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Some detailed examples of how Cognitive Science, Artificial Intelligence and Computing influenced and shaped the debate of the Philosophyof Mind

Some detailed examples of how Cognitive Science, Artificial Intelligence and

Computing influenced and shaped the debate of the Philosophy of Mind

Introduction

In this essay I will start with a short account on the debate in the philosophy of

mind in the 17th and 18th century, shortly summarising views held by Ren

Descartes and Gottfried Wilhelm Leibniz. I will further discuss theories of

consciousness and the mind, that were largely influenced, shaped and based upon

advancements in the fields of Cognitive Science, Artificial Intelligence and

Computing, such as The Computational Theory of Mind and the situated approach

to Artificial Intelligence, also known as Nouvelle AI. I will then go on to conclude

which of the two theories, in my opinion, is a better approach for explaining

consciousness and the mind.

At the advent of the modern world

And new philosophy calls all in doubt,

The element of fire is quite put out,

The sun is lost, and th'earth, and no man's wit

Can well direct him where to look for it.

This short excerpt from John Donne's An Anatomy of the World captures the

spirit of the time of the Industrial and Scientific Revolution, at the advent of the

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modern world, that should not only influence how we live and how we work, but

also how we, as humans, think, and who we are.

In his Meditations, Ren Descartes liberated himself from his physical appearance

and concluded that he is a thinking thing and that this thinking thing is of a

diferent substance than physical matter (Descartes 1641). Descartes therefore

was a Substance Dualist who held the believe that body and mind are made up of

two dif

erent substances (The Stanford Encyclopedia of Philosophy 2011,

Dualism). Descarts (1641, Meditation III) states this as follows, [f]or when I think

a stone is a substance, or a thing capable of existing of itself, and that I am

likewise a substance, although I conceive that I am a thinking and non-extended

thing, and that the stone, on the contrary, is extended and unconscious, there

being thus the greatest diversity between the two concepts, yet these two ideas

seem to have this in common that they both represent substances.

Leibniz, on the contrary, who denied dualism, was a monist, but unlike most

monists, he denied materialism. For him, consciousness could only arise in an

indivisible unity, the I, and not in infinitely divisible matter (The Stanford

Encyclopedia of Philosophy 2008, Leibniz's Philosophy of Mind).

He further held the view that perception is inexplicable on mechanical principles

and imagined a machine whose construction would enable it to think, to sense,

and to have perception. He continued in imagining the machine being large

enough to be able to enter it, while retaining the same proportions. Supposing



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this, one should, when visiting within it, find only parts pushing one another, and

never anything by which to explain a perception. Thus it is in the simple

substance, and not in the composite or in the machine, that one must look for

perception (The Stanford Encyclopedia of Philosophy 2008, Leibniz's Philosophy

of Mind).

I will return to this example, which I think is a very interesting argument against

thinking machinery, in the next section of this essay, in the discussion about

The Computational Theory of Mind.

The Computational Theory of Mind

The Computational Theory of Mind is a result of both, theoretical and practical

advancements in the field of Computing and had its heydays over the past 30

years. The mind is seen as being like a digital computer, processing information,

taking input through the senses and producing output after computational

operations on the input information (The Stanford Encyclopedia of Philosophy

2011, The Computational Theory of Mind).

One of he most often cited arguments for the mind working like a digital

computer is Alan Turings Universal Turing Machine and the Curch-Turing Thesis. I

will not go into depth in explaining both of these principles, but shortly

explained, if there is an efective method for obtaining the values of a

mathematical function, the function can be computed by a Turing machine (The



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Stanford Encyclopedia of Philosophy 2008, The Church-Turing Thesis). In turn,

each computation that can be done by one or more Turing machines, can be

simulated by a Universal Turing Machine (The Stanford Encyclopedia of Philosophy

2011, Turing Machines). Church's working hypothesis said that a function of

positive integers is efectively calculable only if recursive (The Stanford

Encyclopedia of Philosophy, 2008, The Curch-Turing Thesis). Both theses were

found to be equivalent (The Stanford Encyclopedia of Philosophy 2008, The

Church-Turing Thesis).

Supporters of the thesis, that the mind behaves to the brain as software behaves

to hardware, include Jerry Fodor and his Language of Thought. Fodor (1975, p.

52) imagined that a human decision process in itself is equivalent to a

computation. According to Fodor (1975, p. 52) an agent in a certain situation

(S), supposes that a set of behavioural options (B1, B2, ...Bn) is available to him in

S. The agent goes on to compute the hypothetical consequences, Ci, of all

behavioural options, along with the adherent probabilities of all consequences. He

then assigns a preference ordering to the consequences, therefore the choice of

behaviour is determined as a function of the preferences and the probabilities

assigned (Fodor 1975, p. 52).

