth, Language, and Objectivity' (Florian Franken Figueiredo); Ch.3 'Pascal Boyer's Miscellany of Homunculi: A Wittgensteinian Critique of Religion Explained' (Robert Vinten); Ch.4 'The Brain Perceives/Infers' (Hans van Eyghen); Ch.5 'The Imaginary Inner Inside Cognitive Science of Religion' (Christopher Hoyt); Ch.6 'Cognitive Theories and Wittgenstein: Looking for Convergence not for Divergence' (Olympia Panagiotidou); Ch. 7 'Wittgenstein, Naturalism, and Interpreting Religious Phenomena' (Thomas Carroll); Ch.8 'Natural Thoughts and Unnatural Oughts: Lessing, Wittgenstein, and Contemporary CSR' (Guy Axtell); Ch.9 'Normative Cognition in Cognitive Science of Religion' (Mark Addis); Ch.10 'Brains as the Source of Being: Mind/Brain Focus and the Western Model of Mind in Dominant Cognitive Science Discourse' (Rita McNamara); Ch.11 'On Religious Practices as Multiscale Active Inference: Certainties Emerging From Recurrent Interactions Within and Across Individuals and Groups' (Inês Hipólito and Casper Hesp). (shrink)

For me, personally, Wittgenstein’s philosophy poses the greatest challenge: if he is right, the sort of philosophy I am attempting to do is impossible. Wittgenstein argued powerfully that there can be no such thing as a general philosophical theory of language, mind, consciousness, society, and so on. I wanted and still do want to do precisely that: to present a general philosophical theory of language, mind, consciousness, society, and so on.

John Searle first made his name with his work in the philosophy of language on speech acts, but cemented his place at the centre of contemporary philosophy with his arguments against computational theories of mind. A rare academic, who writes original work for both general and specialist readers, he has more recently focused on the construction of social reality. He is the Slusser Professor of Philosophy at the University of California, Berkeley.

John Searle first made his name with his work in the philosophy of language on speech acts, but cemented his place at the centre of contemporary philosophy with his arguments against computational theories of mind. A rare academic, who writes original work for both general and specialist readers, he has more recently focused on the construction of social reality. He is the Slusser Professor of Philosophy at the University of California, Berkeley.

Depending on what one means by the main connective of logic, the -if..., then... -, several systems of logic result: classic and modal logics, intuitionistic logic or relevance logic. This book presents the underlying ideas, the syntax and the semantics of these logics. Soundness and completeness are shown constructively and in a uniform way. Attention is paid to the interdisciplinary role of logic: its embedding in the foundations of mathematics and its intimate connection with philosophy, in particular the philosophy of (...) language. Set theory is presented both as a conditio sine qua non for logic and as a interesting exact ontology. The study of infinite sets yields perplexing results. Formalization of informal number theory results in formal number theory; Godel's incompleteness is treated. At appropriate places attention is paid to paradoxes, intuitionism, conditionals, the historical development of logic, to logic programming and automated theorem proving for classical logic.". (shrink)

Jerry Fodor is one of the most important philosophers of mind in recent decades. He has done much to set the agenda in this field and has had a significant influence on the development of cognitive science. Fodor's project is that of constructing a physicalist vindication of folk psychology and so paving the way for the development of a scientifically respectable intentional psychology. The centrepiece of his engagement in this project is a theory of the cognitive mind, namely, the computational (...) theory of mind, which postulates the existence of a language of thought. Fodor: Language, Mind and Philosophy is a comprehensive study of Fodor's writings. Individual chapters are devoted to each of the major issues raised by his work and contain extensive discussion of his relationships to key developments in cognitive science and to the views of such philosophical luminaries as Dennett, Davidson and Searle. (shrink)

In his bestselling work of popular science, Sir Roger Penrose takes us on a fascinating roller-coaster ride through the basic principles of physics, cosmology, mathematics, and philosophy to show that human thinking can never be emulated by a machine.

