ARTIFICIAL INTELLIGENCE: IS IT POSSIBLE?
Rob Harle (c) 1999
The notion of creating an artificial entity, that
is, “a human created in the image of a human” has been around a lot
longer than the last thirty or forty years of the Computer Age. Mary Shelley’s
“Frankenstein” dealt with the ‘scientific’ creation of a human-like
entity on many levels. One
of these levels was socialisation and in an indirect, somewhat ironic
way, is relevant to the possible creation in the early twenty first
century of an intelligent, conscious silicone - digital - molecular
discuss the socialisation aspect of AI in detail further on.
The creation of computational
devices and those with a ‘memory’ goes back many thousands of years. The Chinese invented the
Abacus some 5,000 years ago, the water clock around 3,000 years. The first truly mechanical
clock, which ticked, was built in 725CE.
In 1642 Pascal invented the world’s first automatic
calculating machine, the Pascaline.
Shortly after in 1694 a computer was invented by
Weaving was to see many
mechanical and computational innovations at the beginning and during
the Industrial Revolution. The
Jacquard loom, around 1805, was operated by punch cards, this was a
significant ‘advance’ in transferring instructions from a human to a
machine to produce a product, in absentia. This was of course the
precursor to punch card computers of the mid-nineteen hundreds.
Charles Babbage developed the
Analytic Engine, the world’s first ‘real’ computer.
Ada Lovelace published her own notes on this engine
and “speculated on the ability of computers to emulate human
date was 1843! Hollerith
perfected the automatic punch card tabulating machine and founded a
company which later became IBM.
In 1921 the word “robot” was
coined by Czech dramatist, Capek. His science fiction drama “Rossum’s
Universal Robots” describes how intelligent machines, originally
servants of humanity, end up taking over and destroying their creators.
In 1937 Turing developed his
famous Turing Machine, a theoretical model of a computer. In 1950 he developed his
almost infamous, “Turing Test” to assess the intelligence of a machine
compared with that of a human. The
usefulness of this test is now seriously doubted. (see Searle and
about this time on computers simply became faster and with greater and
greater capacity and problem solving capabilities (Kurzweil, 1999.
Relays gave way to vacuum tubes, these gave way
to transistors which in turn gave way to the silicone chip. This ubiquitous ‘chip’ may
soon give way to a new technology known as molecular organic circuitry. Silicone chips are
reaching maximum efficiency due to physical limitations, a
custom-designed molecule called rotaxane, may replace the old style
digital silicone computer with a molecular computer within five years
(Chang, 1999.) This
very brief history helps ground the following discussion and shows the
progressive nature of human invention. In a sense it helps justify the
predictions of futurists, such as Kurzweil, that machines will be
conscious and equally as intelligent as humans within thirty years
Before I address the question
of artificial consciousness we need to have a clear idea of what
constitutes ‘natural’ human consciousness.
This is no easy task, which is evidenced by the
monumental amount of literature devoted to the “race for consciousness”. Searle defines
consciousness as, “...a biological feature of human and certain animal
brains. It is
caused by neurobiological processes and is as much a part of the
natural biological order as any other biological features such as
photosynthesis, digestion, or mitosis” (Searle, 1992. p.90).
Hobson believes, “...the mind is all the
information in the brain” and defines consciousness as, “...the brain’s
awareness of some of that information” (Hobson, 1994. pp.202-204). Hobson also believes that
the brain-mind is a unified system, they are inextricably linked (ibid.
theory is supported by a large amount of testable, neurophysiological,
Drawing on this evidence and
the ideas of Searle, Dennett and Gelernter I believe when we refer to
‘the mind’ we are referring to a highly complex system, which is a
combination of electrochemical-neural interactions in the organ in the
skull called the brain. The
brain interacts with the physical body, and through sensory
input/output, the environment external to it.
Embodiment with sensory input is an essential
requirement for a mind to exist. This
sensory input further allows for another essential requirement for the
creation and maintenance of mind and that is socialisation.
