Modularity of Mind
The concept of modularity has loomed large in philosophy and psychology since the early 1980s, following the publication of Fodor’s ground-breaking book The Modularity of Mind (1983). In the twenty-five years since the term ‘module’ and its cognates first entered the lexicon of cognitive science, the conceptual and theoretical landscape in this area has changed dramatically. Especially noteworthy in this regard has been the development of evolutionary psychology, whose proponents argue that the architecture of the mind is more pervasively modular than the Fodorian perspective allows. Where Fodor (1983, 2000) draws the line of modularity at the low-level systems underlying perception and language, post-Fodorian theorists such as Carruthers (2006) contend that the mind is modular through and through, that is, up to and including the high-level systems responsible for thought. The concept of modularity has also played a role in recent debates in epistemology, philosophy of language, and other core areas of philosophy—further evidence of its utility as a tool for thinking about the mind.
- 1. Fodorian modules
- 2. Modest modularity
- 3. Massive modularity
- 4. Philosophical ramifications
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- Related Entries
In his classic introduction to modularity, Fodor (1983) lists nine
features that collectively characterize the type of system that
interests him. In original order of presentation, they are:
- Domain specificity
- Mandatory operation
- Limited central accessibility
- Fast processing
- Informational encapsulation
- ‘Shallow’ outputs
- Fixed neural architecture
- Characteristic and specific breakdown patterns
- Characteristic ontogenetic pace and sequencing
A cognitive system counts as modular in Fodor’s sense if it is modular
“to some interesting extent,” meaning that it has most of these
features to an appreciable degree (Fodor, 1983, p. 37). This is a
weighted most, since some marks of modularity are more important than
others. Information encapsulation, for example, is more or less
essential for modularity, as well as explanatorily prior to several of
the other features on the list (Fodor, 1983, 2000).
Each of the items on the list calls for explication. To streamline
the exposition, I will cluster most of the features thematically and
examine them on a cluster-by-cluster basis, along the lines of Prinz
Encapsulation and inaccessibility. Informational
encapsulation and limited central accessibility are two sides of the
same coin. Both features pertain to the character of information flow
across computational mechanisms, albeit in opposite directions.
Encapsulation involves restriction on the flow of information into a
mechanism, whereas inaccessibility involves restriction on the flow of
information out of it.
A cognitive system is informationally encapsulated to the extent
that in the course of processing a given set of inputs it cannot access
information stored elsewhere; all it has to go on is the information
contained in those inputs plus whatever information might be stored
within the system itself, for example, in a proprietary database. In
the case of language, for example:
A parser for [a language] L contains a grammar of
L. What it does when it does its thing is, it infers from
certain acoustic properties of a token to a characterization of certain
of the distal causes of the token (e.g., to the speaker’s intention
that the utterance should be a token of a certain linguistic type).
Premises of this inference can include whatever information about the
acoustics of the token the mechanisms of sensory transduction provide,
whatever information about the linguistic types in L the
internally represented grammar provides, and nothing else.
(Fodor, 1984/1990, pp. 245–246)
Similarly, in the case of perception—understood as a kind of
non-demonstrative (i.e., defeasible, or non-monotonic) inference from
sensory ‘premises’ to perceptual
‘conclusions’—the claim that perceptual systems are
informationally encapsulated is equivalent to the claim that “the data
that can bear on the confirmation of perceptual hypotheses includes, in
the general case, considerably less than the organism may know” (Fodor,
1983, p. 69). The classic illustration of this property comes from the
study of visual illusions, which typically persist even after the
viewer is explicitly informed about the character of the stimulus. In
the Müller-Lyer illusion, for example, the two lines continue to
look as if they were of unequal length even after one has convinced
oneself otherwise, e.g., by measuring them with a ruler (see Figure 1,
Figure 1. The Müller-Lyer illusion.
