## 1. What is a mental module?



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: 


1. Domain specificity
2. Mandatory operation
3. Limited central accessibility
4. Fast processing
5. Informational encapsulation
6. 'Shallow' outputs
7. Fixed neural architecture
8. Characteristic and specific breakdown patterns
9. 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, we will cluster most of the features thematically and
examine them on a cluster-by-cluster basis, along the lines of Prinz
(2006).



*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, pp. 245-246; italics in original)
> 



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 tend to persist even after the viewer is explicitly
informed about the character of the stimulus. In the Muller-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, below). 



![Mueller-Lyer diagram of lines](mueller-lyer.png)
Figure 1. *The Muller-Lyer illusion*.




Informational encapsulation is related to what Pylyshyn (1984, 1999)
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, SS2.1). Likewise, a system could be unencapsulated
relative to beliefs and utilities yet encapsulated relative to
perception; it's plausible that central systems have this
character, insofar as their operations are sensitive only to
post-perceptual, propositionally encoded information. Strictly
speaking, then, cognitive impenetrability is a specific type of
informational encapsulation, albeit a type with special architectural
significance. 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.



*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 (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.



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 tend to be
more costly for a system to compute, 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
*per se*, then, but highly theoretical concepts like PROTON,
which are too informationally specific and too computationally
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. A system is strongly localized just in case it is (a)
implemented in neural circuitry that is both relatively circumscribed
in extent (though not necessarily in contiguous areas) and (b)
dedicated to the realization of that system alone. Localization in
this sense goes beyond mere implementation in local neural circuitry,
since a given bit of circuitry could subserve more than one cognitive
function (Anderson, 2010). Proposed candidates for strong localization
include systems for color vision (V4), motion detection (MT), face
recognition (fusiform gyrus), and spatial scene recognition
(parahippocampal gyrus).



*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, 2000).



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, based on the notion of canalization, 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).
Other candidates include visual object perception (Spelke, 1994) and
low-level mindreading (Scholl & Leslie, 1999).


## 2. Modularity, Fodor-style: A modest proposal



The hypothesis of modest modularity, as we shall call it, has two
strands. The first strand of the hypothesis 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 modular. 



In this section, we assess the case for modest modularity. The next
section (SS3) will be devoted to discussion of the hypothesis of
massive modularity, which retains the positive strand of Fodor's
hypothesis while reversing the polarity of the second strand from
negative to positive--revising the concept of modularity in the
process.



The positive part of the modest modularity hypothesis 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. Roughly speaking, the product of sensory
transduction is raw sensory data. Input processing involves
non-demonstrative inferences from this raw 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, and those
systems in turn pass their outputs to systems responsible for the
production of behavior.



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
SS1. 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. 47-101.)


### 2.1. Challenges to low-level modularity



Fodor's claim about the modularity of input systems has been
disputed by a number of philosophers and psychologists (Churchland,
1988; Arbib, 1987; Marslen-Wilson & Tyler, 1987; McCauley &
Henrich, 2006). The most wide-ranging philosophical critique is due to
Prinz (2006), who argues that perceptual and linguistic systems rarely
exhibit the features characteristic of modularity. In particular, he
argues that such systems are not informationally encapsulated. To this
end, Prinz adduces two types of evidence. First, there appear to be
cross-modal effects in perception, which would tell against
encapsulation at the level of input systems. The classic example of
this, also from the speech perception literature, is the McGurk effect
(McGurk & MacDonald, 1976). 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/). Second, 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 the missing phoneme (the /s/ sound
in *legislatures*) has been deleted and replaced with the sound
of a cough (Warren, 1970). By hypothesis, this filling-in is driven by
listeners' understanding of the linguistic context. 



How convincing one finds this part of Prinz's critique, however,
depends on how convincing one finds his explanation of these effects.
The McGurk effect, for example, seems 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).
If speech perception is a multi-modal system, the fact that its
operations draw on both auditory and visual information need not
undermine the claim that speech perception is encapsulated. Other
cross-modal effects, however, resist this type of explanation. In the
double flash illusion, for example, viewers shown a single flash
accompanied by two beeps report seeing two flashes (Shams et al.,
2000). The same goes for the rubber hand illusion, in which
synchronous brushing of a hand hidden from view and a
realistic-looking rubber hand seen at the usual location of the hand
that was hidden gives rise to the impression that the fake hand is
real (Botvinick & Cohen, 1998). With respect to phenomena of this
sort, unlike the McGurk effect, there is no plausible candidate for a
single, domain-specific system whose operations draw on multiple
sources of sensory information.