In a normal human adult the
unified brain-mind system has both nonconscious mental states
(memories, regulation of respiration etc.) and at times conscious
mental states. Consciousness
is simply one state of this unified brain-mind system.
Consciousness is largely controlled by the brain’s
chemical system know as the aminergic-cholinergic system.
The aminergic system (amines)
governs our waking state and the cholinergic (acetylcholine) system
governs our dreaming state. These
systems are in dynamic equilibrium and neither one is ever totally
inactive. The ratio
of these chemicals can now account for many previously mysterious
states of conscious such as hypnosis, dementia and fantasy. As we
approach sleep the cholinergic chemical increases and maintains
dominance whilst asleep. As
we wake up normally, the reverse happens and the aminergic system
becomes dominant. If
we are awoken suddenly we temporarily experience confusion and
disorientation because the chemical system needs a little time to
re-establish its correct ratio/balance for the respective, consciously
desired? states (Hobson, 1994. pp.14-16).
I have noted a most interesting correlation in the
work of Gelernter. He
believes mental focus moves from high to low, at the high focus end we
are most alert, logical and deal with step-by-step problem solving. At the low focus end, that
is, as we move down the spectrum we do not think logically, our minds
move easily from one unrelated subject to another, creative solutions
to problems occur at this level, ones that have previously defied
logical solution. It is at this level that inspiration suddenly hits
us. Further down the spectrum the onset of sleep and then dreaming
occurs. We must bear in mind that during REM sleep we dream, the
awareness of dreams or dream fragments, even though we are asleep, is
still part of a conscious state. This
description of mental states fits in perfectly with the action of the
I can see that some
philosophers, though happy enough with the above, may still argue that
it does not say what consciousness actually is.
Searle helps overcome this conundrum through his
belief that our vocabulary and consequently our mode of thinking is at
fault. It is
incorrect to think that a state must be either mental or physical,
Searle believes such apparent oppositions as these are false,
“Consciousness is a mental, and therefore physical property of the
brain in the sense in which liquidity is a property of systems of
molecules, eg. H2O (Searle, 1992. p.14).
Further, “...consciousness qua
consciousness, qua mental, qua subjective, qua
qualitative is physical, and physical because mental (ibid. p.15). This approach I believe is
plausible in answering the elusive question of what consciousness is.
Dennett discussing Jaynes and
Nagel, describes the chasm between inert matter and the inwardness of a
conscious being, in the example of brick and bricklayer (Dennett, 1998.
p.122). If we
accept that a brick cannot be conscious, and it is by no means a
universally accepted conclusion, many tribal societies believe
inanimate objects such as a stone do have a kind of consciousness or at
least spiritual essence. In
principle we must remain open to this because we are not stones so can
never ‘really’ know what it is like to be a stone. If we do not accept
this possibility and insist that a stone is inert and a stonemason is
conscious how can this be? Suppose
we ‘deconstruct’ both stone and stonemason.
Prior to total deconstruction we get down to
molecules and atoms, say carbon, silica, hydrogen and so on, the very
same building blocks are fundamentally present in both stone and
on, we arrive at Quantum states, probabilities, particles and waves. So how and where from this
‘oneness’ does consciousness become an attribute of the stonemason and
not the stone? I
believe that Hobson and Searle are correct in insisting that
consciousness arises from brain-mind states.
The reason it can arise is because a functioning system,
with just the right attributes causes it to exist. It seems clear from
scientific ‘deconstruction’ of stones that they do not have a
brain-mind system and therefore cannot be conscious in any sense that
Franklin argues that mind is
graded not Boolean, this fuzzification of mind allows
for, some degree of mind in animals and possibly machines,
though it may be in the mechanical sense, that is, without qualia
(Franklin, 1995. p.412).
