Symbol Grounding Problem

From: Smith, Wendy (WS93PY@psy.soton.ac.uk)
Date: Tue Jan 23 1996 - 09:23:22 GMT


Searle (1980) proposed that computation alone was not cognition. He
suggested that cognition was some sort of computational process and
output, combined with some form of intentional phenomena. Furthermore,
the production of the intentional phenomena cannot be merely by running
a program. The Chinese Room argument is an ingenious mind experiment
devised to support this hypothesis.

Before we look as the Chinese Room, we have to look at the Turing Test.
The Turing Test sets the stage of having a computer in one room, and a
human being in another room. Identical messages are sent into both
rooms. If, from the replies , we are unable to distinguish between the
computer and the person, then deciding that one has a mind and one
doesn't is, on the surface, arbitrary rather than based on evidence.

Searle was criticising strong AI which, he claimed, considered the
programs to be explanations of cognitive states, rather than tools to
explore explanations. He quoted a program devised by Schank, which
provided a script and a story. The script referred to the "usual"
sequence of events in a certain type of situation, and the story was of
a specific situation of this type. Questions could then be asked which
couldn't be answered directly from the story, but could be inferred
from the knowledge of the script. Some workers considered that the
ability of a machine running these programs to answer the questions
correctly, as a human would, was evidence of understanding.

Searle asked us to imagine that he was locked in a room with a set of
Chinese symbols. He knows no Chinese, and the squiggles are meaningless
to him. He is then given a second set of Chinese symbols, along with a
rule book. The rules are written in English, and set out how he can
correlate the second batch of symbols with the first. He is then given
a third batch of symbols. By following he rules in his book, he can
correlate this batch with the other two batches, and return certain of
the symbols. To the people outside the door, they have provided Searle
with a script, a story and a question, all in Chinese; he has answered
in Chinese; ergo, he understands Chinese. From Searle's point of view,
he took some symbols and manipulated them in various ways based on
their shape. Understanding never entered the proceedings at any point.
Searle did not understand Chinese when he received the symbols;
manipulation of the symbols did not produce understanding; and he did
not understand Chinese when he gave the "answer" to the question.
Therefore, if the computer can understand, it isn't by virtue of it's
program, because Searle could "run" the same program and not
understand. Understanding is not intrinsic within the program. The
understanding was provided by an outside agent interpreting the input
and output of the system.

Therefore, if by computation we mean the manipulation of symbols based
on their shape, then computation alone is not cognition. There needs to
be something else. Searle had described this as an "intentional
phenomena", but this is not well specified. Searle did not understand
Chinese: the manipulations were syntactic, and based on the shape of
the symbols rather than their meanings. However, if the same mind
experiment had been performed with letters from an English alphabet,
then a different situation would arise. Searle would have performed the
same manipulations, but rather than being syntactic, the manipulations
would have been semantic, and the symbols would have had meaning.
Searle would have understood them, because the symbols were grounded.
The next problem is how the symbols are grounded.

The answer can't be within the symbols. This would be like trying to
learn Chinese with only a Chinese-Chinese dictionary to help. One
symbol would lead to a mass of other symbols, and so on, but the
meaning of the symbols would never appear. Some sort of "Rosetta Stone"
process is needed to ground the symbols. However, even this won't work;
it suggests we could learn Chinese from a Chinese-English dictionary.
Perhaps we could, but we are still left with the question of how we
learned English in the first place.

One suggestion is to connect the symbol system to the world. If this is
done "properly" it will ground the symbols. However, this also begs the
question, and gives rise to a Homuncular argument. It just replaces the
English-Chinese dictionary with a "something"-Chinese dictionary. Using
an arbitrary symbol system to ground an arbitrary symbol system just
leads into an infinite regression. It can't be ground that way without
a Rosetta Stone, and that just involves a homonculus. The symbolic
approach does not appear successful. So, it would seem that the
symbols have to be grounded in non-symbolic representations. These are
not arbitrary, but are grounded in the real world.

Two basic, non-symbolic representations can be described. The first is
an iconic representation. Objects and events in the real world are
accessed by the sensory equipment, which gives rise to an "iconic
representation" - an analog of the object or event. From these
representations, certain invariant features can be extracted (by an
innate mechanism), to form "categorical representations". From this,
elementary symbols can arise, and "symbolic representations" can be
grounded in the elementary symbols.

This still leaves the question of how this could be done. Perhaps we
need to return to the Turing Test for this. One problem here is that
the machine and the person are locked in a room, and all that is being
tested are their linguistic capacities. This is not sufficient - the
test can be passed with a system with no "mind", as Searle showed.
However, humans have more than linguistic abilities. For example, if we
consider a robot which also has sensorimotor c apabilities, we can give
it an object it has to name, a flower. Searle would do this by looking
at the flower, touching the flower, smelling the flower, and then
replying "rose". The robot also touches the flower, receives data input
from the flower, and replies "rose". Before, with only linguistic
capacity, we could say that the program was not generating
understanding, because Searle could run the same program without
understanding. However, once we introduce sensorimotor abilities, the
situation becomes more difficult. Searle understands the concept "rose"
through his sensorimotor capacities. The robot appears to be doing the
same thing. The robot may or may not have understanding, and a "mind",
but there again, that statement could also apply to Searle! The robot
may not be performing exactly the same processes to arrive at the same
results, but nevertheless it is interacting with the object in a
meaningful way, without he need of an external interpreter. Therefore,
if we decide that the robot does not have a mind, it is an arbitrary
decision, rather than because it is observably distinguishable from a
human.

To summarise, Searle described the Chinese room argument, which
demonstrated that the program running a machine could not guarantee
understanding, because he could "run" the same program and produce the
same results without any understanding. However, the machine being
tested had only linguistic capacities. When sensorimotor capacities
were added, this claim could no longer be made. It was not possible,
for example, to claim that the robot was not "seeing", in the same way,
because Searle could "see". Therefore, if the robot receives input
through sensorimotor c hannels, rather than arbitrary symbols, it is
more difficult to judge that it is not understanding. One of the
problems with understanding symbols is that t hey have to be grounded
in something other than more arbitrary symbols. One solution is that
they could be grounded in non-symbolic representations, which are not
arbitrary, and are acquired through sensorimotor interaction with the
objects in the real world. Through connectionism, these iconic and
categorical representations can be associated with their linguistic
symbols.



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