Regarding phoneme restoration, 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 higher-level
contextual information. Hence, it's unclear whether the case of
phoneme restoration described above counts as a top-down effect. But
not all cases of phoneme restoration can be accommodated so readily,
since the phenomenon also occurs when there are multiple lexical items
available for filling in (Warren & Warren, 1970). For example,
listeners fill the gap in the sentences *The \*eel is on the
axle* and *The \*eel is on the orange*
differently--with a /wh/ sound and a /p/ sound,
respectively--suggesting that speech perception is sensitive to
contextual information after all.



A further challenge to modest modularity, not addressed by Prinz
(2006), comes from evidence that susceptibility to the
Muller-Lyer illusion varies by both culture and 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 Muller-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 Muller-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
for.



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. Given the observed
variation in how people see the Muller-Lyer illusion, it may be
that the visual system is modular in much the same way, with its
development is constrained by features of the visual environment. Such
a possibility seems consistent with the claim that input systems are
modular in Fodor's sense.



Another source of difficulty for proponents of input-level modularity
is neuroscientific evidence against the claim that perceptual and
linguistic systems are strongly localized. Recall that for a system to
be strongly localized, it must be realized in dedicated neural
circuitry. Strong localization at the level of input systems, then,
entails the existence of a one-to-one mapping between input systems
and brain structures. As Anderson (2010, 2014) argues, however, there
is no such mapping, since most cortical regions of any size are
deployed in different tasks across different domains. For instance,
activation of the fusiform face area, once thought to be dedicated to
the perception of faces, is also recruited for the perception of cars
and birds (Gauthier et al., 2000). Likewise, Broca's area, once
thought to be dedicated to speech production, also plays a role in
action recognition, action sequencing, and motor imagery (Tettamanti
& Weniger, 2006). Functional neuroimaging studies generally
suggest that cognitive systems are at best weakly localized, that is,
implemented in distributed networks of the brain that overlap, rather
than discrete and disjoint regions.



Arguably the most serious challenge to modularity at the level of
input systems, however, comes from evidence that vision is cognitively
penetrable, and hence, not informationally encapsulated. The concept
of cognitive penetrability, originally introduced by Pylyshyn (1984),
has been characterized in a variety of non-equivalent ways (Stokes,
2013), but the core idea is this: A perceptual system is cognitively
penetrable if and only if its operations are directly causally
sensitive to the agent's beliefs, desires, intentions, or other
nonperceptual states. Behavioral studies purporting to show that
vision is cognitively penetrable date back to the early days of New
Look psychology (Bruner and Goodman, 1947) and continue to the present
day, with renewed interest in the topic emerging in the early 2000s
(Firestone & Scholl, 2016). It appears, for example, that vision
is influenced by an agent's motivational states, with
experimental subjects reporting that desirable objects look closer
(Balcetis & Dunning, 2010) and ambiguous figures look like the
interpretation associated with a more rewarding outcome (Balcetis
& Dunning, 2006). In addition, vision seems to be influenced by
subjects' beliefs, with racial categorization affecting reports
of the perceived skin tone of faces even when the stimuli are
equiluminant (Levin & Banaji, 2006), and categorization of objects
affecting reports of the perceived color of grayscale images of those
objects (Hansen et al., 2006). 



