Essentially, Richard & others are replaying the same old problems of
computational explosions - see "computational complexity" in this history of
cog. sci. review - no?
Mechanical Mind
Gilbert Harman
Mind as Machine: A History of Cognitive Science. Margaret A. Boden. Two
volumes, xlviii + 1631 pp. Oxford University Press, 2006. $225.
The term cognitive science, which gained currency in the last half of the
20th century, is used to refer to the study of cognition-cognitive
structures and processes in the mind or brain, mostly in people rather than,
say, rats or insects. Cognitive science in this sense has reflected a
growing rejection of behaviorism in favor of the study of mind and "human
information processing." The field includes the study of thinking,
perception, emotion, creativity, language, consciousness and learning.
Sometimes it has involved writing (or at least thinking about) computer
programs that attempt to model mental processes or that provide tools such
as spreadsheets, theorem provers, mathematical-equation solvers and engines
for searching the Web. The programs might involve rules of inference or
"productions," "mental models," connectionist "neural" networks or other
sorts of parallel "constraint satisfaction" approaches. Cognitive science so
understood includes cognitive neuroscience, artificial intelligence (AI),
robotics and artificial life; conceptual, linguistic and moral development;
and learning in humans, other animals and machines.
click for full image and caption
Among those sometimes identifying themselves as cognitive scientists are
philosophers, computer scientists, psychologists, linguists, engineers,
biologists, medical researchers and mathematicians. Some individual
contributors to the field have had expertise in several of these more
traditional disciplines. An excellent example is the philosopher,
psychologist and computer scientist Margaret Boden, who founded the School
of Cognitive and Computing Sciences at the University of Sussex and is the
author of a number of books, including Artificial Intelligence and Natural
Man (1977) and The Creative Mind (1990). Boden has been active in cognitive
science pretty much from the start and has known many of the other central
participants.
In her latest book, the lively and interesting Mind as Machine: A History of
Cognitive Science, the relevant machine is usually a computer, and the
cognitive science is usually concerned with the sort of cognition that can
be exhibited by a computer. Boden does not discuss other aspects of the
subject, broadly conceived, such as the "principles and parameters" approach
in contemporary linguistics or the psychology of heuristics and biases.
Furthermore, she also puts to one side such mainstream developments in
computer science as data mining and statistical learning theory. In the
preface she characterizes the book as an essay expressing her view of
cognitive science as a whole, a "thumbnail sketch" meant to be "read entire"
rather than "dipped into."
It is fortunate that Mind as Machine is highly readable, particularly
because it contains 1,452 pages of text, divided into two very large
volumes. Because the references and indices (which fill an additional 179
pages) are at the end of the second volume, readers will need to have it on
hand as they make their way through the first. Given that together these
tomes weigh more than 7 pounds, this is not light reading!
Boden's goal, she says, is to show how cognitive scientists have tried to
find computational or informational answers to frequently asked questions
about the mind-"what it is, what it does, how it works, how it evolved, and
how it's even possible." How do our brains generate consciousness? Are
animals or newborn babies conscious? Can machines be conscious? If not, why
not? How is free will possible, or creativity? How are the brain and mind
different? What counts as a language?
The first five chapters present the historical background of the field,
delving into such topics as cybernetics and feedback, and discussing
important figures such as René Descartes, Immanuel Kant, Charles Babbage,
Alan Turing and John von Neumann, as well as Warren McCulloch and Walter
Pitts, who in 1943 cowrote a paper on propositional calculus, Turing
machines and neuronal synapses. Boden also goes into some detail about the
situation in psychology and biology during the transition from behaviorism
to cognitive science, which she characterizes as a revolution. The metaphor
she employs is that of cognitive scientists entering the "house of
Psychology," whose lodgers at the time included behaviorists, Freudians,
Gestalt psychologists, Piagetians, ethologists and personality theorists.
Chapter 6 introduces the founding personalities of cognitive science from
the 1950s. George A. Miller, the first information-theoretic psychologist,
wrote the widely cited paper "The Magical Number Seven, Plus or Minus Two,"
in which he reported that, as a channel for processing information, the
human mind is limited to about seven items at any given time; more
information than that can be taken in only if items are grouped as "chunks."
Jerome Bruner introduced a "New Look" in perception, taking it to be
proactive rather than reactive. In A Study of Thinking (1956), Bruner and
coauthors Jacqueline Goodnow and George Austin looked at the strategies
people use to learn new concepts. Richard Gregory argued that even systems
of artificial vision would be subject to visual illusions. Herbert Simon and
Allen Newell developed a computer program for proving logic theorems. And
Noam Chomsky provided a (very) partial generative grammar of English in
Syntactic Structures (1957).