This example clearly runs along the lines of a function a Universal Turing Machine

is able to compute, as a finite set of behavioural options is available,

consequences and adherent probabilities are computed and the choice is

determined as a function of the preferences assigned. With this example Fodor



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suggests that the mind operates on discrete principles, however I think that his

example is too idealised and theoretical. For me he seems to ask, Suppose

yourself in situation X, how would you respond and how do you get to this

response?, leaving no space for impulsive, emotional or reflexive responses and

so excluding many real world decisions. It further involves the, on my opinion,

wrong assumption, that every decision is a conscious and rational, therefore

computational, process.

Jerry Fodor (1975, p. 53) also coined the term, no computation without

representation, to which I will return in the next section in this essay, in the

discussion about Nouvelle AI.

The theory was rejected and opposed by, among others, John Searle with his

famous Chinese Room example. Searle (1980, p. 141), on his own account, unable

to understand or even recognise Chinese, imagined himself being locked in a

room with a large batch of Chinese writing, a second batch of Chinese script

together with a set of [english] rules, to correlate both batches and to identify the

Chinese symbols by their shape. Further, Searle is given a third batch of Chinese

symbols alongside some more english rules that instruct him how to return

certain Chinese symbols as answers to other Chinese symbols provided to him as

questions. After a while he imagines himself as being so good at manipulating the

symbols, that to outsiders, it seems, they are interacting with a native chinese

speaker and so, Searle (1980, p. 144) further claimed, that he would pass the

Turing Test.



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Searle (1980, p. 142) argued that there is nothing in the room that actually

understands chinese but simply that the whole operation consists of dull symbol

processing. He also rejected the reply, among others, that claimed that he is just

part of a larger system that actually understands (The Systems Reply), because

neither in the system as a composite nor in any part of the system is anything that

really understands whats going on (Searle 1980, p. 143).

Although I wouldn't agree that Searle passes the Turing Test with his Chinese

Room (which I won't discuss in this essay), I would agree with him that there is no

actual understanding going on, neither in himself, nor in the whole room as a

composite, and would argue that Searle's Chinese Room largely follows Leibniz's

argumentation of the 18th century which claimed that there is no part to explain a

perception in his imagined thinking machine, but only parts pushing one

another (The Stanford Encyclopedia of Philosophy 2008, Leibniz's Philosophy of

Mind).

Further, in my opinion, I think that The Computational Theory of Mind could not

and can not work because computers and computer programs are based on binary

and purely logical principles, making it hard to impossible to compute algorithms

which are of an exponential complexity, underlying in the understanding of

natural language for example. Humans on the other hand are essentially good at

understanding and processing natural language, I would therefore argue that

consciousness and the mind must be based on diferent principles than

computers and programs.



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Nouvelle AI (The situated approach)

Nouvelle AI is quite a radical break with paradigms that think of the mind as a

symbol processing, abstract unit. The new approach, starting to get tenure in the

beginning of the 1990s, thanks to works of, among others, Rodney Brooks and

Tim van Gelder. This new attitude towards the philosophy of mind is a result of

dissatisfaction with existing models, such as The Computational Theory of Mind,

advances in Computing and Cognitive Science that resulted in the belief that the

mind may more be like an active control agent rather than a passive [...] organ

for recognition, classification and problem solving (Clark 1998 p. 516). It further

led to the conclusion that building human-like intelligence requires human-like

interaction with the world (Brooks et al 1999, p. 58).

Rodney Brooks, whose early works resulted in an autonomous robot that is able to

find and collect empty drinking cans on laboratory desks, claimed that, in order to

build an intelligent, autonomous agent, one doesn't need a central control and

planning unit and also no internal representations (Brooks 1991, pp. 148-149).

Further, Brooks identified four central control aspects of human intelligence

which are development, social interaction, embodiment and integration (Brooks et

al 1999, pp. 57-59).

Brooks' can collecting robot is based on the subsumption architecture (Brooks

1991, pp. 150-154), which is a multilayered, hierarchical approach, where each

layer pursues a diferent goal. Each layer may be suppressed or inhibited by



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another layer and only one layer can be in control at a time. He goes on to

summarise the robots actions as a collection of competing behaviours (Brooks

1991, p. 149).

Tim van Gelder supports the view of Rodney Brooks, that an intelligent system

needn't involve any representations about itself or its environment at all. Van

Gelder further proposes that consciousness and cognition may be explained in

terms of a dynamical system which is state dependent and based on

numerically measurable quantities and whose rule of evolution specifies

sequences of such numerical states (van Gelder 1995, pp. 365-367; 376-377).

Both Cognitive Scientists share the opinion, that representations are not required

to achieve intelligent behaviour, however, I think that in order to create

completely autonomous agents, which are able to survive on their own, internal

representations are necessary. Rodney Brooks' robots are only responsive within

their environment and not truly active. I think with this responsive behaviour the

robot would not be able to survive on its own. Further when I think of

independent survival as the most basic intelligent behaviour in nature, some kind

of internal representations seem to sneak in. For example a fox, living in a wood,

somehow needs to diferentiate, when coming across certain animal tracks or

smells, that this other animal is a potential threat or a potential dinner. Further,

the fox somehow needs to memorise routes to water sources and to the fox-

kennel. I don't think that all this is achievable without some kind of internal

representations.