Perhaps the degree of consciousness is
proportional to the complexity of the system from which it arises. Hence we might imagine a
consciousness complexity scale from one to one hundred, along which; a
plant may be zero, an ant two, a dog sixty, an ape seventy and a human
figures are of course speculative but it helps illustrate the point. This consciousness scale
has nothing to do with Gelernter’s low-high focus of consciousness. His model applies
separately to each species which is conscious.
Rather than providing a precise
definition of consciousness, in the foregoing I have attempted to
approach the phenomena from various angles, to at least find some
things consciousness is not and others that must be present for
consciousness to arise. Two
characteristics of consciousness that are particularly relevant to this
discussion are awareness and intentionality.
Without awareness we are not
conscious, more precisely we are not conscious ‘of’ something. Awareness may be of
external events or internal brain-mind mentation, such as the dreams of
REM sleep. Various
meditational states, like dreams, have absolute minimal external
stimulus yet the individual may be consciousness of these, as an
example, consciousness of ‘nothingness’.
Austin explains much of this mysterious mental
phenomena in a large body of research work, represented in, “Zen and
For an agent to be considered
conscious it must display Intentionality.
As Searle points out this does not mean that
intentionality is consciousness though. “Intentionality is that
property of many mental states and events by which they are directed at
or about or of objects and states of affairs in the world” (Searle,
1983. p.1). Intentionality needs to be divided into intrinsic and
‘as-if’ intentionality for clarification and for consideration in an
artificially intelligent entity.
If a person makes a statement
such as, “I am afraid of snakes”, this is an example of intrinsic
your personal computer displays a message, ‘I am afraid of snakes’ this
is, as-if intentionality. Many
devices display as-if intentionality, a thermostat is a good example,
but none of these devices ‘so far’ have the presence of any mental
phenomena. If an
office thermostat controlling the air conditioning had a speaker
attached and always reported when it was turning up the heating and
then one day said, “I’m not turning up the heating today because I‘ve
had it with you people treating me like a dumb wallflower!” then it
would be displaying intrinsic intentionality. Deciding between as-if
and intrinsic intentionality will be a criteria for assessing true
artificial intelligence and will not be as easy as it may seem.
For an entity to be considered
consciously aware that it exists it must possess intrinsic
intentionality, if consciousness and intentionality are features of a
unified brain-mind system we need to ask how do brain-mind states come
about, over and above their chemically controlled basis? If the brain-mind is
simply an ‘information-processing’ organ, with on-off switching and
access to a huge knowledge database (memory), that is, computational
power plus knowledge, we would already have developed rudimentary
artificial intelligent conscious machines.
I seems to me, in principle, this approach to AI is
One reason for this is that all
the information in the world is not the measure of intelligence, one
measure of intelligence is the ability of an organism to function
within its environment and survive the normal hazards of that
walking encyclopedia will walk over a cliff, for all its knowledge of
cliffs and the effects of gravity, unless it is designed in such a
fashion that it can find the right bits of knowledge at the right time,
so it can plan its engagement with the real world (Dennett, 1998.
The failure of traditional or classical AI led
to the development of the connectionist paradigm, this included neural
networks operating in parallel, similar to the way the brain operates
and accesses subsystems which, ‘do their own thing’, at a local level. The connectionist model
allows a system to
learn and expand its program as it encounters various situations. Whereas classic AI
(rule-and-symbol-based) is good at logic and long term planning it is
inadequate for real-time motor control and perceptual recognition
(Clark, 1997. p.59).
Classic AI often sees the
computer as analogous to the human brain, little wonder scholars such
as Black argue that, “The digital computer analogy is fatally
misleading” (Black, 1991. p.3). Black
further argues that the software-hardware dichotomy is artificial,
“...software and hardware are one and the same thing in the nervous
system” (ibid.). Whilst
Black is no doubt correct in that DNA instructions are encoded right in
the cell, ‘on site’ ready to do their job, I do not agree they are “one
and the same thing”. They
are instructions embedded into the molecular matrix of particular parts
of the cell.