The so-called integration problem concerning mechanistic and computational explanation asks how they are related to each other. One approach is that a computational explanation is a species of mechanistic explanation. According to this view, computational or mathematical descriptions are mechanism sketches or macroscopic descriptions that include computationally relevant and exclude computationally irrelevant physical properties. Some suggest that this results in a so-called single hierarchy view of physical computation, where computational or mathematical properties sit together in the same mechanistic hierarchy with (...) the implementational properties. This view can be contrasted with a separate hierarchy view, according to which computational and physical descriptions have their own hierarchies which are related to each other via a bridging implementation relation. The single hierarchy view has been criticized for downplaying the explanatory value of computational explanations and not being hospitable to multiple realization of cognitive processes. In this paper, I argue that the aforementioned criticisms fail, and there might be a deeper problem with the single hierarchy view, which is that the single hierarchy view might collapse into a separate hierarchy view. The kind of abstraction used by the single hierarchy view does not seem to grant mathematical or computational descriptions but only more stripped physical or implementational descriptions. (shrink)

The book starts with the assumption that vagueness is a fundamental property of this world. From a philosophical account of vagueness via the presentation of alternative mathematics of vagueness, the subsequent chapters explore how vagueness manifests itself in the various exact sciences: physics, chemistry, biology, medicine, computer science, and engineering.

Many books explain what is known about the universe. This book investigates what cannot be known. Rather than exploring the amazing facts that science, mathematics, and reason have revealed to us, this work studies what science, mathematics, and reason tell us cannot be revealed. In The Outer Limits of Reason, Noson Yanofsky considers what cannot be predicted, described, or known, and what will never be understood. He discusses the limitations of computers, physics, logic, and our own thought processes. Yanofsky describes (...) simple tasks that would take computers trillions of centuries to complete and other problems that computers can never solve; perfectly formed English sentences that make no sense; different levels of infinity; the bizarre world of the quantum; the relevance of relativity theory; the causes of chaos theory; math problems that cannot be solved by normal means; and statements that are true but cannot be proven. He explains the limitations of our intuitions about the world -- our ideas about space, time, and motion, and the complex relationship between the knower and the known. Moving from the concrete to the abstract, from problems of everyday language to straightforward philosophical questions to the formalities of physics and mathematics, Yanofsky demonstrates a myriad of unsolvable problems and paradoxes. Exploring the various limitations of our knowledge, he shows that many of these limitations have a similar pattern and that by investigating these patterns, we can better understand the structure and limitations of reason itself. Yanofsky even attempts to look beyond the borders of reason to see what, if anything, is out there. (shrink)

This book covers completeness of first-order logic, some model theory, Gödel's incompleteness theorems and related results, and a smattering of computability theory. The text is self-contained and provides full proofs of the main facts. Ideally, the reader of this work has already taken at least one introductory logic course; however, everything needed to understand the syntax and semantics of first-order logic is presented herein. Students from philosophy, linguistics, computer science, physics, and other related subjects will find this work useful and (...) enlightening. (shrink)

Andrew Boucher (1997) argues that ``parallel computation is fundamentally different from sequential computation'' (p. 543), and that this fact provides reason to be skeptical about whether AI can produce a genuinely intelligent machine. But parallelism, as I prove herein, is irrelevant. What Boucher has inadvertently glimpsed is one small part of a mathematical tapestry portraying the simple but undeniable fact that physical computation can be fundamentally different from ordinary, ``textbook'' computation (whether parallel or sequential). This tapestry does indeed immediately imply (...) that human cognition may be uncomputable. (shrink)

The Computational Theory of Mind (CTM) holds that the mind is a computer and that cognition is the manipulation of representations. CTM is commonly viewed as the main hypothesis in cognitive science, with classical CTM (related to the Language of Thought Hypothesis) being the most popular variant. However, other computational accounts of the mind either reject LOTH or do not subscribe to RTM. CTM proponents argue that it clarifies how thought and content are causally relevant in the physical world, and (...) they frame this argument in terms of the physical symbol hypothesis, formalism, or syntactic engines. This article focuses on specific problems with CTM, with four main sections covering the introduction of the three main variants of CTM, the most important conceptions of computational explanation in cognitive science, skeptical arguments against CTM raised by Hilary Putnam, and common objections to CTM. (shrink)

