Kasparov and Chess
Chess has an exceptionally clear and distinct goal—achieving checkmate. It also follows a relatively simple set of rules and has no element of chance or randomness. And yet, as anybody who has played chess has realized, using those simple rules to achieve that simple goal is not at all easy. It requires deep concentration to survive more than a couple of dozen moves into a chess game, let alone to actually win one. Early computer programmers in the 1960s had a vision that chess might be an excellent challenge to assess artificial intelligence.
Programmers and chess players discussed and debated four potential advantages for computers over the next four decades:
- They are very fast at making calculations.
- They won’t make errors, unless the errors are encoded in the program.
- They won’t get lazy and fail to fully analyze a position or all the possible moves.
- They won’t play emotionally and become overconfident in an apparent winning position that might be squandered or grow despondent in a difficult one that might be salvaged.
These may be weighed against four distinctly human advantages:
- Our minds are flexible, able to shift gears to solve a problem rather than rigidly follow a set of codes or algorithms.
- We have the capacity for imagination.
- We have the ability to reason.
- We have the ability to learn.
A chess game, like everything else, has three parts: the beginning, the middle and the end. What’s a little different about chess is that each of these phases tests different intellectual and emotional skills, making the game a mental triathlon of speed, strength, and stamina.
In the beginning of a chess game the center of the board is an empty space, with pawns, rooks, and bishops neatly aligned in the first two rows. The possibilities are almost infinite. White can open the game in any of twenty different ways, and black can respond with twenty of its own moves, creating 4,000 possible sequences after the first full turn. After the second full turn, there are 71,852 possibilities; after the third, there are 9,132,484. The number of possibilities in an entire chess game, played to completion, is so large that it is a significant problem even to estimate it. Diego Rasskin-Gutman has written, “There are more possible chess games than the number of atoms in the universe.”
In the middle of the match, once the pieces are locked in combat and threaten one another, there are many strategic objectives available. It is a matter of devising tactics to accomplish them, and forecasting which might have the most beneficial effects on the remainder of the game. Chess players learn through memory and experience where to concentrate their thinking and assess their own strengths--some prefer knight combinations, while others excel at placing rooks in strong positions.
In the final stage of a chess game, the endgame, the number of pieces on the board are fewer, and winning combinations are sometimes easier to see--the chess puzzles on websites and in newspapers and magazines depend on the limited possibilities to assert with authority there is a "best" move. This phase of the game necessitates a lot of precision, since closing out a narrowly winning position often requires dozens of moves to be executed in careful order without any mistakes.
Machines that replace physical labor have allowed us to focus more on what makes us human: our minds. Intelligent machines will continue that process, taking over the more menial aspects of cognition and elevating our mental lives toward creativity, curiosity, beauty, and joy. These are what truly make us human, not any particular activity or skill like swinging a hammer—or even playing chess.--Garry Kasparov, Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins, 2017, p. 10.