Two important meetings occurred in 1956, one lasting two months at Dartmouth
and a shorter one at MIT. There was also a third meeting in 1958 in London.
Soon after that, Miller, Eugene Galanter and Karl Pribram published an
influential book, Plans and the Structure of Behavior (1960), and Bruner and
Miller started a Center for Cognitive Studies at Harvard. These events were
followed by anthologies, textbooks and journals. "Cognitive science was
truly on its way."
In the remainder of Boden's treatment, individual chapters offer
chronological accounts of particular aspects of the larger subject. So,
chapter 7 offers an extensive discussion of computational psychology as it
has evolved since 1960 in personality psychology, including emotion; in the
psychology of language; in how psychologists conceive of psychological
explanation; in the psychology of reasoning; in the psychology of vision;
and in attitudes toward nativism. The chapter then ends with an overview of
the field of computational psychology as a whole. Boden acknowledges that
"we're still a very long way from a plausible understanding of the mind's
architecture, never mind computer models of it," but she believes that the
advent of models of artificial intelligence has been extraordinarily
important for the development of psychology.
Chapter 8 discusses the very minor role of anthropology as the "missing," or
"unacknowledged," discipline of cognitive science. Here Boden touches on the
work of the relatively few anthropologists who do fit into cognitive
science.
Chapter 9, the last in volume 1, describes Noam Chomsky's early impact on
cognitive science, discussing his famous review of B. F. Skinner's book
Verbal Behavior, his characterization of a hierarchy of formal grammars, his
development of transformational generative grammar and his defense of
nativism and universal grammar. Boden notes that psychologists, including
Miller, lost interest in transformational grammar after realizing that the
relevant transformations were ways of characterizing linguistic structure
and not psychological operations.
As Boden mentions, many people, including me, raised objections in the 1960s
to Chomsky's so-called nativism-his view that certain principles of language
are innate to a language faculty. She seems unaware that Chomsky's reasons
for this view became clearer as time went on and formed the basis for the
current, standard principles-and-parameters view, which explains otherwise
obscure patterns of differences between languages.
Perhaps the heart of Boden's story is her account of the development of
artificial intelligence, broadly construed. There were two sorts of
artificial intelligence at the beginning: One treated beliefs and goals
using explicit languagelike "propositional" representations, whereas the
other-the connectionist approach-took beliefs and goals to be implicitly
represented in the distribution of excitation or connection strengths in a
neural network.
The proposition-based approach, outlined in chapter 10, initially developed
programs for proving theorems and playing board games. These were followed
by studies of planning, puzzle problem solving, and expert systems designed
to provide medical or other advice. Special programming languages were
devised, including LISP, PROLOG, PLANNER and CONNIVER. Systems were
developed for default reasoning: For instance, given that something is a
bird, assume it flies (in the absence of some reason to think it does not
fly); given that it is a penguin, assume it does not fly (in the absence of
some reason to think it does fly).
There were difficulties. One was "computational complexity"-almost all
methods that worked in small "toy" domains did not work for more realistic
cases, because of exponential explosions: Operating in even slightly more
complex domains took much longer and used many more resources. Another issue
was whether "frame" assumptions (such as that chess pieces remain in the
same position until captured or moved) should be built into the architecture
of the problem or should be stated explicitly. This became a pressing issue
in thinking about general commonsense reasoning: Is it even possible to
explicitly formulate all relevant frame assumptions?
On the other side was the connectionist neural-net approach, considered in
chapter 12, which seeks to model such psychological capacities as
perception, memory, creativity, language and learning, using interconnected
networks of simple units. Connectionism was especially concerned with
rapidly recognizing and classifying items given their observed
characteristics, without having to go through a long, complicated chain of
reasoning.
In the simplest case of a single artificial perceptron, several real-number
inputs represent the values of selected aspects of the observed scene, and
an output value (the activation of the perceptron in question), possibly 1
or 0, indicates yes or no. The perceptron takes a weighted sum of the input
values and outputs 1, or yes, if the sum is greater than some threshold
value; if not, the output is 0. Perceptrons can be arranged in feed-forward
networks, so that the output of the first layer goes to perceptrons in the
second layer, whose outputs are inputs to a third layer, and so on until a
decision is made by a final threshold unit. Given appropriate weights and
enough units, a three-layer network can approximate almost any desired way
of classifying inputs. Relevant weights do not need to be determined ahead
of time by the programmer. Instead, the network can be "trained" to give
desired outputs, by making small corrections when the network's response is
incorrect.