Computation is central to the foundations of modern cognitive science, but its role is controversial. Questions about computation abound: What is it for a physical system to implement a computation? Is computation sufficient for thought? What is the role of computation in a theory of cognition? What is the relation between different sorts of computational theory, such as connectionism and symbolic computation? In this paper I develop a systematic framework that addresses all of these questions. Justifying the role of computation (...) requires analysis of implementation, the nexus between abstract computations and concrete physical systems. I give such an analysis, based on the idea that a system implements a computation if the causal structure of the system mirrors the formal structure of the computation. This account can be used to justify the central commitments of artificial intelligence and computational cognitive science: the thesis of computational sufficiency, which holds that the right kind of computational structure suffices for the possession of a mind, and the thesis of computational explanation, which holds that computation provides a general framework for the explanation of cognitive processes. The theses are consequences of the facts that (a) computation can specify general patterns of causal organization, and (b) mentality is an organizational invariant, rooted in such patterns. Along the way I answer various challenges to the computationalist position, such as those put forward by Searle. I close by advocating a kind of minimal computationalism, compatible with a very wide variety of empirical approaches to the mind. This allows computation to serve as a true foundation for cognitive science. (shrink)

An examination of the ways human movement can be represented as a formal language and how this language can be mediated technologically. In Motion and Representation, Nicolás Salazar Sutil considers the representation of human motion through languages of movement and technological mediation. He argues that technology transforms the representation of movement and that representation in turn transforms the way we move and what we understand to be movement. Humans communicate through movement, physically and mentally. To record and capture integrated movement (...) (both bodily and mental), by means of formal language and technological media, produces a material record and cultural expression of our evolving kinetic minds and identities. Salazar Sutil considers three forms of movement inscription: a written record (notation), a visual record (animation), and a computational record (motion capture). He focuses on what he calls kinetic formalism—formalized movement in such pursuits as dance, sports, live animation, and kinetic art, as well as abstract definitions of movement in mathematics and computer science. He explores the representation of kinetic space and spatiotemporality; the representation of mental plans of movement; movement notation, including stave notation (Labanotation) and such contemporary forms of notation as Choreographic Language Agent; and the impact of digital technology on contemporary representations of movement—in particular motion capture technology and Internet transfer protocols. Motion and Representation offers a unique cultural theory of movement and of the ever-changing ways of representing movement. (shrink)

Realism about computation is the view that whether or not a particular physical system is performing a particular computation is at least sometimes a mindindependent feature of reality. The caveat ’at least sometimes’ is necessary here because a realist about computation need not believe that all instances of computation should be realistically construed. The computational theory of mind presupposes realism about computation. If whether or not the human nervous system implements particular computations is not a natural fact about the world (...) that is independent of whether we represent it as doing so, then the computational theory of mind fails to naturalise the mind. Realism about computation is also presupposed by attempts to use computational principles such as Landauer’s Principle to dispel Maxwell’s Demon. Realism about computation has been challenged by Hilary Putnam and John Searle among others. Various arguments have been put forward purporting to show that any physical system of sufficient complexity trivially implements all computations. Ladyman et al. offer a precisification and general proof Landauer’s Principle. In order to do this they present an analysis of what it is for a physical process to implement a logical transformation. In this paper, their analysis is explained and its implications for realism about computation and the use of Landauer’s Principle in foundational debates is assessed. (shrink)

