- Tapa blanda: 464 páginas
- Editor: Basic Books; Edición: Reprint (18 de marzo de 2003)
- Idioma: Inglés
- ISBN-10: 0465087868
- ISBN-13: 978-0465087860
- Valoración media de los clientes: 1 opinión de cliente
- Clasificación en los más vendidos de Amazon: nº92.068 en Libros en idiomas extranjeros (Ver el Top 100 en Libros en idiomas extranjeros)
The Way We Think: Conceptual Blending And The Mind's Hidden Complexities (Inglés) Tapa blanda – 18 mar 2003
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Reseña del editor
In its first two decades, much of cognitive science focused on such mental functions as memory, learning, symbolic thought, and language acquisition - the functions in which the human mind most closely resembles a computer. But humans are more than computers, and the cutting-edge research in cognitive science is increasingly focused on the more mysterious, creative aspects of the mind. The Way We Think is a landmark synthesis that exemplifies this new direction. The theory of conceptual blending is already widely known in labouratories throughout the world this book is its definitive statement. Gilles Fauconnier and Mark Turner argue that all learning and all thinking consist of blends of metaphors based on simple bodily experiences. These blends are then themselves blended together into an increasingly rich structure that makes up our mental functioning in modern society. A child's entire development consists of learning and navigating these blends. The Way We Think shows how this blending operates how it is affected by (and gives rise to) language, identity, and concept of category and the rules by which we use blends to understand ideas that are new to us. The result is a bold, exciting, and accessible new view of how the mind works.
Biografía del autor
Gilles Fauconnier is Professor and Chairman of the Cognitive Science Department at the University of California, San Diego. Mark Turner is Associate Director of the centre for Advanced Study in behavioural Sciences at Stanford University.
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And we do it all the time, unceasingly, and in large measure, unconsciously. And at different levels of complexity, one of which, double-scope blending, is posited to be the crucial step that allowed human symbolic thought and precipitated language, art, and symbolic representation of all types.
I love the idea here, and in a very general way, it must be true, right? The very definition of thought by many is the combining of concepts. (In this view, even the exclamation Bear! Is really the implicit form of: It’s a bear!) But the real center of this work is the way the authors have brought to light in detail the many varieties and types of conceptual blending.
The concepts that are brought to bear in any argument or theory are a good place to begin examining that theory.
In the language acquisition process, many would say the conceptual blending is accomplished by syntax.
Susan Carey, in The Origin of Concepts, describes Quinean bootstrapping as a process where new symbols are sometimes used as placeholders with little or no meaning; then, as the particular new conceptual system is mastered, meaning is gradually gained through integration and interpretation with the other concepts in that system.
Terrence Deacon, in The Symbolic Species, describes symbolic takeoff in humans as a process, first outlined by Charles Peirce, involving 3 stages. First, there is the process of iconicity, in which we recognize objects as being the same or similar. (I take this to be a close approximation to identity in The Way We Think.)
Secondly, there are indexical relationships in which one thing signals another by being contiguous in time or space or correlation. (Smoke and Fire)
Thirdly, there is a point in time when these earlier relationships of iconicity and association are temporarily set aside, as in the apes learning symbols; new unifying concepts are learned, and it is realized that the symbols have relationships with each other that encompass and direct the iconic and indexical relationships.
My intuition is that these are all different descriptions of the same process, to wit, symbolic takeoff.
But the idea that these prior iconic and indexical relationships must be mastered before a symbolic system can be achieved grounds the process in the physical world, and leads me to one opposite conclusion than that of the authors. They believe that the ability to blend conceptually precipitated language, art, and all our other symbolic activities. According to the models up above, especially Deacon’s, I think it more likely the other way around: our symbolic use in language precipitated advanced conceptual blending. As also mentioned above, this symbolic use would entail syntax to be truly symbolic, and this sets aside, for present purposes, whether gesture or some type of proto language existed prior, though my feeling, due to tool use, anatomy, and other evidence, is that one did.
Now, because of the dearth of direct evidence I could certainly be wrong, and this is not a critical point for the authors’ enterprise. I also believe that the processes of metaphor play a more important and central part in our thought than they represent. Language expands into abstraction largely through metaphor.
The conceptions, descriptions, and elaboration of the different types of conceptual blends and their use in human thought is a truly amazing pioneering effort, however, and I have the feeling it will be remembered and studied as long there are those who study these things. The Way We Think is an original work both breathtaking and audacious in scope.
Note: My reviews are generally 5 star reviews, not because I am undiscriminating, but because I only review books that I really like and consider valuable. Otherwise, for me personally, I have better ways to spend the time.
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.
I know I can go to Kindle PC and see the pictures there with all the colors etc. but one must agree that it is a pain in the butt to switch to the computer every time I needed to see a picture.
So, if I had purchased the printed book, I would give it 5 stars, but the Kindle version has flaws.
About the book's content, it carries very useful information if you look for something beyond a pure recipe book.