• Wordless Thoughts and Non-Linguistic Minds•
A Study of Cognitive Representation Michael J. Yule
∙ Contents ∙ ∙1∙
◦ Abstract ◦∙2∙
◦ One ◦ On Thought and the Supposed Necessity of Language
∙3∙
◦ Two ◦On Cartographic Representation
∙7∙
◦ Three ◦ On Diagrammatic Representation
∙13∙
◦ Four ◦ On Linguistic Representation
∙18∙
◦ Five ◦ On the Cognitive Capabilities of Chimpanzees
∙20∙
◦ Six ◦On Linguistic Readiness
∙26∙
◦ Conclusion ◦ ∙29∙
1
◦ Bibliography and Works Cited ◦ ∙31∙
◦ Abstract ◦ There has been a prevailing tradition in much
of Western philosophy which holds language as the necessary
basis for cognition. Without language, it is argued, there
can be no thought. Yet there is such a great variety of
intelligent life that surrounds us; animals which operate
with efficiency and capability in an array of tasks,
sometimes even out-performing humans, that this assumption
seems outmoded. Humans and other animals represent the world
in a number of different ways using systems and vehicles
capable of supporting the complex cognition which has so
often been reserved solely for the linguistic human mind. I
will examine the ‘systematicity argument’ for the necessity
of language in order to outline two non-linguistic
representational systems – cartographic and diagrammatic –
and to compare them with the linguistic. I delineate how
each of these systems might function, their limitations and
2
advantages, in order to assess their theoretical capacity
for cognitive representation. My concern is to ground all
discussion in empirical scientific research, and hence I
will examine the possibility of Savannah Elephant use of
cartographic vehicles, and of Baboon use of diagrammatic
representation. In the latter sections, I take the
Chimpanzee as a case study, assessing their cognitive
capacity in order to highlight the level of higher-order
thought of which a non-linguistic animal is capable. Against
a backdrop of this, and our own evolutionary history, I
argue that rather than language being necessary for thought,
a pre-existing higher-order cognitive architecture is
necessary prior to the advent of protolanguage.
◦ One ◦
On Thought and the Supposed Necessity of Language
3
For the purposes of this essay, what I refer to
as thought from hereon will be what might be understood as
‘higher-order’ or conceptual thought, such as the abilities
of reasoning, abstraction and conceptualisation; this
genuine thought is representational and stimulus-independent.
But, this level of cognition is one end of a scale, a matter
of degree. All manner of animals possess a central nervous
system which processes inputs and outputs - systems which
range in complexity from the mere 302 neurones which enable
the worm, Caenorhabditis elegans, to actively respond to its
environment all the way up to the 100 billion neurone super-
structure that is the human brain.1 I do not wish to claim
that Caenorhabditis elegans is a rational being capable of
love, hate and numb apathy for its fellow creatures, or even
that it is truly thinking at all, but it is my aim in this
section to show that this cannot be ruled out solely by
virtue of the worm’s lack of a linguistic system.
Philosophical examination of thought and cognition must be
informed by the sciences if it is to have any hope of being
more than mere ivory-tower musings. The fact at a base
1 Carl Zimmer, ‘100 Trillion Connections’, Scientific American, http://www.scientificamerican.com/article/100-trillion-connections/
4
level, the human brain and the worm’s nervous system are
both neural networks means that in approaching the study of
the mind and thought we must have an awareness of this great
scale of increasing complexity rather than regarding the
human brain as ‘special’ or distinct from others in the
animal kingdom.
Evidently, there is a great distance along this
scale before we reach an animal such as Pan troglodytes (the
chimpanzee, which I will offer as a case study in Section
Five) capable of performing a vast array of complex tasks.
But it seems clear to me that such abilities and processes
are all a matter of degree and we should not rule out in
principle the assignment of cognitive qualities often
withheld from nonhuman animals. This has been a mistaken
first step, I feel, in much of the great tradition of
Western philosophy. This is in part due to the historically
religious sentiment that underpinned much of Western
thinking; man was made in God’s image and hence thought of
as separate and above beasts. On top of this, language is
unique to humans, and hence has been taken to be a hallmark
of intelligence and separation from animals. Given this and
5
the remarkable power of the human brain it is easy to assume
a direct correlation, and that has led to the truly glorious
status that language has been awarded in a great deal of
Western philosophy at the expense of much meaningful
discussion of, and value for, the minds of non-linguistic
animals.
The classic argument for thought necessarily
being language-like, as Elisabeth Camp points out, has been
articulated both by more rationalist leaning and by
empirical philosophers; it is based upon the systematicity of
thought.2 Camp offers a condensed account of this Language of
Thought argument:
1. There are systematic relations among thecontents that a thinker can represent and reasonabout.
2. Systematic relations in content must bereflected by correlative structure in athinker’s representational and reasoningabilities.
3. Structured representational abilities require asystem of representational vehicles which arecomposed of recurring discrete parts combinedaccording to systematic rules.
4. Any system of representational vehicles composedof recurring discrete parts according tosystematic rules is a language.
2 Elisabeth Camp, ‘Thinking With Maps’, Philosophical Perspectives 21:1, (Oxford: Wiley-Blackwell, 2007); p. 146.
6
Therefore: there must be a language of thought.(Camp, 2007, p.146)
Systematicity can be framed either as a normative claim
about the nature of thought or as an empirical observation.