Informational encapsulation is related to what Pylyshyn (1984) calls
cognitive impenetrability. But the two properties are not the same;
instead, they are related as genus to species. Cognitive
impenetrability is a matter of encapsulation relative to information
stored in central memory, paradigmatically in the form of beliefs and
utilities. But a system could be encapsulated in this respect without
being encapsulated across the board. For example, auditory speech
perception might be encapsulated relative to beliefs and utilities but
unencapsulated relative to vision, as suggested by the McGurk effect
(see below, §2). Likewise, a system could be unencapsulated
relative to beliefs and utilities yet encapsulated relative to
perception; it’s not implausible, for example, that the practical
reasoning system has this character (again, see §2). Strictly
speaking, then, cognitive impenetrability is a specific type of
informational encapsulation, albeit a type with special salience in the
Fodorian scheme. Lacking this feature means failing the encapsulation
test, the litmus test of modularity. But systems with this feature
might still fail the test, due to information seepage of a different
(i.e., non-central) sort.
The flip side of informational encapsulation is inaccessibility to
central monitoring. A system is inaccessible in this sense if the
intermediate-level representations that it computes prior to producing
its output are inaccessible to consciousness, and hence unavailable for
explicit report. In effect, centrally inaccessible systems are those
whose internal processing is opaque to introspection. Though the
outputs of such systems may be phenomenologically salient, their
precursor states are not. Speech comprehension, for example, likely
involves the successive elaboration of myriad representations (of
various types: phonological, lexical, syntactic, etc.) of the stimulus,
but of these only the final product—the representation of the
meaning of what was said—is consciously available (at best).
Mandatoriness, speed, and superficiality. In addition to
being informationally encapsulated and centrally inaccessible, modular
systems and processes are “fast, cheap, and out of control” (to borrow
a phrase by roboticist Rodney Brooks). These features form a natural
trio, as we’ll see.
The operation of a cognitive system is mandatory just in case it is
automatic, that is, not under conscious control (cf. Bargh &
Chartrand, 1999). This means that, like it or not, the system’s
operations are switched on by presentation of the relevant stimuli and
those operations run to completion. For example, native speakers of
English cannot hear the sounds of English being spoken as mere noise:
if they hear those sounds at all, they hear them as English. Likewise,
it’s impossible to see a 3D array of objects in space as 2D patches of
color, however hard one may try (despite claims to the contrary by
painters and other visual artists influenced by Impressionism).
Speed is arguably the mark of modularity that requires least in the
way of explication. But speed is relative, so the best way to proceed
here is by way of examples. Speech shadowing is generally considered to
be very fast, with typical lag times on the order of about 250 ms.
Since the syllabic rate of normal speech is about 4 syllables per
second, this suggests that shadowers are processing the stimulus in
syllabus-length bits—probably the smallest bits that can be
identified in the speech stream, given that “only at the level of the
syllable do we begin to find stretches of wave form whose acoustic
properties are at all reliably related to their linguistic values”
(Fodor, 1983, p. 62). Similarly impressive results are available for
vision: in a rapid serial visual presentation task (matching picture to
description), subjects were 70% accurate at 125 ms. exposure per picture
and 96% accurate at 167 ms. (Fodor, 1983, p. 63). In general, a
cognitive process counts as fast in Fodor’s book if it takes place in a
half second or less.
A further feature of modular systems is that their outputs are
relatively ‘shallow’. Exactly what this means is unclear.
But the depth of an output seems to be a function of at least two
properties: first, how much computation is required to produce it
(i.e., shallow means computationally cheap); second, how constrained or
specific its informational content is (i.e., shallow means
informationally general) (Fodor, 1983, p. 87). These two properties are
correlated, in that outputs with more specific content are typically
more expensive for a system to produce, and vice versa. Some writers
have interpreted shallowness to require non-conceptual character (e.g.,
Carruthers, 2006, p. 4). But this conflicts with Fodor’s own gloss on
the term, in which he suggests that the output of a plausibly modular
system such as visual object recognition might be encoded at the level
of ‘basic-level’ concepts, like DOG and CHAIR (Rosch et
al., 1976). What’s ruled out here is not concepts, then, but highly
theoretical concepts like PROTON, which are too specific and too
expensive to meet the shallowness criterion.
