Peter Williams (201407)
STAS Topic #3
Science, Technology and Society
‘The brain is just a computer made of meat’
This brave statement by Marvin Minsky, one of the Artificial Intelligence pioneers in
the 1950s, brings about the question which has been plaguing AI experts since the
birth of the field – What exactly constitutes intelligence? Without knowing the answer
to this question where can we draw the line and say we have made a machine that is
truly intelligent? Is intelligence merely the ability to solve problems? If so, any
computer from a calculator to a Cray would have some degree of intelligence. Alan
Turing developed a chess program in 1952 – even though he didn’t have a computer
which was powerful enough to run the program – which undoubtedly could plan the
next move, analyse the opponent’s and execute its own. It was ‘thinking’, but does
thinking actually constitute intelligence?
‘The key to understanding cognition rests, to some degree, in understanding
memory, perception, language and other cognitive phenomena’ (Morelli & Brown,
1992, p.2). Reasoning and judgement can also be added to the list of common
definitions of cognition. It is evidently clear that there is much more to the brain than
just knowledge and calculation. Alan Turing believed that if someone could develop a
machine which can be asked questions and formulate an answer through the user of
this perception, understanding of language, reasoning and judgement (and fool the
individual asking the question into believing that it was human) then the machine
would be intelligent. Nobody has yet been able to do this.
Maybe we need to look at the brain in a medical perspective. Dr Eric Chudler,
an expert on neuroscience at the University of Washington, identifies the differences
and similarities between brains and computers, ‘both computers and brains store
memories; both computers and brains can be modified to perform new tasks.
Computers and brains both have the ability to monitor their surroundings and respond
with behaviour to manipulate their environment’ (Chudler, 2001, p6-7).
This cause/effect selection may be the largest similarity between brains and
computers – it forms the basis of every human thought and computer calculation.
Basic computers like calculators respond to a set of given numbers and operators and
output an answer; the brain responds to ‘sensors’ in the body when cold, and responds
by making you shiver. A thermostat (just a switch, of which a computer is made from
millions) responds to the cold by turning on the boiler. Obviously this type of
‘intelligence’, if you can call it that, doesn’t compare to the complexity of human
intelligence, but thousands of similar cause/effect, input/output actions happen in the
brain every second.
Dr. Chudler does however mention the fact that the big difference between a
human brain and a computer is consciousness and awareness. ‘You know you are
here… [Computers] do not experience the emotions, dreams and thoughts that are an
essential part of what makes us human’ (Chudler, 2001, p6-7).
This consciousness or awareness is what throws the validity of the Turing test
into question – If a computer were able to fool a human into believing that it were
another human would it be intelligent? Is it consciously fooling the human, or has it
just got a large knowledge base and extensive adaptive programming?
Consciousness, in the context of this topic, means the knowledge of one’s own
existence, condition (i.e. state), sensations, etc. Computers can certainly be in an ‘on’
condition or state – in other words conscious – but are they actually aware of this state
like a human is? Basic human consciousness constitutes a set of automatically
controlled actions such as the beating of the heart, breathing, and temperature control.
Without these measures the body would surely malfunction. The brain knows this,
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Peter Williams (201407)
STAS Topic #3
Science, Technology and Society
and thus controls these actions to ensure a malfunction does not occur. This is
consciousness.
In a computer these actions, or controls, can be likened to the computer clock,
the states of the critical processes, and memory management. If these controls were
not in place, the computer would surely malfunction. The computer knows this, and
therefore ensures that faults do not occur. Is this not also consciousness? By
comparing two systems with remarkably different architectures surely their
definitions of consciousness will be similar in context but different in substance. Why
would this make a computer less intelligent than the brain? Maybe the psychological
abilities of brains and computers may provide an insight into their different types of
intelligence.
What can a brain do? The brain is very versatile and can perform many
different types of activity. Some of the prominent characteristics are:
 Recognition of signals from the body and responding to them.
 When confronted with a problem the brain will (sometimes – see emotion)
logically formulate a response based on facts, knowledge and often form
opinion from the combination of these factors.
 The ability to learn; basically adaptation according to fact and knowledge,
learning from mistakes, or avoiding them due to ‘common sense’.
 Learning the art of language – pronunciation through to vocabulary,
grammar through to presentation of a topic (like writing an essay!).
 Experiencing emotion. Happiness, sadness, love, anger, fear, etc. are a
collage of emotions that can affect, either by hindering or improving, the
outcome of a human’s actions or opinions.
So, is it possible for a computer to have these characteristics?
A computer recognises signals from its inputs and responds to them via its
outputs. This forms the basis of the Input  Process  Output model. A computer
can be given a problem and logically formulate a response based on information
stored. If a computer was programmed to take a wealth of information and work out
the pros and cons of each bit of information, I am sure it would be possible for the
machine to form an opinion of sorts based on facts and knowledge.
