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 | | The Way We Think: Conceptual Blending and The Mind's Hidden Complexities by Gilles Fauconnier, Mark Turner ISBN-10: 9780465087853 ISBN-10: 0-465-08785-X ISBN-13: 9780465087853 ISBN-13: 978-0-465-08785-3 Hardcover 2002-04 Basic Books Find Lowest Price |
Editorials | ||
Product Description A long-awaited synthesis that marks a major turning point in cognitive science. Until recently, cognitive science focused on such mental functions as problem solving, grammar, and pattern--the functions in which the human mind most closely resembles a computer. But humans are more than computers: we invent new meanings, imagine wildly, and even have ideas that have never existed before. Today the cutting edge of cognitive science addresses precisely these mysterious, creative aspects of the mind. The Way We Think is a landmark analysis of the imaginative nature of the mind. Conceptual blending is already widely known in research laboratories throughout the world; this book, written to be accessible to both lay readers and interested scientists, is its definitive statement. Gilles Fauconnier and Mark Turner show that conceptual blending is the root of the cognitively modern human mind, and that conceptual blends themselves are continually combined and reblended to create the rich mental fabric in which we live. The Way We Think shows how this blending operates; how it is affected by (and gives rise to) language, identity, culture, and invention; and how we imagine what could be and what might have been. The result is a bold and exciting new view of how the mind works. | ||
Reviews | ||
Wonderful book, not for the fainthearted A book for those interested in how the brain processes information, makes links between new information and existing knowledge, and uses "metaphor" in the widest sense of the word. Fauconnier and Turner present a thorough and complete theory of the higher level operation of the mind called "conceptual blending". The theory is fascinating and compelling. The book builds from simple examples to complex examples, and lays down a robust and well constructed foundation for thinking about your own thinking. For me, the book offered new insight into my use of metaphor to help my coaching clients and students change. One word of warning. Although the book is written in a pleasant and readable style, the material presented is not simple. Expect to be challenged! | ||
Introduction to the combinatorics of concepts In the fields of cognitive science and artificial intelligence, the most important unresolved problem concerns the methodology by which the human brain combines concepts from two or more disparate domains. The solution of this problem will result in a dramatic breakthrough in how we perceive human thought and how we can implement it in computing machines. To this day no scientist, technician, or engineer can claim to have a full view of how the human brain can take information about a musical composition for example and combine it with information detailing the rules of a chess game. It is easy to see that a musical composition can be thought of as a series of symbols written down in a definite order under the constraint of certain rules of harmony. A chess game may be viewed as a series of moves on a chessboard under the constraint of the rules of chess. These movies can easily be transcribed in symbolic form. Musical compositions and chess games can therefore be viewed as a series of symbols written on paper or computer screen. In this way one can view musical composition and chess playing as part of the same category, namely the category that describes how entities in time, here musical notes or chess moves, can be represented by symbols. But having this knowledge will not allow one to become a good composer and good chess player. For that one requires an understanding of the proper places in conceptual space that both of these activities lie, and how to combine these concepts in highly creative ways. What at first glance may be very disparate domains, musical composition and chess playing could be combined into one or more concepts that retain certain features of each domain but form a compact and effective knowledge base for which to compose music or play chess. The authors of this book call this process "conceptual blending" and have done an excellent job of presenting to the reader their research and commentary on how the human mind performs this activity. Many readers, especially those who demand their support from cognitive neuroscience, will of course view their opinions as controversial. But as a whole they are a good first step in trying to understand what might be called the combinatorics of concepts. Readers in the artificial intelligence community, especially those that are determined to implement these ideas in real computing machines, may find the book helpful but will no doubt also realize after reading it that much remains to be done for a total understanding of domain-general human thinking. Some of the examples that the authors use in the book are somewhat elementary but this was no doubt by design so as to make it more accessible to a general audience. There are places where this is not the case, as for example their use of the complex number system as being a "double-scoped network." Imagination plays a big role in conceptual blending, and this sets it apart from mere symbol manipulation, i.e. from the deceptions of the "Eliza" machine. They outline four different types of `blending' or `integration' networks and