All three of the features just discussed—mandatoriness, speed,
and shallowness—are associated with, and to some extent
explicable in terms of, informational encapsulation. In each case, less
is more, informationally speaking. Mandatoriness flows from the
insensitivity of the system to the organism’s utilities, which is one
dimension of cognitive impenetrability. Speed depends upon the
efficiency of processing, which positively correlates with
encapsulation in so far as encapsulation tends to reduce the system’s
informational load. Shallowness is a similar story: shallow outputs are
computationally cheap, and computational expense is negatively
correlated with encapsulation. In short, the more informationally
encapsulated a system is, the more likely it is to be fast, cheap, and
out of control.
Dissociability and localizability. To say that a system is
functionally dissociable is to say that it can be selectively impaired,
that is, damaged or disabled with little or no effect on the operation
of other systems. As the neuropsychological record indicates, selective
impairments of this sort have frequently been observed as a consequence
of circumscribed brain lesions. Standard examples from the study of
vision include prosopagnosia (impaired face recognition), achromatopsia
(total color blindness), and akinetopsia (motion blindness); examples
from the study of language include agrammatism (loss of complex
syntax), jargon aphasia (loss of complex semantics), alexia (loss of
object words), and dyslexia (impaired reading and writing). Each of
these disorders have been found in otherwise cognitively normal
individuals, suggesting that the lost capacities are subserved by
functionally dissociable mechanisms.
Functional dissociability is associated with neural localizability
in a strong sense, namely, the system in question is implemented in
neural circuitry that is both relatively circumscribed in extent
(though not necessarily in contiguous areas) and dedicated to the
realization of that system and that system only. Localizability in this
sense goes beyond mere implementation in local neural circuitry, since
a given bit of circuitry could (and often does) subserve more than one
cognitive function. Candidate examples of systems that might be
strongly localizable include color vision (in V4), visual motion
detection (in MT), and visual face recognition (in lateral fusiform
Domain specificity. A system is domain specific to the
extent that it has a restricted subject matter, that is, the class of
objects and properties that it processes information about is
circumscribed in a relatively narrow way. As Fodor (1983) puts it,
“domain specificity has to do with the range of questions for which a
device provides answers (the range of inputs for which it computes
analyses)” (p. 103): the narrower the range of inputs a system can
compute, the narrower the range of problems the system can
solve—and the narrower the range of such problems, the more
domain specific the device. Alternatively, the degree of a system’s
domain specificity can be understood as a function of the range of
inputs that turn the system on, where the size of that range determines
the informational reach of the system (Carruthers, 2006; Samuels,
Domains (and by extension, modules) are typically more fine-grained
than sensory modalities like vision and audition. This seems clear from
Fodor’s list of plausibly domain-specific mechanisms, which includes
systems for color perception, visual shape analysis, sentence parsing,
and face and voice recognition (Fodor, 1983, p. 47)—none of which
correspond to perceptual or linguistic faculties in an intuitive sense.
It also seems plausible, however, that the traditional sense modalities
(vision, audition, olfaction, etc.), and the language faculty as a
whole, are sufficiently domain specific to count as displaying this
particular mark of modularity (McCauley & Henrich, 2006).
Innateness. The final feature of modular systems on Fodor’s
roster is innateness, understood as the property of “develop[ing]
according to specific, endogenously determined patterns under the
impact of environmental releasers” (Fodor, 1983, p. 100). On this view,
modular systems come on-line chiefly as the result of a brute-causal
process like triggering, rather than an intentional-causal process like
learning. (For more on this distinction, see Cowie, 1999; for an
alternative analysis of innateness, see Ariew, 1999.) The most familiar
example here is language, the acquisition of which occurs in all normal
individuals in all cultures on more or less the same schedule: single
words at 12 months, telegraphic speech at 18 months, complex grammar at
24 months, and so on (Stromswold, 1999). Visual object perception is
another, less obvious candidate (Spelke, 1994).
