Showing papers on "Human intelligence published in 1990"

The Age of Intelligent Machines

Abstract: What is artificial intelligence? At its essence, it is another way of answering a central question that has been debated by scientists, philosophers, and theologians for thousands of years: How does the human brain - three pounds of ordinary matter - give rise to thought? With this question in mind, inventor and visionary computer scientist Raymond Kurzweil probes the past, present, and future of artificial intelligence, from its earliest philosophical and mathematical roots through today's moving frontier, to tantalizing glimpses of 21st-century machines with superior intelligence and truly prodigious speed and memory. Lavishly illustrated and easily accessible to the nonspecialist, The Age of Intelligent Machines provides the background needed for a full understanding of the enormous scientific potential represented by intelligent machines and of their equally profound philosophic, economic, and social implications. It examines the history of efforts to understand human intelligence and to emulate it by building devices that seem to act with human capabilities. Running alongside Kurzweil's historical and scientific narrative, are 23 articles examining contemporary issues in artificial intelligence by such luminaries as Daniel Dennett, Sherry Turkle, Douglas Hofstadter, Marvin Minsky, Seymour Papert, Edward Feigenbaum, Allen Newell, and George Gilder. Raymond Kurzweil is the founder, chairman, and chief executive officer of Kurzweil Applied Intelligence, Kurzweil Music Systems, and the Kurzweil Reading Machines division of Xerox. He was the principal developer of the first print-to-speech reading machine for the blind and other significant advances in artificial intelligencetechnology.

Just Say No to Subtest Analysis: A Critique on Wechsler Theory and Practice:

Abstract: Wechsler's beliefs about the nature of human intelligence and its measurement have profoundly influenced contemporary theory and practice. He encouraged interpretations not only of more global intellective indices, such as IQ but encouraged as well the search for pathognomonic meaning in patterns of underlying, more specific, subtest scores. This article examines the evidence that concerns the interpretation of Wechsler and similar tests as measures of specific rather than global ability. Popular practices that involve use of subtests for both intraindividual and interindividual assessment are viewed in the light of empirical research, and recommendations are presented.

Art education and human development

Abstract: The production and appreciation of art involves thought processes that have excluded from traditional measures of human intelligence. This book, written by a leading cognitive scientist, makes a compelling case for broadening these definitions and discusses the value other cultures place on artistic abilities. Gardner explores the function of art in human development as well as the strategies children employ in the process of constructing images.

Intelligence: The Psychometric View

Abstract: 1. Meaning of Intelligence 2. Factor Analysis 3. Factor Analyses of Human Abilities 4. Measuring Intelligence 5. Intelligence and Educational and Occupational Success 6. Heritability of Intelligence 7. Intelligence and Mental Speed 8. Cognitive Processing and Intelligence 9. EEG and Intelligence 10. The Nature of g References Name Index

Drama and Intelligence: A Cognitive Theory

Abstract: Drama, as defined by Courtney, encompasses all kinds of dramatic action, from children's play to social roles and theatre. He shows not only that teachers have found educational drama and spontaneous improvisation to be an invaluable learning tool but that many skills required for work and leisure reflect the theatrical ability to "read" others and see things from their point of view. The main thrust of Drama and Intelligence is that drama can enhance and develop various aspects of intelligence. Courtney suggests that the "costumed player" must bring into play many levels of intelligence in the rehearsal and execution of dramatic acts and that such acts offer unsurpassed opportunities to practice and develop these cognitive skills. He uses the term intelligence to refer to the potential for specific types of mental activity and employs a theoretic-analytic method to view cognition and intelligence in a post-structuralist and semiotic mode. Courtney examines such issues as the relation of the actual to the fictional; the dramatic creation of meaning; signs, symbols, and practical hypotheses; and experi-mental logic, intuition, and tacit modes of operation. Drama and Intelligence will interest not only scholars and students of developmental drama, but also those in the fields of dramatic and performance theory, educational drama, and drama therapy.

Mindfulness and Intelligence: A Comparison

Abstract: The theory of mindfulness (Langer, 1989a) shares with some current theories of intelligence an emphasis on the importance of cognitive flexibility. The mindfulness approach to cognitive flexibility differs from the intelligence approach in its conception of the relation between individuals and their environment. Intelligence theory employs a criterion of optimal fit between individual and environment. Mindfulness theory emphasizes that individuals may always define their relation to their environment in several ways. We examine the historical background of this difference between mindfulness and intelligence and find that (a) the concept of intelligence is embedded in a theory of correspondence that has been inherited from the 19th century; (b) current intelligence theories continue to focus on thought as adaptively corresponding to external reality; (c) despite apparent differences between unidimensional and multidimensional approaches to intelligence, common reliance on a criterion of optimal fit engend...