What is a language? What do scientific grammars tell us about the structure of individual languages and human language in general? What kind of science is linguistics? These and other questions are the subject of Ryan M. Nefdt's Language, Science, and Structure. -/- Linguistics presents a unique and challenging subject matter for the philosophy of science. As a special science, its formalisation and naturalisation inspired what many consider to be a scientific revolution in the study of mind and language. Yet (...) radical internal theory change, multiple competing frameworks, and issues of modelling and realism have largely gone unaddressed in the field. Nefdt develops a structural realist perspective on the philosophy of linguistics which aims to confront the aforementioned topics in new ways while expanding the outlook toward new scientific connections and novel philosophical insights. On this view, languages are real patterns which emerge from complex biological systems. Nefdt's exploration of this novel view will be especially valuable to those working in formal and computational linguistics, cognitive science, and the philosophies of science, mathematics, and language. (shrink)

This book addresses a single overriding question in contemporary philosophy: Given that we know from physics, chemistry, and the other hard sciences that the universe consists entirely of mindless, meaningless physical particles in fields of force, and that these are organized into systems, how do we account for the human reality - the reality of mind, meaning, consciousness, intentionality, society, science, aesthetics, morality, and all of social organization including money, property, government, and marriage? The book features a discussion of the (...) problem of the freedom of the will as well as an account of the problems of political philosophy, particularly the notions of power and human rights. Originally written as lectures, the book includes in an appendix questions on the lectures and John Searle's replies. (shrink)

In everyday life, as well as in science, we have to deal with and act on the basis of partial (i.e. incomplete, uncertain, or even inconsistent) information. This observation is the source of a broad research activity from which a number of competing approaches have arisen. There is some disagreement concerning the way in which partial or full ignorance is and should be handled. The most successful approaches include both quantitative aspects (by means of probability theory) and qualitative aspect (by (...) means of graphical or causal models or logic). Some of these approaches have important impacts on various disciplines including philosophy, computer science, statistics, mathematics, physics, and social science. Most notably, the relation between causal and probabilistic information is a topic of interest in all of these fields. The general question of how uncertainty is related to ignorance, and the connection thereof to causality, have been the key topics of the international summer school at the University of Konstanz, Germany, in August 2004. This was the third event in a series of summer schools organized by the interdisciplinary research group “Philosophy, Probability, and Modeling”. The group was in operation from September 1st, 2001, until August 31, 2005. The first summer school, held in September 2002, focused on the application of probability theory to topics of philosophical interest. Problems and questions that arise when probabilistic models and techniques are being applied in the special sciences were then discussed during the second summer school, held in July 2003. The fourth and final event in the series, in August 2005, was devoted to philosophical questions related to the application and interpretation of probabilities in physics. Each of the four summer schools attracted 40–50 people from many different countries. It was an inspiring forum for an interdisciplinary discussion among researchers and students from many different areas. This special issue collects a selection of the invited and contributed papers presented at the summer school in 2004. We acknowledge the generous support of the Center for Junior Research Fellows at the University of Konstanz, the Gesellschaft für analytische Philosophie e.V., the Centre for Philosophy of Natural and Social Science at the London School of Economics, the Alexander von Humboldt Foundation, the Federal Ministry of Education and Research and the Program for the Investment in the Future (ZIP) of the German Government through a Sofja Kovalevskaja Award. We thank the referees of the papers for their work, and James Moor for his interest in dedicating a special issue of this journal to Causality, Uncertainty and Ignorance. (shrink)

__Language Proof and Logic_ is available as a physical book with the software included on CD and as a downloadable package of software plus the book in PDF format. The all-electronic version is available from Openproof at ggweb.stanford.edu._ The textbook/software package covers first-order language in a method appropriate for first and second courses in logic. An on-line grading services instantly grades solutions to hundred of computer exercises. It is designed to be used by philosophy instructors teaching a logic course to (...) undergraduates in philosophy, computer science, mathematics, and linguistics. Introductory material is presented in a systematic and accessible fashion. Advanced chapters include proofs of soundness and completeness for propositional and predicate logic, as well as an accessible sketch of Godel's first incompleteness theorem. The book is appropriate for a wide range of courses, from first logic courses for undergraduates to a first graduate logic course. The software package includes four programs: Tarski's World 5.0, a new version of the popular program that teaches the basic first-order language and its semantics; Fitch, a natural deduction proof environment for giving and checking first-order proofs; Boole, a program that facilitates the construction and checking of truth tables and related notions ; Submit, a program that allows students to submit exercises done with the above programs to the Grade Grinder, the automatic grading service. Grade reports are returned to the student and, if requested, to the student's instructor, eliminating the need for tedious checking of homework. All programs are available for Windows, Macintosh and Linux systems. Instructors do not need to use the programs themselves in order to be able to take advantage of their pedagogical value. More about the software can be found at lpl.stanford.edu. The price of a new text/software package includes one Registration ID, which must be used each time work is submitted to the grading service. Once activated, the Registration ID is not transferable. (shrink)

