a linguistics research paper
TRANSCRIPT
Drawn into the Fray 1
Running head: DRAWN INTO THE FRAY
Drawn into the Fray of Scientific Battle:
Computational Theory, Modularity in the Mind, and Scientific Inquiry
11 April 2023
Darin L. Hammond
Idaho State University
Drawn into the Fray 2
Table of Contents
Introduction and
Methodology...................................................................................................................
3
Genesis of the Computational
Model.........................................................................................................
4
Chomsky’s Generative Grammar: A First
Step...........................................................................
5
Deconstructing Behaviorist Models of
Language.........................................................
5
Towards a Universal
Grammar........................................................................................
5
Generative Building
Blocks...............................................................................................
6
Language
Innateness..........................................................................................................
7
The Cognitive Machinery of Language: Generative Grammar and Binary
Code....
8
Fast Forward to Computation and Modularity in Cognition: Fodor and
Pinker................................
9
Cognitive
Computation...................................................................................................................
10
Cognitive
Modularity.......................................................................................................................
11
Pinker Versus Fodor Round One--The Basics of
Modularity..................................................
12
Pinker Versus Fodor Round Two—Homunculi and
Demons................................................
19
Pinker Versus Fodor Final Round—Hunger and 20
Drawn into the Fray 3
Thirst...........................................................
Discussion: Assessing the Debate, Entering the Fray as a New
Researcher........................................
21
Conclusions: The Way
Forward..................................................................................................................
24.
References...........................................................................................................................
............................
25
List of Illustrations
Figure
1...........................................................................................................................................
.................
9
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Introduction and Methodology
I suspect that most teachers in public schools and community colleges
are like me and were not aware that there has been a cognitive revolution.
However, beginning with Noam Chomsky’s(1957;1959;1965) refutation of
Skinner’s 1957 explication of the behaviorist view of language acquisition
and then his publications in the 1950’s and ‘60’s the world of cognition
began to open up as a relative domain of knowledge, proliferating more
specific disciplines that focused more narrowly on interrelated but distinct
studies of mental processes. New departments were popping up on
campuses across the United States and Europe, thriving upon Chomsky’s
having opened up the black treasure box of the brain, at least as far as
language is an entry point into the workings of the mind. He broke
language apart and put the pieces back together again, analyzing how they
separated and then came back together, meticulously studying and
observing language as the means of acquiring empirical data,
hypothesizing, and experimenting. With the means provided by his
concepts of generative and universal grammar, scientists had the tools, the
binary code of sorts, that would help others put together the theories of the
computational and modular mind.
The present study asks several critical questions as a means of
assessing the current status of computational and modular models. How did
theorists first make the leap from Chomsky’s generative and universal
grammar to computational and modular mind? What are the different
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debates that researchers are arguing and grappling with and where will
they go from there?
Through a close review of several key authors in the fields of syntax,
psycholinguistics, cognitive science, and evolutionary psychology, this study
illustrates that generative and universal grammar were key in the genesis of
the cognitive sciences because 1) the grammars provide an entry point into
the brain through an examination of language processing and production, 2)
the grammars predict an inheritable system of modules that innately
prepare the brain to acquire a language, and 3) the grammars led to the x’
bar which clearly demonstrated how, with discrete pieces in the lexicon,
humans produce and combine phrase structures with infinite variety and
that an infinite variety of grammatical sentences can be parsed and
processed by another speaker of the language. These discrete pieces
helped scientists to conceive the brain thinking and processing as a
machine or computer might, though by analogy only rather than literally.
The current status of the field of study is an environment of heated debate
and relative stagnation compared to preceding decades. The debate is how
the mind operates using modules that are specific to certain functions. In
the conclusion, I suggest that while the arguing is frustrating at times, the
independent and courageous voices within the sciences who resist easy
answers and push other thinkers to analyze their own assumptions are
essential to the progress of sciences in general, and modularity in the mind
specifically. The path for the future is to follow the unique voices within the
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sciences while actively questioning the veracity of our own assumptions and
those of other scholars. Given the current, immature status of these
cognitive sciences, I speculate that the individual, specialized disciplines
will remain un-integrated with the whole (the cognitive sciences
collectively) until they gain a firm grasp on their narrow scope and as
theorists continue to contest competing models of computation and
modularity. So, fields like L2 acquisition and eye tracking that have not yet
influenced one another significantly will do so more as the fields mature. I
judge this to be healthy for new fields of study.
Genesis of the Computational Model
For a new theory to take hold in linguistics or any other science, a
scholar must first create a need for new explanations based upon the
inadequacies of the current models. When Noam Chomsky began publishing
in the field of syntax, B.F. Skinner’s behaviorist model of language was in
the spotlight, a natural extension from his studies in operant conditioning
with pigeons. Skinner’s behaviorist view popularity gained prominence
because it was so intuitive, and his ideas breathed life into a stagnating
discipline that had no place to go since Saussure’s arbitrary signs demoted
linguistics from a science to a pseudo-empirical investigation of the
subjective nature of language. Skinner’s ideas were tangible and provided
a simple explanation of language that could be tested empirically. While
Chomsky was not the only linguist to attack Skinner, he was the most
effective in large part because he had an alternative. His transformational
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grammar not only filled the void left after blowing Skinner out of the water,
it described the complexity of human language, a complexity that mocked
Skinner’s simple behaviorist explanation.
