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mental processes can now observe the functioning of the living brain
while their subjects think, perceive, and initiate voluntary actions.
I once saw the taped records of an experiment in which a professional
pianist wearing a helmet containing the tomographic array of radiation
detectors for fMRI scanning was asked to listen to a piece of piano
music with which he was not familiar. Next, he was asked to listen to
that same piece for a second time, but now to try to remember it well
enough so that he would be able to transcribe it note by note. As it
turned out, the tomographic fMRI patterns recorded from the subject's
brain during the first and second session were significantly different,
even though the sensory input to his auditory system was exactly the
same in both sessions. What was different was the subject's mental state.
So it doesn't seem out of the question that one of these days cleverly
designed comparative applications of these novel brain-imaging methods
to blindsighted and normally sighted subjects might reveal the NCC at last.
Richard Grimm:
I think you have sounded a good cautionary note that
despite Moore's Law, and although research is obviously moving for–
ward in important scientific areas, not all scientific and technological
issues are linked to progress in terms of something on the order of
Moore's Law. But now, we'll turn to Guy Burgess.
Guy Burgess:
Predicting the future of anything, including technology, is a
risky business. In the first place, there is chaos-the tendency of simple
and well-understood systems to become chaotically unpredictable when
they interact with one another. At the National Center for Atmospheric
Research in Boulder they have a marvelous exhibit which demonstrates
this principle. They start with one of the most predictable machines- a
pendulum. They then hang two more pendulums from a bar at the end of
the pendulum, and the result is pure chaos, not predictability.
When you start trying to predict human systems, things get even
more difficult because humans change their behavior based on their
own predictions. I have a good story which illustrates this principle even
though it might not be altogether true. Years ago, I knew an ace com–
puter programmer. He and his colleague fed staggering amounts of data
about the stock market into their computers. The computers then pro–
duced a series of equations which were able to predict the past behavior
of the stock market with astonishing accuracy. While my friend thought
that this was scientifically amusing, his colleague thought that it was a
way to get rich. When he used the program to play the stock market, how–
ever, he lost. Part of the reason was that his computer skills weren't all that