Skeptics of cognitive penetrability point out, however, that
experimental evidence for top-down effects on perception can be
explained in terms of effects of judgment, memory, and relatively
peripheral forms of attention (Firestone & Scholl, 2016; Machery,
2015). Consider, for example, the claim that throwing a heavy ball
(vs. a light ball) at a target makes the target look farther away,
evidence for which consists of subjects' visual estimates of the
distance to the target (Witt, Proffitt, & Epstein, 2004). While it
is possible that the greater effort involved in throwing the heavy
ball caused the target to look farther away, it is also possible that
the increased estimate of distance reflected the fact that subjects in
the heavy ball condition judged the target to be farther away because
they found it harder to hit (Firestone & Scholl, 2016). Indeed,
reports by subjects in a follow-up study who were explicitly
instructed to make their estimates on the basis of visual appearances
only did not show the effect of effort, suggesting that the effect was
post-perceptual (Woods, Philbeck, & Danoff, 2009). Other purported
top-down effects on perception, such as the effect of golfing
performance on size and distance estimates of golf holes (Witt et al.,
2008), can be explained as effects of spatial attention, such as the
fact that visually attended objects tend to appear larger and closer
(Firestone & Scholl, 2016). These and related considerations
suggest that the case for cognitive penetrability--and by
extension, the case against low-level modularity--is weaker than
its proponents make it out to be. 


### 2.2. Fodor's argument against high-level modularity



I turn now to the dark side of Fodor's hypothesis: the claim
that central systems are not modular.



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
this:


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.
4. Belief fixation cannot be carried out by an informationally
encapsulated system. [from 2 and 3]
5. Modular systems are informationally
encapsulated.
6. Belief fixation is not modular. [from 4 and 5]


Hence:


7. Central systems are not modular. [from 1 and 6]



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 example, linking solar physics and
evolutionary theory. On Fodor's view, since scientific
confirmation is akin to belief fixation, the fact that scientific
confirmation is isotropic suggests that belief fixation in general has
this property. 



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; italics
> in original).
> 



Here again, the analogy between scientific thinking and thinking in
general underwrites the supposition that belief fixation is Quinean.




Both isotropy and Quineanness are features that preclude
encapsulation, since their possession by a system would require
extensive access to the contents of central memory, and hence a high
degree of cognitive penetrability. Put in slightly different terms:
isotropic and Quinean processes are 'global' rather than
'local', and since globality precludes encapsulation,
isotropy and Quineanness preclude encapsulation as well. 



By Fodor's lights, the upshot of this argument--namely, the
nonmodular character of 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 systems are unlikely to be associated
with local brain architecture, thereby rendering them unpromising
objects of neuroscientific study:



> 
> We have seen that isotropic systems are unlikely to exhibit
> articulated neuroarchitecture. If, as seems plausible,
> neuroarchitecture is often a concomitant of constraints on information
> flow, then neural equipotentiality is what you would expect in systems
> in which every process has more or less uninhibited access to all the
> available data. The moral is that, to the extent that the existence of
> form/function correspondence is a precondition for successful
> neuropsychological research, there is not much to be expected in the
> way of a neuropsychology of thought (Fodor, 1983, pp. 127).
> 



Second, and more importantly, global processes are resistant to
computational explanation, making them unpromising objects of
psychological study:



> 
> The fact is that--considerations of their neural realization to
> one side--global systems are per se bad domains for computational
> models, at least of the sort that cognitive scientists are accustomed
> to employ. The condition for successful science (in physics, by the
> way, as well as psychology) is that nature should have joints to carve
> it at: relatively simple subsystems which can be artificially isolated
> and which behave, in isolation, in something like the way that they
> behave *in situ*. Modules satisfy this condition;
> Quinean/isotropic-wholistic-systems by definition do not. If, as I
> have supposed, the central cognitive processes are nonmodular, that is
> very bad news for cognitive science (Fodor, 1983, pp. 128).
> 



By Fodor's lights, then, considerations that militate against
high-level modularity also militate against the possibility of a
robust science of higher cognition--not a happy result, as far as
most cognitive scientists and philosophers of mind are concerned.



Gloomy implications aside, Fodor's argument against high-level
modularity is difficult to resist. The main sticking points are these:
first, the negative correlation between globality and encapsulation;
second, the positive correlation between encapsulation and modularity.
Putting these points together, we get a negative correlation between
globality and modularity: the more global the process, the less
modular the system that executes it. As such, there seem to be only
three ways to block the conclusion of the argument:


1. Deny that central processes are global.
2. Deny that globality and encapsulation are negatively
correlated.
3. Deny that encapsulation and modularity are positively
correlated.