The thesis of modest modularity, as I shall call it, has two strands.
The first strand of the thesis is positive. It says that input systems,
such as systems involved in perception and language, are modular. The
second strand is negative. It says that central systems, such as
systems involved in belief fixation and practical reasoning, are not
In this section I will present and assess the case for modest
modularity. The next section (§3) will be devoted to discussion of
the stronger thesis of massive modularity, which retains the positive
strand of Fodor’s thesis while reversing the polarity of the second
strand from negative to positive—though not without changing the
subject to a certain extent as well (Wilson, 2008).
Modularity around the edges. The first, positive part of
the modest modularity thesis is that input systems are modular. By
‘input system’ Fodor (1983) means a computational mechanism
that “presents the world to thought” (p. 40) by processing the outputs
of sensory transducers. (A sensory transducer is a device that converts
the energy impinging on the body’s sensory surfaces, such as the retina
and cochlea, into a computationally usable form, without adding or
subtracting information.) As noted earlier, input processing involves
non-demonstrative inferences from sensory data to hypotheses about the
layout of objects in the world. These hypotheses are then passed on to
central systems, for the purpose of belief fixation.
Fodor argues that input systems constitute a natural kind, defined
as “a class of phenomena that have many scientifically interesting
properties over and above whatever properties define the class” (Fodor,
1983, p. 46). He argues for this by presenting evidence that input
systems are modular, where modularity is marked by a cluster of
psychologically interesting properties—the most interesting and
important of these being informational encapsulation, as discussed in
§1. In the course of that discussion, we reviewed a representative
sample of this evidence, and for present purposes that should suffice.
(Readers interested in further details should consult Fodor, 1983, pp.
Fodor’s claim about the modularity of input systems has encountered
stiff resistance over the years (Churchland, 1988; Arbib, 1987;
Marslen-Wilson & Tyler, 1987; McCauley & Henrich, 2006). The
most thorough and up-to-date critique is due to Prinz (2006), who
argues that perceptual and linguistic systems rarely (if ever) satisfy
the criteria of modularity. In particular, he argues that such systems
are not informationally encapsulated. To this end, Prinz adduces two
types of evidence. First, he points to what look to be top-down effects
on visual and linguistic processing, the existence of which would tell
against cognitive impenetrability, i.e., encapsulation relative to
central systems. Some of the most striking examples of such effects
come from research on speech perception. Probably the best-known is the
phoneme restoration effect, as in the case where listeners ‘fill
in’ a missing phoneme in a spoken sentence (The state
governors met with their respective legi*latures convening in the
capital city) from which that phoneme (the /s/ sound in
legislatures) has been deleted and replaced with the sound of
a cough. By hypothesis, this filling-in is governed by listeners’
background beliefs about the linguistic context. Second, there appear
to be cross-modal effects in perception, which would tell against
encapsulation relative to non-central systems. The classic example of
this, also from the speech perception literature, is the McGurk effect.
Here, subjects watching a video of one phoneme being spoken (e.g.,
/ga/) dubbed with a sound recording of a different phoneme (/ba/) hear
a third, altogether different phoneme (/da/).
How convincing one finds this part of Prinz’s critique, however,
depends on how convincing one finds his interpretation of the evidence
for these effects. And the situation is not as clear-cut as it might
first appear. Regarding phoneme restoration, for example, it could be
that the effect is driven by listeners’ drawing on information stored
in a language-proprietary database (specifically, information about the
linguistic types in the lexicon of English), rather than by their
background beliefs about the linguistic context. In other words, it’s
not clear that phoneme restoration is a top-down effect. As for the
McGurk effect, this seems perfectly consistent with the claim that
speech perception is an informationally encapsulated system, albeit a
system that is multi-modal in character (cf. Fodor, 1983, p.132n.13).
The fact that auditory speech perception is influenced by information
derived from visual speech perception, that is, in no way undermines
the claim that speech perception simpliciter is encapsulated.
(For doubts about other aspects of Prinz’s case against input-system
modularity, see Samuels, 2006.)