Software instructions are part
of a machine’s memory, embedded electrically in the matrix of the
memory medium. In
all but the oldest AI programs these instructions form part of feedback
loops which modify and expand the original instructions and also
rearrange their positions and relevance in the software’s hierarchical
Further to this, it has always
struck me as naive and almost absurd that AI researchers, up until a
few years ago, imagined they could create an artificially intelligent
machine and do so with the machine in isolation, simply by increasing
speed and adding more computational power.
This procedure has resulted in very powerful
machines which can outperform humans in many respects, however, this
has nothing to do with intelligence.
The nurturing period of a human infant, with the
longest neoteny of any species, together with the interaction of infant
with other infants and adults is partly the basis of human intelligence. In this period, up to
three years of age, the development of the limbs, the structuring of
neural pathways and the gradual appreciation by the infant that it is
an autonomous agent all take place.
In my opinion without an equivalent
period of infancy no machine will ever even
approximate human consciousness.
I think much wasted discussion
and programming effort has taken place because of the limited vision of
just what an AI entity would require prior to being able to develop
internal states that could give rise to consciousness.
The coming into existence of
the World Wide Web may be a great benefit for the socialisation of AI
entities, entities could be on-line for extended periods and use the
Web as a classroom for learning facts and as a place for social
cannot speculate on the benefits of Virtual socialisation over real
socialisation but there are futurists who regard it as equally
in a paper presented to NASA discussed the possibility of computer
networks ‘waking up’, the Web with its millions of users at any one
time could possibly be regarded as an intelligent, ‘artificial’ entity
in its own right (Vinge, 1993).
Regardless of how an entity
experiences socialisation its first requirement is embodiment, that is,
the ‘mind’ part of the entity must have some sort of physical
attributes which help locate it spatially.
An entity cannot be aware of its existence unless it
has reference to other objects which are not
and Smith have dome some important pioneering work in developmental
psychology which has been especially relevant in dispelling the
entrenched Cartesian notion of ‘mind’ as a separate, controlling
homunculus like thing. Known
as the Dynamic Systems approach to development of cognition and action,
this approach has proven beyond all doubt that various parts of a
system, ‘do their own thing’. Literally,
the brain does not know how to do certain things nor that they have
occurred, such as some of the aspects of an infant learning to walk
(Thelen & Smith, 1994. Chap.1).
These discoveries have major implications for AI,
the low-level design of the body of an entity allows for local
knowledge and control without the burden of complex, resource hungry
central executive control.
This fundamental approach has
been implemented in MIT’s, COG Project.
I was excited to come across this work as it is
actually doing what I thought were the minimum necessary basic steps in
creating an intelligent artificial entity.
As well as utilising local feedback control, the
process of socialisation is being carried out equally with hardware
(body) modification and programming evolution.
Before describing this project
in detail it is worth noting that Collins towards the end of the
eighties was insisting that socialisation and enculturation are
essential components of intelligence.
Although he did not describe the way machines must
be socialised to exhibit intelligence his work pre-empted what is
happening with the Cog project. Collins
made a very interesting point which few people seem to think about and
that is, perhaps, rather than humans trying to make machines like
humans, they are becoming more like machines themselves. Quoting Dreyfus, “Our risk
is not the advent of superintelligent computers but of subintelligent
human beings (Collins, 1990. p.190).
The Cog Project at MIT, under
the direction of Rodney Brooks, is an ongoing concern which seeks to
build “human-like artificially intelligent systems”, not systems which
master a single domain but those which can adapt to many complex tasks
in the real world in real time. This
goal has led to the rejection of many of the procedures in classical AI
and also of the assumptions about human intelligence which are feature
of this discipline.
The guiding principle of the
Cog team, is that, “...human intelligence is a direct result of four
intertwined attributes: developmental
organisation, social interaction, embodiment and physical coupling, and multi-modal
integration (Brooks et al., 1998).
