An Essay on the Claims of Strong Artificial Intelligence

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Computational and modular approaches in Cognitive Science

Master of Artificial Intelligence, K.U. Leuven 1999-2000

Believe it or not

An essay on the claims of strong AI

Author: Stefan Hendrickx, December 1999

1. Abstract 1

2. Disillusionment 23. Ambiguity 2

4. The end of Meta narratives 3

5. Strong AI: a consistent Meta narrative 4

6. Convergence by emergence 4

7. Self-organizing systems and strong AI 5

8. Conclusion 6

9. Literature 7

10. References 8

1. AbstractThe attempt of this paper is on the one hand, to try to find out the reasons why so many people

are confused and reluctant about the claims of strong AI. On the other hand, we will look at the clever,

however erroneous, counter arguments some philosophers have come up with. Perhaps surprisingly,

evidence for the origin of their misconception of thinking machines seems to be present in philosophy

itself. Furthermore, suggestions will be made in which way the claims of strong AI are realistic, making

use of the concepts presented in complexity theory.

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2. DisillusionmentEver since its origin, lets say Renaissance period, modern science has developed an insulting

attitude towards mans beliefs. In 1543, Nicolaus Copernicus moved us from the center of the universe

to the periphery with his book De Revolutionibus orbium coelestium. Another crucial moment of

disillusionment was in 1859, when Charles Darwin published his most controversial book "On the Origin

of the Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for

Life". The idea of survival of the fittest and, even worse, our descent from the ape didnt really match

with the story of Creation. At this moment, the great indignation people have towards the claims of strong

AI is very similar: a scientific theory dramatically upsets their intuitive self-image. Darwin left at least the

illusion of people possessing unique mental capacities.

What is it that strong AI exactly claims? John Searle describes it in his paper Minds, brains, and

programs as follows:

According to strong AI, the computer is not merely a tool in the study of the mind: rather, the

appropriately programmed computer really is a mind, in the sense that computers given the right

programs can be literally said to understand and have other cognitive states. In strong AI, because

the programmed computer has cognitive states, the programs are not mere tools that enable us to test

psychological explanations: rather, the programs are themselves the explanations.

3. AmbiguitySearles counter argument to the claims of strong AI can be stated to be a typical classical

philosophers answer to a scientific problem. To begin with, essential terms in his paper (causality,

intentionality, mental states,) are not properly, if at all, defined. Starting from weak foundations,

Searle builds up a reasoning, not taking into account any empirical, in this context to be interpreted

as measurable or formally provable, evidence, since most philosophers do not really believe in the

empirical. An exception to this generalisation is, of course, the school of the empiricists, whose theories

are identified with the concept of science itself. The kind of brick Searle uses for his building, because he

is a philosopher, is natural language.

Here lies a fundamental problem of philosophy (and also of non experimental psychology). The

relationship of natural language and reality is namely one to many. In other words, the ambiguity of our

natural way of communicating is one of the worst kinds. It is generally accepted that evolution has come

up with natural language in order to have us referring, representing, and communicating our world in a

clever, though, and also therefore, simplified way. It makes abstraction of details that are irrelevant, and

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most often, not understood. It is a projection of reality, which differs from person to person, and within

one person from one moment to another.

This has to be understood as bad news for the ambitions of classical philosophy, and metaphysics

in particular. The lack of appropriate tools and concepts to utter a clear and objective statement

about reality cannot be overcome. This acute problem has also resulted in the existence of as many

philosophical theories as philosophers, and few of their theories being compatible.

4. The end of Meta narrativesPoststructuralism1 and especially postmodernism2 in philosophy have understood this problem

fully. Jean-Franoise Lyotard: "I define postmodernism as incredulity toward meta narratives"3. James

Berlin4 notes that Lyotard "renounces the totalizing discourse of such schemes as Hegelianism or

Marxism or the faith in scientific progress or the invisible hand of economic law. All are declared

language games that are inherently partial and interested, intended to endorse particular relations of

power and to privilege certain groups in historical struggles.

1 Poststructuralism with people like Derrida, Lacan, and Foucault, heavily reacted against the insistence

of classical Western philosophy on looking for the ultimate Truth. Derrida deconstructed language

and Western philosophy with his theory of signifiers and signifieds. Lacan de-centered the source of

knowledge and assumptions of Western thought by destabilizing self. Foucault deconstructed systemsof social thought, for which he used the metaphor of prisons and the panopticon. It is noteworthy that it

wasnt a centralized power, such as a state, which controlled people in his metaphor, but people are said

to control each other in power networks. With this claim, Foucault probably referred to the inflexible,

conservative, and controlling attitudes people show in all kinds of social systems, such as cultures,

villages, or scientific communities. People are giving up their own identity, their self, in order to be

accepted in the social network. This relates to sociology, more precisely the paperThe Established and

the Outsiders by N. Elias and J. Scotson.