A further challenge to modest modularity, not addressed by Prinz
(2006), comes from evidence that susceptibility to the Müller-Lyer
illusion varies by both culture and chronological age. For example, it
appears that adults in Western cultures are more susceptible to the
illusion than their non-Western counterparts; that adults in some
non-Western cultures, such as hunter-gatherers from the Kalahari
Desert, are nearly immune to the illusion; and that within (but not
always across) Western and non-Western cultures, pre-adolescent
children are more susceptible to the illusion than adults are (Segall,
Campbell, & Herskovits, 1966). McCawley and Henrich (2006) take
these findings as showing that the visual system is diachronically (as
opposed to synchronically) penetrable, in that how one experiences the
illusion-inducing stimulus changes as a result of one’s wider
perceptual experience over an extended period of time. They also argue
that the aforementioned evidence of cultural and developmental
variability in perception militates against the idea that vision is an
innate capacity, that is, the idea that vision is among the “endogenous
features of the human cognitive system that are, if not largely fixed
at birth, then, at least, genetically pre-programmed” and “triggered,
rather than shaped, by the newborn’s subsequent experience” (p. 83).
However, they also issue the following caveat:
[N]othing about any of the findings we have discussed
establishes the synchronic cognitive penetrability of the
Müller-Lyer stimuli. Nor do the Segall et al. (1966) findings
provide evidence that adults’ visual input systems are
diachronically penetrable. They suggest that it is only during
a critical developmental stage that human beings’ susceptibility to the
Müller-Lyer illusion varies considerably and that that variation
substantially depends on cultural variables. (McCauley &
Henrich, 2006, p. 99; italics in original)
As such, the evidence cited can be accommodated by friends of modest
modularity, provided that allowance is made for the potential impact of
environmental, including cultural, variables on
development—something that most accounts of innateness make room
A useful way of making this point invokes Segal’s (1996) idea of
diachronic modularity (see also Scholl & Leslie, 1999). Diachronic
modules are systems that exhibit parametric variation over the course
of their development. For example, in the case of language, different
individuals learn to speak different languages depending on the
linguistic environment in which they grew up, but they nonetheless
share the same underlying linguistic competence in virtue of their
(plausibly innate) knowledge of Universal Grammar (UG). Given the
observed variation in how people see the Müller-Lyer illusion, it
is possible that the visual system is modular in much the same way.
Such a possibility seems perfectly consistent with the claim that input
systems are modular in the operative sense.
Non-modularity at the center. I turn now to the dark side
of Fodor’s thesis: the claim that central systems are not
Among the principal jobs of central systems is the fixation of
belief, perceptual belief included, via non-demonstrative inference.
Fodor (1983) argues that this sort of process cannot be realized in an
informationally encapsulated system, and hence that central systems
cannot be modular. Spelled out a bit further, his reasoning goes like
1. Central systems are responsible for belief fixation. 2. Belief fixation is isotropic and Quinean. 3. Isotropic and Quinean processes cannot be carried out by informationally encapsulated systems. Hence (from 2 and 3): 4. Belief fixation cannot be carried out by an informationally encapsulated system. But: 5. Modular systems are informationally encapsulated. Hence (from 4 and 5): 6. Belief fixation cannot be carried out by a modular system. Hence (from 1 and 6): 7. Central systems are not modular.
The argument here contains two terms that call for explication, both
of which relate to the notion of confirmation holism in the philosophy
of science. The term ‘isotropic’ refers to the epistemic
interconnectedness of beliefs in the sense that “everything that the
scientist knows is, in principle, relevant to determining what else he
ought to believe. In principle, our botany constrains our astronomy, if
only we could think of ways to make them connect” (Fodor, 1983, p.
105). Antony (2003) presents a striking case of this sort of long-range
interdisciplinary cross-talk in the sciences, between astronomy and
archaeology; Carruthers (2006, pp. 356–357) furnishes another nice
example, this time linking solar physics and evolutionary theory.