This work represents Dr. Jaki's rebuttal of contemporary claims about the existence of, or possibility for, man-made minds. His method includes a meticulously documtned survey of computer development, a review of the relevant results of brain research, and an evaluation of the accomplishments of physicalist schools in psychology, symbolic logic, and linguistics.

We characterize abstraction in computer science by first comparing the fundamental nature of computer science with that of its cousin mathematics. We consider their primary products, use of formalism, and abstraction objectives, and find that the two disciplines are sharply distinguished. Mathematics, being primarily concerned with developing inference structures, has information neglect as its abstraction objective. Computer science, being primarily concerned with developing interaction patterns, has information hiding as its abstraction objective. We show that abstraction through information hiding is a (...) primary factor in computer science progress and success through an examination of the ubiquitous role of information hiding in programming languages, operating systems, network architecture, and design patterns. (shrink)

In contrast to many areas of contemporary philosophy, something like a carnival atmosphere surrounds Searle’s Chinese room argument. Not many recent philosophical arguments have exerted such a pull on the popular imagination, or have produced such strong reactions. People from a wide range of fields have expressed their views on the argument. The argument has appeared in Scientific American, television shows, newspapers, and popular science books. Preston and Bishop’s recent volume of essays reflects this interdisciplinary atmosphere. The volume includes essays (...) from computer science, neuroscience, artificial intelligence, cognitive science, sociology, science studies, physics, mathematics, and philosophy. There are two sides to this interdisciplinary mix. On the one hand, it makes for interesting and fun reading for anyone interested in the Chinese room argument, but on the other, it raises the threat that the Chinese room argument might be left in some kind of interdisciplinary no man’s land. The Chinese room argument (CRA) is an argument against the possibility of Strong artificial intelligence (Strong AI). The thesis of Strong AI is that running a program is sufficient for, or constitutive of, understanding: it is merely in virtue of running a 1 particular program that a system understands. Searle appreciates that understanding is a complex notion, and so he has a particular form of understanding in mind: the understanding of simple stories. It seems intuitively obvious that when I read a simple story in English, I understand that story. One could say that somewhere in my head there is understanding going on. However, if I read a simple story written in Chinese (a language I do not speak), then there is no understanding going on. What makes the difference between these two cases? The advocate of Strong AI says that the difference.. (shrink)

With the rise of the internet and the proliferation of technology to gather and organize data, our era has been defined as "the information age." With the prominence of information as a research concept, there has arisen an increasing appreciation of the intertwined nature of fields such as logic, linguistics, and computer science that answer the questions about information and the ways it can be processed. The many research traditions do not agree about the exact nature of information. By bringing (...) together ideas from diverse perspectives, this book presents the emerging consensus about what a conclusive theory of information should be. The book provides an introduction to the topic, work on the underlying ideas, and technical research that pins down the richer notions of information from a mathematical point of view. The book contains contributions to a general theory of information, while also tackling specific problems from artificial intelligence, formal semantics, cognitive psychology, and the philosophy of mind. There is focus on the dynamics of information flow, and also a consideration of static approaches to information content; both quantitative and qualitative approaches are represented. (shrink)