There are other kinds of connectionist networks. For example, in certain
sorts of recurrent networks, the activations of the units settle into a more
or less steady state.
Boden describes these developments in loving detail, along with bitter
disputes between proponents of proposition-based research and those who
favored the connectionist approach. The disagreements were fueled by abrupt
changes in U.S. government funding, which are noted in chapter 11. Much of
the government money available was provided in the expectation that
artificial intelligence would prove to be militarily useful. In the 1980s,
funders decided to switch their support from proposition-based artificial
intelligence to connectionism. They did so both because of perceived
stagnation in the proposition-based approach (mainly due to the difficulties
mentioned above), and because connectionism became more attractive with the
discovery (or rediscovery) of back-propagation algorithms for training
multilayer networks.
More recent developments are described in chapter 13. These include
virtual-reality systems, attempts to construct societies of artificial
agents that interact socially, and CYC-a project aimed at explicitly
representing enough of the commonsense background to enable an artificial
system to learn more by reading dictionaries, textbooks, encyclopedias and
newspapers. Chapter 14 is a rich account of computational and cognitive
neuroscience. Topics touched on include challenges to the computational
approach, theories of consciousness and philosophy of mind. In chapter 15,
Boden describes the origins of artificial life and then discusses
reaction-diffusion equations, self-replicating automata, evolutionary
networks, computational neuro-ethology (computational interpretation of the
neural mechanisms that underlie the behavior of an animal in its habitat)
and work on complex systems. Chapter 16 reviews philosophical thinking about
mind as machine. Is there a mind-body problem? If a robot simulation of a
person were developed, would it be conscious? Would it suffer from a
mind-body problem? Would it be alive? A very brief final chapter lists
promising areas for further research.
This is, as far as I know, the first full-scale history of cognitive
science. I am sure that knowledgeable readers may have various quibbles
about one or another aspect of this history (like my own objection above to
the discussion of Chomsky's work in linguistics). But I doubt that many, or
in fact any, readers will have the detailed firsthand knowledge that Boden
has of so much of cognitive science. Future histories of the subject will
have to build on this one.
Reviewer Information
Gilbert Harman is Stuart Professor of Philosophy at Princeton University,
where in the past he was chair of the Program in Cognitive Studies and
codirector of the Cognitive Science Laboratory. He is coauthor with Sanjeev
Kulkarni of Reliable Reasoning: Induction and Statistical Learning Theory
(The MIT Press, 2007).
Source: American Scientist
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9. Book Review: Young Minds in Social Worlds - Experience, Meaning, and
Posted by: "Robert Karl Stonjek" [EMAIL PROTECTED] r_karl_s
Tue Dec 11, 2007 3:03 am (PST)
Constructing Cognition
Ethan Remmel
Young Minds in Social Worlds: Experience, Meaning, and Memory. Katherine
Nelson. xiv + 315 pp. Harvard University Press, 2007. $49.95.
The two patron saints of the study of cognitive development (which involves
how thinking and knowledge change with age) are the Swiss psychologist Jean
Piaget and the Russian psychologist Lev Vygotsky. Both were born in 1896,
but Piaget lived and wrote into his 80s, whereas Vygotsky died of
tuberculosis at age 37. Both advocated forms of constructivism, the theory
that children actively construct knowledge, rather than being passively
molded by experience (as in behaviorism) or programmed by biology (as in
nativism). However, Piaget viewed cognitive development as a product of the
individual mind, achieved through observation and experimentation, whereas
Vygotsky viewed it as a social process, achieved through interaction with
more knowledgeable members of the culture.
Developmental psychologist Katherine Nelson is an apostle of the Vygotskian
approach, known as social constructivism. She is opposed to the currently
popular descendant of the Piagetian approach known as theory theory, which
holds that children construct causal conceptualizations of different domains
of knowledge ("folk theories") using the same cognitive processes that
scientists use to construct scientific theories (that is, children think
like little scientists).
Nelson contends that theory theorists such as Alison Gopnik commit the
psychologist's fallacy-attributing one's own thought processes to others-and
thereby forsake one of constructivism's central insights: that children's
cognition is qualitatively different from that of adults, not simply
quantitatively inferior. In other words, children don't just know less, they
think differently.
