Last Updated on May 10, 2015, by eNotes Editorial. Word Count: 2769
An analogy seems an appropriate way to begin a review of a book whose central theme is creative analogies: This review is to Douglas Hofstadter’s book as a musician’s improvisations are to the melody upon which he or she is improvising. For Hofstadter, this and other analogies grow out of the human ability, which lies at the core of creativity, to see similarities in things that appear otherwise dissimilar. Book reviewing, improvising a jazz solo, and discovering computer analogues to human thinking involve, respectively, new and preconceived ideas, musical phrases, and computer structures that are creative responses to a particular task, situation, or problem. Creativity is a very complex process, and over the centuries, different people have studied it in astonishingly different ways. One of the most difficult things for creative people to do is to choose a path through what at first seems a chaos of experiences and ideas, because in choosing a single theme to organize their thinking, they are forced to ignore many other facets of an inexhaustible subject. The risk that Hofstadter takes in Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought is awesome, since he is gambling that his study of concepts and analogy making will capture really big game—the essence of human cognition.
Douglas Hofstadter, the son of a Nobel Prize-winning physicist, has been interested in science, mathematics, music, and art from childhood. He became known to the public with his Pulitzer Prize-winning bookGödel, Escher, Bach: An Eternal Golden Braid (1979), a fascinating interdisciplinary study of how ideas of pattern recognition in the aesthetically driven work of a mathematician, an artist, and a musician could illuminate one another and also shed light on human creativity. Since 1977, when Hofstadter became an assistant professor of computer science at Indiana University, he and his graduate students have been developing computer models of how humans create concepts and discover new analogies. Fluid Concepts and Creative Analogies is the product of this research.
For almost as long as humans have thought about what it means to be human, mental activity—the ability to form concepts and to solve problems of increasing complexity—has been considered a unique attribute of the species. Hofstadter and other cognitive scientists believe, however, that a machine—the computer—will be able to model human thinking, and thus the chief tool of Hofstadter’s research has been the computer program. The greater part of his book consists of chapters describing specific computer programs that explore how to solve number sequences, anagrams, letter analogies, pointing analogies, and the recognition and creation of artistic typefaces. Though some of these programs succeeded in solving their targeted problems, this was not their principal purpose. Hofstadter used these programs to gain insight into analogy making, which he believes is the heart and soul of intelligence. The human mind is also adept at using fluid concepts that stretch to adapt to unanticipated situations. According to Hofstadter, the mental mechanism that enables humans to use fluid concepts and develop creative analogies is a system of many independent and parallel “subcognitive” agents that collectively construct coherent mental structures.
The fluid properties of thought suggested the name of Hofstadter’s group, the Fluid Analogies Research Group (FARG), but his book seems less like a work of group authorship than the product of the synthesizing intelligence of Hofstadter himself. He wrote four chapters, ten prefaces, and the prologue and epilogue, and he shared authorship of six other chapters, leaving only one with a sole other author. Therefore Hofstadter’s theme of pattern finding as the key to human consciousness, intelligence, and creativity dominates the book and undergirds all the computer programs designed to imitate human thinking.
An early program that enabled Hofstadter to begin this process was called Seek-Whence because the program would seek whence a sequence of numbers originated. For example, it would investigate the sequence 1, 3, 6, 10, 15, 21, and so on. These are called “triangular numbers,” because the Pythagoreans classified the numbers according to the shapes made by arranging dots in sand, and these numbers correspond to triangularly arranged dots. This number sequence of triangular numbers thus constitutes a puzzle, and the computer program had to find its underlying rule. In this case the rule is that the nth number is the sum of the first n integers; for example, the fifth triangular number is 15, since 1 + 2 + 3 + 4 + 5 = 15. This may seem simple, but to get a machine to do it (and other number sequences) proved to be very difficult, since guessing a pattern from a short sequence is like trying to predict what sort of adult a child will eventually become. For both number sequences and children, a prodigious number of possibilities exist, so the program is designed to make guesses, but such risks sometimes result in failure.
Because the initial program resisted moving off the beaten track, he developed another that used such “aesthetic pressures” as simplicity, consistency, symmetry, and elegance to make sense of number-sequence patterns. In formal terms, the program solved number sequences by parallel processing with probabilistic biases. Though the developed Seek-Whence program was able to find patterns in some number sequences, it was unable to succeed in many others, since the ability to perceive a theme in novel sequences required the generation of unforeseen concepts.
