Studies in Cognitive Systems – serie

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data-processing systems of all kinds, no matter whether human. (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. No problem within the field of cognitive inquiry is more difficult than that of developing an adequate conception of the nature of mind and of its mode of operation. Our purpose in compiling the present volume has been to contribute to the pursuit of this objective by bringing together a repre­ sentative cross-section of the principal approaches and the primary players who are engaged in contemporary debate on these crucial issues. The book begins with a comprehensive introduction composed by David Cole, the senior editor of this work, which provides a background for understanding the major problems and alternative solutions, and ends with a selected bibliography intended to promote further research. If our efforts assist others in dealing with these issues, they will have been worthwhile. J. H. F. David J. Cole et at. (eds. ), Philosophy, Mind, and Cognitive Inquiry, ix.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data­ processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psycholo­ gy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial in­ telligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these prob­ lems and domains, empirical, experimental, and methodological studies will also appear from time to time. The perspective that prevails in artificial intelligence today suggests that the theory of computability defines the boundaries of the nature of thought, precisely because all thinking is computational. This paradigm draws its inspiration from the symbol-system hypothesis of Newell and Simon and finds its culmination in the computational conception of lan­ guage and mentality. The "standard conception" represented by these views is subjected to a thorough and sustained critique in the pages of this book. Employing a distinction between systems for which signs are signif­ icant for the users of a system and others for which signs are significant for use by a system, I have sought to define the boundaries of what AI, in principle, may be expected to achieve.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data­ processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psycholo­ gy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial in­ telligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these prob­ lems and domains, empirical, experimental, and methodological studies will also appear from time to time. The perspective that prevails in artificial intelligence today suggests that the theory of computability defines the boundaries of the nature of thought, precisely because all thinking is computational. This paradigm draws its inspiration from the symbol-system hypothesis of Newell and Simon and finds its culmination in the computational conception of lan­ guage and mentality. The "standard conception" represented by these views is subjected to a thorough and sustained critique in the pages of this book. Employing a distinction between systems for which signs are signif­ icant for the users of a system and others for which signs are significant for use by a system, I have sought to define the boundaries of what AI, in principle, may be expected to achieve.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data-processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interest from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental powers of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimen­ tal, and methodological studies will also appear from time to time. The present volume reflects the kind of insights that can be obtained when research workers in philosophy, artificial intelligence, and computer science explore problems of common concern. The issues here tend to fall into two broad but varied sets, namely: those concerned with content and concepts, on the one hand, and those concerned with semantics and epistemology, on the other. The collection begins with a prologue that focuses upon the relations between connectionism and alternative conceptions of nativism and ends with an epilogue that examines the significance of alternative conceptions of the Frame Problem for artificial intelligence. Because these papers are rich and diverse, they ought to appeal to a wide and heterogeneous audience. J.H.F.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data­ processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychol­ ogy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. The problems posed by metaphor and analogy are among the most challenging that confront the field of knowledge representation. In this study, Eileen Way has drawn upon the combined resources of philosophy, psychology, and computer science in developing a systematic and illuminating theoretical framework for understanding metaphors and analogies. While her work provides solutions to difficult problems of knowledge representation, it goes much further by investigating some of the most important philosophical assumptions that prevail within artificial intelligence today. By exposing the limitations inherent in the assumption that languages are both literal and truth-functional, she has advanced our grasp of the nature of language itself. J.R.F.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data­ processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemological aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. One of the most, if not the most, exciting developments within cognitive science has been the emergence of connectionism as an alternative to the computational conception of the mind that tends to dominate the discipline. In this volume, John Tienson and Terence Horgan have brought together a fine collection of stimulating studies on connectionism and its significance. As the Introduction explains, the most pressing questions concern whether or not connectionism can provide a new conception of the nature of mentality. By focusing on the similarities and differences between connectionism and other approaches to cognitive science, the chapters of this book supply valuable resources that advance our understanding of these difficult issues. J.H.F.