In her new book, Young Minds in Social Worlds, Nelson also argues that
computational theories of mind (based on the premise that the mind operates
like a computer) are inadequate, because the ultimate function of human
cognition is not to process abstract information, but to interpret
experience and share cultural meanings with others. She criticizes
evolutionary cognitive psychologists such as Steven Pinker and nativist
developmental psychologists such as Elizabeth Spelke for allegedly
overemphasizing genetic influences on development and underemphasizing the
importance of social and cultural influences. And Nelson draws on
developmental systems theory to describe development as a complex,
interactive, dynamic process in which cognitive structure gradually emerges,
rather than being built into the genes or copied from the environment.
The bulk of the book reviews cognitive and language development during the
first five years of life, seen from Nelson's theoretical perspective. Her
target audience appears to be other developmental psychologists, as she
refers to many theories and studies without giving much explanation for
readers not already familiar with them. Developmentalists, however, will not
learn much factual information because she presents no new research.
Instead, what they may gain is an appreciation of Nelson's theoretical
perspective on development, which she calls experiential (to emphasize the
importance of the child's individual experience).
Nelson suggests that a child's consciousness develops in levels that
correspond to the stages proposed by cognitive neuroscientist Merlin Donald
for the evolution of the human mind. Nelson presented this model in more
detail in Language in Cognitive Development (1996), so those who have read
that book will find it familiar.
In Young Minds in Social Worlds, the early chapters on cognitive development
in the infant and toddler ages are uncontroversial and, frankly,
unmemorable. The middle chapters on the acquisition of language and symbols
are much more interesting, perhaps because here Nelson can draw more on her
own research. She is critical of current theories about word learning that
assume that children have the same conceptual structures as adults and
simply need to map the words that they hear onto the concepts that they
already have. Nelson argues convincingly that children gradually construct
concepts through linguistic interaction. In other words, children do not
simply match labels to pre-existing categories, but rather use linguistic
cues to bring their conceptual boundaries in line with those shared by their
linguistic community.
A corollary of this position is that production may sometimes precede
comprehension (a reversal of the usually assumed sequence): Children may
imitate the use of a word in a particular context and only gradually acquire
a context-independent understanding of the meaning of the word. In Nelson's
view, which is indebted to the psycholinguist Dan Slobin, language is less
than a necessary ingredient for thought itself (that is, nonlinguistic
thought is possible), but more than a neutral vehicle for the expression of
thought. Language is needed for sharing thoughts, and those thoughts are
inevitably shaped by the particular language used.
Nelson raises the interesting question of why children seem to understand
symbolic representations (for example, words, which do not resemble their
referents-onomatopoeia excepted) before they understand iconic
representations (for example, scale models, which do resemble their
referents), even though the former relation, being arbitrary, would seem
harder to comprehend. Although elsewhere she criticizes nativist
explanations ("it's built in"), here she suggests that perhaps humans have a
specific evolved capacity to understand symbols but must learn to interpret
icons. Perhaps, but I think it's more likely that icons are challenging
because, as Judy DeLoache has observed, they have a dual nature, being both
representations and objects in their own right-for example, a scale model
can be interpreted as a toy. This conflict creates greater demands on
executive functions than words do, because words have no meaning except as
representations.
Nelson stumbles a few times in the later chapters on cognitive development
in preschoolers. She writes that "young children tend to remember the gist
of a complex situation and lose track of details." But in fact, research
based on Charles Brainerd and Valerie Reyna's fuzzy-trace theory finds
exactly the opposite: Children rely more on memory for verbatim details, and
adults rely more on memory for gist. For example, when asked to remember a
list of words that cluster around a theme, adults are more likely to
erroneously include a word that is semantically related to the words
supplied, whereas children are more likely to incorrectly include a word
that rhymes with a word actually presented.
Nelson criticizes research on children's theory of mind (their understanding
of mental states) for overemphasizing one particular development during the
preschool years: understanding of beliefs (that people can believe different
things, including things that are false). But Nelson then does the same
thing herself-saying, for example, that "competence in representational
language is essential for entering the community of minds (and for solving
theory of mind problems)." Nelson means that the maturation of
representational language during the preschool years enables children to
understand beliefs. However, she neglects the fact that children solve some
other theory-of-mind problems much earlier. For example, 18-month-olds
understand desires (that people want different things).
Nelson also argues that children's understanding of mind is not based on
some sort of underlying theory, because "nothing guarantees that one person
can correctly interpret another." But her argument misses the mark, because
nobody claims that theories are guaranteed to produce correct
interpretations. If theories did, science would be a lot easier! And despite
her antipathy toward theory theory, she writes that "children's questions
indicate that they are mentally instigating investigations of the causal
structure of aspects of the world, both psychological and physical." That
sure sounds to me like they're theorizing.