2 Jean-Franois Lyotard formulated in The Postmodern Condition (La Condition Postmoderne) (1979)

a number of critiques on modernism. The term postmodern, which he introduced, corresponds with a

synthesis of critiques on modernism as formulated by poststructuralists Derrida, Foucault, Deleuze, and

Baudrillard, as well as critiques of Heidegger and Nietzsche, who have tried their own way of refuting the

relevance of the metaphysical concepts.

3 Jean-Franois Lyotard, The Postmodern Condition, p. xxiv

4 Berlin, James A. Postmodernism, Cultural Studies, and the Composition Classroom: Postmodern

Theory in Practice, Rhetoric Review, 11.1, 1992______________________________________________________________________________________________Stefan Hendrickx

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The key issues of metaphysics, namely grounded ethics, eternal truths, and values, are given up

entirely by postmodernism. They do so because not any philosophical, or other theory has ever been

proven to be timeless. Hence, theories are rather to be considered as working models, updated and thrown

away on a regular basis, according to new insights and our needs for effectiveness and efficiency.

The concept of subject is also heavily attacked in postmodernism. The claim is that the classical

idea of identity is an illusion. Evidence is to be found in our (postmodern) society: tradition has lost its

role in giving us cues for inner values. Technology, and especially mobility has moved us away from

stable communities with unambiguous codes. People are rather picking up their cues from others, who

are supposedly in the know, as a strategy to hold out in all the different compartments of their fragmented

life.

5. Strong AI: a consistent Meta narrative

It is important to note that science too, is considered to be a meta narrative in postmodernism, and

that its not to produce an adequate model or replication of some outside reality, but rather simply to

produce more work"5.

The question is whether this point would be inconsistent with the claims of strong AI. The answer

is probably no, because strong AI does not pretend to explain the eternal Truth. It just claims it to be

arbitrary to make a distinction between understanding, as we intuitively perceive it, and how machines

will be able to, one day. Furthermore, science has, unlike philosophy, appropriate tools to explain reality

in a consistent way. Also therefore, scientists can build on the strong foundations of their colleges from

centuries ago.

Strong AI also claims for a continuous, rather than a discrete (yes or no) definition of

understanding and intelligence, not with ourselves having as an absolute reference. For example, it is

quiet clear to believers in strong AI, that a stomach can be ascribed intelligence, opposite to Searles point

of view. A stomach can interact with its environment in a proper way, can adapt itself to changes in its

environment, and can learn, all over different time scales. Within one lifetime: a baby's stomach can only

process milk, whereas an adult can process toxic substances such as coffee and alcohol. Over a period

of ten thousands of years: a species' stomach can evolve from the life style of an herbivore to that of a

carnivore.

It is also important to realize that because science too is a Meta narrative, we cannot expect

anything more truthful (whatever that means) than the Turing test in detecting human like intelligence.

5 Jean-Franois Lyotard, The Postmodern Condition, p. ix.______________________________________________________________________________________________

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How may strong AI than be able to build a machine that can successfully undergo the severe ordeal of

Turing? This will be the subject of the following sections.

6. Convergence by emergenceThere exists a tendency towards a grand unification theory6 in sciences, which is able to

describe, in a consistent way, the evolution of our universe, based on the concepts of complexity theory.This theory brings together sciences as different as sociology, economy and physics.

A visionary of this synergetic science was Ilya Prigogine, a Belgian physicist who in 1977

won the Noble prize for his contributions to non-equilibrium thermodynamics. His holy grail was the

question why our universe shows the tendency to gain order and structure, however the second law of

thermodynamics imposes the opposite. Prigogine proved that for some systems, it is theoretically not

possible to use the initial conditions to calculate the conditions at a later time to infinite precision. This is

an extremely important discovery, because it shows how we can escape from classical physics' assertion

that the world is deterministic. Prigogine realized that this chaos phenomenon and the existence of

positive feedback mechanisms together are the driving force for our universes tendency towards order

and structure. He called this a self-organising system.