"Soar: A Cognitive Architecture in Perspective" represents a European perspective on Soar with the exception of the special contribution from Allen Newell arguing for Unified Theories of Cognition. The various papers derive from the work of the Soar Research Group that has been active at the University of Groningen, The Netherlands, since 1987. The work reported here has been inspired in particular by two topics that precipitated the group's interest in Soar in the first place: - road user behaviour and the temporal organization of behaviour, more specifically planning. At the same time, the various contributions go beyond the simple use of Soar as a convenient medium for modelling human cognitive activity. In every paper one or more fundamental issues are raised that touch upon the very nature and consistency of Soar as an intelligent architecture. As a result the reader will learn about the operator implementation problem, chunking, multitasking, the need to constrain the depth of the goal stack, and induction etc. Soar is still at a relatively early stage of development.It does, nevertheless, constitute an important breakthrough in the area of computer architectures for general intelligence. Soar shows one important direction that future efforts to build intelligent systems should take if they aim for a comprehensive, and psychologically meaningful, theory of cognition. This is argued by Newell in his contribution to this volume. For this reason, the Soar system will probably play an important integrative role within cognitive science in bringing together important subdomains of psychology, computer science, linguistics, and the neurosciences. Although Soar is not the only "architecture for intelligence", it is one of the most advanced and theoretically best motivated architectures presently available. This work should be of special interest to researchers in the domains of cognitive science, computer science and artificial intelligence, cognitive psychology, and the philosophy of mind.

When agency or intentional causation has occurred, the theory presented here identifies an object ascribable to the agent - his action - which, through its properties, reveals its intentional cause. Such a unified view of agency and action leads to unitary views of intention and the intentional end of all explanatory objects ascribable to agents. While at odds in these matters with the prevailing theories of action, the semantics of this explanatory theory is shown to better satisfy widely accepted criteria for a viable theory of action. The revelatory character of action and its essential reference to agency shows that action theory needs agency theory. To this end, a logic of practical rational agency is developed which is intended to be neutral between competing theories of mind. A sketch of the computer program, PRAGMA, is given which, on the basis of this model of agency and action, analyzes cases of agency in natural discourse. PRAGMA and its manual are available separately.This work should be of interest to theorists concerned with the fundamental practical rational structure of persons, their actions and the discourse appropriate to them: to philosophers and to political, legal, AI and economic theorists.

"What Robots Can and Can't Be" is a self-contained argument for the unique, two-sided position that (side One) AI will continue to produce machines with greater and greater capacity to pass stronger and stronger versions of the Turing Test; but that (side Two) the "Person Building Project" (the attempt by cognitive engineers to build a machine which is a person) will inevitably fail. The defence of side Two rests in large part on a refutation of the proposition that persons are automata - a refutation involving an array of issues, from free will to Godel to introspection to Searle and beyond. The defence of side One brings the reader face to face with Sherlock Holmes and Dr. Watson as they tackle perhaps their toughest case (Silver Blaze); the upshot of this visit with Conan Doyle's duo is an algorithm-sketch for the solving of murder mysteries. Side Two also involves a look at the author's mechanical approach to writing fiction, and the philosophical side of computerized story generation.

Many metaphors go beyond pointing to the existing similarities between two objects - they create the similarities. Such metaphors, which have been relegated to the back seat in most of the cognitive science research, are the focus of attention in this study, which addresses the creation of similarity within an elaborately laid out interactive framework of cognition. Starting from the constructivist views of Nelson Goodman and Jean Piaget, this framework resolves an apparent paradox in interactionism: how can reality not have a mind-independent ontology and structure, but still manage to constrain the possible worlds a cognitive agent can create in it? A comprehensive theory of metaphor is proposed in this framework that explains how metaphors can create similarities, and why such metaphors are an invaluable asset to cognition. The framework is then applied to related issues of analogical reasoning, induction, and computational modelling of creative metaphors.

Among the most important problems confronting computer science is that of developing a paradigm appropriate to the discipline. Proponents of formal methods - such as John McCarthy, C.A.R. Hoare and Edgar Dijkstra - have advanced the position that computing is a mathematical activity and that computer science should model itself after mathematics. Opponents of formal methods - such as Richard DeMillo, Richard Lipton and Alan Perlis - by contrast, suggest that programming is the activity which is fundamental to computer science and that there are important differences that distinguish it from mathematics, which therefore cannot provide a suitable paradigm. Disagreement over the place of formal methods in computer science has recently arisen in the form of renewed interest in the nature and capacity of programme verification as a method for establishing the reliability of software systems. A paper that appeared in Communications of the ACM, entitled "Programme Verification: The Very Idea", by James H.Fetzer, triggered an extended debate that has been discussed in several journals and that has endured for several years, engaging the interest of computer scientists (both theoretical and applied) and of other thinkers from a wide range of backgrounds who want to understand computer science as a domain of inquiry.