Chomsky’s Generative Grammar: A First Step
Deconstructing behaviorist models of language.
In 1957, Chomsky wrote a scathing review of B. F. Skinner’s (1992,
1957) most important work on language, Verbal Behavior. In his short
review Chomsky (2008) dismantled Skinner’s argument deftly, labeling the
idea of language “through reinforcement ... quite empty” (p. 12), and then
expounded his critique into book length two years later (Chomsky, 1959).
The importance of Chomsky’s (1957) review work was to create room for
the more impressive Syntactic Structures published the same year as
Skinner’s work. His transformational and generative grammar was the real
crushing blow for the behaviorists because this new model accounted so
well for the complexity of human language. Chomsky’s work in the late
1950’s established the transformational mechanisms that could manipulate
words, phrases, and clauses into an indefinite number of structures that a
normal speaker can both produce and process. The theoretical implications
of this transformational system laid the foundation for Chomsky (1965) to
elaborate his ideas of generative and universal grammars, especially in
Aspects of the Theory of Syntax.
Towards a universal grammar.
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While the three terms are used interchangeably, they differ in
connotations—transformational emphasizing the syntactic operations,
generative stressing the infinite nature of the language possibilities, and
universal emphasizing the (attempted) cross-language description of
language structures. The latter two are recent additions to linguistic
terminology (Generative Grammar, 2000), but universal (or philosophical)
grammar is a concept that goes as far back as 1751, referring to the same
basic idea of creating “a scheme of classification capable of including all the
grammatical categories recognized in actual languages” (Universal
Grammar, 2000). Breaking the syntax of language into finite, fundamental
units allowed Chomsky to push closer to an understanding of how language
might work in the human mind. He hoped that this would lead to the ever
illusive universal grammar (UG), representing the rules of structure that
connect all human languages. In returning to the idea of a UG, Chomsky
(2006) built upon the long forgotten foundation of the concept in the
“rationalist philosophy of language [which] merged with various other
independent developments in the seventeenth century, leading to the first
really significant general theory of linguistic structure” (p. 12). The concept
of a UG suggests a link to L2 acquisition as a common ground in languages
across cultures should inform the way teach grammar to both L1 and L2
learners. UG provides hope in pointing to commonality between languages
and cultures across the globe.
Generative building blocks.
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Chomsky still strives describe and understand the UG (now through
minimalism) provides a backdrop to the current study though an in-depth
discussion is beyond the scope of the current research. The generative
aspect of Chomsky’s grammar represents a more explicit precursor to
current computational models of the mind. Prior to Chomsky, no theory had
been able to account for the generative and creative nature of language
(especially not the behaviorism), but in the combinatorial transformations of
discrete language units, Chomsky could parse a sentence into its smallest
components, illustrating cognitive manipulations that had power to build
utterances all the way from the phonological to the syntactic and semantic
levels. Chomsky’s (1965) definition clarifies this:
By a generative grammar I mean simply a system of rules that in some
explicit and well-defined way assigns structural descriptions to
sentences. Obviously, every speaker of a language has mastered and
internalized a generative grammar that expresses his knowledge of
his language. This is not to say that he is aware of the rules of the
grammar or even that he can become aware of them, or that his
statements about his intuitive knowledge of the language are
necessarily accurate. (p. 8)
The system of rules describe the structure of sentences that, on the
syntactic level of noun phrases, verb phrases, and clauses, form the surface
structure of an utterance and correspond to a deep structure that comes
closer to the mental representation of the components. Chomsky hints here
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at powerful abstractions that have become some of his most important and
productive concepts.
Language innateness.
The definition of generative grammar above entails that humans are
born with the cognitive machinery of language in place to a certain extent,
suggesting that “every speaker of a language has mastered and internalized
... his intuitive knowledge of the language” (Chomsky, 1965, p. 12). The
innateness of language accounts for the insufficient input feeding the
behaviorist model. Chomsky (2006) breathes new life into Descartes’
concept of innate ideas stating, against strong opposition in some factions
of the linguistic community that “there are certain innate conditions on the
form of grammar that determine what constitutes linguistic experience and
what knowledge will arise on the basis of this experience” (p. 159). The
power in this model lies in the fact that establishes an intimate relationship
between hidden cognition and tangible grammar. In other words,
innateness suggests that by understanding the nature of generative
grammar, linguists can begin to comprehend the workings of the mind.
This grammar to brain connection revolutionized linguistics, but equally
important, Chomsky gave birth to a multiplicity of completely new scientific
disciplines that now held a conceptual link to the human brain:
psycholinguistics, cognitive science, nuerolinguistics, nuerophilosophy,
computer science, artificial intelligence, etc. The generative ability of
language innateness to broaden the scope of science so productively
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provides a proof of generative grammar. Few theorists have so positively
affected a human science as Chomsky.
The cognitive machinery of language: generative grammar and binary
code.
