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9 of 10 people found the following review helpful:
5.0 out of 5 stars
Superb, July 26, 2004
This review is from: The Creative Mind: Myths and Mechanisms (Paperback)
The nature and origins of creativity is of great interest in the field of human psychology, and research on creativity has occupied the time of many individuals. This book, written by an individual well recognized in the field, gives a fascinating account of her ideas on creativity, and has been a major influence for those attempting to realize creativity in non-human machines. Throughout its pages, the author attempts not only to define creativity, but also to give criteria for distinguishing new ideas that are creative from simply new ideas. The most important goal of the book though is to frame the nature of creativity in a computational paradigm.
Philosophers, writers, artists, musicians, and others in the humanities will perhaps frown on the author's project to use computational concepts to assist in the understanding of human creativity. Many of those who work in these professions will point to "intuition" as being the source of creative ideas and works, regardless of their vague understanding of this term. The author demands, rightfully, a clarification of the notion of intuition, but she does not seek to do this herself in the book, but instead looks to the computational paradigm to settle the issue of human and machine creativity. She argues at length throughout the book that not only can this paradigm assist in the understanding of human creativity, but that non-human machines can appear to be creative and can also recognize creativity. The question as to whether non-human machines really are creative is also addressed towards the end of book.
Having a computational model of creativity would allow the design of machines that could produce novel scientific theories, musical compositions, architectural designs, and works of art. It would also give those working in the cognitive sciences greater insight into the understanding of the mechanisms involved in human creative thinking, such as the ability to make analogies, formulate complicated mathematical ideas, or classify patterns. In addition, having a generic computational model of creativity would give insight on how to create novel ideas in a manner that is independent of the domain or context in which one is working. Machines could thus be built that would be able to generate creative ideas in many different domains. For example, a machine that generates new mathematical ideas would also be able to create interesting works of art. This would be a major advance in machine intelligence if such machines could be built.
In the book, the author introduces two notions of creativity that she feels is necessary for her study. One of these is called 'P-creativity', and is a personal and psychological notion. The other is called 'H-creativity' and is a historical notion. Given an idea that arises in a particular person, this idea would be called P-creative if the person could not have had it before. It is irrelevant how many other people already have the same idea. An idea is called H-creative if it is P-creative and no one in human history has ever had it before. As can be seen from the definition, it would be difficult to check whether an idea is really H-creative, since it would require quite an extensive statistical survey. But such a survey would be unnecessary, for the author contends that there is no theory that can explain solely H-creative ideas, but that since H-creative ideas are also P-creative, an explanation of P-creative ideas would also apply to H-creative ideas.
According to the author, the ability to distinguish first-time novelty from genuine originality involves an understanding of what generative processes were involved in the production of the idea. A "novel" idea is one that can be described or produced by the same set of generative rules as other familiar ideas, whereas a genuinely original idea is one that cannot. Therefore, the designation of ideas as "genuinely creative" is always done relative to a specific generative system.
Conceptual spaces, in the author's view, are styles of thinking, and creativity must be thought of in terms of the mapping, exploration, and transformation of conceptual spaces. Conceptual spaces are used to organize and give structure to a particular domain of interest, such as checkers game or a Bach concerto. The structure of a conceptual space can be mapped by forming mental representations of it, and these maps can be use to explore them and to change them if necessary. As one example of this, the author quotes the investigations of tonal harmony in post-Renaissance Western music. The dropping of the home-key constraint in tonal music transformed the conceptual space of tonal music to create the conceptual space of atonal music. The deliberate dropping of a constraint is one method by which conceptual spaces can be generated. Another method is to negate a constraint. The author illustrates this method with a discussion of the discovery of the benzene ring due to Friederich Kekule.
A highly interesting and totally unexpected discussion in the book involves the connection of unpredictability with creativity. Since H-creative ideas are ones that have not appeared before in human history, they are unpredicted. The author emphasizes though that this does not mean that H-creative ideas are unpredictable. The role of serendipity, chance, and coincidences in creative thinking are discussed in terms of the computational paradigm. The author concludes from this discussion that creativity cannot be due to chance alone, but that chance with judgment can. The author also discusses three different notions of randomness, with the intent of shedding light on the belief that determinism is incompatible with creativity. These three notions are labeled 'absolute', 'explanatory', and 'relative'. The first is total absence of any order or structure within the domain; the second the lack of any explanation or cause, and the third lack of any order relevant to some specific consideration. Human creativity is relatively unpredictable the author asserts, and it is easy to believe this considering our folklore understanding of it. The computational paradigm of the author has assisted our understanding of it, but more research is needed.
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5 of 6 people found the following review helpful:
3.0 out of 5 stars
Not Very Creative, May 16, 2009
This review is from: The Creative Mind: Myths and Mechanisms (Paperback)
This work was initially published in 1990, amidst a bumper crop of books about the brain, mind and consciousness. Neuroscientists, psychologists and no-nonsense philosophers were setting off to reclaim the mind from the dark superstitions of religion, art and human specialness. Psychologist / philosopher Margaret Boden decided to stake a claim in the territory of human creativity. In "The Creative Mind: Myths & Mechanisms", she seeks to vanquish those who would defend the irreducible quality of human consciousness with the wonders of its creativity.
Boden tries diligently to capture the squishy idea of creativeness. She looks at famous examples of creativity in the arts and the sciences, and comes up with a number of "heuristics" or rules of thumb about it. She then analyzes the creative nature of children in various ways (including analysis of typical children's drawings across ages and stages of development). Next, she examines how computer programs, especially massively parallel neural-networks, are making progress in mimicking human problem-solving. Some programs have indeed come up with problem solutions that humans had not though of.