The Computational Theory of Mind (CTM) holds that cognitive processes are essentially computational, and hence computation provides the scientific key to explaining mentality. The Representational Theory of Mind (RTM) holds that representational content is the key feature in distinguishing mental from non-mental systems. I argue that there is a deep incompatibility between these two theoretical frameworks, and that the acceptance of CTM provides strong grounds for rejecting RTM. The focal point of the incompatibility is the fact that representational content is (...) extrinsic to formal procedures as such, and the intended interpretation of syntax makes no difference to the execution of an algorithm. So the unique 'content' postulated by RTM is superfluous to the formal procedures of CTM. And once these procedures are implemented in a physical mechanism, it is exclusively the causal properties of the physical mechanism that are responsible for all aspects of the system's behaviour. So once again, postulated content is rendered superfluous. To the extent that semantic content may appear to play a role in behaviour, it must be syntactically encoded within the system, and just as in a standard computational artefact, so too with the human mind/brain - it's pure syntax all the way down to the level of physical implementation. Hence 'content' is at most a convenient meta-level gloss, projected from the outside by human theorists, which itself can play no role in cognitive processing. (shrink)

Four modes of language acquisition and communication are presented translating ancient Indian expressions on human consciousness, mind, their form, structure and function clubbing with the Sabdabrahma theory of language acquisition and communication. The modern scientific understanding of such an insight is discussed. . A flowchart of language processing in humans will be given. A gross model of human language acquisition, comprehension and communication process forming the basis to develop software for relevantmind-machine modeling will be presented. The implications of such a (...) model to artificial intelligence and cognitive sciences will be discussed. The essential nature and necessity of a physics, communication engineering , biophysical and biochemical insight as both complementary and supplementary to using mathematical and computational methods in delineating the theory of language processing in humans is put forward. (shrink)

A set theory model of reality, representation and language based on the relation of completeness and incompleteness is explored. The problem of completeness of mathematics is linked to its counterpart in quantum mechanics. That model includes two Peano arithmetics or Turing machines independent of each other. The complex Hilbert space underlying quantum mechanics as the base of its mathematical formalism is interpreted as a generalization of Peano arithmetic: It is a doubled infinite set of doubled Peano arithmetics having a remarkable (...) symmetry to the axiom of choice. The quantity of information is interpreted as the number of elementary choices (bits). Quantum information is seen as the generalization of information to infinite sets or series. The equivalence of that model to a quantum computer is demonstrated. The condition for the Turing machines to be independent of each other is reduced to the state of Nash equilibrium between them. Two relative models of language as game in the sense of game theory and as ontology of metaphors (all mappings, which are not one-to-one, i.e. not representations of reality in a formal sense) are deduced. (shrink)

The idea that human thought requires the execution of mental algorithms provides a foundation for research programs in cognitive science, which are largely based upon the computational conception of language and mentality. Consideration is given to recent work by Penrose, Searle, and Cleland, who supply various grounds for disputing computationalism. These grounds in turn qualify as reasons for preferring a non-computational, semiotic approach, which can account for them as predictable manifestations of a more adquate conception. Thinking does not ordinarily require (...) the execution of mental algorithms, which appears to be at best no more than one rather special kind of thinking. (shrink)

The idea that human thought requires the execution of mental algorithms provides a foundation for research programs in cognitive science, which are largely based upon the computational conception of language and mentality. Consideration is given to recent work by Penrose, Searle, and Cleland, who supply various grounds for disputing computationalism. These grounds in turn qualify as reasons for preferring a non-computational, semiotic approach, which can account for them as predictable manifestations of a more adquate conception. Thinking does not ordinarily require (...) the execution of mental algorithms, which appears to be at best no more than one rather special kind of thinking. (shrink)