With the mind-language connection established, another feature of
generative grammar accelerated an understanding of cognition. Since
linguists could breakdown utterances from the surface structure of syntax
down through phonology, they began to think about language in unique and
productive ways. Looking at grammar through the generative lens made
the pieces look more like code that could be manipulated by the human
brain and by a computer. By analogy, researchers began to think of the
processes of the human mind as a subject for empirical observation and
analysis. This was shocking to the scientific climate of psychology as Barrett
and Kurzban (2006) capture saying:
Prior to the cognitive revolution of the 1960’s, it was popular to view
the mind as a kind of black box and to view conjectures about its
contents as unscientific. The cognitive revolution reversed this
climate, rendering the search the contents of the black box—a
description of its internal structure that could account for the
systematic relationships between information inputs and behavioral
outputs—a key scientific objective of psychologists. (p. 628)
The cognitive revolution initiated by Chomsky began to morph the metaphor
of the black box into the white box of a computer monitor, the brain
XP
Specifier XFigure 1: A representation of the basic, repeatable pattern of Jackendoff’s (1977) x’ theory of phrase structure where x corresponds to a lexical entry such as a noun, verb, or adjective (I created this graphic).
Drawn into the Fray 12
becoming increasingly understandable as linguistics, the new cognitive and
nuero-sciences, biology, and medicine converged on the common target of
the mind. And, the computer metaphor actually became the new framework
for thinking about the mind.
Fast Forward to Computation and Modularity in Cognition: Fodor and
Pinker
Here my account shifts from Chomsky to several threads that extend
from his ground breaking theoretical work, a necessarily abridged account
as the field quickly became crowded with
researchers following his lead. Historically,
Chomsky shifted as well, moving to language in
the realm of politics and ideologies while still
keeping his finger linguistics (most recently with
minimalism). In the realm of syntax, Ray
Jackendoff (1977) clarified and simplified
Chomsky’s generative/transformational grammar
with the x-bar theory that mapped phrase structure with artistic simplicity
in his seminal X’ Syntax : A Study of Phrase Structure (see figure 1). The
sleekness of the basic phrase structure theory assisted those who were
beginning to see the mind at work in combining finite elements to create
infinite unique utterances. Jackendoff’s x’ theory certainly meets Chomsky’s
(1965) standard “to generate an indefinitely large number of structures”
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(pp. 15, 16). The small phrases are easy to manipulate, and the x’ theory
allows for movements such as the “wh” trace. The structure also allows
embedded and relative clauses as well as clauses joined by conjunctions. As
the smallest unit in the grammar moves all the way down to phrases, one
can visualize the relative ease in producing and processing the chunks that
fit together hierarchically which moves the language closer to the language
of computation and computers, the bits of data being combined by a
language user in an infinite variety of ways. Also, Chomsky (1965) and
Jackendoff (1977)both point to the even more discrete studies of phonology
and morphology that are busy analyzing words into their smallest units, and
one can follow the x’ chain up from phonemes to the higher levels of
semantics, pragmatics, and discourse analysis. The important concept here
is that language can be broken down into bits and built up into discourse.
The manipulation of large number of small units closely resemble the binary
1s and 0s of computer code. The x’ theory attracted masses of researchers
who were now able, with Jackendoff’s framework, to visualize how the brain
might be able to manipulate the pieces of data in the way that a computer
processes input.
Cognitive computation.
Jackendoff accelerated the study of syntax and also the proliferation
of original research seeking to understand first the parsing method, and
then what this theory of language revealed about the human brain.
However, scholars had already begun work to think through the nature of
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the mind. Specifically, Pinker (1997) refers to Alan Turing’s research
published beginning in 1950, even before scientists mastered the science
that would give birth to computers (pp. 67, 68). Turing (1950) theorized
that a machine could be invented that would “think” through basic
information processing, computations, and information production. He
actually constructed a basic machine drawing from this vision which
succeeded in computing simple data by processing the input and then
computing and producing the response. The machine did not really serve
any useful purpose as it could not do much and computers were on the way,
but the key was that Turing proved that a machine, in a very basic way,
could act like a simple process of computation in the brain (Pinker, 1997 p.
69). Chronologically, the Turing (1950) machine came almost 10 years
before Chomsky started to publish work on generative grammar which
shows that some psychologists were moving in the direction of seeing the
brain as a powerful computational organ even before the analysis of
language became an important body of evidence. When Chomsky, and later
Jackendoff, provided the basic structure, scientists were already waiting to
put it to the test.
For the purpose of this study, I am going to fast forward through the
intermediary stages development of a complex model of the computational
mind in order to assess the current status in what has become the fields of
cognitive science and psycholinguistics. The inner workings of the human
mind had been a tough nut to crack as there were very few scientific
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methods available to analyze the brain at work. Even when more
neurophysiologists discovered how neurons fire and transmit signals,
cognitive scientists had to puzzle through the processes involved in
computation. Scholars are still mystified by the complexity and multiplicity
of tasks the human brain can compute its way through to completion, and a
single organ doing all these distinct types of processing seemed beyond the
realm of plausible. With sensory information processing, abstract thinking,
math calculating, muscle stimulating and controlling, and language
production and processing, just to name a few mental processes, a single
organ would have to be miraculous in order to be capable of processing
such specific tasks with such a broad array functions. The answer that
cognitive scientists are clarifying and debating requires that scientists look
at the brain using an entirely different frame.