The purpose of this book is to illustrate how empirical and conceptual problems interact in modern cognitive science. A multidisciplinary approach encourages us to redraw the boundaries between conceptual and empirical research. The pervading theme is the distinction between ontology and phenomenology. Part I "Cognitive models of consciousness" reviews and evaluates the contemporary discussion concerning consciousness. It is suggested that the first-person, phenomenological point of view should be preserved in theories of consciousness. Part II "Cognitive schemata" deals with methodological issues, especially with cognitive explanations in anthropology. In Part III "Relativism and cognitivism" the classical problem of relativism inherent in the study of doxastic diversity is studied in the novel context provided by cognitivism. Cognitivism appears to provide a solution to the problem of relativism but, by the same token, it invites a more profound version of relativism. This text is suitable for students and scholars in cognitive science, especially those working in cognitive anthropology and neuropsychology. It does not require any previous education in philosophy.The philosophical themes and their relevance in modern empirical research are presented in accessible form. The book can be used as a university textbook for the courses that serve to introduce the students to the philosophical background of cognitive science.

The rise of cognitive science in the 1960s was widely heralded as a scientific revolution - an interpretation that implied the decline and eventual death of behavioral psychology. Although many forms of behavioral psychology did indeed disappear, there was a striking exception: the program of operant psychology founded by B.F. Skinner. This program actually grew at a rapid pace during the 'cognitive revolution' and shows no signs of fading away. What, then, is its place within psychology, and in particular, what is its relationship with cognitive psychology? This book attempts to answer that question. Distinguishing between operant psychology and the philosophy of radical behaviorism, it concludes that even though radical behaviorism may have been a failure, the operant program of research has been a success. Furthermore, operant psychology and cognitive psychology complement one another, each having its own domain within which it contributes something valuable to, but beyond the reach of, the other.

Creativity is one of the least understood aspects of intelligence and is often seen as `intuitive' and not susceptible to rational enquiry. Recently, however, there has been a resurgence of interest in the area, principally in artificial intelligence and cognitive science, but also in psychology, philosophy, computer science, logic, mathematics, sociology, and architecture and design. This volume brings this work together and provides an overview of this rapidly developing field. It addresses a range of issues. Can computers be creative? Can they help us to understand human creativity? How can artificial intelligence (AI) enhance human creativity? How, in particular, can it contribute to the `sciences of the artificial', such as design? Does the new wave of AI (connectionism, geneticism and artificial life) offer more promise in these areas than classical, symbol-handling AI? What would the implications be for AI and cognitive science if computers could not be creative? These issues are explored in five interrelated parts, each of which is introducted and explained by a leading figure in the field. - Prologue (Margaret Boden) - Part I: Foundational Issues (Terry Dartnall) - Part II: Creativity and Cognition (Graeme S. Halford and Robert Levinson) - Part III: Creativity and Connectionism (Chris Thornton) - Part IV: Creativity and Design (John Gero) - Part V: Human Creativity Enhancement (Ernest Edmonds) - Epilogue (Douglas Hofstadter) For researchers in AI, cognitive science, computer science, philosophy, psychology, mathematics, logic, sociology, and architecture and design; and anyone interested in the rapidly growing field of artificial intelligence and creativity.

Human knowing is examined as it emerges from classical empirical psychology, with its ramifications into language, computing, science, and scholarship. While the discussion takes empirical support from a wide range, claims for the significance of logic and rules are challenged throughout. Highlights of the discussion: knowing is a matter of habits or dispositions that guide the person's stream of consciousness; rules of language have no significance in language production and understanding, being descriptions of linguistic styles; statements that may be true or false enter into ordinary linguistic activity, not as elements of messages, but merely as summaries of situations, with a view to action; in computer programming the significance of logic, proof, and formalized description, is incidental and subject to the programmer's personality; analysis of computer modelling of the mental activity shows that in describing human knowing the computer is irrelevant; in accounting for the scholarly/scientific activity, logic and rules are impotent; a novel theory: scholarship and science have coherent descriptions as their core. The discussion addresses questions that are basic to advanced applications of computers and to students of language and science.

On its polemical side, this work argues against the computationalism of Jerry Fodor, against the behavioural holism of Willard Quine, and against the emergentist and externalist pragmatic realism of Hilary Putnam, to the more general conclusion that analytic philosophy of mind and meaning has cut itself off from the classical tradition of, among others, Locke and Descartes, whose positions did not suffer from the problems besetting these analytic trends. On its positive side, the text offers a theory of mind, meaning and knowledge in the classical tradition. An account of a priori synthetic and a priori analytic knowledge is used to set up a formal system in which modal properties of propositions (such as necessity, possibility, and so forth) can be naturally construed, including the modalities of conditionals and the validity of argument. The author raises the question of the biological implementation of the mind, as a symbolic system, and puts forward the conjecture that mental symbols are implemented in the brain at the genetic level, as patterns of gene expression within certain neural cells.Audience: The book will be of interest to philosophers of mind and meaning, cognitive scientists, logicians, biologists of cognition, linguists, and generally to students of mind and rational processes.