It seems clear that the thoughts and concepts we employ are
systematically related; I can apply the concept ‘sad’ to any
number of people and understand that they share a quality. I
can entertain the thought ‘Sarah saddens Sasha’, and then
make sense of ‘Sasha saddens Sarah’. The fact that we are
capable of reasoning also reveals the systematic relations
in thought; Camp states that ‘the reason that the transition
from believing that a is F, b is F, and a is not b to believing that at
least two things are F is justified is that there are systematic,
truth- and justification-preserving relations in the
contents of those beliefs’.3 The argument also presents us
with the ‘Generality Constraint’ which Evans defines as
follows: ‘if a subject can be credited with the thought that
a is F then he must have the conceptual resources for
entertaining the thought that a is G, for every property of
being G of which he has a conception’.4 This constraint is
3 Ibid. p. 147. 4 Evans, as quoted by Camp, (2007); p. 148.
7
useful in distinguishing between the thought that is the
topic of this essay and simple ‘proto-thought’.
There are, of course, a number of objections to
each of the premises but it is the fourth which troubles me.
It can be understood as a definition; that if a creature
thinks systematically then its representational vehicles
constitute an inner ‘language’ of some kind, but this is not
the philosophically interesting claim, as that inner-
language might employ a variety of representational
vehicles. The other interpretation is to understand Premise
4 as either the claim that systematic thought must be
syntactically structured in the same way as language, or,
the stronger claim that thought requires an external natural
language.5 I will focus on the weaker of these two more
interesting claims, as its refutation entails that of the
stronger. At best, the argument establishes that a mind
capable of operating and producing systematic thoughts which
satisfy the Generality Constraint must have a systematic and
recombining representational system. Rather than necessarily
linguistic, in theory, that system could be anything that is
5 See Davidson for the stronger claim.
8
capable of representing content with combinatorial formal
features, such as a diagram or map. Therefore at the
theoretical level, we ought not to immediately assume the
necessity of language for systematic thought.
9
◦ Two ◦
On Cartographic Representation Maps, like language, have both
structural/syntactic features, and content/semantic
features. There are systematic rules of syntax which govern
recombinable abstract content symbols - such as a cross for
a church or a blue line for a river – which means that maps
satisfy the Generality Constraint. A thinker using a
cartographic system to represent any given set of roads,
buildings and train stations can recombine those features
and represent them in any spatial configuration. The syntax
and semantic features and their corresponding rules are
entirely different from linguistic representation and a
cartographic system is exactly that – systematic; this means
that Premise 4 (above) is quite simply false.
10
Arguably in terms of fundamental structure, maps
are simply sentences in strange notation but Elisabeth Camp
notes that although, like language, maps employ an arbitrary
semantics there is a key structural difference. A map might
employ the arbitrary symbol of a cross (which could easily
be a pair of praying hands, for example) to represent the
location of a church, and the similarly arbitrary blue lines
to indicate rivers. These semantic components are combined
according to syntax of spatial configuration.
Linguistically, ‘the church is between two rivers’ also
employs arbitrary semantics (‘xvqzw’ could correspond to the
same concept as ‘church’) but the components are arranged
according to logical, sentential syntax. As Camp states,
despite both systems employing arbitrary constituents, for
maps ‘the principle according to which those constituents
are combined relies on a spatial rather than purely logical
isomorphism between the structure of those constituents and
the structure of the corresponding elements in the content’.6
This cements cartographic representation as sufficiently
distinct and establishes it as both non-linguistic and
6 Camp, (2007); p. 159.
11
systematic. In this section I will examine how such a system
might function, assess the limits of its capacity for
representation and reasoning and its practical application
beyond the realm of the theoretical.
A map is significantly more efficient for
specific types of reasoning than sentences; it is capable of
representing spatial relationships between each and every
icon simultaneously and in an immediately accessible way.
This is less cumbersome than the time consuming process of
deducing such relations from a list of descriptive
sentences, which is error-prone. This processing advantage
is obvious from our use of road maps for navigation rather
than hefty tomes of sentences describing all the relevant
spatial relationships. In order to function for higher-order
thought, however, a cartographic system must be capable of
representing the truth-functional relations of conjunction,
disjunction, negation and conditionalisation. Conjunction on
a single map is already achieved and has no need of further
explicit representation; for example, ‘A ∧ B’ would simply be
the presence of both the A icon and the B icon. For a
thinker using multiple maps, conjunction must be understood
12
as relations between these planes in order to make use of
relevant or contiguous information across multiple maps.
Camp notes that, ‘these higher-order relations between maps
can be captured in implicit rules for using the maps, but
they can’t themselves be represented explicitly on any map’.7
A set of implicit syntactic rules would govern what the maps
look like and how they relate to each other, enabling them
to be used in conjunction and to relate the information
represented across different maps. There is no reason to
think that this would put any significant extra strain on
cognitive resources as a set of rules is required for any
representational system, such as grammar for language. For
maps, there might be a rule that if two maps are bordered in
blue then they are both relevant to the thinker’s current
location, such as a city, despite not being spatially
contiguous.