Nelson concludes by maintaining that cognitive development is not a process
of individual internalizing of objective knowledge, but rather is a
collaborative interpretation of subjective experience. However, she eschews
the solipsism of postmodern relativism. She sometimes presents the obvious
as profound, in such statements as "this view reflects the position that
cognitive processes are an integral part of memory itself" and "this view
resolves the issue of why thinking in a different language is different from
thinking in a first language; it is different because the languages are
different." She aims for a pragmatic and balanced account of development,
which unfortunately sometimes feels vague and bland. She may be right, but
her book is less fun to read than those of more provocative writers such as
Steven Pinker. For a more engaging exposition of a similar sociocultural
perspective, I recommend two books by Michael Tomasello: The Cultural
Origins of Human Cognition (1999) and Constructing a Language: A Usage-Based
Theory of Language Acquisition (2003).
Reviewer Information
Ethan Remmel is a cognitive developmental psychologist at Western Washington
University in Bellingham. His research focus is the relationship between
language experience and children's understanding of the mind.
Source: American Scientist
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10. Book review: Language, Consciousness, Culture - Essays on Mental Str
Posted by: "Robert Karl Stonjek" [EMAIL PROTECTED] r_karl_s
Tue Dec 11, 2007 3:04 am (PST)
The Functionalist's Dilemma
George Lakoff
Language, Consciousness, Culture: Essays on Mental Structure. Ray
Jackendoff. xxvi + 403 pp. The MIT Press, 2007. $36.
Science, as Thomas Kuhn famously observed, does not progress linearly. Old
paradigms remain as new ones begin to supplant them. And science is very
much a product of the times.
The symbol-manipulation paradigm for the mind spread like wildfire in the
late 1950s. Formal logic in the tradition of Bertrand Russell dominated
Anglo-American philosophy, with W. V. O. Quine as the dominant figure in
America. Formalism reigned in mathematics, fueled by the Bourbaki tradition
in France. Great excitement was generated by the Church-Turing thesis that
Turing machines, formal logic, recursive functions and Emil Post's formal
languages are equivalent. The question naturally arose: Could thought be
characterized as a symbol-manipulation system?
The idea of artificial intelligence developed out of an attempt to answer
that question, as did the information-processing approach to cognitive
psychology of the 1960s. The mind was seen as computer software, with the
brain as hardware. The software was what mattered. Any hardware would do: a
digital computer or the brain, which was called wetware and seen
(incorrectly) as a general-purpose processor. The corresponding philosophy
of mind, called functionalism, claimed that you could adequately study the
mind independently of the brain by focusing on the mind's functions as
carried out by the manipulation of abstract symbols.
The time was ripe for Noam Chomsky to adapt the symbol-manipulation paradigm
to linguistics. Chomsky's metaphor was simple: A sentence was a string of
symbols. A language was a set of such strings. A grammar was a set of
recursive procedures for generating such sets. Language was
syntacticized-placed mathematically within a Post system, with abstract
symbols manipulated in algorithmic fashion by precise formal rules. Because
the rules could not look outside the system, language had to be
"autonomous"-independent of the rest of the mind. Meaning and communication
could play no role in the structure of language. The brain was irrelevant.
This approach was called generative linguistics, and it continues to have
adherents in many linguistics departments in the United States.
In the mid-1970s, another paradigm shift occurred. Neuroscience burst onto
the intellectual stage. Cognitive science expanded beyond formalist
cognitive psychology to include neural models. And cognitive linguistics
emerged, whose proponents (including me) see language and thought not as an
abstract symbol-manipulation system but as physically embodied and
reflecting both the specific properties and the limitations of our brains
and bodies. Cognitive linguistics has been steadily developing into a
rigorously formulated neural theory of language based on neural-computation
theory and actual developments in neuroscience.
Ray Jackendoff's new book, Language, Consciousness, Culture, is set solidly
within the old generative-linguistics paradigm. In it, Jackendoff staunchly
defends functionalism and the symbol-manipulation paradigm. "Some
neuroscientists say we are beyond this stage of inquiry, that we don't need
to talk about 'symbols in the head' anymore. I firmly disagree," he notes.
He goes on to argue that the symbolic representations given by linguists are
simply right, and he takes the brain to be irrelevant. Interestingly, he
does not cite the major work arguing the opposite, Jerome Feldman's 2006
book, From Molecule to Metaphor. Feldman shows how the analyses of language
and thought done by cognitive linguists can be characterized in terms of
neural computation. But, as Jackendoff says, "Cognitive Grammarians . . .
have been steadfastly ignored by mainstream generative linguistics." Just as
Kuhn would have predicted.