Perhaps then creativity isn't such a mysterious thing. Evolution has given brains with powerful problem-solving capacity to the homo sapiens species, explaining much of their success (thus far). Historical creativity thus becomes a matter of the right person being in the right situation at the right time. The more creative people among us are those with brain abilities most appropriate to the challenge at hand (and the foresight to recognize the value of their thoughts). Einstein, Mozart and Shakespeare alike had the right combination of mind strengths relative to their particular surroundings, allowing them to come up with surprising new works. The other 99.999 percent of us don't change history, but still have occasional moments when our brains link conceptual spaces together in novel and useful ways (to us, anyway).
If evolution has given us creative ability, then creativity should reflect the nature of evolution. I.e., it must progress through random trial and error. As we teach our computing machines to mimic the "parallel emergence" process of the brain, we can speed up this process by "rolling the dice" faster and more often. Thus, we now have machines that come up with chess strategies not previously considered. Our chess masters, unassisted, probably would have derived these tactics eventually; but computers can think faster than we can (that is, once we teach them how to think).
To nail all of this down, Dr. Boden expands upon the amazing things happening in the world of computerized thinking. She introduces various computer systems designed to solve problems in mathematics, science, psychology, political analysis, and even art. Perhaps the most famous to date is the IBM Deep Blue chess program; but another very interesting example is EURISKO, a strategy program used to compete against human teams in a naval battle simulation. EURISKO came up with a surprising tactic that seemed all wrong, i.e. lots of little "one shot and out" boats (versus standard fleet strategy based on a smaller number of well-armed, well-defended ships grouped together). Of course, the computer tactic surprised everyone and won -- two years in a row.
But has Dr. Boden won? Have Deep Blue and EURISKO fully captured the essence of human creativity? Are our own minds and our conscious experiences just a bigger, more developed version of these new problem-solving machines?
Unfortunately, Dr. Boden hardly spends time comparing human creativity with examples of creative acts within the higher animal kingdom. In the final chapter she ponders the hoverfly and reassures us that we are not insects, even if we all are ultimately machine-like. But what about dolphins and chimps? Shouldn't their creativity be a lot more like ours? Chimps and dolphins have been observed finding creative solutions to survival challenges in their environment, both individually and socially. But they don't do art. They don't set up monuments marking the graves of their comrades. They don't evidence concern about justice, equality and ultimate meaning in the universe.
Humans, by contrast, expend resources on these things. We have obviously gone through a mental "phase shift", discovering something ontologically different. Yes, this "emergence" certainly involves the exchange of conceptual symbols (i.e., language) and the survival benefits this brings. And yet, our speaking ability was formed as much to capture the "poetic feeling" as to capture food and lightening.
Our machines can come up with creative music, artwork and legal systems; but only because we taught them how. They could not have derived the basic inspirations behind such things. Our machines share the same physical processes that support our own lives, but differ in a fundamental way. They are hot-house flowers. They do not face the challenge of survival amidst limited resources. They worry not where their next kilowatt is coming from. They don't need a wide range of continual information from the environment to survive. They don't see the stars at night and the sun rising; they don't feel the sting of snow on their frame covers, or the warmth from a companion's CPU; they don't smell the flowers; they don't taste the sweetness of apples (nor the amps being consumed through their power assemblies). As such, there are things about the world that we "know" that machines cannot.
(That is, unless we turn our machines loose to survive and reproduce on their own, as in science fiction. But science fiction warns us over and over just how badly that scenario could go, if our new machine species turns out even a fraction as imperfect and neurotic as the human race.)
Unfortunately, Dr. Boden doesn't reach this level of analysis. She stays close to the traditional philosophy-of-mind debate. She bogs down fighting the "mental stuff" argument (i.e., only the carbon-based chemistry that we know of in our ecosphere can support mental life), and in evicting John Searle from his "Chinese Room". She wins many battles, but isn't very creative in justifying the alleged war victory of computationalism.
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3 of 6 people found the following review helpful:
4.0 out of 5 stars
The wrong approach?, January 15, 2006
This review is from: The Creative Mind: Myths and Mechanisms (Paperback)
The idea of seeking to better understand human creativity through comparing it to certain kinds of computer operation , I must admit, seemed to me , at the outset , less than exciting. This is not to say that the Boden approach of exploring conceptual spaces in the mind, transforming them through computational concepts drawn from artificial intelligence, and through this revealing certain insights into human creativity- is totally barren or meaningless. I myself do not really feel I have the qualification to say, whether some of these insights might be useful or not.
What I can say , is that this kind of analysis seems to me , not really relevant to understanding the kinds of literary creation I know a certain amount about. Consider the following lines of poetry, or for that matter any lines of poetry. " Shall I compare thee to a summer day/ Thou art more lovely and more temperature/ Rough winds do shake the darling buds of May/ And Summer's lease hath all too short a date/ ......
The language of poetry cannot really be translated into mathematical language, whether it is gobbyldegook or not. Nor I would argue can the language of any kind of real "Literature"
The kind of explanations given for Creativity in Literary work here seem to me to be ' reductions' to a 'lower level'. The complexities and ambiguities of literary language, the vast hinting and suggesting which move much poetry it seems to me, are wholly out of keeping with a clear mathematical language , analogue or digital.
To put this another way, this book does not give me 'the feeling' that the kinds of creativity I appreciate are even touched upon by its concepts.
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