The other truth-functional relations present more
of an issue but in theory, maps are capable of such
representation. Camp lays out some possible ways in which
this could be achieved which I have summarised here:
7 Ibid. pp.162-3.
13
Disjunctive and conditional elements: non-spatialicons relating distinct maps, icons which isolatethe salient differences, eg:
Red flashing lights around two ‘Bob’ iconsto indicate Bob could be at either of thoselocations.
Solid blue lights to represent anantecedent, flashing blue lights toindicate its consequent.
Negation and negative information: sets ofcorresponding icons to represent that one or theother state obtains, coloured icons andbackgrounds to represent positive or negativeinformation, eg:
Grey to represent neutrality, black torepresent certain presence and white torepresent certain absence with correlativeshades in between.
Sets of icons with alternately flashingyellow lights to indicate one state oranother.
(See: Camp, 2007,pp. 163-5)
Theoretically then, higher-order relations can be
represented but it seems that the efficiency advantage of
maps is beginning to wane. Consider trying to represent a
large number of relationships across multiple maps of
incongruous spatiality through an indefinite period of time
rather than as a fixed state of affairs. With every added
type of information, new and distinct alterations to icons
and backgrounds are needed; this would complicate and
clutter the representation, making even the simple spatial
14
relations cognitively costly to discern. This is not to say,
however, that it is beyond the realm of possibility; even
intentionality and theory of mind could be represented
cartographically, with a thinker holding distinct maps for
their interpretation of different thinker’s spatial beliefs.
If another individual did not know of the presence of a
gemstone in a room, but I did, I might represent a map of
the room from what I believe to be their perspective, with
that locational information omitted. But despite this, given
the limited cognitive resources of all animals, efficiency
is paramount and it seems unlikely that in the natural world
a purely cartographic representational system would be
capable of supporting a human-like range of thoughts.
For an animal with a more limited range of
cognitive needs, cartographic representation is a system
capable of supporting conceptual thought processes. It seems
plausible, for example, that elephants rely on a largely
cartographic representation of the world around them and
there is a great deal of truth in the old adage that
‘elephants never forget’. African Savannah elephants travel
vast distances for food and water; given their desert
15
environment, a precise locating ability is the difference
between life and death. Byrne and Bates cite studies in
which elephants ‘have been described travelling hundreds of
kilometres to arrive at remote water sources shortly after
the onset of a period of rainfall […] along routes that
researchers believe had not been used for many years’.8 This
indicates that more than simple memory, elephants are
capable of abstract representations of places from their
distant past and conceptually understand the cause and
effect relationship of rainfall upon such areas, timing with
precision when precipitation will arrive. It seems to me
that this suggests elephants represent conditionals of the
kind ‘if it rains in location X, then that location Y will
be suitable’ and the corresponding negation (as the
elephants do not simply wander aimlessly to these areas
without the antecedent of rain). Further to this, Byrne and
Bates highlight that, ‘families with older matriarchs range
over larger areas during droughts, apparently drawing on the
knowledge of the older females about the locations of
8 Richard W. Byrne & Lucy A. Bates, ‘Elephant cognition: what we know about what elephants know’, The Ambolesi Elephants, eds. Cynthia J. Moss, Harvey Croze & Phyllis C. Lee, (Chicago: University of Chicago Press, 2011); p. 175.
16
permanent, drought-resistant sources of food and water’.9 The
fact the elephants do this only in times of drought without
‘trial-and-error’ visiting their usual sources of water
suggests that they are capable of responding to the
condition of ‘drought’ and conceptually reasoning that many
of their usual sources will not be suitable at that time.
With the strong social structure of elephant
families playing a key role in their survival, it is also
important that elephants know their locations. Again, this
is an extraordinary ability noted by Byrne and Bates whose
studies show that elephants track the positions of up to 30
individuals. When urine samples of individuals who had been
travelling behind the test subject were placed in its path,
the elephants responded with far more interest and apparent
confusion than to samples from individuals who were in front
of them.10 This indicates the elephant’s ability to recognise
information which is contradictory to its own
representation; the urine simply should not be there.
Attempting to ‘translate’ all this constantly changing
location information about individuals and water/food
9 Ibid.10 Ibid. p.176
17
sources into language would be a mammoth task - impractical
and inefficient. With spatial relations being so important
to elephant survival, a cartographic representational system
would be superior within the specific domain of needs.
In theory, cartographic systems meet the
requirements of the LoT argument and whilst maps make more
efficient vehicles within a narrow domain, cartographic
systems lack practical general application for organisms
with greater cognitive needs. Even given limitless cognitive
resources however, Camp notes the problem with a directly
isomorphic syntax is that ‘there are only so many non-
spatial but still physical ways to manipulate icons. To
represent multiply embedded higher-order relations, and to
represent multiple higher-order relations of the same kind
on a single map we will eventually need something like
sentential notation’.11 There are finite manipulations that
can be applied to a map because it is not recursive in the
way language is. Once flashing red icons have been used to
represent a conditional, they cannot be used to represent
anything else; in language however, ‘if…then’ can be re-used
11 Camp, (2007); p. 168.
18
for any conditional. The limits of cartographic
representation therefore, are not the complexity of thought
it can support, but the range of domains.