Computation is central to the foundations of modern cognitive science, but its role is controversial. Questions about computation abound: What is it for a physical system to implement a computation? Is computation sufficient for thought? What is the role of computation in a theory of cognition? What is the relation between different sorts of computational theory, such as connectionism and symbolic computation? In this paper I develop a systematic framework that addresses all of these questions. Justifying the role of computation (...) requires analysis of implementation, the nexus between abstract computations and concrete physical systems. I give such an analysis, based on the idea that a system implements a computation if the causal structure of the system mirrors the formal structure of the computation. This account can be used to justify the central commitments of artificial intelligence and computational cognitive science: the thesis of computational sufficiency, which holds that the right kind of computational structure suffices for the possession of a mind, and the thesis of computational explanation, which holds that computation provides a general framework for the explanation of cognitive processes. The theses are consequences of the facts that computation can specify general patterns of causal organization, and mentality is an organizational invariant, rooted in such patterns. Along the way I answer various challenges to the computationalist position, such as those put forward by Searle. I close by advocating a kind of minimal computationalism, compatible with a very wide variety of empirical approaches to the mind. This allows computation to serve as a true foundation for cognitive science. (shrink)

This volume is a collection of papers on philosophy of mathematics which deal with a series of questions quite different from those which occupied the minds of the proponents of the three classic schools: logicism, formalism, and intuitionism. The questions of the volume are not to do with justification in the traditional sense, but with a variety of other topics. Some are concerned with discovery and the growth of mathematics. How does the semantics of mathematics change as the subject develops? (...) What heuristics are involved in mathematical discovery, and do such heuristics constitute a logic of mathematical discovery? What new problems have been introduced by the development of mathematics since the 1930s? Other questions are concerned with the applications of mathematics both to physics and to the new field of computer science. Then there is the new question of whether the axiomatic method is really so essential to mathematics as is often supposed, and the question, which goes back to Wittgenstein, of the sense in which mathematical proofs are compelling. Taking these questions together they give part of an emerging agenda which is likely to carry philosophy of mathematics forward into the twenty first century. (shrink)

The question ‘What is computation?’ might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely a matter of (...) an observer choosing to view it as such. According to one view, which we dub bold anti-realist pancomputationalism, every physical object computes every computer program. According to another, more modest view, some computational systems can be ascribed multiple computational descriptions. We argue that the first view is misguided, and that the second view need not entail observer-relativity of computation. At least to a large extent, computation is an objective phenomenon. Construed as a form of information processing, we argue that information-processing considerations determine what type of computation takes place in physical systems. (shrink)

There are different ways to present a Presidential Address to the APA; the one I have chosen is simply to report on work that I am doing right now, on work in progress. I am going to present some of my further explorations into the computational model of the mind.\**.

In Mind: An Introduction, for the first time John Searle offers a general introduction to the philosophy of the mind. Giving a broad survey of all the major issues under discussion in the field, including philosophical issues in cognitive science and neurobiology, Searle argues for his own distinctive point of view. He leads the reader through the variety of theories that reduce the mind to aspects that can be fully explained by physics, and then concludes with his own view that (...) such reductionist theories ignore or cannot adequately explain the most fundamental aspect of the mind - subjective consciousness. (shrink)

Meaning, believing, thinking, understanding, reasoning, calculating, learning, remembering, intending, expecting, loving, longing: these experiences are, according to Wittgenstein, embodied actions. In Certainty in Action, Danièle Moyal-Sharrock argues that there is hardly anything traditionally thought to be a mental process or state, that, in fact, Ludwig Wittgenstein has not shown to be primarily embodied or enacted. The book traces the radical, diverse and recurrent importance of action and 'ways of acting' as the original and cohesive thread weaving through all of (...) Wittgenstein's philosophy, especially language and memory. Moyal-Sharrock highlights throughout Wittgenstein's clarification of 'the inner' and his belief in the certainty of action. With Wittgenstein's philosophy increasingly influencing multiple branches of psychology, particularly those concerned with child development, language acquisition and memory, Certainty in Action is essential reading for students and researchers interested in the philosophy underpinning these areas, as well as Wittgenstein specialists. (shrink)