All this creates a dilemma for Jackendoff. He sees the limitations of the
functionalist paradigm and rails correctly against Chomsky's
syntacticization of meaning, but he stays with a version of symbolic logic,
in which meaning is also syntacticized by a formal logical syntax.
Jackendoff has read widely in cognitive science and neuroscience, while
"steadfastly ignoring" the literature of cognitive and neural theories of
language, which answers many of the questions he raises, although in a
paradigm he refuses to consider. He sees correctly that the cognitive and
brain sciences ought to be taken seriously by philosophers and social
scientists, but his forays into social, moral and political ideas are
limited by his functionalist approach.
Take the question of meaning. In 1963, I proposed a theory of generative
semantics in which a version of formal logic became an input to generative
grammars. I was later joined in this enterprise by James D. McCawley and
John Robert Ross, two of Chomsky's best-known students. Among our tenets
were that conceptual structure is generative, that it is prior to and
independent of language, and that it is inaccessible to consciousness.
Jackendoff argued strongly against this position at the time, but in this
book, only 40 years later, he accepts these tenets, while keeping Chomsky's
idea that syntactic structure is independent of meaning. Jackendoff adopts a
parallel-structure theory in which he holds both ideas at once. As we did
then, he now declares that Chomsky's syntactocentrism is a "scientific
mistake." Yet, as a Chomskyan syntactician, he has to keep a version of the
"scientific mistake"-an autonomous syntax for grammar alongside his
autonomous syntax for meaning (a kind of symbolic logic).
In the 1960s, Charles J. Fillmore proposed a theory of "case grammar" in
which there were semantic roles (agent, patient, experiencer and so on) and
principles mapping these roles to grammar. This idea was accepted in
cognitive linguistics and has been developed over the past 40 years by
Fillmore and many others in the theory of grammatical constructions, in
which semantics is directly paired with syntactic form. Jackendoff adopts a
version of this theory without mentioning Fillmore. Laudable, if a little
late.
In 1975, Fillmore began the development of "frame semantics," expanding the
notion in great detail over the next three decades. Conceptual framing has
become central in cognitive linguistics worldwide and is widely applied, as
in my work on political analysis over the past decade. Jackendoff accepts a
much less precise and less worked-out version of frames set forth by Erving
Goffman and Marvin Minsky in the mid-1970s, but he "steadfastly ignores"
Fillmore's elaborate research and its widespread application.
In 1997, Srini Narayanan, in his dissertation at the University of
California, Berkeley, worked out a neural computational account of actions
and events, which generalizes to the semantics of aspect (event structure)
in linguistics and actually computes the logic of aspect. In Language,
Consciousness, Culture, Jackendoff tries to adapt Chomsky's syntactic
structures to action structure, which Patricia Greenfield of UCLA first
attempted in the 1960s. Jackendoff's account, coming a decade after
Narayanan's, doesn't characterize actions nearly as well, does not compute
the logic of actions, does not characterize the semantics of aspect and does
not fit the theory of neural computation. But it is gratifying to see
Jackendoff trying to link motor actions to linguistics (as Chomsky never
would), in an attempt to break out of the functionalist mold without leaving
it.
Jackendoff is asking questions well beyond the Chomskyan enterprise, and in
some cases he approaches what cognitive linguists have achieved. But one
place he gets it very wrong is conceptual metaphor.
Mark Johnson and I wrote Metaphors We Live By (1980) almost three decades
ago. Since then hundreds of researchers have developed a whole field of
study around the subject. In our 1999 book Philosophy in the Flesh, Johnson
and I elaborated in great detail on Narayanan's neural computational theory
of metaphor.
In the neural theory, conceptual metaphor arises in childhood when
experiences regularly occur together, activating different brain regions.
Activation repeatedly spreads along neural pathways, progressively
strengthening synapses in pathways between those brain regions until new
circuitry is formed linking them. The new circuitry physically constitutes
the metaphor, carrying out a neural mapping between frame circuitry in the
regions and permitting new inferences. The conceptual metaphor MORE IS UP
(as in "prices rose," "the temperature fell") is learned because brain
regions for quantity and verticality are both activated whenever you pour
liquid into a glass or build any pile. AFFECTION IS WARMTH (as in "She's a
warm person," or "She's an ice queen") because when you are held
affectionately as a child by your parents, you feel physical warmth.
Hundreds of such primary metaphors are learned early in life. Complex
metaphors are formed by neural bindings of these primary metaphors. And
metaphorical language expresses both primary and complex metaphors.