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 slightly more
appealing, but only slightly. The idea that central processes are
relatively global, even if not as global as the process of
confirmation in science suggests, 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 *any* 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 wide-scope encapsulated can draw
on exogenous information during the course of its operations--it
just cannot draw on *all* of that information. (Compare:
"No exogenous information is accessible" vs. "Some
exogenous information is not accessible.") This is encapsulation
in a weaker sense of the term than Fodor's. Indeed,
Carruthers's use of the term 'encapsulation' in this
context is a bit misleading, insofar as wide-scope encapsulated
systems count as unencapsulated in Fodor's sense (Prinz,
2006).



Dropping the (narrow-scope) encapsulation requirement on modules
raises a number of issues, not the least of which being that it
reduces the power of modularity hypotheses to explain functional
dissociations at the system level (Stokes & Bergeron, 2015). That
said, if modularity requires only wide-scope encapsulation, then
Fodor's argument against central modularity no longer goes
through. But given the importance of narrow-scope encapsulation to
Fodorian modularity, all this shows is that central systems might be
modular in a non-Fodorian way. The original argument that central
systems are not Fodor-modular--and with it, the motivation for
the negative strand of the modest modularity
hypothesis--stands.


## 3. Post-Fodorian modularity



According to the massive modularity hypothesis, the mind is modular
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, 2006), the
hypothesis 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 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, automaticity, neural localizability, and central
inaccessibility. Conspicuously absent from the list is informational
encapsulation, the feature most central to modularity in Fodor's
account. What's more, Carruthers goes on to drop domain
specificity, automaticity, and strong localizability (which rules out
the sharing of parts between modules) from his initial list of five
features, making his conception of modularity even more sparse
(Carruthers, 2006, p. 62). Other proposals in the literature are
similarly permissive in terms of the requirements a system must meet
in order to count as modular (Coltheart, 1999; Barrett & Kurzban,
2006). 



A second point, related to the first, is that defenders of massive
modularity have chiefly been concerned to defend the modularity of
central cognition, taking for granted that the mind is modular at the
level of input systems. Thus, the hypothesis at issue for theorists
like Carruthers might be best understood as the conjunction of two
claims: first, that input systems are modular in a way that requires
narrow-scope encapsulation; second, that central systems are modular,
but only in a way that does not require this feature. In defending
massive modularity, Carruthers focuses on the second of these claims,
and so will we.


### 3.1. The case for massive modularity



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:


1. Biological systems are designed systems, constructed
incrementally.
2. Such systems, when complex, need to be organized in a pervasively
modular way, that is, as a hierarchical assembly of separately
modifiable, functionally autonomous components.
3. The human mind is a biological system, and is complex.
4. Therefore, the human mind is (probably) massively modular in its
organization. (Carruthers, 2006, p. 25)



The crux of this argument is the idea that complex biological systems
cannot evolve unless they are organized in a modular way, where
modular organization entails that each component of the system (that
is, each module) can be selected for change independently of the
others. In other words, the evolvability of the system as a whole
requires the independent evolvability of its parts. The problem with
this assumption is twofold (Woodward & Cowie, 2004). First, not
all biological traits are independently modifiable. Having two lungs,
for example, is a trait that cannot be changed without changing other
traits of an organism, because the genetic and developmental
mechanisms underlying lung numerosity causally depend on the genetic
and developmental mechanisms underlying bilateral symmetry. Second,
there appear to be developmental constraints on neurogenesis which
rule out changing the size of one brain area independently of the
others. This in turn suggests that natural selection cannot modify
cognitive traits in isolation from one another, given that evolving
the neural circuitry for one cognitive trait is likely to result in
changes to the neural circuitry for other traits. 



A further worry about the Argument from Design concerns the gap
between its conclusion (the claim that the mind is massively modular
*in organization*) and the hypothesis at issue (the claim that
the mind is massively modular *simpliciter*). The worry is this.
According to Carruthers, the modularity of a system implies the
possession of just two properties: functional dissociability and
inaccessibility of processing to external monitoring. Suppose that a
system is massively modular in organization. It follows from the
definition of modular organization that the components of the system
are functionally autonomous and separately modifiable. Though
functional autonomy guarantees dissociability, it's not clear
why separate modifiability guarantees inaccessibility to external
monitoring. According to Carruthers, the reason is that "if the
internal operations of a system (e.g., the details of the algorithm
being executed) were available elsewhere, then they couldn't be
altered without some corresponding alteration being made in the system
to which they are accessible" (Carruthers, 2006, p. 61). But
this is a questionable assumption. On the contrary, it seems plausible
that the internal operations of one system could be accessible to a
second system in virtue of a monitoring mechanism that functions the
same way regardless of the details of the processing being monitored.
At a minimum, the claim that separate modifiability entails
inaccessibility to external monitoring calls for more justification than
Carruthers offers. 