The renowned philosopher John Searle reveals the fundamental nature of social reality. What kinds of things are money, property, governments, nations, marriages, cocktail parties, and football games? Searle explains the key role played by language in the creation, constitution, and maintenance of social reality. We make statements about social facts that are completely objective, for example: Barack Obama is President of the United States, the piece of paper in my hand is a twenty-dollar bill, I got married in London, etc. (...) And yet these facts only exist because we think they exist. How is it possible that we can have factual objective knowledge of a reality that is created by subjective opinions? This is part of a much larger question: How can we give an account of ourselves, with our peculiar human traits DS mind, reason, freedom, society - in a world that we know independently consists of mindless, meaningless particles? How can we account for our social and mental existence in a realm of brute physical facts? In answering this question, Searle avoids postulating different realms of being, a mental and a physical, or worse yet, a mental, a physical, and a social. There is just one reality: Searle shows how the human reality fits into that one reality. Mind, language, and civilization are natural products of the basic facts of the physical world described by physics, chemistry and biology. Searle explains how language creates and maintains the elaborate structures of human social institutions. These institutions serve to create and distribute power relations that are pervasive and often invisible. These power relations motivate human actions in a way that provides the glue that holds human civilization together. Searle shows how this account illuminates human rationality, free will, political power, and human rights. Our social world is a world created and maintained by language. (shrink)

This chapter provides an overview of the basic research strategies and analytic techniques deployed in computational cognitive neuroscience. On the one hand, “top-down” strategies are used to infer, from formal characterizations of behavior and cognition, the computational properties of underlying neural mechanisms. On the other hand, “bottom-up” research strategies are used to identify neural mechanisms and to reconstruct their computational capacities. Both of these strategies rely on experimental techniques familiar from other branches of neuroscience, including functional magnetic resonance imaging, single-cell (...) recording, and electroencephalography. What sets computational cognitive neuroscience apart, however, is the explanatory role of analytic techniques from disciplines as varied as computer science, statistics, machine learning, and mathematical physics. These techniques serve to describe neural mechanisms computationally, but also to drive the process of scientific discovery by influencing which kinds of mechanisms are most likely to be identified. For this reason, understanding the nature and unique appeal of computational cognitive neuroscience requires not just an understanding of the basic research strategies that are involved, but also of the formal methods and tools that are being deployed, including those of probability theory, dynamical systems theory, and graph theory. (shrink)

Sabdabrahma Siddhanta, popularized by Patanjali and Bhartruhari will be scientifically analyzed. Sphota Vada, proposed and nurtured by the Sanskrit grammarians will be interpreted from modern physics and communication engineering points of view. Insight about the theory of language and modes of language acquisition and communication available in the Brahma Kanda of Vakyapadeeyam will be translated into modern computational terms. A flowchart of language processing in humans will be given. A gross model of human language acquisition, comprehension and communication process forming (...) the basis to develop software for relevant mind-machine modeling will be presented. The implications of such a model to artificial intelligence and cognitive sciences will be discussed. The essentiality and necessity of a physics, communication engineering , biophysical and biochemical insight as both complementary and supplementary to using mathematical and computational methods in delineating the theory of Sanskrit language is put forward. Natural language comprehension as distinct and different from natural language processing is pointed out. (shrink)

What is ‘certainty’ in our everyday life and work? AI changing what it means to ‘be certain’. For example, when we engage with others and are doing our work, we make judgments in which we ‘trust our instinct’. Are we still able to do so if we engage with the ‘certainty’ of the machine? How is ‘being certain’ in ‘dialogue’ affected by our conceptions of what it means to be human in interaction with the ‘machine’, and consequent distinctions (...) between body and mind? Descartes first likened the human body to a machine (albeit a machine created by God) and endowed reason as being a transcendent universal instrument. La Mettrie proposed that language and culture separates humans from ‘animals’. However, in Diderot’s writing, ‘knowledge’ is seen as embodied, coming from our senses and language, and where gesture and rhythm evolve in practice. For D’Alembert, human ‘instinct’ is a skill, a learnt practice, and Rousseau believes that human certainty is something that cannot be measured. These questionings of the dichotomies of body and mind and human and animal, that relate practice and knowledge, also question the place and meaning of ‘rules’ of engaged practice. For Wittgenstein, one learns to make judgments through personal experience, ‘rules in practice’, whereby language is necessarily culturally situated and embodied, and calculation and Judgement are part of each other. (shrink)