Because we first experience governance within the family, one widespread
primary metaphor is A GOVERNING INSTITUTION IS A FAMILY, with authority
based on parental authority. Within the literal Family Frame, rights and
obligations arise from what is allowed and required, given the desires and
responsibilities of parents and children. Children want to be fed and taken
care of, and parents are required to provide for them. Children have other
desires that may be allowed or forbidden. Parents may require certain things
of children.
Under the metaphor A GOVERNING INSTITUTION IS A FAMILY, what is required by
an authority is called an obligation, and what is allowed or has to be
provided by an authority is called a right. The metaphor applies at various
levels, so there are higher governing institutions, such as societies,
nature or the universe, and metaphorical authorities, such as social or
moral norms, natural laws and God. At each level, the logic of family-based
authority is metaphorically duplicated for rights and obligations, with
authorities at a lower level subjected to authority at a higher level. No
special metaphors unique to rights and obligations are needed. Other
independently existing primary metaphors flesh out the complexities: Because
ACHIEVING A DESIRED PURPOSE IS GETTING A DESIRED OBJECT, rights are seen as
metaphorical possessions, which can be given to you, held onto or lost.
Because requirements can be difficult and DIFFICULTIES ARE BURDENS, we speak
of "taking on" or "undertaking" obligations.
You would never know any of this from reading Jackendoff's brief discussion
of whether rights and obligations are understood metaphorically. He reaches
the conclusion he has to reach: that no conceptual metaphor at all is used
in understanding rights and obligations. This is not surprising, because
typically he has largely ignored the cognitive linguistics literature.
Had the discussion of rights and obligations in Language, Consciousness,
Culture appeared in the late 1960s, it would have been seen as excellent.
But coming out nearly 40 years later, it is inadequate, because it fails to
explain why we reason about rights and obligations as we do, both in the
West and elsewhere in the world. The neural-metaphorical understanding gives
a correct account of the data plus an explanation grounded in biology. Such
explanations are lacking throughout the book because Jackendoff still holds
to functionalism.
For a cognitive linguist like myself, reading Jackendoff's book is both
painful and hopeful-painful because he keeps trying to do interesting and
important intellectual work while being stuck in a paradigm that won't allow
it, and hopeful because he may help the transition from a brain-ignoring
symbol-manipulation paradigm to a brain-based neural theory of thought and
language. I wish that other linguists, both generative and cognitive, had
his scope and intellectual ambition.
Reviewer Information
George Lakoff is Richard and Rhoda Goldman Distinguished Professor of
Cognitive Science and Linguistics at the University of California, Berkeley,
and Senior Fellow at the Rockridge Institute. His recent books include Moral
Politics (University of Chicago Press, 1996 and 2002), Don't Think of an
Elephant! (Chelsea Green Publishing, 2004), Whose Freedom? (Picador, 2006),
and Thinking Points (Farrar, Straus & Giroux, 2006), with the Rockridge
Institute. The Political Mind will appear from Viking/Penguin in 2008.
Source: American Scientist
http://www.americanscientist.org/BookReviewTypeDetail/assetid/56419
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Robert Karl Stonjek
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11a. Book Review: The First Word - The Search for the Origins of Language
Posted by: "Robert Karl Stonjek" [EMAIL PROTECTED] r_karl_s
Tue Dec 11, 2007 3:04 am (PST)
Not the Last Word
Michael C. Corballis
The First Word: The Search for the Origins of Language. Christine Kenneally.
x + 357 pp. Viking, 2007. $26.95.
In 1866, the Linguistic Society of Paris famously banned all discussion of
the origins of language. The London Philological Society followed suit in
1872. Speculation about the evolution of language remained stifled for a
century, and it was only in the 1970s that muted discussion began to emerge,
often with an air of apology. Eventually, though, the floodgates opened, and
the past two decades have seen a deluge of articles, books and conferences
on the topic. The current state of the field is largely one of chaos, to the
point that some observers might be tempted to think the ban should be
reinstated. Most agree that language is in essence uniquely human, so that
evidence as to its evolution remains indirect, and speculation can run wild.
Nevertheless, recent advances in genetics, archeology, neurophysiology and
computer modeling have provided powerful if sometimes conflicting leads.
Christine Kenneally reviews the current state of the field in her new book.
An experienced science journalist with a Ph.D. in linguistics, she is well
qualified for the task. The focal point for her discussion is a high-profile
symposium on the evolution of language held in 2005 at Stony Brook, New
York, where many of the leading players met and gave talks, but her reading
and interviews range more widely. The First Word is almost certainly not the
last word, but it does provide a lucid, readable, comprehensive account of
the different ideas that are now current.