Cognitive modularity.
Complex tasks, Jerry Fodor (1983) reasoned, require a complex
machinery and architecture, something far more intricate than the Turing
machine or even the most powerful computer. With a background from MIT
in philosophy, psychology, and linguistics prepared him to create a new
vision of the brain at work. By 1981, Fodor had written many in-depth books
on the computational mind and language (Fodor & Katz, 1964; Fodor,
Bever, & Garrett, 1974; Fodor, 1975; Fodor, 1981), and it is likely that this
early work lead him to re-conceptualize the human brain. As he researched
and theorized, he began to re-envision the mind not as a single organ, but
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as multiple organs or modules which culminated in the publication of The
Modularity of Mind : An Essay on Faculty Psychology (Fodor, 1983). With
multiple modules that are able to specialize in the various operations
required of the brain, the mind gains processing power exponentially.
Modules in the brain laid the foundational architecture for the extremely
complex multitasking required (to varying degrees), so the brain can, for
example, manage involuntary needs of the human anatomy and physiology,
see a person, and communicate with her through language, all
simultaneously and with ease. Fodor’s vision of modularity quickly caught
hold in cognitive (and all related) sciences, and as he tested and further
developed his theory, other researchers jumped in to explore the
functionality of Fodor’s model. Almost immediately, divisions among the
scholars emerged as they conceived different possibilities for a modular
mind, and to this day they are still arguing and probably will be as the
intricacies of the mind resist interpretation (Barrett & Kurzban, 2006, pp.
628-631).
The initial model Fodor proposed was too small for theorists such as
Pinker (1994; 1997; 2007), Tooby, Cosmides, and Barret1, and Jackendoff
(2003) who have rejected, or rather replaced, what they see as a narrow
scope of modularity. Fodor (1983), in his initial publication qualified the
modularity with nine features that he described as characteristics of
modules. Two of these, “domain specificity, [and] encapsulation” (Barrett &
Kurzban, 2006, p. 629) are the most contentious as the philosophy of the 1 Found in The Innate Mind (Carruthers, Laurence, & Stich, 2005).
Drawn into the Fray 17
mind is virtually inseparable from the cognitive science, and Fodor’s
features, therefore, have profound philosophical implications. Fodor
introduced modularity to handle many processes of the brain that were “of a
very specific kind—reflex like, hardwired devices that process narrow types
of information in highly stereotyped ways” (Barrett & Kurzban, 2006, p.
628). This has been labeled as the narrow conception of modularity, and
despite the fact that Fodor said that these features were not set in stone
when he published, many dominant thinkers in the computational and
modular mind envision a “massive modularity” (Barrett & Kurzban, 2006).
Fodor has dug in his heals resisting this shift as you will see.
Pinker versus Fodor round one—the basics of modularity.
The battle began in the academic journals after the publication of
Fodor’s precedent setting 1983 book. Steven Pinker (1997)—then from MIT,
now at Harvard—with his experience in psycholinguistics, cognitive science,
and the relatively new field of evolutionary psychology, sees the processes
of natural selection in the brain as he attempts to reverse engineer the
selections that have been made through evolution in the human brain. By
reverse engineering, evolutionary psychologists like Pinker (Daniel Dannett,
Jared Diamond, John Tooby, and Leda Cosmides are some others)2 look at
natural forces that might have shaped the mind into a modular organ. He
claims that the proper approach would be to look at the “functional
2 The title evolutionary psychologist, it turns out, is currently a malleable job description. Since the science is newly defined by these scholars, their credentials and initial disciplines vary—Pinker, psycholinguistics; Daniel Dennett, philosophy; Jared Diamond, physiology and membrane biophysics; John Tooby, anthropology; Leda Cosmides, psychology.
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specialization” (Barrett & Kurzban, 2006, p. 629) that shaped the modules
and attempt to describe the processes at work rather than prescribe
characteristics that the modules must have (referring to Fodor’s list of nine
features).3 The functional specialization that the evolutionary psychologists
look for in the modules are the mental processes that work in a specific way
to accomplish tasks, and so the focus is on possible functions of a module
rather than on delineating the boundaries that define the module (1997).
Using the angle of his perspective in evolutionary psychology, Pinker (1997)
published How the Mind Works as compendium of his view of computation
and modularity (he does not use the label “massive” that Fodor applied to
this model). Though not explicitly stated by Pinker, his book is an extended
response to Fodor’s ideas which Pinker gives him credit for. He criticizes
Fodor for remaining fixed with his initial model while evolutionary and
linguistic evidence suggest that he does not have it quite right. Pinker
claims that scientists should expect to find a huge number of modules
within the brain because each module will be specialized as shaped by
natural selection, a process that leads to specialization (Barrett & Kurzban,
2006, p. 629).
Natural selection, as supposed by the evolutionary psychologists, has
evolved the brain that human beings now possess, and to neglect the
shaping forces of selection over time that create the modules that do the
3 According to Barrett and Kurzban (2006) these are: “domain specificity, encapsulation, mandatory operation (automaticity), inaccessibility to consciousness, speed, shallow outputs, fixed neural localization, and characteristic breakdown patterns” (p. 629).