Before disusing these attributes in detail I will
describe the assumptions about intelligence which classical AI still
believes, and Brooks et al, eschew; monolithic internal models,
monolithic control and general purpose processing.
Humans have no full
monolithic internal models.
When performing a copying task we do not build an
internal model of the complete scene we are attempting to copy. Experiments have shown
that, “...humans tend to only represent what is immediately relevant
environment and those representations do not have full access to one
Humans have no
monolithic control. Evidence from cognitive
science whilst acknowledging control structures finds no support for a
single unitary control system. Observation
of various split brain patients suggests, “... that there are multiple
independent control systems, rather than a single monolithic one”
Humans are not general
purpose. Despite the
conventional, commonsense view that humans are equally good at any
tasks they attempt, experiments have shown this to be false. The way information is
presented affects the ability to solve problems quite significantly.
“Humans, often do not use subroutine-like rules for
making decisions” (ibid.) Quite often emotional rather than rational
factors are the major aspects of decision making.
The work of Damasio is seminal in this regard
These three factors alone shift significantly,
the approach to designing intelligent machines and I would add,
assessing the intelligence and consciousness levels of other natural
animals. Together with the four previously mentioned attributes or
“essences of human intelligence” required in an entity it is little
wonder classical AI has not achieved its optimistic goals. Expert
Systems, such as Weizenbaum’s famous “Eliza” program,
impressive as they were, really had little to do with true artificial
intelligence (Weizenbaum, 1976). Although
numerous ‘hopefuls’ believed these systems did display elements of true
AI I do not think Weizenbaum himself ever made such claims.
Returning now to the essential
attributes for the development of intelligence (and the possibility) of
conscious awareness I will look first at development. (a) Development is the framework within which
an infant gradually acquires more and more complex skills. “Humans are not born with
complete reasoning systems, complete motor systems, or even complete
sensory systems” (Brookes et al. 1998). The earlier developmental
processes seem to, “...prepare and enable more advanced forms of
behavior to develop within the situated context they provide” (ibid.).
(b) Social Interaction. “The presence of a
caregiver to nurture a child as it grows is essential. This reliance on
social contact is so integrated into our species that it is hard to
imagine a completely asocial human” (ibid.).
The ABC, some three years ago, televised some
secretly obtained footage of children’s institutions in Russia where
very young children were abandoned and had absolutely minimal social
and physical contact, and certainly none with a carer.
The children were assessed by Aid workers to be
severely emotionally (and from memory) intellectually, undeveloped. Work with autistic
children also gives clues as to the importance of social integration, a
number of scholars including Sacks, Synder and Baron-Cohen work and
investigate within this field.
As Brookes et al. note the most obvious and clearly
overlooked aspect of human intelligence is that it is embodied. There
is a direct physical coupling between action and perception without the
need for intermediary representation.
“For an embodied system, internal representations
can be ultimately grounded in sensory-motor interactions with the world
(Lakoff, 1987) (ibid.).
One reason for it being
‘overlooked’ I believe is a religious one.
For the last two thousand years the dominant
influence on Western thinking has been Christianity.
Christianity maintains the ‘flesh’ is unclean,
necessary for a time to be sure, but ultimately it is the spirit that
in this tradition Descartes separated the body and mind, as though the
body was more or less irrelevant to the mind.
I mention this not just as an aside but because of
the pervasive influence of spiritual traditions both East and West on
the psyche of humanity. If
the body is essential to the maintenance and formation of mind and
consciousness, it raises very serious problems for such doctrines as
The importance and impact of
the realisation that mind and body are not separate, that embodiment is
essential to the development of anything that can be considered ‘mind’
has not yet been realised by society at large.
The corporeal/mental (spirit-soul-mind) dichotomy is
so entrenched in our languages and culture that when it is fully
realised that there is no central controlling executive, no esoteric
special ‘matter’ that constitutes mind, it will be equivalent, in my
opinion, to a Copernican Revolution.