One figure who continues to exert a major if not always benign influence is
Noam Chomsky, the dominant linguist of the past half-century, who made a
rare appearance at the symposium. It might be said that Chomsky actually
helped prolong the ban, because he has long argued that one simply cannot
know how language evolved and has even suggested that language may not be
the product of natural selection. This position was first explicitly
questioned by Steven Pinker and Paul Bloom (who were not present at the
symposium but are appropriately included in Kenneally's story) in a classic
article published in 1990, in which they retained much of the Chomskyan
stance but made a strong case for the incremental evolution of language
through natural selection. Much of the subsequent development has been in
more direct opposition to Chomsky and seems set to redefine the nature of
language itself. As the book relates, Chomsky appeared at the symposium only
to give a public address, which I and many of the others in attendance found
largely incomprehensible; he arrived and departed without engaging with any
of the other speakers.
Chomsky first achieved prominence with his 1957 book Syntactic Structures,
which argued that syntax could not be explained in terms of associations.
However, theorists such as Simon Kirby and Morten Christiansen have made
considerable progress toward developing connectionist theories; language may
after all depend on learning principles, and not on some innate
language-acquisition device. Sue Savage-Rumbaugh is accorded her rightful
place as a pioneer in the effort to discover the linguistic abilities of
apes, but the notion of a continuity between ape language and human language
remains implacably opposed by those who retain at least vestiges of
Chomskyan theory, a group that includes Steven Pinker, Ray Jackendoff and
Derek Bickerton.
Kenneally also describes the idiosyncratic work of Luc Steels, who has
established artificial robot-inhabited worlds in which languagelike
structures arise spontaneously. As Jim Hurford, another prominent
symposiast, remarked, we may be witnessing the demise of the Chomskyan
notion of universal grammar, the supposedly innate structure, unique to
humans and peculiar to language itself, that is said to underlie all
languages. Instead, language may depend on more general cognitive abilities.
One complaint I have is that most of the experts discussed in the book seem
to equate language with speech. (Kenneally herself writes that speech "is
crucial to language.") A partial exception is Michael Arbib, who grounds
language evolution in manual gestures, building a scenario in which an
intermediate form of communication, which he calls proto-sign, forms the
scaffold for the incorporation of vocalization in an ascending spiral toward
full syntactic speech. Arbib draws on so-called mirror neurons, first
discovered in the monkey brain, which respond both when the subject makes
grasping movements and when it observes the same movements made by others.
These neurons are found in areas homologous to speech areas in the human
brain and seem to provide a natural platform for the evolution of language.
Mirror neurons, though, may be an overworked commodity in modern
evolutionary and cognitive theory, providing convenient explanations for
anything from language to imitation to theory of mind.
Yet language can consist of a combination of hand gestures and facial
expressions rather than vocalizations. Even Arbib appears not to recognize
that signed languages are indeed true languages; he seemingly confuses them
with pantomime. My own view, which I presented at the symposium and which is
mentioned in the book, is in fact similar to Arbib's but allows that
language might well have evolved as a sophisticated form of ritualized and
grammaticalized gesture before the eventual takeover by vocalization; even
now manual gestures are woven into our speech. Arbib is quoted as saying
"It's hard to build up a rich tradition just through gesture," but a visit
to Gallaudet University in Washington, D.C., where the language of
instruction is American Sign Language, might persuade him otherwise. Missing
from The First Word are sign-language experts such as Ursula Bellugi, Karen
Emmorey, David F. Armstrong, Sherman Wilcox and the late William C. Stokoe.
Given the book's breadth of coverage, such an omission is all the more
surprising. But that is perhaps a minor quibble. Kenneally's dilemma is
that, although she found herself excited by the ideas she encountered, many
of them are mutually incompatible, so no clear pattern emerges.Nevertheless,
she writes in an engaging, chatty style, and readers will gain a broad
understanding of what language is about and how it might have evolved. She
ends in a rather gimmicky fashion by asking various researchers their
opinion as to whether and how language would evolve in a boatload of babies
shipwrecked on the Galápagos Islands but provided with the sustenance to
survive and thrive. My response? They might well develop language, but
they'd surely all have different theories as to how it happened.
Reviewer Information
Michael C. Corballis is professor of psychology at the University of
Auckland and is the author of, among other books, From Hand to Mouth: The
Origins of Language (Princeton University Press, 2002) and The Lopsided Ape:
Evolution of the Generative Mind (Oxford University Press, 1991).
Source: American Scientist
http://www.americanscientist.org/BookReviewTypeDetail/assetid/56421
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