In short, the Argument from Design is susceptible to a number of
objections. Fortunately, there's a slightly stronger argument in
the vicinity of this one, due to Cosmides and Tooby (1992). It goes
like this: 


1. The human mind is a product of natural selection.
2. In order to survive and reproduce, our human ancestors had to
solve a number of recurrent adaptive problems (finding food, shelter,
mates, etc.).
3. Since adaptive problems are solved more quickly, efficiently, and
reliably by modular systems than by non-modular ones, natural
selection would have favored the evolution of a massively modular
architecture.
4. Therefore, 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 (Fodor,
2000; Samuels, 2000; Woodward & Cowie, 2004). First, the premise
exemplifies adaptationist reasoning, and adaptationism in the
philosophy of biology has more than its share of critics. Second, it
is doubtful whether adaptive problem-solving in general is easier to
accomplish with a large collection of specialized problem-solving
devices than with a smaller collection of general problem-solving
devices with access to a library of specialized programs (Samuels,
2000). Hence, insofar as the massive modularity hypothesis postulates
an architecture of the first sort--as evolutionary
psychologists' 'Swiss Army knife' metaphor of the
mind implies (Cosmides & Tooby, 1992)--the premise seems
shaky. 



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
(2008):


1. Animal minds are massively modular.
2. Human minds are incremental extensions of animal minds.
3. Therefore, the human mind is (probably) massively modular.



Unfortunately for friends of massive modularity, this argument, like
the argument from design, is vulnerable to a number of objections
(Wilson, 2008). We'll mention two of them here. First,
it's not easy to motivate the claim that animal minds are
massively modular in the operative 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, a la Gallistel, 1990--adds up to less than
what's needed. The problem is that domain specificity is not sufficient for Carruthers-style modularity; indeed, it is not even one of the central characteristics of modularity in Carruthers' account. So 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.



Finally, we have the Argument from Computational Tractability
(Carruthers, 2006, pp. 44-59). For the purposes of this
argument, we assume that a mental process is computationally tractable
if it can be specified at the algorithmic level in such a way that the
execution of the process is feasible given time, energy, and other
resource constraints on human cognition (Samuels, 2005). We also
assume that a system is encapsulated if in the course of its
operations the system lacks access to at least some information
exogenous to it.


1. The mind is computationally realized.
2. All computational mental processes must be tractable.
3. Tractable processing is possible only in encapsulated systems.
4. Hence, the mind must consist entirely of encapsulated
systems.
5. Hence, the mind is (probably) massively modular.



There are two problems with this argument, however. The first problem
has to do with the third premise, which states that tractability
requires encapsulation, that is, the inaccessibility of at least some
exogenous information to processing. What tractability actually
requires is something weaker, namely, that not all information is
accessed by the mechanism in the course of its operations (Samuels,
2005). In other words, it is possible for a system to have unlimited
access to a database without actually accessing all of its contents.
Though tractable computation rules out exhaustive search, for example,
unencapsulated mechanisms need not engage in exhaustive search, so
tractability does not require encapsulation. The second problem with
the argument concerns the last step. Though one might reasonably
suppose that modular systems must be encapsulated, the converse
doesn't follow. Indeed, Carruthers (2006) makes no mention of
encapsulation in his characterization of modularity, so it's
unclear how one is supposed to get from a claim about pervasive
encapsulation to a claim about pervasive modularity. 



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 high-level cognition, but it invites skepticism,
especially given the paucity of empirical evidence directly supporting
the hypothesis (Robbins, 2013). For example, it has been suggested
that the capacity to think about social exchanges is subserved by a
domain-specific, functionally dissociable, and innate mechanism (Stone
et al., 2002; Sugiyama et al., 2002). However, it appears that
deficits in social exchange reasoning do not occur in isolation, but
are accompanied by other social-cognitive impairments (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
(Currie & Sterelny, 2000). The type of mindreading impairments
characteristic of Asperger syndrome and high-functioning autism, for
example, co-occur with sensory processing and executive function
deficits (Frith, 2003). In general, there is little in the way of
neuropsychological evidence to support the idea of high-level
modularity. 