◦ Three ◦
19
On Diagrammatic Representation
The primary issue with a purely cartographic
representational system is the largely direct isomorphism of
its syntax restricting efficient functionality to the domain
of spatial relations. For diagrams, however, whilst the
syntax of each individual diagram is restricted to a domain
or small set of relations, in theory diagrams could be
constructed for any conceivable relation. Quantificational
information is perhaps impossible for cartographic vehicles
to represent; as Camp states, ‘the bare existential
information that something or other, somewhere or other, is F falls
below the minimum bound of cartographically representable
information’.12 Equally at the other extreme, anything with a
universal quantifier is too much information for a map.
There is no such issue for diagrammatic systems, consider
the following example:
12 Camp, (2007); p. 165.
20
Fig. 1
Along the x axis, left to right, runs quantity from ‘at least
one’ to ‘all’ for the domain G. The positions of F, D and H
along this correspond to their quantity within domain G. This
highly simplistic, one dimensional diagram, using the
existential and universal quantifiers, is capable of
representing that ‘at least one F is G’, ‘numerous Ds are G’ (the expanse
between is easily capable of both indefinite and definite
quantities - numbered divisions could be added to give ‘712
Ds are G’), and ‘all Hs are G’. On top of this the comparative
relations between F, D and H are also presented with clarity,
even without a definitive number we are able to represent
that ‘more Ds are G than Fs are G’, for example. This information
is efficiently represented in a more intuitive and
21
immediately accessible way than that of which linguistic
vehicles are capable.
Additional dimensions could be added to Fig. 1 in
order to represent these relations across further
categories; for example, any given state and location: ‘all Hs
at location M were G and in state Q’. This could be achieved by adding
a y axis, with a number of locations marked along it, and a z
axis with a number of states (for example, emotions) along
its length. H would therefore be plotted according to three-
dimensional coordinates with a value for each axis. But it
is here that we reach the limit of any diagrammatic
representation because they still rely on basic geometry and
hence cannot represent more than the three perceivable
dimensions. Using multiple corresponding diagrams, a further
aspect such as time can be introduced, with each individual
diagram representing the state of affairs at a specific
point or period in time. Like with multiple maps, these
diagrams would require implicit relational use rules but the
advantage here is that they could be represented with
‘higher-order diagrams’. For example, a Venn diagram might
be used to represent rules for which diagrams to use:
22
Fig. 2
Fig. 2 is a higher-order diagram which represents a
thinker’s 7 first order diagrams which all relate to food
sources, explicitly representing that they share a domain.
Strictly speaking, in practice there would be other
arbitrary symbols to replace the words I have used for ease
of presentation here. This higher-order diagram represents
the diagrams according to two weather conditionals and
indicates as a rule to the thinker which diagrams to use if
either or both those states pertain. For example, if the
conditions were both raining and freezing then the thinker
would refer to d.2 and d.5 in order to find food. Given that
there are few rules about what any particular diagram might
23
look like, and theoretically infinite tokens of each type
could be utilised by a thinker, then in theory, diagrammatic
representation would be capable of supporting the full range
of human cognition. However, there are practical problems
with this.
The sheer number of types of diagram,
and their individual tokens that would be required to
represent the full spectrum of human cognition is
overwhelming and would necessitate a vast amount of ‘storage
space’. Relying on diagrammatic representation for a wide
range of domains would likely be incredibly draining on
cognitive resources. Arguably, this could simply be down to
contingent facts about human brain structure – perhaps this
would involve too much ‘imaging’ for the visual cortex to
compute at the same time as perceiving the world. However,
it certainly seems to me that the greater the range of
domains and relations, the more cumbersome diagrammatic
representation becomes, losing the efficiency advantage it
has over language. Perhaps an artificial intelligence with
theoretically infinite processing resources and storage
space would be able to exploit the representational
24
efficiency of token diagrams but it seems unlikely that this
would be possible for a natural mind. In principle though,
it must be reinforced, a diagrammatic representational
system would be at least as functional as a linguistic one,
with few conceivable limitations, fully capable of
supporting higher-level cognition.
For an animal with a narrow range of cognitive
needs, a small number of diagrams would provide efficient
vehicles for higher-level cognition. Diagrammatic
representation is arguably the best explanation for the
complex hierarchical social structure of Baboons. Camp
assesses Baboon Metaphysics (2007) in which, she argues, Cheney
and Seyfarth implicitly make the claim that ‘baboon
cognition [is] distinctively language-like’.13 From their study
of the extraordinary level of complexity in baboon social
structure, Cheney and Seyfarth conclude that baboon thought
exhibits the higher-level cognitive properties of being
representational, hierarchically structured, rule-governed,
propositional and independent of sensory modality.14 It is13 Elisabeth Camp, ‘A language of baboon thought?’, The Philosophy of Animal Minds, ed. Robert W. Lurz, (Cambridge: Cambridge University Press, 2009); p. 113.14 My own summary of Cheney and Seyfarth (2007) section quoted by Camp, (2009); p. 113.