In the early days of complexity theory, Prigogine also suggested that economy is the same kind

of self-organising system as our universe, however it would take many years to be accepted in theoretical

economy7. Nowadays, not only economical, but also demographic and sociological problems are

successfully modeled by means of self-organising systems. Hence, the key to understanding our universe

seems to be laying in going to the bottom of the emergent properties of simple elements that constitute

self-organising systems.

7. Self-organising systems and strong AIComplexity theory does not only provide us a better clue to understand the evolutionary

processes of the universe. It has also shown to be a proper tool to formalize the things we intuitively

understand as learning, self-awareness and intelligence. Furthermore, the uncomputable and non-

algorithmic aspects of the mind (cf. Penrose) are perfectly consistent with this theory, because of the

6 This Grand Unification Theory hasnt got to do with the efforts people are doing in theoretical physics

to bring all the physical forces together into a single model.

7 Classical economy theory has suffered from its jealousy at the purity and also the deterministic character

of classical physics. For this reason, economists often didnt take into account sociological and political

aspects in their models, because these are too hard to estimate. Furthermore, they assumed individuals tobe omniscient and perfectly rational.______________________________________________________________________________________________

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undeterministic character of self-organising systems.

Although we are far away from simulating a system as complex as the human mind, one

successful simulation of a self-organising system should be reported, namely the emergent intelligence

of ant colonies. A single ant does not understand the colonys plan; the intelligent collective behavior

emerges from local interactions. With the exponential growth in computational power8, it is reasonable to

assume that, one day, we will be able to build a mind simulator, by means of simple neuron-like elements,

able to pass the Turing test.

8. ConclusionSome critical problems of the relationship between AI and philosophy have been raised. In the

first place, the nature of the confusion and reluctance about the claims of strong AI were put in broader

perspective. In the second place, the relevance of the arguments of classical Western philosophy against

the claims of strong AI was questioned. The conflicts were suggested to be of the same nature as those of

the philosophical school of postmodernism with metaphysics and classical Western philosophy in general.

The arguments of postmodernism were naturally in favor of strong AI, because it also refutes the concepts

of metaphysics. In the third place, the fact that, within this framework, science too is a Meta narrative,

was stressed. Science is not capable to explain the eternal Truth, but it shows to be capable to describe

the universe in a consistent way. Furthermore, complexity theory was introduced, as an argument for the

feasibility to build a mind like machine. Mind like, because it is implausible to have a better test than the

one Alan Turing introduced in 1950. Hence, in conclusion one could say that believe will remain a key

issue in these matters, as we will never be able to observe the mind itself, only its induced actions and

behaviours.

8 Moores Law: the logic density of silicon integrated circuits has closely followed the curve (bits

per square inch) = 2^(t - 1962), where t is the time in years. This means that the amount of storable

information and computational power on a given amount of silicon has roughly doubled every year, ever

since the introduction of silicon based integrated circuits (1962).______________________________________________________________________________________________

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9. Literature Searle, J. (1980) Minds, brains, and programs, The Behavioral and Brain Sciences, 3, p. 417-457.

Minsky, M. (1985) Communication with Alien Intelligence, published in Extraterrestrials:

Science and Alien Intelligence (Edward Regis, Ed.) Cambridge University Press, Cambridge.

Lyotard, J-F. (1985) The Postmodern Condition: A Report on Knowledge (La Condition

Postmoderne), University of Minnesota Press, Minneapolis.

Penrose, R. (1990) Prcis of The emperors new mind: Concerning computers, minds, and the

laws of physics, The Behavioral and Brain Sciences, 13, p. 643 705.

Berlin, James A. (1992) Postmodernism, Cultural Studies, and the Composition Classroom:

Postmodern Theory in Practice, Rhetoric Review, 11.1

Lyotard J-F. (1992) Het postmoderne uitgelegd aan onze kinderen (Le postmoderne expliqu aux

enfants), Kok Agora, Den Haag.

Mitchell Waldrop, M. (1993) De rand van chaos: Over complexe systemen (Complexity: The

Emerging Science at the Edge of Order and Chaos), Uitgeverij Contact, Amsterdam.

N. Elias & J. Scotson (1994) The Established and the Outsiders, published in: Sage, London, p.

xv-lii.

Soros, G. (1998) De crisis van het mondiale kapitalisme: De ondergang van de vrije wereld (The

Crisis of Global Capitalism: Open Society Endangered), Uitgeverij Contact, Amsterdam.

Heynen, H. (1999) Architecture and Modernity: A Critique, MIT Press, London.

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Stefan Hendrickx

Dec 1999

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An Essay on the Claims of Strong Artificial Intelligence