Drawn into the Fray 19
computing in the brain is to ignore the essence of the function of the mental
organs. Pinker (1997) defends this view:
Natural selection cannot directly endow an organism with
information about its environment, or with the computational
networks, demons, modules, faculties, representations, or mental
organs that process the information. It can only select among genes.
But genes build brains, and different genes build brains that process
information in different ways. The evolution of information processing
has to be accomplished at the nuts-and-bolts level by selection of
genes that affect the brain-assembly process. (p. 176)
Pinker responds here to the criticism by Fodor that he lacks any sort of
proof to justify that natural selection can foster modularity, and that without
evidence, his claim is mere speculation without support (Fodor, 2005).
Pinker counters by dodging the criticism and repeating the claim, “genes
build brains” and natural selection determines genes to be perpetuated. He
provides an unusual support later, based upon artificial intelligence.
Computer scientists have been able to create genetic algorithms that mimic
the natural selection process. So, virtual creatures in the form of software
programs are made to reproduce or duplicate while inserting random
deviations in the programming with each generation. This is analogous to
random gene mutations in organisms as they reproduce over generations.
In these experiments, the reproduction was accelerated so that they could
observe in a short amount of time what would take thousands of years in an
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organism. Their objective was to test whether this algorithm would tend
toward more sophistication or intelligence, and they have found that “after
many cycles of computation, selection, mutation, and reproduction, the
surviving programs are often better than anything a human programmer
could have designed” (pp. 176-177). Pinker reports that they have
attempted to create this same type of evolutionary migration by modeling
neural networks on a computer program and accelerating the process of
natural selection by virtual reproduction, merging gene halves (analogous
to the male and female genetic contribution), and causing random
mutations. He claims that the modeling works, that the networks tend
toward complexity and a “higher intelligence” over generations. Oddly, in
the end of his argument Pinker harkens back to the behaviorists that
Chomsky refuted in the infancy of modern linguistics and cognitive science.
He invokes B. F. Skinner to show that learned behaviors can lead to a better
selection potential (p. 180). Retrieving this idea of learned behavior as
inheritable by offspring, I agree is a stretch and smells pseudo-scientific and
pseudo-Darwinian. Natural selection, the evolutionary mechanism that both
Darwin and Pinker champion, operates on the principle of random
mutations that have a selection advantage and are therefore perpetuated.
While peripherally this behaviorist leap might hold true, but it seems that
nature will select the most fit that pass on genes, not the learned behavior,
and the evolutionary migration is effect of random mutation rather than any
mechanism connected with behavior.
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In reference to this portion of the argument, despite clever types of
evidence such as the software analogy, I agree that there is a lack of
evolutionary evidence to support the natural selection of modularity in the
human mind. Grasping at Skinner’s failures as a source of evidence seems
misguided. But, on the other hand, what sort of evidence could Pinker
present that what satisfy Fodor’s criteria? Reverse engineering the natural
selection process can, after all, only be a thought (or computer) experiment
unless Fodor wants some sort of old school phrenology study. To say that
More to the heart of the issue, Fodor will not accept any evidence
short of empirical data, observable and repeatable, so he appears to distrust
the methodology used by evolutionary psychologists (the two terms paired,
after all, do seem to be an oxymoron) which may be a valid concern, but he
skirts the issue of defining what methodologies are acceptable in this
science—the study of modularity and computation in the human mind.
Fodor himself can only go so far in his theorizing, yet somehow he has the
power to forward his claims as valid without evidence but nobody can.
Fodor’s complaint of his is the problem of black box, the metaphor for the
mind discussed previously. The black box, in many ways, will always remain
closed and resistant to certain kinds of observation and analysis. Pinker
says that we can speculate (using reverse engineering for example) with
reasonable assumptions and creative evidence from fields that are not
restricted to linguistics and psychology. Fodor rejoins that this is not
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empirical science; that is speculation. In the end, perhaps they both are
right.
Continuing the fight, Fodor (2001) published The Mind Doesn't Work
That Way : The Scope and Limits of Computational Psychology (TMD, the
author’s initialism that I will use from here on) as an obvious rejection of
Pinker’s (1997) How The Mind Works (HTMW , again the author’s
initialism). Fodor, in addition to “massive modularity,” adds a new label to
the faction that supports the function and specialization as shapers of many
modules that merely operate in syntactic language, the modules
hierarchically ordered in some cases, “The New Synthesis” (Fodor, 2001) .
Fodor disparagingly describes the:
Turing architecture of syntactically structured mental representations
and syntactically driven computational operations defined on these
representations. The New Synthesis thus shares with traditional
rationalism its emphasis on innate content; but it has added Turing's
idea that mental architecture is computational in the proprietary
syntactic sense. (p. 19)
Not only is the title of his book polemic, but the argument from the
beginning is disparaging, Fodor labeling Pinker with Turing’s (1950)
machine as if it were a primary piece of evidence. Pinker is obviously giving
a historical overview of computation in HTMW, and he sees as significant
Turing’s step forward conceptually to conceive the mind as operating in a
machine-like fashion (1997). Turing even built the mechanism to prove his
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point, and Pinker uses him to trace the history and provide a visual,
concrete example of what he is explaining. After all, if Pinker’s primary aim
with the Turing example was create a realistic model for brain function, he
would have simply chosen a powerful computer which would be a more apt
analogy to processing in the brain. Pinker does look at computers and
electronics throughout HTMW as examples of how the brain might function
in an analogous biological way. Pinker (2005) restates this, perhaps more
clearly in a later article saying “’computation’ in this context does not refer
to what a commercially available digital computer does but to a more
generic notion of mechanical rationality, a concept that Fodor himself has
done much to elucidate (Fodor, 1968; 1975; 1981; 1994)” (p. 2). Fodor
intentionally misreads the function of Pinker’s evidence and overextends it
in hyperbolic fashion in order to deride and discredit Pinker. Such a blatant
attempt to manipulate information and misguide his readers with a biased
appeal to pathos, makes Fodor’s credibility questionable.
