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Stan Franklin is the perfect tour guide through the contemporary interdisciplinary matrix of artificial intelligence, cognitive science, cognitive neuroscience, artificial neural networks, artificial life, and robotics that is producing a new paradigm of mind. Along the way, Franklin makes the case for a perspective that rejects a rigid distinction between mind and non-mind in favor of a continuum from less to more mind.
"Humans may not be Earth's most intelligent beings for much longer: the world champions of chess, Go, and Jeopardy! are now all AIs. Given the rapid pace of progress in AI, many predict that it could advance to human-level intelligence within the next several decades. From there, it could quickly outpace human intelligence. What do these developments mean for the future of the mind? In Artificial You, Susan Schneider says that it is inevitable that AI will take intelligence in new directions, but urges that it is up to us to carve out a sensible path forward. As AI technology turns inward, reshaping the brain, as well as outward, potentially creating machine minds, it is crucial to beware. Homo sapiens, as mind designers, will be playing with "tools" they do not understand how to use: the self, the mind, and consciousness. Schneider argues that an insufficient grasp of the nature of these entities could undermine the use of AI and brain enhancement technology, bringing about the demise or suffering of conscious beings. To flourish, we must grasp the philosophical issues lying beneath the algorithms. At the heart of her exploration is a sober-minded discussion of what AI can truly achieve: Can robots really be conscious? Can we merge with AI, as tech leaders like Elon Musk and Ray Kurzweil suggest? Is the mind just a program? Examining these thorny issues, Schneider proposes ways we can test for machine consciousness, questions whether consciousness is an unavoidable byproduct of sophisticated intelligence, and considers the overall dangers of creating machine minds."--Provided by publisher.
“Artificial intelligence has always inspired outlandish visions—that AI is going to destroy us, save us, or at the very least radically transform us. Erik Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. This is a timely, important, and even essential book.” —John Horgan, author of The End of Science Many futurists insist that AI will soon achieve human levels of intelligence. From there, it will quickly eclipse the most gifted human mind. The Myth of Artificial Intelligence argues that such claims are just that: myths. We are not on the path to developing truly intelligent machines. We don’t even know where that path might be. Erik Larson charts a journey through the landscape of AI, from Alan Turing’s early work to today’s dominant models of machine learning. Since the beginning, AI researchers and enthusiasts have equated the reasoning approaches of AI with those of human intelligence. But this is a profound mistake. Even cutting-edge AI looks nothing like human intelligence. Modern AI is based on inductive reasoning: computers make statistical correlations to determine which answer is likely to be right, allowing software to, say, detect a particular face in an image. But human reasoning is entirely different. Humans do not correlate data sets; we make conjectures sensitive to context—the best guess, given our observations and what we already know about the world. We haven’t a clue how to program this kind of reasoning, known as abduction. Yet it is the heart of common sense. Larson argues that all this AI hype is bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we are to make real progress, we must abandon futuristic talk and learn to better appreciate the only true intelligence we know—our own.
Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental, and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. Beginning with an overview of the historical, methodological, and technical issues in the field of cognitively inspired artificial intelligence, Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realize biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biological and cognitive accuracy of artificial systems in order to project and predict their explanatory power with respect to the natural systems taken as a source of inspiration. Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science.
Mind design is the endeavor to understand mind (thinking, intellect) in terms of its design (how it is built, how it works). Unlike traditional empirical psychology, it is more oriented toward the "how" than the "what." An experiment in mind design is more likely to be an attempt to build something and make it work—as in artificial intelligence—than to observe or analyze what already exists. Mind design is psychology by reverse engineering. When Mind Design was first published in 1981, it became a classic in the then-nascent fields of cognitive science and AI. This second edition retains four landmark essays from the first, adding to them one earlier milestone (Turing's "Computing Machinery and Intelligence") and eleven more recent articles about connectionism, dynamical systems, and symbolic versus nonsymbolic models. The contributors are divided about evenly between philosophers and scientists. Yet all are "philosophical" in that they address fundamental issues and concepts; and all are "scientific" in that they are technically sophisticated and concerned with concrete empirical research. Contributors Rodney A. Brooks, Paul M. Churchland, Andy Clark, Daniel C. Dennett, Hubert L. Dreyfus, Jerry A. Fodor, Joseph Garon, John Haugeland, Marvin Minsky, Allen Newell, Zenon W. Pylyshyn, William Ramsey, Jay F. Rosenberg, David E. Rumelhart, John R. Searle, Herbert A. Simon, Paul Smolensky, Stephen Stich, A.M. Turing, Timothy van Gelder
Explores universal questions about humanity's capacity for living and thriving in the coming age of sentient machines and AI, examining debates from opposing perspectives while discussing emerging intellectual diversity and its potential role in enabling a positive life.
Made-Up Minds addresses fundamental questions of learning and concept invention by means of an innovative computer program that is based on the cognitive-developmental theory of psychologist Jean Piaget. Drescher uses Piaget's theory as a source of inspiration for the design of an artificial cognitive system called the schema mechanism and then uses the system to elaborate and test Piaget's theory. The approach is original enough that readers need not have extensive knowledge of artificial intelligence, and a chapter summarizing Piaget's work assists readers who lack a background in developmental psychology.
"Machines who think—how utterly preposterous," huff beleaguered humanists, defending their dwindling turf. "Artificial Intelligence—it's here and about to surpass our own," crow techno-visionaries, proclaiming dominion. It's so simple and obvious, each side maintains, only a fanatic could disagree. Deciding where the truth lies between these two extremes is the main purpose of John Haugeland's marvelously lucid and witty book on what artificial intelligence is all about. Although presented entirely in non-technical terms, it neither oversimplifies the science nor evades the fundamental philosophical issues. Far from ducking the really hard questions, it takes them on, one by one. Artificial intelligence, Haugeland notes, is based on a very good idea, which might well be right, and just as well might not. That idea, the idea that human thinking and machine computing are "radically the same," provides the central theme for his illuminating and provocative book about this exciting new field. After a brief but revealing digression in intellectual history, Haugeland systematically tackles such basic questions as: What is a computer really? How can a physical object "mean" anything? What are the options for computational organization? and What structures have been proposed and tried as actual scientific models for intelligence? In a concluding chapter he takes up several outstanding problems and puzzles—including intelligence in action, imagery, feelings and personality—and their enigmatic prospects for solution.
Drawn from the pages of Scientific American and collected here for the first time, this work contains updated and condensed information, made accessible to a general popular science audience, on the subject of artificial intelligence.
Glen examines the potential for future integration between man and machine drawing on examples in medicine (the Jarvik heart, Utah arm, Triad hip, etc) and advances in human-like processing via machine in terms of speech recognition and other information technologies. While the author touches on topics ranging from philosophy and religion to science and politics, the unifying theme is what he sees as the inescapable blending of machine-enhanced humans and ‘conscious’ artificial intelligence.