- seCtIon FoUR: eVoLUtIon
From this emerged the ‘computational theory of mind’. As Searle later put it:
Many people still think that the brain is a digital computer and that the
conscious mind is a computer program, though mercifully this view is much
less wide-spread than it was a decade ago. Construed in this way, the mind
is to the brain as software is to hardware.
(1997, p. 9)Searle distinguished two versions of this theory: ‘Strong AI’ and ‘Weak AI’.
According to Strong AI, a computer running the right program would be
intelligent and have a mind just as we do. There is nothing more to having
a mind than running the right program. Searle claimed to refute this with
his famous Chinese Room thought experiment
(which we look at later in this chapter). According
to Weak AI, computers can simulate the mind and
simulate thinking, deciding, and so on, but they
can never create real mind, real intentionality,
real intelligence, or real consciousness, only as-if
consciousness. This is like a meteorologist’s com-
puter that may simulate storms and blizzards but
will never start blowing out heaps of fluffy cold
snow.
A similar distinction is made between ‘Weak AC’
(or MC) and ‘Strong AC’ (or MC). One strand of
research uses computational, robotic, and other
artificial means to model consciousness, hoping
to understand it better: this is Weak AC, Weak
MC, or MMC (Machine Modelling of Conscious-
ness; Clowes, Torrance, and Chrisley, 2007). ‘The
key intention of the MMC paradigm is to clarify
through synthesis [of notions from psychology,
neuroscience, philosophy, and introspection] the
notion of what it is to be conscious’ (Aleksander,
2007, p. 89). The other strand, Strong AC, aims to
actually construct a conscious machine for its own
sake. By analogy with the arguments over AI, we
might say that someone who believes in Weak AC
thinks we can learn about consciousness by build-
ing machines; someone who believes in Strong AC
thinks we can create consciousness by building
machines.DEVELOPMENTS IN
COMPUTING
According to Moore’s Law on Integrated Circuits, the
number of transistors on a chip doubles every two
years. Remarkably, this observation (not really a trueBRAIns AnD ComPUteRs
ComPAReD
Digital v. analogue. the vast
majority of computers are digital, even
though they may simulate analogue pro-
cesses. A digital system works on discrete
states, whereas an analogue system works
on continuous variables. In music recording,
for example, digital CDs code the frequency
and intensity of sound (a naturally analogue
signal) by discrete digits, whereas analogue
vinyl records represent them by contours in
the groove. Digital coding makes higher-fi-
delity copying possible because slight varia-
tions are automatically eliminated as long as
they are not large enough to switch a 0 to a
1, or vice versa.
Is the human brain digital or analogue? the
answer is both. A neuron either fires (a wave
of depolarisation runs along its membrane) or
not, and to this extent is digital, yet the rate of
firing is a continuous variable. Another ana-
logue process is spatial summation. Imagine an axon with a
synapse on a second cell’s dendrite (see Figure 12.2). When
the first cell fires, neurotransmitters cross the synapse and
change the state of polarisation of the post-synaptic mem-
brane briefly and for a short distance around the synapse.C
on
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t
12.1