25
these qualities, it is argued, that make baboon thought
necessarily linguistic. Once again, this relies on the same
unjustifiable assumption of Premise 4 of the LoT argument as
delineated in Section One. It is certainly possible to
contest any of these properties, offering alternative
explanations but even if we accept that they are exhibited
to at least some degree, these properties do not necessarily
make baboon thought language-like as I have shown other
representational systems as being sufficient to meet these
criteria. Camp notes however, that in other cognitive areas,
baboons appear to lack these abilities entirely; they are
unable to learn simple sign language and ‘their very lack of
theory of mind constitutes another domain where they don’t
manifest an ability to think hierarchically structured
thoughts which would be quite useful for them’.15 If baboons
were using a linguistic representational system, eo ipso non-
domain-specific and highly flexible, would make it
incredibly unlikely that they would only be capable of
applying it to social structure. It is much more likely that
baboons employ a domain-specific diagrammatic representation
15 Camp, (2009); p. 125.
26
module for social structure; as Camp states, ‘it would be
more parsimonious to explain baboons’ cognitive abilities by
hypothesizing that they employ a tree-like structure’, the
combinatorial principle of which ‘has a dedicated
significance, of dominance’.16 Granting the qualities that
Cheney and Seyfarth posit to even a minimal degree, baboon
social structure is arguably a natural-mind example of a
representational system which is at least non-linguistic,
and likely diagrammatic, supporting higher-level cognition.
◦ Four ◦
On Linguistic Representation
16 Ibid. p. 124.
27
It has now been established that both in theory
and in practice, non-linguistic representational systems can
function and act as vehicles for higher-level cognition, and
therefore that Premise 4 of the LoT systematicity argument
is false. The most significant difference between a
diagrammatic or cartographic system, and a linguistic
system, is not in the kinds of thought they can support, but
in the scope. Cartographic vehicles are to a major degree
directly isomorphic in relation to the spatial
configurations in the world represented which makes them
highly efficient and capable for representing spatial
relations but comes with increasing difficulty and a gradual
loss of this processing advantage as more complex elements
and a broader range of relations are introduced.
Diagrammatic representation holds a similar advantage in
efficiency of representation on individual diagrams, or
collections of related token diagrams. Although diagrams are
representations at a higher level of abstraction than maps,
the syntax makes diagrams useful only for specific tasks
within a narrow domain, though certainly one which is far
wider than for the cartographic. Whilst at a purely
28
theoretical level this is not a problem - a theoretical
thinker could employ any number of different diagrams – in
the natural world it seems unlikely that this would be
practical given the huge amount of cognitive resources that
would be required to rely solely upon diagrammatic vehicles.
What makes language unique amongst these vehicles
is that although in domain-specific tasks it may be more
cumbersome, linguistic vehicles are capable of supporting
thought across a much broader range of tasks and domains due
to the lack of isomorphic relation to what is being
represented. Language uses an abstract, indirect syntax,
meaning that the structure is not directly related to
features of what it represents (as opposed to spatial
location for maps, and the indirect use of geometry for
diagrams). Coupled with an arbitrary semantics, this leaves
it relatively unrestricted in what it can represent. In
addition, language is recursive; it uses the same rules and
classes of symbols regardless of the domain being
represented. If a thinker’s needs are sufficiently wide-
ranging it is therefore less cumbersome and draining on
cognitive resources than a diagrammatic system. It is this
29
flexibility and general applicability which are the
distinctive features of linguistic thought, not that it is
the only type of ‘genuine thought’, or that language is the
only vehicle capable of supporting higher-level cognition.
◦ Five ◦
30
On the Cognitive Capabilities of Chimpanzees
Pan troglodytes – chimpanzees - exhibit a great deal
of complex behaviour indicative of higher-order cognitive
capacities, including their complex social structures and
well documented tool use.17 The use of tools indicates a
relatively high level of abstract thought as it requires the
thinker to have fore-thought, understand cause and effect,
and it means the thinker must be goal-seeking and problem-
solving. At the symposium ‘The Mind of the Chimpanzee’ in
2007, over 300 scientists presented and reviewed the
cumulative research of the past few decades and noted an
array of cognitively complex behaviours, including hunting,
self-recognition, mourning, and even caring for a group
member with Cerebral Palsy.18 These findings have even led to
a growing movement in ethics for the consideration of
chimpanzees and some other animals as non-human persons. Due
to the space constraints of this essay, I will focus on
17 For a recent example see - Mathias Osvath, Helena Osvath, ‘Chimpanzee (Pan troglodytes) and orangutan (Pongo abelii) forethought’, Animal Cognition 11:4, (October 2008); pp. 661-674.18 John Wilford, ‘Almost Human and Sometimes Smarter’, The New York Times, (17 April 2007).
31
recent evidence for theory of mind and the related trait of
metacognition. This is a much more contentious attribution
and hence, if the evidence is suggestive of this even to
some degree, then it is a great step in showing the extent
of the non-linguistic mind’s capability. Some might argue
that metacognition is necessary in order to have theory of
mind, and therefore that showing chimpanzees to have the
latter necessitates their having the former; this is a line
of argument I will not pursue here though it does have some
plausibility. I will then move onto domain-specific tasks in
which chimpanzees outperform humans in order to examine the
cognitive costs and benefits of differing modes of primary
representation.