We come to learning. Basic learning is based on adaptive behaviour, a theory
called ‘Knowledge of Results (KR) – where a stimulus or behaviour is performed and
the resulting response is recorded and acknowledged’ (Annett, 1969, p.9). There are
two types of this associative learning – Classical conditioning and Operant
conditioning. I will focus on operant conditioning, where the brain associates a reward
with a successful behaviour and a punishment with an unsuccessful behaviour. This is
an example of trial and error, or learning from your mistakes.
Dr Tarassenko from the Robotics department at Oxford University believes
that computers that learn through trial and error are not intelligent. The robots that he
works on navigate a room, and when they hit an obstacle they know that it is there and
do not hit it again. He believes that his robot doesn’t meet the criteria set by classical
AI research, “knowledge”, “planning”, and “reasoning”. Dr Tarassenko says, “[The
robot] doesn’t plan, it reacts to collisions. It has no concept of what an obstacle is at
all, and it doesn’t reason about it because it proceeds by trial and error.” (Connor,
1993). The author of the article came to the conclusion that learning through mistakes
is not enough to constitute intelligence, even though that sort of behaviour is that
possessed by a young child or animal. However, I personally believe that operant
conditioning is an important way of learning and that a computer can definitely be
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Peter Williams (201407)
STAS Topic #3
Science, Technology and Society
programmed to store examples of why it was rewarded and why it was punished and
learn from it – after all, children learn most of what they learn through this method.
Computers find it extremely hard to understand human language. ‘Computers
remain lousy at context, at disambiguation, at getting jokes, at intent, at meaning, at
everything we call understanding.’ (Censorware, 2000). This is because every word
read by computers that supposedly understand language is read into the computer
without considering many of the words around it. Even though they understand the
vocabulary, and some ‘intelligent’ systems can understand a bit of context – for
instance the type of verb – they can’t quite get the gist of grammar or presentation.
There is a long way to go to replicate the type of language used by, for instance, HAL
in the film 2001: A Space Odyssey, where the computer talks perfectly to its
operators.
No computer can currently experience emotion in the way HAL did; But why
would we want to mimic a trait often seen as a hindrance to our own human
performance? Although there are cons to integrating emotion into computers – what is
the point of having a computer that gets all upset when it crashes – ‘Emotion provides
us with a motivation and drive, with a set of personal preferences, with a uniqueness
that is desirable in a sophisticated AI.’, (Reingold, 1999). There are two types of
emotion – external and internal. External emotion in the AI field is where the
computer appears to have emotion (i.e. synthesised speech), and this is definitely an
advantage. At the moment, computer interfaces usually take quite a while to learn.
Even Microsoft’s Windows takes months for a person that has never used a computer
to get the hang of. An interface that could understand the emotion of the user, and
display its own emotion – with the combination of language skills – would be very
easy to use, and would make it very much more human. Internal emotion would mean
that the machine would actually have feelings that would affect the way it operated
and performed. It would give the machine the drive and motivation that humans have,
it would also give the computer a personality of sorts. This is all influential in
improving human interaction with computers. It would make the machine more
efficient when interfacing with humans, and would help the computer form opinions
in a similar way to a human. This would, in turn, make the computer seem more
intelligent.
Is a brain just a computer made of meat? Maybe if we reverse the question,
and ask if a computer could be a brain made of electronic components in the future, a
system that has all or maybe just some of the traits above might just be considered
intelligent. I believe it will be possible to beat the Turing test, but we must look at the
issue from a psychological perspective instead of a computer science one. Intelligence
- the ability to comprehend; to understand and profit from experience, an ability to
acquire, retrieve, and use knowledge in a meaningful way, and an ability to learn and
understand new knowledge or reason in new situations are all definitions. I would
consider a friendly talking computer with problem solving skills, conditioning by
association, the ability to formulate an opinion of it’s own and not it’s programmers,
and a passion to solve the problem would be a very clever machine indeed. I do not
think it will be too long before we can not just emulate but integrate some of these
traits into a computer, and maybe call a computer intelligent. However, if intelligence
is only available to those with a brain, in conclusion to the whole debate we must
remember that the brain is only a computer made of meat!
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Peter Williams (201407)
STAS Topic #3
Science, Technology and Society
Reference List
Morelli, R & Miller Brown, W. (1992). Minds, Brains & Computers. Norwood, NJ:
Ablex.
Chudler, E. (2001, March). A Computer in Your Head? - Odyssey Magazine, 10:6-7.
(Note: Digitised at http://faculty.washington.edu/chudler/computer.html)
Annett, J. (1969). Feedback and Human Behaviour. Harmondsworth: Penguin.
Connor, S. (1993, November 7). The Brain Machines. The Independent on Sunday.
The Censorware Project. (Sep 7 2000). Computers and Language. Retrieved May 03
2004, from http://censorware.net/essays/ai_jm.html
Reingold, E. (1999). Can Computers Possess Emotional Intelligence? Retrieved May
04 2004, from the University of Toronto,
http://www.psych.utoronto.ca/~reingold/courses/ai/emotional.html
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