### 3.2. Doubts about massive modularity



Just as there are general theoretical arguments for massive
modularity, there are general theoretical arguments against it. One
argument takes the form of what Fodor (2000) calls the 'Input
Problem'. The problem is this. Suppose that the architecture of
the mind is modular from top to bottom, and the mind consists entirely
of domain-specific mechanisms. In that case, the outputs of each
low-level (input) system will need to be routed to the appropriately
specialized high-level (central) system for processing. But that
routing can only be accomplished by a domain-general, non-modular
mechanism--contradicting the initial supposition. In response to
this problem, Barrett (2005) argues that processing in a massively
modular architecture does not require a domain-general routing device
of the sort envisaged by Fodor. An alternative solution, Barrett
suggests, involves what he calls 'enzymatic computation'.
In this model, low-level systems pool their outputs together in a
centrally accessible workspace where each central system is
selectively activated by outputs that match its domain, in much the
same way that enzymes selectively bind with substrates that match
their specific templates. Like enzymes, specialized computational
devices at the central level of the architecture accept a restricted
range of inputs (analogous to biochemical substrates), perform
specialized operations on that input (analogous to biochemical
reactions), and produce outputs in a format useable by other
computational devices (analogous to biochemical products). This
obviates the need for a domain-general (hence,
non-modular) mechanism to mediate between low-level and high-level
systems. 



A second challenge to massive modularity is posed by the 'Domain
Integration Problem' (Carruthers, 2006). The problem here is
that reasoning, planning, decision making, and other types of
high-level cognition routinely involve the production of conceptually
structured representations whose content crosses domains. This means
that there must be some mechanism for integrating representations from
multiple domains. But such a mechanism would be domain general rather
than domain specific, and hence, non-modular. Like the Input Problem,
however, the Domain Integration Problem is not insurmountable. One
possible solution is that the language system has the capacity to play
the role of content integrator in virtue of its capacity to transform
conceptual representations that have been linguistically encoded
(Hermer & Spelke, 1996; Carruthers, 2002, 2006). On this view,
language is the vehicle of domain-general thought. 



Empirical objections to massive modularity take a variety of forms. To
start with, there is neurobiological evidence of developmental
plasticity, a phenomenon that tells against the idea that brain
structure is innately specified (Buller, 2005; Buller and Hardcastle,
2000). However, not all proponents of massive modularity insist that
modules are innately specified (Carruthers, 2006; Kurzban, Tooby, and
Cosmides, 2001). Furthermore, it's unclear to what extent the
neurobiological record is at odds with nativism, given the evidence
that specific genes are linked to the normal development of cortical
structures in both humans and animals (Machery & Barrett, 2008;
Ramus, 2006). 



Another source of evidence against massive modularity comes from
research on individual differences in high-level cognition (Rabaglia,
Marcus, & Lane, 2011). Such differences tend to be strongly
positively correlated across domains--a phenomenon known as the
'positive manifold'--suggesting that high-level
cognitive abilities are subserved by a domain-general mechanism,
rather than by a suite of specialized modules. There is, however, an
alternative explanation of the positive manifold. Since post-Fodorian
modules are allowed to share parts (Carruthers, 2006), the
correlations observed may stem from individual differences in the
functioning of components spanning multiple domain-specific
mechanisms. 


## 4. Modularity and philosophy



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). The ensuing debate on this issue
(Churchland, 1988; Fodor, 1988; McCauley & Henrich, 2006) holds
lasting significance for the general philosophy of science,
particularly for controversies regarding the status of scientific
realism. Relatedly, evidence of the cognitive penetrability of
perception has given rise to worries about the justification of
perceptual beliefs (Siegel, 2012; Stokes, 2012). In ethics, evidence
of this sort has been used to cast doubt on ethical intuitionism as an
account of moral epistemology (Cowan, 2014). 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 relevance of the concept
of modularity to philosophical inquiry in a variety of domains.