give real-world examples of each. As one might expect, the blending of concepts is a complex process, with the production of concepts never the result of applying just one mapping. It is also natural to expect that any logical inferences that take place in each of the domains may not survive when these domains are subjected to conceptual blending. The resulting blend may have vestiges (one might call them "shadows") of these inferences but the creative process involved in conceptual blending may result in inferences that are completely at odds with those in the original domains. Along these same lines it would seem that conceptual blending is irreversible, with this irreversibility even more apparent the more "entangled" the blended concepts are. This would raise the question as to the evolutionary advantage or energy requirements of conceptual blending, with the answer to this question no doubt arising from the view that a degree of compression is involved in it. Therefore the recollection/storage of huge knowledge bases becomes unnecessary, due to the ability to blend many ideas or concepts into a compact and useful form. A natural question to ask is whether these networks can be embedded in the computational paradigm, and if so, how computationally complex this implementation would be in real computing machines. The authors emphasize strongly that conceptual blending is not algorithmic, and so any machine implementation may require new computing paradigms and data structures than what have been developed hitherto. There are many researchers in the artificial intelligence community who are working feverishly to implement conceptual blending in some form or another. These efforts have been classified as "artificial general intelligence" and although most of this activity is outside of the realm of the academia, it has attracted the attention of many highly talented (and courageous) individuals. It might be tempting to view the theory of conceptual blending as outlined in this book as being one that could be easily viewed in terms of the field of category theory in mathematics. But in the latter concepts in one domain are related to another by "functors" that retain most the logic of each domain. Conceptual blending on the contrary mixes up this information and creates objects that could be very dissimilar to the ones in the starting domains. Of course, this does not mean that some sort of generalized category theory could not be invented that would emulate most of the features of conceptual blending. This would be an interesting research project for those who want to give the theory of conceptual blending a more rigorous mathematical foundation. In this regard a branch of mathematics called `topos theory' may be of assistance here. | ||
Absolutely Brilliant The bad stuff first: this book almost has to be read twice. The idea of conceptual blending has many different sides (the different types of conceptual blend, compression within a blend, how certain grammatical structures call up this or that blend, etc.), and there is just no way to provide all of these different sides at once. The first few chapters are therefore pretty rough going, since some of the material that you should ideally have in order to understand them does not come until much later. Part of this is due to imperfect arrangement on the part of the authors, and part of it comes from the complexity of the topic itself. This is not a beach read by any means. However, if you can plow through the first few chapters, the ideas within are extremely useful. The authors explain metaphor as a special case of what they call conceptual blending, which can also explain how certain words have the meanings which they do (e.g., "prevent," "fake," "eligible") as well as how certain syntactical structures call up meanings in our minds (e.g., "Joe is my boss," "jailbait," "houseboat"). The point is that literal meaning is not the default that our mind uses, with metaphor being the mind's last resort: rather, conceptual blending is the basis for how the mind constructs meaning, with judgments about the literal or metaphorical nature of meaning being added on later. This book works marvellously well alongside certain works by George Lakoff and Mark Johnson (e.g., Philosophy Made Flesh). Definitely a good addition to your library if you're curious about the nature and origins of language, meaning, and higher-order rational thought in human beings. | ||
Intriguing but Vague The beginning of the book is very good with a perspective on scientific thinking. The idea of blending is then clearly explained with a multitude of examples. But it is overdone with too many examples and too many question and answer discussions. One has almost the impression that the text is in fact intended as a study supplement. But in the end one asks, isn't this all just another word for association and so what any way. It is vague in a way not to be useful. Nevertheless the text is referenced by many cognitive linguists and is a source of inspiration apparently. | ||
Hidden Complexities are Revealed The book is a sort of complement for the authors previous works (1994, 1996, 1997). It is an outstanding work as it clarifies the ways nets, frames, blends and intregations function. It is a didactical book because it goes and returns with examples which help us understand its terminology and content. It is a book of great help for all the ones interested in analysing texts competently and understanding how our mind uses linguistic expressions (triggers)to build up meaning. | ||