Seek-Whence acquainted Hofstadter with the difficulties of artificially simulating basic cognitive processes, and in his next program, Jumbo, he carefully designed a restricted domain where only certain salient characteristics of human understanding would be modeled. The Jumbo program tried to imitate the particular human skills used in solving anagrams; that is, it attempted to construct potential English words out of a group of letters by putting them into plausible combinations. The program had no English dictionary; it was a construction program. It started with isolated units (the letters), gradually constructed chunks of letters, and then combined these chunks into various clusters, syllables, and words. The process is analogous to how complex molecules are constructed inside living cells. Hofstadter also compares Jumbo’s strategy to the way bonds of human friendship are formed in the social world. Random selection characterizes the artificial microworld of Jumbo just as it characterizes the natural macroworld of human life. Some letters are strongly attracted to each other (as with t and h), whereas others rarely interact (j and x). Like the way most people select potential mates on the basis of a small set of parameters, such as age, appearance, intelligence, and so forth, the Jumbo program encourages sensible groupings and discourages fatuous groupings.
The most important idea to emerge from the Jumbo project was the parallel terraced scan, which Hofstadter describes as an investigation of many possibilities simultaneously to different levels of depth where promising lines of inquiry are selected over unpromising ones. Can this scan be called intelligent? Hofstadter realizes that cognitive scientists constantly confront the danger of reading too much into their programs. Some researchers have made grandiose claims that they have programmed computers to write a novel in the style of contemporary best-sellers or that their computers have created analogies between such abstruse domains as thermodynamics and hydrodynamics. Yet to write a real novel, the computer would have to understand how people feel, think, talk, and interact, and it does not. To make a true analogy between heat flow through a metal bar and water flow through a pipe, the computer would have to grasp what water means in terms of human sense experience, and it does not. This tendency to overestimate computer results, especially when they are presented in human languages, is called the “Eliza effect,” after the program developed by Joseph Weizenbaum to play the role of a nondirective psychotherapist (à la Carl Rogers). The truly creative person sees what everyone else has seen and thinks what no one else has thought, but these computer programs are unable to take a fresh look at situations, since they are locked into a rigid categorical set of responses.
To avoid these difficulties, Hofstadter and Melanie Mitchell designed a computer program that seriously attempted to mimic human creativity. It was called Copycat, and it explored the nature of concepts and their interrelationships by solving letter-analogy problems. The program worked with linear strings of letters such as abc. A sample problem is the following: Suppose the letter-string abc were changed to abd; how would one change the letter string ijk in the same way? Most people would answer ijl, and the program does manage to find this solution, but it also presents a number of strange answers. Hofstadter believed that it was critical for the program to be allowed to follow risky pathways. The risk paid off in the program’s solution of the following letter-analogy problem: Suppose the letter-string abc were changed to abd, how would one change the letter-string xyz in the same way? The computer program came up with wyz, a clever response, since the role of d as the successor to c in an ascending sequence mirrors the role of w as the predecessor of x in a descending sequence. Copycat was able to discover previously unincluded concepts because it had parallel terraced scanning, so it could make comparisons at various levels of depth whose promise could be constantly evaluated.
Critics attacked the supposed creativity of Copycat because Hofstadter used such dangerously loaded terms as “concepts,” “discovery,” and “insight” in explaining his results. In less anthropomorphic terms, the program actually involved correspondences between letters and groups of letters, with randomness entering the mix in the interplay between one network, which modeled the letters and such relations as same, opposite, and successor, and another network, which assembled and disassembled structures. Any “discoveries” resulted from the randomness that provided subjects for a selective process, and this process, according to Hofstadter’s critics, was not conscious.
For these critics, cognition is such an enormously complex phenomenon that no computer system, however sophisticated, will ever achieve awareness. Hofstadter points out, however, that this criticism involves a double standard: one for machines, another for brains. He believes that his critics must agree that the human brain is composed of lifeless molecules carrying out numerous electrical and chemical reactions in utterly mechanical ways, yet consciousness does not vanish when one reduces a brain to these individual meaningless reactions. Those who doubt the materialistic basis of mind in the brain have only to think about the victims of certain types of brain trauma who are doomed to spend their lives without emotion.
Hofstadter rejects a radical division between consciousness and nonconsciousness; he believes that his computer programs might have a low level of consciousness. Like other cognitive scientists who reject a rigid distinction between mind and nonmind, he favors a continuum of consciousness from less to more mind. He is convinced that ultimately mind will be acquirable by machines, but the major questions are when, how much mind, and how do we do it? For Hofstadter, the brain’s special organization makes it conscious, and this enables it to have concepts and to be self-monitoring. Since the human mind can reflect upon itself, it can criticize its own actions. Though some critics believe that no machine will ever be able to do this, Hofstadter believes otherwise.