A second dimension of confirmation holism is that confirmation is
‘Quinean’, meaning that:
[T]he degree of confirmation assigned to any given
hypothesis is sensitive to properties of the entire belief system
… simplicity, plausibility, and conservatism are properties that
theories have in virtue of their relation to the whole structure of
scientific beliefs taken collectively. A measure of
conservatism or simplicity would be a metric over global
properties of belief systems. (Fodor, 1983, pp. 107–108).
Both isotropy and Quineanness are features that preclude encapsulation,
since their possession by a system would require potentially unlimited
access to the contents of central memory, and hence cognitive
penetrability to the max. Put in slightly different terms: isotropic
and Quinean processes are global rather than local, and since globality
rules out encapsulation, isotropy and Quineanness rule out
By Fodor’s lights, the upshot of this argument—namely, the
exclusion of modularity from central systems—is bad news for the
scientific study of higher cognitive functions. This is neatly
expressed by his “First Law of the Non-Existence of Cognitive Science,”
according to which “[t]he more global (e.g., the more isotropic) a
cognitive process is, the less anybody understands it” (Fodor, 1983, p.
107). His grounds for pessimism on this score are twofold: first,
global processes are resistant to computational modelling, making them
unpromising objects of psychological study; and second, global systems
are unlikely to be associated with local brain architecture, thereby
rendering them unpromising objects of neuroscientific study. For these
reasons, Fodor’s argument against central modularity seems to deliver a
knock-out punch against the very possibility of a science of higher
cognition—not a happy result, as far as most cognitive scientists
and philosophers of mind are concerned.
Be that as it may, Fodor’s argument is a difficult one to resist.
The main sticking points are these: first, the strong negative
correlation between globality and encapsulation; second, the strong
positive correlation between encapsulation and modularity. Putting
these points together, we get a strong negative correlation between
globality and modularity: the more global the process, the less modular
the system that executes it. Hence, it seems there are only three ways
to block the conclusion of the argument:
- deny that central processes are (strongly) global;
- deny that globality and encapsulation are (strongly) negative
- deny that encapsulation and modularity are (strongly) positively
Of these three options, the second seems least attractive, as it seems
something like a conceptual truth that globality and encapsulation pull
in opposite directions. The first option is perhaps a bit more
appealing, though the idea that central processes are global to a
substantial extent (if not to the max) is hard to deny—and that
is all the argument really requires.
That leaves the third option: denying that modularity requires
encapsulation. This is, in effect, the strategy pursued by Carruthers
(2006). More specifically, Carruthers draws a distinction between two
kinds of encapsulation: ‘narrow-scope’ and
‘wide-scope’. A system is narrow-scope encapsulated if it
cannot draw on information held outside of it in the course of its
processing. This corresponds to encapsulation as Fodor uses the term.
By contrast, a system that is encapsulated in the wide-scope sense
can draw on exogenous information during the course of its
processing—it just can’t draw on all of that information at once
(that is, all of the information is accessible, but not all of it can
be accessed on any given occasion). This is encapsulation in a much
weaker sense of the term than Fodor’s. Indeed, Carruthers’s use of the
term ‘encapsulation’ here is something of a misnomer
In any case, if modularity requires only weak (i.e., wide-scope)
encapsulation, then Fodor’s argument against central modularity no
longer goes through. But given the importance of strong (i.e.,
narrow-scope) encapsulation to Fodorian modularity, all this really
shows is that central systems might be modular in a non-Fodorian
sense. (We might call it ‘modularity*’, so as to avoid
confusion.) The original argument that central systems are not modular
(that is, not modular in the Fodorian sense)—and with it, the
motivation for the negative strand of the modest modularity
According to the massive modularity thesis, the mind is modular (in
some sense) through and through, including the parts responsible for
high-level cognition functions like belief fixation, problem-solving,
planning, and the like. Originally articulated and advocated by
proponents of evolutionary psychology (Sperber, 1994, 2002; Cosmides
& Tooby, 1992; Pinker, 1997; Barrett, 2005; Barrett & Kurzban,
2005), the thesis has received its most comprehensive and sophisticated
defense at the hands of Carruthers (2006). Before proceeding to the
details of that defense, however, we need to consider briefly what
concept of modularity is in play.