There has been much to suggest that chimpanzees
may have theory of mind, understand intentionality and
ascribe these attitudes to others. The research of the last
few decades has revealed that ‘theory of mind’ is not a
simple attribute that a creature may have or not have, but
that there are many aspects of how animals understand one
another.19 This provides support for the view I delineated in
19 Josep Call and Michael Tomasello, ‘Does the chimpanzee have a theory of mind? 30 years later’, Trends in Cognitive Science 12:5, (May 2008); pp.
32
Section One and which I wish to maintain, namely that
cognition ought to be seen as a matter of degree. Even a
very basic chimpanzee theory of mind would be of great
significance because being able to attribute knowledge or
lack thereof to another chimpanzee would require a high
level of systematic thought, achieved by non-linguistic
representation.
Call and Tomasello review a large number of
studies, of varying methods and aims, all of which fall
under the category of theory of mind. They argue that ‘there
is solid evidence from several different experimental
paradigms that chimpanzees understand the goals and
intentions of others, as well as the perception and
knowledge of others’ but that ‘there is currently no
evidence that chimpanzees understand false beliefs’- that is
to say, chimpanzees do not understand that they, or another
individual, may possess a belief that is false rather than
simply understanding and ascribing the presence or absence
of a belief.20 Their balanced outlook is attractive because
it does not try to force strong conclusions based on any
187-192. 20 Ibid., p. 187.
33
pre-existing bias, but instead relies upon the data thus
far. Call and Tomasello delineate many characteristics about
chimpanzee cognition from over 30 studies, a number of which
I have selected below:
Gaze following
1. Follow gaze on the basis of face/eye direction2. Check back with gazer if nothing relevant at
target location3. Ignore distracting objects on the way to target
location4. Move to the side of opaque barriers to view target
location5. Understand that gaze stops at an opaque barrier
Gestural communication
6. Use visual gestures mostly whenconspecifics/experimenter are oriented to them
7. Position oneself to gesture in front of others 8. Face/eye orientation of recipient determine
gesture production
Food competition
9. Pick the food that a dominant individual orexperimenter cannot see
10. Visually/auditorially conceal approach tofood
11. Take food that a dominant individual did notsee being hidden
12. Understand that if competitor picks first, hewill have chosen the food he saw (not food he didnot see)
34
Getting/finding food
13. Leave earlier and beg more intensely from anexperimenter who is unwilling as opposed to unableto deliver food
14. Select the box acted on intentionally (eg.lid being lifted and replaced) versus accidentally(box being knocked by experimenter)
Reacting to a partner’s actions
15. Give the object that the experimenter istrying to reach
16. Take the food that a competitor is trying toreach
17. Anticipate where experimenter is going basedon potential goals available
18. When food is stolen retaliate against thief,not against innocent receiver of stolen food
Imitation
19. Produce target action based on observing afailed attempt
20. Copy intentional actions more often thanaccidental actions
21. Selectively copy freely chosen acts but notthose forced by circumstances
(see: Call & Tomasello, 2008,pp. 198-90)
The exhibition of these behaviours strongly suggests that
chimpanzees are capable of understanding the intentions and
knowledge of others, and of attributing mental states.
Whilst there has been no evidence so far to suggest that
they understand false beliefs, these behaviours and the
35
underlying cognition they suggest amount to what may be
termed a ‘proto-theory of mind’.
Sceptics are reluctant to attribute any such
qualities to animal cognition and have argued that such
behaviour is better explained by simpler cognition such as
‘behaviour-reading’ as opposed to ‘mind–reading’. Carruthers
grants that animals have thought, but that it can be
explained in terms of first-order desires rather than
higher-order cognition. He argues this on the basis that
there is no reason to think that cognition, to the level of
theory of mind, should be easy to come by through
evolutionary development. On the one hand, this
consideration is certainly the right view to take; we must
respect this complexity and care should be taken not to push
conclusions further than the data allows. But equally, there
is no reason at all to think that just because a proposed
theory of mind isn’t as complex as the human one, that it
doesn’t constitute a genuine theory of mind. Carruthers’
scepticism and rigorous analysis of studies into chimpanzee
cognition, questioning both methodology and conclusions, has
been a significant driving force in studies recently with
36
researchers taking on board his comments and revising study
techniques and tests.
One such example is a 2013 study by Beran et al.
into information-seeking behaviour in chimpanzees; test
subjects recognised when they did not have the relevant
information and would search for it in order to name the
food in a concealed container.21 The chimpanzees had to
correctly name the food category, using indicatory symbols,
in order to receive it on instances when they had seen the
food placed into the container, or when this was done behind
a screen. The study involved two experiments, the first of
which used a methodology Carruthers had previously objected
to arguing that for the results, ‘all we need to assume, in
fact, is that the animal possesses […] first-order mental
states’ – that the chimpanzees were simply acting according
to learned behavioural rules.22 The second was designed
specifically to discount the possibility that the
chimpanzees were simply acting along a first-order
behavioural rule and the results showed little deviation
21 Beran et al., ‘Language Trained Pan troglodytes Name What They Have Seen but Look First at What They Have Not Seen’, Psychological Science (March2013); pp. 1-7. 22 Carruthers, (2008).