The vertical dimension of mental functioning

Abstract: A hierarchical, six-level model of human intelligence is described. The first four levels, which correspond to those found in Bernstein's theory of motor control, are concerned with palaeokinetic regulations (A), synergies (B), the spatial field (C), and object actions (D). The two levels of the higher symbolic coordinations embody conceptual structures (E) and metacognitive coordinations (F). The model is supported by experimental results from several subfields of cognitive research: e.g., different types of learning are specifically connected with the components of this hierarchical structure. Learning by the restructuring of existing knowledge proceeds by means of the metaprocedures of level F. The incremental accumulation of factual information is connected with the conceptual base of level E. Proceduralization of this knowledge results in the build-up of perceptual automatisms of skilled action (level D), as is often case in the formation of expert knowledge. Arguments for the hierarchical architecture of perception, attention, memory, understanding, thinking, and imagination are provided, and some parallels are drawn with the organization of emotional and motivational processes. It is argued that general, interdisciplinary questions on the nature and sources of mental functioning must be approached with a kind of pluralistic methodology. These questions cannot be answered in an equally general vein, because the localization of mental processes on the vertical dimension of cognitive architecture is to be taken into account.

Artificial Intelligence, Culture and Language: On Education and Work

Abstract: Section I. Introduction.- 1. Introduction.- Section II. Language and Knowledge.- 2. Artificial Intelligence and The Empiricist Picture of Thought.- 3. Seeing and Seeing-As.- 4. Cognitive Science and the Computer Metaphor.- Section III. Tacit Knowledge.- 5. Rule-following and Intransitive Understanding.- 6. Tacit knowledge, Rule-following and Learning.- 7. Tacit Knowledge - An Impediment for AI?.- 8. Language and Action.- 9. Language and Experience.- 10. The Inner Weather Picture.- Section IV. Education, Training, Skill and Work.- 11. The New Technology and the New Training: Reflections on the Past and Prospects for the Future.- 12. Engineering as an Art.- 13. Automation and Skill.- 14. Farmers and Computers.- 15. How to make Materials Data Systems Useful for Designers.- 16. Technological Information and Information Technology in the Information Society.- 17. A Learning Society: Japan Through Australian Eyes.- 18. Unleashing Human Intelligence - More Than a Matter of Computer Technology.- Section V. Expert Systems.- 19. Cultures, Languages, Mediation.- 20. Professional Skill and Traditions of Knowledge.- 21. Design of an Intelligent Tutor System for Use in Medical Education.- 22. Practical Applications of Artificial Intelligence in Education and Training.- Section VI. The Information Society.- 23. "I have no idea where I am going, so to make up for that I go faster".- 24. Is Socrates to Blame for Cognitivism?.- 25. Socratic Dialogue: On Dialogue and Discussion in the Formation of Knowledge.- 26. And in the End, the Epilogue?.- 27. The Personal Signature.

Explanations, machine learning, and creativity

Abstract: Creativity is obviously a crucial aspect of human intelligence, and yet it has not been explored much by AI researchers. A principal reason for this lack of attention is the mystical aura that the word “creativity” has about it. Creativity is thought to be something so mysterious that AI researchers have been intimidated by it. We claim that creativity is a much simpler, more algorithmic process than many have thought and that AI is ready to start designing creative computers.

Business expert systems: the competitive edge

Abstract: Artificial Intelligence (AI) and its subfield of Expert Systems, with its focus on emulating human intelligence and its potential for displacing human mental activity in the same way that earlier machines have displaced human and animal physical labor, is prominently at the crest of the automation wave. What is artificial intelligence? What is the current state-of-the-art? What are the areas where artificial intelligence can be best applied in the business world? What are some of the better known commercial applications? Finally, how do we justify and implement artificial intelligence/ expert system applications? This paper addresses all of the above questions. A specific application, the Trader's Assistant, is provided as a case example to illustrate many of the points made.

Toward more intelligent organizations

Abstract: To explicate the belief that learning is key to the development of human intelligence, a triarchic theory of human intelligence is presented and its implications are explored. Specifically, group knowledge-acquisition techniques for capturing and using human expertise are explored. To illustrate the ideas that a synthesis of human expertise and information technology is key to the creation of more intelligent organizations, a collaborative metasystem is proposed as a mechanism to help individuals and organizations manage personal and corporate knowledge systems and thereby deal intelligently with environmental uncertainty and equivocality. >

Chapter 14 Cognitive Development and the Growth of Capacity: Issues in NeoPiagetian Theory

Abstract: In this chapter, neoPiagetian theories about the relation between cognitive development and attentional capacity are reviewed, and some unresolved issues are discussed. The most important of these issues are the analysis and assessment of cognitive tasks, the conceptualization and measurement of capacity, and the nature of the correspondence between cognitive development, and the growth of capacity. In addition, some epistemological problems remain to be explained, including the generativity of human intelligence and the understanding of necessity. Some suggestions are made regarding the ways in which these issues might be resolved through a reconceptualization of capacity in terms of a trade-off between the amount of material represented in short-term representational media and the clarity with which that material is represented.