The ramifications of which we can only barely
imagine at present.
Just as no executive controls our every function, evidence now suggests
that no one sensory input (visual, olfactory) is independent of the
others. The huge
amount of information that comes from the external environment is
processed simultaneously and of course gives us our view of the world.
“Stimuli from one modality can and do influence the perception of
stimuli in another modality” (ibid.). This means any attempt to create
artificial intelligence must take this dependent
phenomenon into consideration.
The Cog team’s methodology,
recognises the above attributes because they are important aspects of
human intelligence and, “...from an engineering perspective, these
themes make the problems of building human intelligence easier” (ibid.)
Apart from the fact that
embodiment is a necessary criteria of intelligence, by giving their Cog
creations, bodies, it allows humans to interact with the robots in a
natural way. Further,
“...the effects of gravity, friction and natural human interaction are
obtained for free, without any computation” (ibid.).
One fascinating and on reflection, essential
attribute of the Cog robots, is that of eyes.
The team has recognised the vital importance of eye
contact between human infants and their carers, and later, eye contact
with adults. The
robots have specially designed complex eyes which allow this
interaction and also enable the robot to visually recognise the various
people it interacts with each day.
The development of the system is incremental,
that is, the earlier learnt behaviours and so on, “...bootstrap the
later structures by providing subskills and knowledge which can be
re-used: (ibid.). Just
like a human infant the system gradually increases it understanding and
gradually becomes able to handle more and more complex problem solving
important thing to realise with this approach is that it is, “...in
stark contrast to most machine learning methods, where the robot learns
in a usually hostile environment, and the bias, instead of coming from
the robot’s interaction with the world, is included
by the designer” [my emphasis] (ibid.).
The Cog team’s approach does
not emphasise enculturation as much as I believe is necessary. Socialisation is not quite
the same thing as enculturation and whilst, “Social interaction allows
humans to exploit other humans for assistance, teaching and knowledge”
(ibid.) this does not necessarily imply that culture is being passed on
per se. Culture is arguably as important in the development of human
intelligence and consciousness as are biological factors, consequently,
an intelligent entity needs to learn and be moulded by cultural inputs
so as to be able to communicate to others in that culture. Granted, part
of this transmission of culture takes place during the
normal socialisation of humans.
One last aspect of the search
for the necessary fundamentals of intelligence and consciousness is the
notion of the Unconscious. A
colleague’s chance remark, asking me just how one would create the
Unconscious, even if it was possible to create the equivalent of the
conscious mind, led me on an intense investigation of the Unconscious. To my knowledge this
aspect of human mentation has not been discussed in the AI literature. Similar to the central
executive controller concept being exposed as a myth so too have I
shown that the notion of the Unconscious, particularly in the Freudian
sense, is an artificial construct.
The Freudian Unconscious with its supposed sexual,
libidinal repressions and its expression, symbolically through the latent dream content, does not exist. The unified brain-mind has
various mental states, most are nonconscious
at any one time, the brain-mind may contain painful suppressed
memories but these are nothing to do with the widely accepted and
almost unchallenged existence of the Unconscious (Harle, 1999). The removal of the
Unconscious from consideration in AI research is one further advance
towards creating true artificial intelligence.
In conclusion, I have attempted to present in this paper the broad issues involved in the project of creating an artificial intelligent, conscious entity. I believe this is practically and, in principle, impossible if we follow the path of classical AI, that is, computational power and huge amounts of knowledge (facts). However, if we pursue the approach developed by the Cog team, and once certain hardware constraints are overcome, especially the creation of massive parallel neural network architectures I can see no plausible argument that denies the possibility of creating an intelligent, conscious, non carbon-based entity.
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Hofstadter, D.R. Fluid Concepts and Creative Analogies: Computer
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Books,Harper Collins., 1995.