The main thing to note here is that the operative notion of
modularity differs significantly from the traditional Fodorian one.
Carruthers is explicit on this point:
[If] a thesis of massive mental modularity is to be
remotely plausible, then by ‘module’ we cannot mean
‘Fodor-module’. In particular, the properties of having
proprietary transducers, shallow outputs, fast processing, significant
innateness or innate channeling, and encapsulation will very likely
have to be struck out. That leaves us with the idea that modules might
be isolable function-specific processing systems, all or almost all of
which are domain specific (in the content [viz. roughly Fodorian]
sense), whose operations aren’t subject to the will, which are
associated with specific neural structures (albeit sometimes spatially
dispersed ones), and whose internal operations may be inaccessible to
the remainder of cognition. (Carruthers, 2006, p. 12)
Of the original set of nine features associated with Fodor-modules,
then, Carruthers-modules retain at most only five: dissociability,
domain specificity, mandatoriness, localizability, and central
inaccessibility. Conspicuously absent from the list is informational
encapsulation, the feature most central to modularity in Fodor’s
A second point, related to the first, is that defenders of massive
modularity have chiefly been concerned to defend the modularity of
central cognition (in some suitably robust sense, not necessarily
Fodor’s), taking for granted that the mind is modular around the edges
(in Fodor’s sense, or something like it). Thus, the thesis at issue for
theorists like Carruthers might be best understood as the conjunction
of two claims: first, that input systems are modular in a strong sense
(that is, the positive strand of modest modularity), and second, that
central systems are modular, but in a considerably weakened sense. In
his (suitably massive) defense of massive modularity, Carruthers
focuses almost exclusively on the second of these claims, and so will
The centerpiece of Carruthers (2006) consists of three arguments for
massive modularity: the argument from design, the argument from
animals, and the argument from computational tractability. Let’s
briefly consider each of them in turn.
The argument from design is as follows:
- Biological systems are designed systems, constructed
- Such systems, when complex, need to have massively modular
- The human mind is a biological system, and is complex.
- So the human mind will be massively modular in its organization.
(Carruthers, 2006, p. 25)
A weakness in this line of reasoning, however, is that even if the mind
is massively modular in its organization, it doesn’t follow
that that the mind is massively modular (i.e., composed throughout of
systems that are domain-specific, mandatory, etc.). Fortunately,
there’s a somewhat stronger argument in the vicinity of this one, due
to Cosmides and Tooby (1992). It goes like this:
- The human mind is a product of natural selection.
- In order to survive and reproduce, our human ancestors had to solve
a range of adaptive problems (finding food, shelter, mates, etc.).
- Since adaptive problems are solved more quickly, efficiently, and
reliably by modular (domain-specific, mandatory, etc.) systems than by
non-modular ones, natural selection would have favored the evolution of
a massively modular architecture.
- So the human mind is probably massively modular.
The force of this argument depends chiefly on the strength of the third
premise. Not everyone is convinced, to put it mildly (Samuels, 2000;
A related argument is the argument from animals. Unlike the argument
from design, this argument is never explicitly stated in Carruthers
(2006). But here is a plausible reconstruction of it, due to Wilson
- Animal minds are massively modular.
- Human minds are incremental extensions of animal minds.
- So human minds are massively modular.
Unfortunately for friends of massive modularity, this argument, like
the argument from design, is vulnerable to a number of objections
(Wilson, 2008). I’ll mention two of them here. First, it’s not easy to
motivate the claim that animal minds are massively modular (in the
operative, post-Fodorian sense). Though Carruthers (2006) goes to
heroic lengths to do so, the evidence he cites—e.g., for the
domain specificity of animal learning mechanisms, à la
Gallistel, 1990—adds up to less than what’s needed. The problem
is that domain specificity is just one of five features characteristic
of modularity in Carruthers’ account, and he adduces little or no
evidence to support the attribution of the other four features. So
unless domain specificity alone suffices for modularity (which seems
unlikely on its face), the argument falters at the first step. Second,
even if animal minds are massively modular, and even if single
incremental extensions of the animal mind preserve that feature, it’s
quite possible that a series of such extensions of animal minds might
have led to its loss. In other words, as Wilson (2008) puts it, it
can’t be assumed that the conservation of massive modularity is
transitive. And without this assumption, the argument from animals
can’t go through.
