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the conversationalists involved. Both synchrony and self-synchrony are extremely
relevant in that signalers, such as nonhuman animals and machines, do not reflect
messages by other physical means than the medium specific to conveying the literal
message (Bavelas et al.
2002
; Knapp and Hall
2006
: 43-54). In other words, the
message is fully formed prior to being broadcast. Rather the message is one of
several means for directing the interaction. Once we have better understood how
problems are solved in organic minds, via some form of nonverbal communication,
we will then revisit how the computer might be implemented as a prosthetic tool
(Licklider
1960
;Wiener
1950
). Though it is popular to say that computers and
brains are nothing alike, it is also popular to apply the same model of processing
to the brain as to machines, with only a vague sense of how processing might
take place. For this reason, while we do not intend to outright debunk the notion
that intelligence can be synthesized (Horzyk and Tadeusiewicz
2005
), but do need
to initially discuss a nuance of processing, which bears on a particular role of
communication and consciousness.
Computers are mechanical tools, which inventors have adjusted to correspond
to our concept of mathematics. Programmers then apply this numerical corre-
spondence to concoct complexes of syllogisms, which can be further reformulated
in very un-mathematical-looking graphics. Insofar as one might
metaphorically
envision circuits and transistors as hierarchical conditional tree diagrams (
as in
Lakoff and Johnson
1980
), the same root assemblage of concepts in the mind
that allow one to make sense of Boolean logic are applied to digital processing.
The assumption is that this empirical scheme applies to any cognitive function
may be more about personal perspectives than about a priori truths (Baron-Cohen
2009
;Boyd
2004
). The case is argued passionately both by those who feel this is
obviously true (Shanahan
1997
; von Neumann and Morgenstern
1944
; Glimcher
2009
) and those who feel this is ridiculously impossible, particularly considering
human interaction (Ackernan and Bargh
2010
;Edelman
1992
; Koch and Tononi
2011
). “Every Boolean function no matter how complex, can be expressed using
three Boolean operators only: And, Or, and Not.” (Nissan and Schocken
2005
:9)
The question remains then whether every task can be expressed as a
conditional
statement,
using one of several variants on the theme “if x, then y.”
A less obvious point remains that the experiences presented in ordinary daily
living are extremely unlikely to prove sufficient to account for the complex concepts,
which we entertain. It is further restrictive that, due to the evolutionary construction
of the brain and DNA, a “lesson plan” must simultaneously be somewhat useful
in our current environment, but applicable to some ancestral species-specific
environment (Bjorklund and Pellegrini
2001
). Olaf Sporns, in his overview of neural
networking, states that “Nervous Systems do not converge onto a final stable pattern
of optimal functionality, rather, their connectivity continues to be in flux throughout
life.” (Sporns
2011
: 252) Thus, no matter how similar a neural network in an organic
brain and one in software process computational tasks, there is still an additional,
perhaps far greater task, which is not remotely addressed by mechanical means,
in ongoing re-contextualization of data, from generalizing to other domains, to
inferring detailed implications (Koch and Tononi
2011
). Because this ability, is not
