• 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

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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).

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◦ 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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