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I would see the Tinbergen experiment as supportive of my argument, as it

suggests that there is some kind of recognition in the wasp when returning to the

nest. I would argue that this recognition must happen because of some internal

representation the wasp has of the nest (Campbell 2006).

Overall I think that Nouvelle AI is the right approach towards creating human-like

intelligence, and maybe someday even explaining consciousness, foremost

because of the four central control aspects of human intelligence as identified by

Rodney Brooks. As discussed in the preceding section, I would only argue for the

necessity of internal representations whose absence in the works of Rodney

Brooks may be explained by still not enough hardware and software power. Also

Tim van Gelder's dynamical system approach is interesting, but instead of the four


Picture 1: The Tinbergen experiment


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central control aspects, which are of social nature, van Gelder uses time as the

central aspect for his dynamical systems theory (van Gelder 1995, p. 379). The

mathematical measurement of behaviour is an interesting beginning for

explaining consciousness and the mind but I think it lacks the, in my opinion

more important, social factors.

Conclusion

I think that Nouvelle AI is a better step towards explaining consciousness and

creating human-like intelligence than The Computational Theory of Mind. I would

further say that thinking of consciousness and the mind as a result of the holistic

unity of body and mind, which is interacting with the world, is the right beginning

towards achieving this goal.



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Bibliography

Barker-Plummer, David (2011), Turing Machines, The Stanford Encyclopedia ofPhilosophy, Stanford: Stanford University. Available from:

http://plato.stanford.edu/archives/spr2011/entries/turing-machine/ (accessed19 December 2011)

Brooks, Rodney A. (1991) Intelligence without representation, Artificial Intelligence,47, pp. 139-159

Brooks, Rodney A. et al (1999) The Cog Project: building a humanoid robot, inNehaniv, CL. (ed.) Computation for metaphors, analogy and agents. Berlin:Springer Verlag, pp. 52-87

Campbell, Neil A. (2006) Biology Exploring Life, Miami: TERRA EnvironmentalResearch Institute. Available from:http://terra.dadeschools.net/books/Biology/BiologyExploringLife04/0-13-115075-8/text/chapter3/concept3.1.html (accessed 3 January 2012)

Clark, Andy (1998) Embodied, situated, and distributed cognition, in Bechtel W.,Graham G. (ed.)A companion to cognitive science. Malden: Blackwell Publishingpp. 506-517

Copeland, B. Jack (2008), The Church-Turing Thesis, The Stanford Encyclopedia ofPhilosophy, Stanford: Stanford University. Available from:http://plato.stanford.edu/archives/fall2008/entries/church-turing/ (accessed 19December 2011)

Descartes, Ren (1641) Meditationes de prima Philosophia (english translation byVeitch, John, 1901). Dayton: Wright State University. Available from:http://www.wright.edu/cola/descartes/mede.html (accessed 28 December 2011)

Donne, John (1611)An Anatomy of the World. Chicago: The Poetry Foundation.

Available from:http://www.poetryfoundation.org/poem/173348

(accessed 29December 2011)

Fodor, Jerry A. (1975) The Language of Thought: First Approximations, in Katz J.,Langendoen DT., Miller GA. (ed.) The Language and Thought Series. Cambridge:Harvard University Press pp. 27-54

Horst, Steven (2011), The Computational Theory of Mind, The StanfordEncyclopedia of Philosophy, Stanford: Stanford University. Available from:http://plato.stanford.edu/archives/spr2011/entries/computational-mind/

(accessed 20 December 2011)



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Kulstad, Mark and Carlin, Laurence (2008), Leibniz's Philosophy of Mind, TheStanford Encyclopedia of Philosophy, Stanford: Stanford University. Available from:http://plato.stanford.edu/archives/fall2008/entries/leibniz-mind/ (accessed 28December 2011)

Robinson, Howard (2011), Dualism, The Stanford Encyclopedia of Philosophy,Stanford: Stanford University. Available from:http://plato.stanford.edu/archives/win2011/entries/dualism/ (accessed 28December 2011)

Searle, John R. (1980) Minds, Brains, and Programs, The Behavioural and BrainSciences, 3, pp. 417-424

Van Gelder, Tim (1995) What Might Cognition Be, If Not Computation?, The Journalof Philosophy, 92(7), pp. 345-381

List of Illustrations

Picture 1: The Tinbergen experiment, Source:http://terra.dadeschools.net/books/Biology/BiologyExploringLife04/0-13-115075-8/text/chapter3/concept3.1.html (accessed 3 January 2012)


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