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144 Are the Androids Dreaming Yet?
The best analogy I can find to illustrate iterative knowledge discovery
is the 1970s family game ‘Battleship. The game consists of two 10 by 10
grids that you plug your ships into. All the ships are linear shapes of a
few squares in length. The players cannot see each other's ships and must
guess where they are. A very simple way to do this would be to ask your
opponent whether they have a ship on the top left square and continue
systematically across the board, square by square, until you reach the
bottom right hand corner. This would eventually find every ship. If every
ship were a piece of knowledge we could discover all the knowledge in
the world by simply stepping through the board one cell at a time, but it
would take a long time.
A better way to play Battleship is to pick a square at random. If you
get a hit, explore linearly around the hit. This will efficiently find the
rest of the ship. The same might be true for knowledge. We could take
random shots, get lucky and move linearly to flesh out our knowledge.
Once we had exhausted an area we could take a step away at random and
again hope for another hit. This process is exactly the way some people
imagine the frontier of knowledge expands.
But, it is wrong.
The monkey moon shot story explains...
‘I believe that this nation should commit itself to achieving the goal,
before this decade is out, of landing a monkey on the moon and
returning him safely to Earth.”
President Monkey
The monkey nation is asked to mount a moon shot. After a little
time a monkey is asked to report on progress.
“I can report, says the monkey, “I have climbed a particularly tall
tree on the tallest hill on my island and have made over seven hundred
meters progress towards the moon, although this is only 0.0001% of the
way there, this has been quick so I believe we are well on the way”
You see of course the problem. Progress in many problems is
nonlinear. Moving a bit of the way towards the goal does not provide any
actual progress: That is the problem with knowledge. It is not linear in
structure. You need to take leaps to discover new knowledge. You can not
simply look around in the general area. Such leaps are mathematically
huge. The chance of making a successful one by pure chance is virtually
zero.
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