The Game of Chess

Abstract: : We have seen that the theory of games that emerges from this research is quite remote in both its concerns and its findings from the von Neumann Morgenstern theory. To arrive at actual strategies for the play of games as complex as chess, the game must be considered in extensive form, and its characteristic function is of no interest. The task is not to characterize optimality or substantive rationality, but to define strategies for finding good moves -- procedural rationality. What is emerging, from research on games like chess, is a computational theory of games: A theory of what it is reasonable to do when it is impossible to determine what is best -- a theory of bounded rationality. The lessons taught by this research may be of considerable value for understanding and dealing with situations in real life that are even more complex that the situations we encounter in chess -- in dealing, say, with large organizations, with the economy, or with relations among nations. The game of chess has sometimes been referred to as the Drosophila of artificial intelligence and cognitive science research - a standard task that serves as a test bed for ideas about the nature of intelligence and computational schemes for intelligent systems. Both machine intelligence -- how to program a computer to play good chess (artificial intelligence) -- and human intelligence -- how to understand the processes that human masters use to play good chess (cognitive science) -- are encompassed in this research. (kr)

The making of the civilized mind

Abstract: Contents: The relationship of human intelligence variability to the content and institutions of culture and civilization. To be used in upper level undergraduate courses. The Making of the Civilized Mind is a new interpretation of the sociobiology of civilizational behavior.

Artificial intelligence and metaphor making: Some philosophic considerations

Abstract: This article argues that the metaphors presently employed in describing artificial intelligence represent the use of personification and anthropomorphism. They attempt to develop an isomorphic relationship between the human mind and a computer’s logic. It is suggested that an analogic metaphor is more appropriate in describing this relationship and is more epistemologically correct.

A Postmodern Critique of Artificial Intelligence

Abstract: I argue that the "postmodern" understanding of language that has developed over the last few decades in Anglo-American philosophy provides the basis for a useful critique of artificial intelligence. This postmodern view corrects an error in the traditional Western conception of language that has led many researchers in AI and cognitive science into taking a rule-based or information-processing approach. Wittgenstein's view that language does not receive its meaning through definition, and Quine's view that neither words nor sentences but only discourse as a whole is the proper unit of meaning, argue against an attempt to formulate rules for understanding language, which is an essential part of "strong" AI. AI researchers are already beginning to correct this mistake, but an understanding of its true extent and depth can lead to the sort of radical rethinking that is necessary. The field of artificial intelligence (AI) aims to reproduce human intelligence by artificial means. The AI community generally concedes that achieving this goal has been harder than anticipated and awaits significant breakthroughs. But it insists that there are no barriers in principle. The obstacles to artificial intelligence are technical in nature, and a vigorous application of human intelligence can eventually overcome them. There are grounds to believe, however, that AI as customarily practiced rests on a fundamental mistake of principle. Hubert Dreyfus, one http://wpweb2.tepper.cmu.edu/jnh/ai.txt (2 of 19) [1/7/2010 1:37:12 PM] http://wpweb2.tepper.cmu.edu/jnh/ai.txt of the loudest of AI's critics, makes such a claim in his book, What Computers Can't Do (1979), and elaborates it in subsequent articles (1984; Dreyfus and Dreyfus, 1984, 1986, 1988). His critique actually has two prongs. He castigates the leading figures of AI for overestimating the prospects of their field and consistently failing to deliver. His shrill polemic along these lines has generated controversy that can obscure the second, more general prong of his critique. It is that AI rests on the mistaken assumption that human intelligence can (roughly speaking) be understood at the information processing level. A philosopher trained in the Continental tradition, he draws on the work of Heidegger to identify the error and show how it surfaces in AI. It is not my purpose to explain or defend Dreyfus' philosophical critique of AI. Rather I want to show that a related critique can be mounted on the "postmodern" understanding of language that has developed in the Anglo-American philosophical tradition, particularly in the work of Ludwig Wittgenstein and Willard Quine. I do not claim that AI is impossible. On the contrary, AI's philosophical underpinnings, as I will identify them, have a complex and indirect relationship to its potential for technical success. But if I am right, AI practitioners have typically operated on a set of assumptions that are not only incorrect but uninformed by Western thought's self-criticism of the last few decades. My critique also applies to the science of cognitive psychology, to the extent that it presupposes that human intelligence can be understood on a purely information processing level. In the five following sections I state my thesis, briefly paint the Western intellectual background that supplies AI with its present "modern" (as opposed to the "postmodern") worldview, explain why Wittgenstein and Quine think this worldview is mistaken, and then outline what I take to be the implications of this mistake for AI.