Turing after all appears in only three pages of HTMW, while the name
occupies lines 19 times in TNHTMW’s first chapter as he tries to make the
label stick. In the same chapter, he uses variations on syntax 46 times, and
rationalist. New Synthesis (Fodor’s capitalization), by contrast, only appears
13 times (see Fodor, 2001, Ch. 1). The only reason I counted these was
because they stand out so dramatically on the page, distracting visually and
creating the effect in the reader of being beaten over the head with a baton.
They are all similar in the sense that Fodor uses them pejoratively to
Drawn into the Fray 24
characterize and dismiss the kind of research and theory Pinker is working
on. For example, he coins the term New Synthesis to label Pinker’s revival
of the rationalist philosophy or psychology (Fodor actually interchanges all
of these terms as if synonymous) that describes the innate ideas and
concepts in language4 that might be transformed through the mechanism of
mutation and inherited by offspring. Pinker draws from Chomsky’s (1965)
ideas on innateness and syntax in the UG, the tool box for learning language
that all children posses in any culture of the world. Fodor uses Chomsky
(only 16 times) and syntax interchangeable referring to the computational
language or software that the brain runs on in the Turing model of the
mind. From the outset, Fodor attempts to subvert Pinker’s argument by
bombarding him with labels while bludgeoning the reader with the same
rhetorical force. This is the form stereotyping the politicians use to smear
other candidates, a low tactic.
Fodor also errs in ignoring Pinker’s careful linking of pieces throughout
the book as lines of support that are coherent as a whole and merit the term
“evidence” in the realm of empirical science. In “Chapter 4 The Mind’s
Eye,” for example, Pinker meticulously explores in-depth knowledge from
diverse disciplines in an attempt to thoroughly examine and describe the
modules that function to create stereovision, 3D (pp. 211-298). He uses
visual, cognitive, linguistic, anatomical, physiological, nuerophysiological,
4 Pinker’s books The Blank Slate: The Modern Denial of Human Nature (2002) and The Stuff of Thought: Language As a Window into Human Nature (2007) develop in much more detail, the ideas of innate language, concepts, and metaphors (drawing from Lakoff) and the connection to human nature and behavior.
Drawn into the Fray 25
neurophilosophical, etc. research to reason through how stereovision
functions so that he can, in turn describe the modules themselves. Pinker
provides evidence through specific, descriptive, and empirical example
repeatedly in HTMW to illustrate and support his view of computation and
modularity. To ignore these as evidence is an injustice.
Fodor is correct that Pinker advocates the innate language structures
and modules, and this actually becomes a point of departure for Pinker in
his book publications, the next two discussing in great depth this innateness
and human nature (footnote 3). Many other would-be psycholinguists have
jumped ship as well, following the lead of Pinker and perhaps Chomsky in
his radical politics and assessment of human nature of the last 30 years,
migrating toward several connected hotly debated topics grounded in
natural selection and human nature in evolutionary psychology. I’m not
sure that it is Fodor’s harsh rhetoric and territorial behavior that has turned
these scholars away from modularity of the mind, but I am sure the current
climate of the discipline makes psycholinguistics and cognitive science
unappealing which is unfortunate. This is a shame since the more great
minds we have at work to discover and delineate the processes and
structures of the mind, the most complex biological (or mechanical) organ,
the more progress will be made.
Pinker versus Fodor round two—homunculi and demons.
Drawn into the Fray 26
This is not Fodor’s only line of argumentation, but it is the most
striking, and establishes a negative precedent in the dialogue between the
two scholars. In contrast, Pinker praises Fodor for the concept of
modularity though he differs with him on some of the details. One hotspot
that Pinker (1997) creates is the need for, what have been called, homunculi
(Pinker likes the term demons) in massive modularity that function as
messengers or processors in the brain. He later adopts the term “access-
consciousness” to give the idea of high level processors a more formal feel
than demons (pp. 138-148), processors of some sort that manage at a higher
level of thought than, say, vision in order to remember, synthesize, and
govern input and output from the nervous system at large (pp. 136-148).