The final project extensively discussed by Hofstadter had its origin in his fascination from childhood with the shapes of letters. How does an artistic calligrapher develop an alphabetic style that is clever, logical, and graceful? To answer this question, Hofstadter designed a computer program with Gary McGraw to study the notion of artistic style among “stick letters” (allowing curves would have made the problem much too difficult). Their program, called Letter Spirit, was based on their belief that creativity is an automatic outcome of flexible and context-sensitive fluid concepts. Given one or a few seed letters representing the start of a style, the program, it was hoped, would create the rest of the alphabet in the same style. At the time of the book’s publication, the program was starting to be able to recognize letters, but it was still very far from being able to create any.
A basic question underlying Letter Spirit is what mechanisms account for the fluidity of human concepts. For example, people’s concept of the letter “a” is so general that they can recognize it in many styles, including some they have never experienced before. They can do this because their mind has somehow abstracted the idea of what it means to be an a from previous experience. Given an a, how would one make a b? Letter design, like music composition, is a highly sophisticated art that requires years of study and practice, and to design a machine that recognizes and creates alphabetic styles will, Hofstadter hopes, provide “an elegant window onto the workings of the mind.”
Computer programs such as Letter Spirit and Copycat have serious limitations, even in their restricted microdomains, and so it is surprising that Hofstadter makes such strong claims for them. He believes that these programs capture fundamental processes of creative intelligence. He even believes that emergent, unpredictable processing characteristic of his programs constitutes the computer’s making its own decisions. This concurs with his view that free will and creativity are closely related, and both depend on random mechanisms of the human brain and of the computer mimicking the brain. Yet precisely how does the brain relate to mind, the traditional source of perception, intelligence, decision making, and the sense of self? Does the conscious mind arise from such purely physical processes as the coordinated firing of electrochemical pulses among neurons in different parts of the brain, as Francis Crick and Christof Koch believe? Or does it derive from the quantum mechanical properties of atoms and molecules in the brain, as Roger Penrose argues? Or does it transcend the physical—is it what traditional thinkers would call the spiritual understanding of the soul? Hofstadter believes that if cognitive scientists are to answer these questions, they will have to pay close attention to fluid concepts and creative analogies, rather than try to create networks of artificial neurons.
The computer models that Hofstadter describes and analyzes present some possible mechanisms for human cognition, but it is much too early to tell whether these can be matched in any way to the complex functioning of such brain structures as neurotransmitters, synapses, dendrites, neurons, neural clusters, and so on. He admits that the underpinnings of human thinking may turn out to lie very far from biological or chemical principles and much closer to abstract organizational principles. Nevertheless, he is a cautious optimist about the possibility of discovering and imitating the hidden mechanics of thought.
In the course of his book, Hofstadter levels some telling criticisms against other computer programs purporting to mimic human thought. He made it a practice to look in the index of books describing these programs to see whether the terms “perception” and “concepts” were discussed; finding no entries for these terms, he realized the serious limitations of their studies of the basic mechanisms of thought. The thoughtful reader of Hofstadter’s book, however, will note that his index has no entries for “emotion” and “morality.” Yet emotions, particularly moral feelings, are very important for any full understanding of what it means to be human. Emotions are central even for rational thought, since they play a key role in learning, decision making, and creativity.
In a “Post Scriptum” at the end of the prologue, Hofstadter mentions that while he was in Italy writing this book, his young wife died shortly after undergoing an emergency brain operation. He states that his wife’s death forever shattered his “happy little bubble of a family,” which included two very young children whose lives have been “irreparably impoverished.” He concludes that “words cannot express my grief at this tragedy.” Yet the argument in the rest of the book readily leads the reader to interpret the thoughts and feelings of Hofstadter’s family as “random associations of subcognitive entities.” The cold finger of cognitive scientific reasoning certainly has a chilling effect when applied to emotionally moving human situations, and it also reveals the gulf that exists between the vision of what it means to be a human being created by cognitive scientists and the understanding of the human condition that has been developed by various humanists over the centuries.
Sources for Further Study
AI Magazine. XVI, Fall, 1995, p. 81.
BYTE. XX, March, 1995, p. 45.
Choice. XXXII, July, 1995, p. 1802.
Kirkus Reviews. LXIII, December 15, 1994, p. 1542.
Los Angeles Times. February 21, 1995, p. E5.
The New York Times Book Review. C, March 12, 1995, p. 11.
Sci Tech Book News. XIX, May, 1995, p. 2.
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