Third and finally, we have the argument from computational
tractability (Carruthers, 2006, pp. 44–59). This is probably the least
transparent of the three arguments, in terms of its underlying
- The mind is computationally realized.
- All computational mental processes must be suitably tractable.
- Only processes that are at least weakly (i.e., wide-scope)
encapsulated are suitably tractable.
- So the mind must consist entirely of at least weakly encapsulated
- So the mind is massively modular.
The main problem here is with the last step. Though one might
reasonably suppose that modular systems must be at least weakly
encapsulated, the converse doesn’t follow. Indeed, Carruthers (2006)
makes no mention of weak encapsulation in his definition of modularity,
so it’s difficult to see how one is supposed to get from a claim about
pervasive encapsulation to a claim about pervasive modularity. At best,
what we get is an argument for the possibility of massive modularity,
rather than its actuality.
All in all, then, compelling general arguments for massive
modularity are hard to come by. This is not yet to dismiss the
possibility of modularity in central-process cognition. For example,
there is recent evidence that the capacity to think about social
exchanges is subserved by a domain-specific, functionally dissociable,
and even innate mechanism (Stone et al., 2002; Sugiyama et al., 2002).
But here too there are grounds for doubt (Prinz, 2006). Skepticism
about modularity in other areas of central cognition, such as
high-level mindreading, also seems to be the order of the day (e.g.,
Currie & Sterelny, 2000; but see Carruthers, 2006, pp. 11–12, for a
As for arguments against massive modularity, there is rather less to
talk about. Buller and Hardcastle (2000) argue that the thesis is
inconsistent with developmental neurobiology, insofar as evidence of
developmental plasticity militates against innateness. (An extended
version of this argument appears in Buller, 2005, pp. 127–200.) There
are two big problems with this argument, however. First, it’s unclear
to what extent the developmental neurobiological record precludes the
innate specification of mental mechanisms. For instance, Machery and
Barrett (2008) contend that the inconsistency here is merely apparent,
not real. In support of their contention, they point to growing
evidence that specific genes are linked to the normal development of
cortical structures, both in humans and other animals (for an overview
of this evidence, see Ramus, 2006). Second, not all proponents of
massive modularity insist that modules are innately specified.
Carruthers (2006) is a case in point; Kurzban, Tooby, and Cosmides
(2001) is another. The broad upshot of these considerations is clear:
appeals to developmental neurobiology do little to undermine the view
of mental architecture favored by evolutionary psychologists and their
Interest in modularity is not confined to cognitive science and the
philosophy of mind; it extends well into a number of allied fields. In
epistemology, modularity has been invoked to defend the legitimacy of a
theory-neutral type of observation, and hence the possibility of some
degree of consensus among scientists with divergent theoretical
commitments (Fodor, 1984/1990). The ensuing debate on this issue
(Churchland, 1988; Fodor, 1988/1990; McCauley & Henrich, 2006)
holds lasting significance for the general philosophy of science,
particularly for controversies regarding the status of scientific
realism. In philosophy of language, modularity has figured in
theorizing about linguistic communication, for example, in relevance
theorists’ suggestion that speech interpretation, pragmatic warts and
all, is a modular process (Sperber & Wilson, 2002). It has also
been used demarcate the boundary between semantics and pragmatics, and
to defend a notably austere version of semantic minimalism (Borg,
2004). Though the success of these deployments of modularity theory is
subject to dispute (e.g., see Robbins, 2007, for doubts about the
modularity of semantics), their existence testifies to the ongoing
relevance of the concept of modularity to philosophical inquiry across
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