37
from Experiment 1; they write, ‘again they responded
proficiently, even on the earliest trials’, ‘chimpanzees
effectively sought information when it was needed and made a
response immediately when information was already
available’.23 This shows chimpanzee awareness of when they
know or don’t know a relevant piece of information. Call and
Tomasello also respond to similar objections to Carruthers’,
but agree that varying methodology has largely rendered such
criticism untenable; they state that, ‘there are now in many
cases multiple experimental paradigms all aimed at a single
psychological state – each presenting chimpanzees with a
highly novel problem – that makes the positing of learned
behavioral [sic] rules a difficult explanatory strategy’.24
The weight of evidence suggests then, that we ought to
conclude that chimpanzees have at least to some degree a
proto-theory of mind and that the conceptual cognition
underpinning this is sufficient that, as a non-linguistic
animal, the chimpanzee refutes the argument that
systematicity requires language.
23 Beran et al., (2013) p. 6.24 Call & Tomasello, (2008); p. 187.
38
Another interesting aspect of chimpanzee
cognition is that in certain tests, they out-perform humans;
this is suggestive of the domain-specific advantages a non-
linguistic representational system confers. At the Primate
Research Institute in Kyoto, Inoue and Matsuzawa compared
chimpanzee and human working memory.25 In an experiment, both
humans and trained chimpanzees were placed in front of a
screen upon which the numerals 1-9 appeared non-sequentially
for a brief time before being covered up by white squares.
The test subject then had to press each of the squares in
numerical order corresponding to the numbers previously
shown. It was found that as the time the numbers were shown
for was decreased, human accuracy rates decreased rapidly to
the point of failure, whereas chimpanzees continued to
respond correctly with ease long after the point of human
failure. Dr. Matsuzawa said of the results that this
suggests a ‘trade-off’ in early humans, ‘they lost the
immediate memory and, in return, learned symbolization, the
language skills’26 This lends support to my argument that the
25 Sana Inoue and Tetsuro Matsuzawa, ‘Working memory of numerals in chimpanzees’, Current Biology 17:23, (December 2007); pp. R1004-5. 26 Matsuzawa, as quoted by Wilford, (2007).
39
domain-specific advantages of non-linguistic
representational systems are lost in a linguistic system
with greater general applicability.
The weight of evidence suggests that
chimpanzees have significant cognitive capacity for higher-
order thought and as non-linguistic animals they are an
important example of the extent to which non-linguistic
representational vehicles may be used in the natural world.
The findings of research into chimpanzee cognition continue
to move in the direction of greater cognitive abilities.27
Philosophy needs to keep up with this progression in the
sciences and to have a greater appreciation for the
importance of non-linguistic minds for philosophical
examination. Chimpanzees represent an empirical rebuttal
against the outmoded claims that thought is necessarily
linguistic and that non-linguistic minds are incapable of
higher-order thought; language is not the only hallmark of
intelligence.
27 Richard Wrangham, as quoted by Wilford, (2007).
40
◦ Six ◦
On Linguistic Readiness
Researchers have repeatedly tried to teach human
language to chimpanzees, with mixed results. Washoe, a
chimpanzee cross-fostered by researchers in the 1960s, was
taught a simplified version of American Sign Language. She
quickly began to use a few signs in her first few months and
eventually, after 51 months she was able to use 132
different signs and could understand many more from
researchers.28 Finegan notes that further to this, when other
chimpanzees raised in a similar manner were moved to a
different institute, ‘an infant chimp named Loulis acquired
at least 47 signs that had no source other than the signings
of his fellow chimps’.29 It is unclear whether this was a
result of active teaching or simply copying, but is
nevertheless remarkable. There are many who are sceptical
about such results, Finegan states that there are those who
28 Edward Finegan, ‘Do Only Humans Have Language?’, Language: Its Structure and Use, 7th Edition, (Cengage Learning, 2014) pp. 17-2029 Finegan (2014); p. 19.
41
argued that ‘the sequences of strings produced by chimps are
not productive sentences that parallel those created by
human children’.30 With Project Nim, researchers attempted to
teach sign language to another chimpanzee but Nim failed to
master more than a few signs and never initiated
communication.31 Even taking a sceptical stance, however, it
appears that chimpanzees possess to a degree at least some
of the cognitive abilities needed to learn language in order
to even make sense of a few basic signs. There is
significance to this because, if even a creature with the
high cognitive capacity of a chimpanzee struggles to learn
language, it suggests that there is a very high level of
cognition required in order for language to be used. If this
is the case, language ought to be viewed simply as one of a
number of representational vehicles employed by a mind that
must already have a high-functioning cognitive capacity, rather than as
being in some mysterious way ‘the key’ to higher-order
cognition.
Michael Arbib theorised a number of conditions
required for a ‘language-ready brain’, criteria that must be
30 Ibid. p. 20. 31 Ibid. p. 20.
42
present in order to support protolanguage, which I have
summarised:
LR1. Complex imitation LR2. Symbolization LR3. Parity32 LR4. Intended communication LR5. Hierarchical structuring and temporalordering LR.6 Recollection of past and imagination offuture LR.7 Pedamorphy and sociality33
(see: Arbib, 2005,p. 108)
Arbib hypothesises that LR1 is required to support the other
requirements and that, currently, this is uniquely human.
