Chapter 3: A Wise Guess
Conventional wisdom would have us believe that clear, rational thought is the basis of human intelligence. Aren’t we taught the power of categorical propositions such as, “All clowns are funny; some clowns are sad people; therefore, the prediction: some sad people are funny”? Venn diagrams (known especially to consultants and business strategists) are common ways to express such logic. And then you have Boolean algebra (named after English mathematician George Boole), which can express these relationships in the language of math. Boolean algebra, in fact, is what drives computers. It allows them to calculate and to solve problems.
But if you want a machine that has human intelligence, that isn’t the way to do it. Imagine that you are playing chess the way a computer must play. It has been calculated that there are not 20, or 50, or 150, or even 3,000 possible moves in a game of chess. There are 10 to the 120th power possible moves—1 followed by 120 zeros. As James Hogan explains it, that sum far exceeds the number of atoms in the universe.
But let’s think of something less taxing than chess. How about taking a simple trip around town to run errands? Suppose you need to make ten stops: the bank, the gas station, the post office, the dry cleaners, four electronics stores (to compare prices), and two clothing stores. Do you know, logically, the possible number of combinations of stops? You have 3.6 million options. Adding only one more stop would push the possible combinations of where to go next to 40 million choices.
Sure, the human brain could calculate all 40 million options before you went shopping, but how long would you be standing at the kitchen table before you went out the door? Trying each option would be the equivalent of opening a combination lock by trying every possible combination. Or finding John Smith in New York City by starting at one end of Manhattan and stopping everyone you encountered until you reached the other side.
That’s not how the human brain works.
In fact, imagine the brain calculations going on in the outfield as your everyday Little Leaguer tries to catch a ball: you have the ball’s distance, its initial velocity, projection angle, ball spin, air resistance, and wind turbulence, not to mention the uneven terrain in left field—and any other thoughts migrating through the outfielder’s mind (pizza, girls, texting)—to contend with and possibly gum up the works. How in the world can the brain make all these calculations simultaneously and speedily? There is no assemblage of computers—not even the hundreds of thousands of computers linked in parallel in a thunder cloud of mechanical intelligence—that could maneuver the mitt to capture that sphere of torn horsehide.