The tools we use to help us think—from language to smartphones—may be part of thought itself.
Later, robots became far more complex. In the nineteen-sixties, a group at Stanford built a human-size robot named Shakey, which could move around an obstacle course and perform an assigned task, such as pushing a block from one room to another. Shakey was equipped with a camera and controlled by a remote computer that had been preprogrammed with a complete two-dimensional map of Shakey’s world.
The world is a cacophony of screeches and honks and hums and stinks and sweetness and reds and grays and blues and yellows and rectangles and polyhedrons and weird irregular shapes of all sorts and cold surfaces and slippery, oily ones and soft, squishy ones and sharp points and edges; but somehow all of this resolves crisply into an orderly landscape of three-dimensional objects whose qualities we remember and whose uses we understand.
It appeared that the brain had ideas of its own about what the world was like, and what made sense and what didn’t, and those ideas could override what the eyes were telling it. Perception did not, then, simply work from the bottom up; it worked first from the top down. What you saw was not just a signal from the eye, say, but a combination of that signal and the brain’s own ideas about what it expected to see, and sometimes the brain’s expectations took over altogether.
One major difficulty with perception, Clark realized, was that there was far too much sensory signal continuously coming in to assimilate it all. The mind had to choose. And it was not in the business of gathering data for its own sake: the original point of perceiving the world was to help a creature survive in it. For the purpose of survival, what was needed was not a complete picture of the world but aone—one that guided action.
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