However, it seems to me that some of the research I have
discussed so far is suggestive of these other qualities.
Even a sceptical interpretation of research into language-
training is indicative of LR2; chimpanzees worldwide are
taught simple symbol systems as a base requirement for other
experiments, with great success.34 Chimpanzee tool use
reflects at least a basic understanding of temporal timing
32 What counts for the speaker/gesturer, counts equally for the listener/receiver. 33 This is the prolonged period in an infantile state during which an individual is nurtured, this is theorised to be essential in creating a rich learning environment for the flourishing of language. 34 Such as chimpanzee use of numerical symbols in Inoue & Matsuzawa (2007) and the symbols to name categories of food in Beran et al. (2013)
43
and of cause and effect which suggests LR5 to some degree.
Chimpanzee understanding of intention, proto-theory of mind
and use of gestures lays a foundation for LR3 and LR4, and
their complex social structures support basic levels of
learning which is similar to the learning/teaching
environment requirement, LR7. I must make clear that I am
not trying to argue that chimpanzees have the complete
cognitive capacity required for protolanguage, but they seem
to exhibit these criteria to a degree significant enough to
deserve comment.
The importance of this is that there are high
requirements for a cognitive system to support
protolanguage, and the chimpanzee exhibits this capacity to
some degree. As the chimpanzee is a non-linguistic animal,
what this suggests is that a mind can operate using non-
linguistic vehicles up to the level required for language,
and hence that the underlying mechanisms and cognitive
architecture which support all higher-level cognition are
pre-linguistic. There is evidence to support this from
archaeo-anthropology and other disciplines investigating
early humans. Camp notes this, stating for example, that
44
‘empirical evidence suggests that early humans developed a
fairly robust capacity for theory of mind before they began
to communicate linguistically’.35 If Arbib’s theory - or
something similar - is correct then for the advent of
language, the current scientific findings indicate that a
mind must already have a complex structure and be able to
think with conceptual abstraction and systematicity. If
higher-order cognition came prior to language, and a complex
cognitive system is required to support language, then
language can be neither necessary for higher-level cognition
nor the only vehicle by which it is achieved.
35 Elisabeth Camp, ‘Putting Thoughts to Work’, Philosophy and Phenomenological Research78:2, (March 2009); p. 184.
45
◦ Conclusion ◦
In engaging with the concept of non-linguistic minds
both theoretically and empirically, I hope to have provided
a strong case for the fact that higher-order cognition can
be achieved without the use of linguistic vehicles. In
theory, there are few limitations on cartographic vehicles
but with increasing complexity and number of relations to be
represented, the direct spatial isomorphism proves
cumbersome. This makes maps unsuitable to be the sole
vehicles of anything like the range of human cognition
though within domain-specific tasks they confer a
significant processing efficiency advantage – as is perhaps
the best explanation for the cognitive capabilities of
African elephants. A diagrammatic representational system is
freed from the isomorphic bonds of the cartographic and in
theory could be used to represent almost any relation. Even
in doing so it retains an intuitive accessibility due to its
exploitation of basic geometry and the relatively
unconstrained syntax allowing for all possible relation
representative structures within the perceivable dimensions
46
of any given mind. But in practice, it seems unlikely a
thinker could rely solely on diagrammatic vehicles once the
range of representative needs is increased to that which
humans require. Though once again, diagrams are incredibly
efficient vehicles for the representation of relations and
hence in a mind with fewer needs are significantly more
suitable than linguistic vehicles given the far lower
cognitive cost of utilising a handful of diagrammatic
vehicles when compared to full language. This is most likely
the case with Baboons for hierarchical social relations, for
example. What marks language out from these other vehicles
is not the kinds of thoughts that can be achieved, but more
the range of applicability. Despite a high cognitive start-
up cost, utilising a linguistic system enables a thinker to
apply themselves to a vast array of tasks and relations due
to its entirely abstract syntax and arbitrary semantics,
with its recursive nature facilitating incredible
flexibility.
Having established the possibility of non-
linguistic vehicles for higher level cognition, the case
study of chimpanzees presents itself as a natural world
47
empirical rebuttal of the claims that once held much esteem
Western philosophy. Their extraordinary cognitive capacity
is achieved without the use of linguistic vehicles and they
exhibit behaviour indicative even of degrees of
metacognitive processing and a proto-theory of mind. Despite
scepticism, the overwhelming consensus and body of evidence
points towards the chimpanzee being a versatile and highly
intelligent conceptual thinker via a non-linguistic
representational system. Chimpanzee cognitive features find
parallel in what we know about the minds of early humans,
and current theories suggest that a pre-existing higher-
order cognitive capacity is required prior to the advent of
protolanguage in any given mind. The findings of three
decades of research into chimpanzee cognition, I have
suggested, perhaps begin to fulfil some of the criteria for
linguistic-readiness and therefore are suggestive of the
cognitive capabilities that pre-linguistic humans might have
possessed. If this theory of complex cognition being primary
is correct, then far from language being necessary for
higher-order cognition, it is the cognition which is
necessary for language. Language is therefore simply one of
48
a number of vehicles by which higher-order thought might be
achieved; it is an incredibly versatile and useful vehicle,
but it is not alone in the capacity to represent ‘genuine
thought’.
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