The two scholars have gone the rounds on this issue more than any other
because Fodor (2001) negates Pinker’s “access-consciousness” as
reminiscent of the antique idea variously termed the ghost in the machine,
demons, or homunculi. These terms refer pejoratively to a little being within
the brain that must be necessary in order to make the incredible complexity
of the mind possible (Fodor, 2001), but to be fair, Pinker (1997) explicitly
addresses and satisfactorily resolves this problem, essentially by saying that
it can wait until later (pp. 79-99). He takes on the role of reporting the data
and research available that inform the lower level cognition in the model of
the computational and modular mind (Pinker, 1997, pp. 91-93). In the role
of evolutionary psychologist, his role for the moment is to try and describe
the features of potential module(s) to lay the foundation for work that can
Drawn into the Fray 27
be done later, once modules are better understood (after description has
been accumulated, classified, critiqued, etc.) (Barrett & Kurzban, 2006, pp.
628-647). Essentially, this access-consciousness is an x value, a variable
that can be defined and articulated later.
Pinker versus Fodor final round—hunger and thirst.
The debate that Pinker (1997) ignites in HTMW continues today, but
the flurry of reviews and replies that followed Fodor’s 2001 publication
TMD, dialogues between the two from a distance, make up the heated,
exhausted battle to the end of the fight (Deborah Tannen (1999)could have
a hay-day with the militaristic language of these two). Pinker (2005) first
responds to Fodor’s (2001) blatant mockery in The Mind Doesn’t Work
That Way (emphasis added) with a defense, disguised as a review of the
book, to Fodor’s vicious rhetoric. Pinker (2005) asks the puzzled and
stunned question “So How Does the Mind Work?” (Pinker’s italics). I think
that he is genuinely confused by what he perceives, correctly as Fodor
flipping to argue the other side, in opposition to his ground breaking work
on modularity. “Fodor, more than anyone,” says Pinker (2005) “has
defended the computational theory of mind ... specialization ... [and]
evolution” as a shaping force in the modular mind (p. 2). At this point,
Pinker still argues that Fodor and himself have much in common in their
writing on the computational and modular theories. And yet, with all this
Drawn into the Fray 28
agreement, here is the trail of blood that follows Pinker and Fodor from the
beginning, each written in response to the other (except Fodor’s initial book
on modularity):
1981-- The Modularity of Mind : An Essay on Faculty Psychology
1997—Pinker, How the Mind Works
2001—Fodor, The Mind Doesn't Work That Way: The Scope and
Limits of Computational Psychology
2005—Pinker, “So How Does the Mind Work?”
2005—Fodor, “Reply to Steven Pinker ‘So How Does the Mind
Work?’”
2005—Pinker, “A Reply to Jerry Fodor on How the Mind Works”
2006—Fodor, “How the Mind Works: What We Still Don’t Know”
In these pieces, they are sometimes angry and sometimes humorous. They
rehash the same arguments, make the same claims, provide the same
evidence. However, in the restating and rethinking of argumentation, both
sides begin to become more focused.
In responding to the question at the core of all this debate, Fodor
(2005) reveals a fundamental truth that has been revealed:
So how does the mind work? [author’s bold and italics]
I don’t know. You don’t know. Pinker doesn’t know. And I rather
suspect, such is the current state of the art, that if God were to tell us,
we wouldn’t understand him. (p. 31)
Drawn into the Fray 29
Fodor’s tone is still a bit playful with the question and answer set up, the
short witty response. But his tone is also serious and almost dark. The
anger, perhaps, seeps out of his language in the heat of the debate, and
invoking God seems odd and out of place. Knowing that Pinker is an ardent
atheist, as I’m sure Fodor does, he seems to be provoking Pinker as if
Pinker may be about to quit the fight so Fodor has to fuel the fire again.
Discussion: Assessing the Debate, Entering the Fray as a New
Researcher
Is this polemic rhetoric effective in moving science forward?
Jackendoff (2003) and the research team of Barret and Kurzban(2006) do
not think so. As a novice researcher in the field of psycholinguistics and
cognitive science, I feel as if I have been sucked into the complexity of this
debate against my will. In fact, I have. The researchers I have discussed
subverted my initial methodology for this study, or at least I allowed them
to. Originally I had intended to ground myself in the theories of modularity
and the computational mind so that I could then see how eye tracking
studies and reading fit into the work of the scholars I discuss here. I have
done all the reading and research for that kind of a paper, and I have found
that at this point they fit together very loosely, not at all integrated into a
nice map of the brain module for reading. I have done the research with L2
acquisition (Clahsen, & Felser, 2006a; 2006b; Cook, 1999; Friesen & Jared,
2007; Fukkink, Hulstijn, & Simis, 2005; Koda, 2007) and eye tracking
(Reichle, Liversedge, Pollatsek, & Rayner, 2009; Reichle, Warren, &
Drawn into the Fray 30
McConnell, 2009; Reichle, Rayner, & Pollatsek, 2003; Reichle, 2006; Kliegl,
Nuthmann, & Engbert, 2006; Rayner, 1993; Rayner, Pollatsek, Drieghe,
Slattery, & Reichle, 2007; Rayner, 2009; Rayner, Smith, Malcolm, &
Henderson, 2009) as well, applying eye tracking research to the pedagogy
in this domain and reading closely what few studies there are in L2 reading
that apply eye tracking research (Duyck, Vanderelst, Desmet, & Hartsuiker,
2008; Elston-Güttler & Friederici, 2007; Keating, 2009; Usó & Martínez,
2006; Yamada, 2009). However, these fields are not as interconnected as I
innocently thought they would be. The domains I have studied are new
disciplines tackling perhaps the largest problems ever confronted by
scientists, with the tools necessary for discovery in many instances
withdrawn because, in contrast to the metaphor of the black box, the
container of the human brain holds the living tissue of a sentient being who
would not appreciate their gray matter being poked and prodded. The
domains and disciplines will converge I suppose, based upon the research,
but I discovered that this is a slow process. The individual disciplines such
as L2 acquisition and eye tracking have to figure out precisely the nature of
their science before they integrate and discover how the separate modules
of science operate within the mind of science as a whole. Perhaps, this type
of research on my part is valuable because I am in the trenches and can
apply the bits and pieces I discover and learn and integrate them into my
classroom. After all, looking back over this subject matter I have covered,
what here does not have pedagogical implications for the English and SLA
Drawn into the Fray 31
classrooms? For that matter, this is what all education is about. Figuring
out how to encourage students to discover their mind and how it works.