This text aims to transform the way we think about consciousness and the physical world. It develops a philosophically satisfying account of the mind/body relationship without doing violence to fundamental physics, expunges popular assumptions about the "in principle" capabilities of cognizers and, with the help of tools from mathematics and scientific fields, supplants flawed notions of representation, function, and mental state with objective and physically grounded alternatives. It debunks quantum theories of consciousness, constructs a simple zombie recipe, and evaluates recent research on chaotic analogue networks. This book is for readers in philosophy of mind, cognitive science, and artificial intelligence, and for mathematicians applying complexity theory or information theory to biological cognition. Audience: General academic/university libraries, plus university departmental libraries in philosophy, artificial intelligence, cognitive science, and computer science. Researchers and specialists in philosophy of mind, cognitive science, artificial intelligence, artificial life, complexity theory, and information theory. Researchers in the telecommunications industry.

What is it about you in virtue of which you are having the thoughts you are now having? The answer will no doubt make some appeal to the state your brain is now in. Most philosophers, however, claim that this is only part of the answer; many of the facts that determine your thoughts lie outside your skin. This view is called externalism, and in this book Keith L. Butler argues that, contrary to widespread philosophical opinion, externalism is implausible. Through critical evaluation of a vast amount of philosophical work on the subject, Butler shows that externalism faces problematic epistemological implications (regarding self-knowledge and knowledge of the external world), and problematic metaphysical implications (regarding mental causation). Moreover, externalism derives no support from an appeal to the cognitive sciences. The controversy generated by this book bears on issues in the philosophy of mind, language, science, and epistemology. It should be of interest to students and professionals concerned with these areas of philosophy.

This work describe the contributions of a behavioural perspective to the major issues of philosophy. Leading behavioural philosophers and psychologists have contributed chapters on: the origins of behaviourism as a philosophy of science; the basic principles of behaviourism; ontology; epistemology; values and ethics; free will, determinism and self-control; and language and verbal behaviour. A concluding chapter provides an overview of some scholarly criticisms of behavioural philosophy. Far from espousing a "black box" perspective on human cognition and philosophical reasoning, behaviourism (as derived from the works of B. F. Skinner) represents a contemporary and viable approach to conceptualizing important philosophical and psychological issues.

This is a comprehensive, systematic study of Sigmund Freud's philosophy of mind. Freud emerges as a sophisticated philosopher who addresses many of the central questions that concern contemporary philosophers and cognitive scientists while anticipating many of their views. While still a student in Vienna, Freud was initiated into philosophy by Franz Brentano. The book charts Freud's intellectual development as he deals with the mind-body problem, the nature of consciousness, folk psychology versus scientific psychology, the relationship between language and thought, realism and antirealism in psychology, and the nature of unconscious mental events. The book also critically examines writings on Freud by Wittgenstein, Davidson, and Searle, demonstrating their weaknesses as interpretations and criticisms of Freud's position.

How can one think about a thing, think something false about it, and still be thinking about that thing at all? If a concept is applied to something outside its meaning, how are we to say it does not mean that thing as well? The problem of misrepresentation is one of the central issues in contemporary philosophy of mind. Here, Mark Perlman criticizes the way all contemporary theories of mental representation seek to account for misrepresentation, concluding that it cannot be explained naturistically. Specifically, Perlman evaluates and criticizes the theories of mental content proposed by Fodor, Dretske, Millikan, Block, Harman and others, as well as examining verificationist approaches to meaning of Quine, Davidson and Stich. The book goes much further than criticism, however: Perlman formulates a naturalistic theory of representation that reluctantly accepts the unfortunate conclusion that there is no misrepresentation. He adds a pragmatic theory of content, which explains apparent misrepresentation as concept change. Mental representations can be good or bad in specific contexts and for specific purposes, but their correctness is not a matter of truth and falsity.The pragmatic approach to mental content has implications for epistemology, theories of truth, metaphysics, psychology, and AI (specifically connectionist networks).

This book offers a multi-disciplinary approach by scientists and philosophers that reveals the stamp of evolution on everyday life: how kinship unravels nurture, how family life affects the personalities we acquire, how our minds develop to negotiate social hierarchies, whether we decide to eat or not, what qualities we prefer in our sexual and marriage patterns, how we name and raise our children, how our thoughts and emotions are framed to make adaptive decisions, and methods for identifying evolved adaptations of the human life-cycle. It serves as an advanced text for students and scholars that critiques the dominating work of Buss, Cosmides and Tooby, Dennett, and Pinker. Taking the field beyond the narrow and contentious innatist--adaptionist view of the mind, it supplies a much sought-after interactional, `biopsycho-sociocultural' paradigm using a variety of evidence to converge on carefully reasoned conclusions.