Chapter Ten Aging and Everyday Cognitive Abilities

Abstract: Summary In this chapter, recent work on everyday cognitive abilities in adults and the elderly is reviewed. Despite substantial theory and data that have been generated in the study of intellectual aging, there has been a recurrent concern that traditional paradigms for assessing intellectual abilities are insensitive to cognitive skills adults use in adapting to the demands of everyday life. In the first section, we examine how this concern has been paralleled by recent studies of people's implicit theories of intelligence. Implicit theories refer to people's ideas and beliefs about intelligence and how it changes across the life span. Findings show that people have distinct concepts of everyday and academic intelligence, and they believe that facets of everyday intelligence become increasingly salient, especially in middle age and late adulthood. In the second section, research on adults' self-conceptions of intelligence and conceptions of ability tests is discussed. The findings underscore the multidimensional nature of everyday intelligence and highlight the distinct importance of practical and social cognitive abilities in conceptions of everyday intelligence. In the third section, two tasks recently developed to assess adults' strategic knowledge about solutions to problems in everyday and stressful situations are described. Results show differences and similarities between performance on everyday and traditional ability

“Language” and intelligence in monkeys and apes: How scientific usages reflect implicit theories: Adaptation, development, instinct, learning, cognition , and intelligence

Abstract: As the anthropological linguist Edward Sapir noted, language is largely unconscious. In everyday life, we all use words without knowing exactly what we mean by them. Examination of scholarly works suggests that we extend this practice into our professional lives as well. The words we use and the way we use them reflect our implicit, unconscious knowledge, presuppositions, and theories (and, equally, our implicit, unconscious ignorance). The nature of one's implicit knowledge (and ignorance) is determined by one's disciplinary training and one's personal intellectual history. Specialists in philosophy, zoology (especially ethology), cognitive sciences, and various branches of psychology, for example, often use the terms learning, intelligence , and cognition in subtly different ways. Scholars in different subdisciplines describe similar phenomena in different terms: Comparative psychologists, especially learning and conditioning theorists, for example, use the term learning to describe the acquisition of instrumental behaviors, whereas comparative developmental psychologists use intelligence or cognition to describe such acquisitions. Through the years, various investigators have used a variety of terms to characterize animal abilities. A brief survey of books on mental abilities of animals, for example, reveals varying usages of the related terms mind/mentality, learning, cognition, intelligence, thought , and consciousness (Table 2.1). Instinct, learning, intelligence , and development are used in different ways by embryologists, learning and conditioning theorists, ethologists, and developmental psychologists. Although William James and John B.

Human intelligence and AI: how close are we to bridging the gap? (open line)

Abstract: A few issues that the author considers of central importance are identified, and their implications for the central question of how relevant current AI studies are to understanding the architecture of human intelligence are analyzed. A plausible strategy for inferring the architecture of human intelligence is outlined and used as a framework for discussing the issues raised by the author. It is concluded that we are far from bridging the gap between human intelligence and AI, because we have not been asking the right questions or tackling the real issues. >

The elusiveness of human nature

Abstract: Sociobiology uses neo‐Darwinism to make wide‐ranging explanatory conjectures about man and society. The ‘naturalism’ of such an enterprise recommends it, but a thoroughgoing and Darwinian naturalism is compatible with a rejection of sociobiological conjectures. Retention of juvenile characteristics explains various human physical features and can be used to account for the playful and curiosity‐driven nature of human intelligence. The malleable and hedonistic character of human sexuality is similarly explained. It has been argued (Wallace and latterly T. Nagel) that human intellectual capacity transcends what is necessary for survival and so cannot be explained by natural selection. This wrongly supposes that all characteristics explained by Darwinism are explained as specifically selected for. Fears about biologically imposed limits to human understanding misrepresent intelligence as an aggregate of specifically adjusted capacities. Conceiving human intelligence as a product of neotenization frees us fro...

The Role of Intelligence Filters in Expert Systems

Abstract: In designing expert systems, we assume all humans have the same level of intelligence when in fact we do not. This assumption and the lack of a proper intelligence definition weakens the role of ES’s. The use of a new concept called the Intelligence Filter which has been developed by the writer is put forward in the paper as a possible solution to the problem.

TAUS: A file-based software understanding tool

Abstract: A program called TAUS, a Tool for Analyzing and Understanding Software, was developed. It is designed to help the programmer analyze and understand the software interactively. Its aim is to reduce the dependence on human intelligence in software understanding and improve the programmer's understanding productivity. The design and implementation of TAUS and its application are described.