Helping them to see how developing the modules with their brains will
benefit their communities and societies as they are more productive and
effective in all that they do, showing them through literature or science, or
any other discipline that developing their thinking skills will help them to
live more satisfactory, happier lives.
Chomsky first aroused my interest in the idea of UG and innateness,
the language of human beings reflecting the operations and processes of
the mind. The fact that a UG could be passed on intrigued me because I
could not see initially how that could happen. Unconsciously, I have always
believed the erroneous concept of babies being born with a “blank slate,”
Locke’s “blank slate” (Stuhr, 2000), but as I began to read Jackendoff and
then Pinker, I could see the real complexity of a language and its acquisition
by human beings. The evidence these three scholars who tend to think in
similar veins persuaded me that the process of learning a whole language
and grammar by the age eight (or at least 13) would be an impossible feat
without some sort of jump start (see Pinker, 1994).
As many before me, I became enamored with the eloquence of Pinker,
the simplicity of Jackendoff (in a positive sense), and the radicalism of
Chomsky. I could not hold myself back as pieces of the mysteries that have
always intrigued me were revealed by each of these authors. My view was
utopian in a sense because I believed naively that Pinker could guide me
Drawn into the Fray 32
through all of the unknown, shedding light on sentience, consciousness, and
the mind.
Fodor, however, opened my mind to the complexity and
contentiousness of the matter, the insolvability of some problems. I read the
documents I describe above almost chronologically with the exception of
reading Pinker’s (1997) HTMW before I read Fodor.5 While still moving
through Pinker’s works, I discovered Fodor (1983) as the father of
modularity and jumped back to review his work The Modularity of Mind. All
was well until I moved on to Fodor’s TMD where I felt attacked along with
Pinker, my new ideas feeling threatened. Pinker was my psycholinguistic
hero by this point. At times, Fodor was witty and humorous, but Pinker
(2005) rightly describes his attitude toward the dialogue of academia saying
“at critical junctures, Fodor refuses to offer arguments for his convictions,
opting instead for peremptory sarcasm” (p. 33). However, to understand
Fodor, I have found is to understand the need for resistance to the popular
trends in scientific thought. Knowing our ignorance pushes us towards
discovery, and Fodor (2006) insightfully reveals this in the last of his
exchanges:
One could make a case that the history of cognitive science,
insofar as it’s been any sort of success, has consisted largely of
finding more and more things about cognition that we didn’t know
and didn’t know that we didn’t. “Throwing some light on how much 5 This actually benefited me as a new researcher because Pinker addresses a wider audience and is easier to read. Also, Fodor has a cantankerous relationship with his intended audience which becomes annoying and discouraging.
Drawn into the Fray 33
dark there is,” as I’ve put it elsewhere. The professional cognitive
scientist has a lot of perplexity to endure, but he can be pretty sure
that he’s gotten in on the ground floor. (p. 86)
Whether this is an attempt at reconciliation with Pinker or justification of
his role in the dialogue, Fodor hits on a truth about science and linguistics
in general—there is always more to be done. Language, computational
processes, and modularity are, at best, only vaguely understood, and the
nature of the work in this field is difficult. Researchers must find creative
entries into the black box, meticulously describe functions and processes,
and walk down costly, dark, dead-end paths, but the progress comes with
costs at times as I have found in this study. Not only are scholars hungry
for new knowledge and discovery as they research and publish, they are just
hungry, and dead-end paths, though necessary to the science, do not put
food on the table. Therefore, the rhetoric in our debates is heated and life
threatening, our adrenal causing us to devour research, observation, and,
sometimes, other researchers, as if they were things to be consumed.
Conclusions: The Way Forward
The reality of the battle between Fodor and Pinker is that they are on
the upper crust of academia, the very top of the ivory tower with a sky view,
and a few of the things keeping them on track, keeping them human and
humane (and perhaps sane), are their ethics and integrity as scientists and
scholars. Recognition of their imperfections as they pursue and create
knowledge may be absolutely necessary to maintain the true scientific mind,
Drawn into the Fray 34
and someone who emphasizes what is unknown, while at the same time
entering the fray productively, though perhaps antagonistically, against any
perceived threat or fear, with a willingness to change one’s mind, arguing
at times in opposition to what he once supported, keeps the upper tier in
academia humble and reminds those of us below that those above do not
have perfect careers nor are our careers failures.
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