An important collection of studies providing a fresh and original perspective on the nature of mind, including thoughtful and detailed arguments that explain why the prevailing paradigm - the computational conception of language and mentality - can no longer be sustained. An alternative approach is advanced, inspired by the work of Charles S. Peirce, according to which minds are sign-using (or `semiotic') systems, which in turn generates distinctions between different kinds of minds and overcomes problems that burden more familiar alternatives. Unlike conceptions of minds as machines, this novel approach has obvious evolutionary implications, where differences in semiotic abilities tend to distinguish the species. From this point of view, the scope and limits of computer and AI systems can be more adequately appraised and alternative accounts of consciousness and cognition can be more thoroughly criticised. Readership: Intermediate and advanced students of computer science, AI, cognitive science, and all students of the philosophy of the mind.

The book provides a valuable text for undergraduate and graduate courses on the historical and theoretical issues of Cognitive Science, Artificial Intelligence, Psychology, Neuroscience, and the Philosophy of Mind. The book should also be of interest for researchers in these fields, who will find in it analyses of certain crucial issues in both the earlier and more recent history of their disciplines, as well as interesting overall insights into the current debate on the nature of mind. From the reviews: "...a book that will help those studying social sciences to realize the mechanical roots of the ongoing debate about cognition, but at the same time will help scholars of AI to put their discourse on intelligence in a historical and social perspective."

This is a book-length presentation of a theory of human and machine cognition, according to which human persons are superminds. Superminds are capable of processing information not only at and below the level of Turing machines (standard computers), but above that level (the "Turing Limit"), as information processing devices that have not yet been (and perhaps can never be) built, but have been mathematically specified; these devices are known as super-Turing machines or hypercomputers. Superminds, as explained herein, also have properties no machine, whether above or below the Turing Limit, can have. The final chapter of this book offers eight prescriptions for the concrete practice of AI and cognitive science in light of the fact that we are superminds.

This is a book-length presentation of a theory of human and machine cognition, according to which human persons are superminds. Superminds are capable of processing information not only at and below the level of Turing machines (standard computers), but above that level (the "Turing Limit"), as information processing devices that have not yet been (and perhaps can never be) built, but have been mathematically specified; these devices are known as super-Turing machines or hypercomputers. Superminds, as explained herein, also have properties no machine, whether above or below the Turing Limit, can have. The final chapter of this book offers eight prescriptions for the concrete practice of AI and cognitive science in light of the fact that we are superminds.

In 1950 Alan Turing (1912-1954) published his famous article, "Computing Machinery and Intelligence" in the journal Mind. This article is arguably the most influential and widely read article in the philosophy of artificial intelligence. Indeed, most of the debate in the philosophy of artificial intelligence over the last fifty years concerns issues that were raised and discussed by Turing. Turing's genius was not only in developing the theory of computability but also in understanding the impact, both practical and philosophical, that computing machinery would have. Turing believed that computers, if properly designed and educated, could exhibit intelligent behavior, even behavior that would be indistinguishable from human intelligent behavior. His vision of the possibility of machine intelligence has been highly inspiring and extremely controversial. In this classic article Turing presented his well known imitation game and predicted that about the year 2000 "an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning" in the imitation game. Based on the results of the Loebner 2000 contest and the accomplishments in the field of AI, as impressive as they are, Turing's prediction remains unfulfilled.

In 1950 Alan Turing (1912-1954) published his famous article, "Computing Machinery and Intelligence" in the journal Mind. This article is arguably the most influential and widely read article in the philosophy of artificial intelligence. Indeed, most of the debate in the philosophy of artificial intelligence over the last fifty years concerns issues that were raised and discussed by Turing. Turing's genius was not only in developing the theory of computability but also in understanding the impact, both practical and philosophical, that computing machinery would have. Turing believed that computers, if properly designed and educated, could exhibit intelligent behavior, even behavior that would be indistinguishable from human intelligent behavior. His vision of the possibility of machine intelligence has been highly inspiring and extremely controversial. In this classic article Turing presented his well known imitation game and predicted that about the year 2000 "an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning" in the imitation game. Based on the results of the Loebner 2000 contest and the accomplishments in the field of AI, as impressive as they are, Turing's prediction remains unfulfilled.