Dixit Magister (part 2)

by admin on September 15, 2012

This post is part two of a three-part series. As explained in my previous post, it is an article that I wrote in 2007 but never published, in which I tell the story of the best game I ever played. More than that, it is an attempt to take non-chess players inside the game so that they, too, can appreciate what beauty means in chess.

DIXIT MAGISTER (continued)

© Dana Mackenzie


Among all sports, chess is one of the most democratic. Cast your eye over the ballroom at the Sands Regency Casino in Reno, Nevada, and you will see 250 players of all abilities, from near-beginners to grandmasters. In what other sport can an amateur enter the same event as a U.S. champion? Or an eight-year-old boy play an 80-year-old man on even terms? (The eight-year-old may even be the favorite.) The crowd includes many chess players of color, many with foreign accents, and even a few women (though not nearly enough).

At the same time, chess is also, like any sport, a ruthless meritocracy. The tournament hall in Reno is strongly segregated by skill, though this may not be apparent to the naked eye. The top ten boards, up on the stage, are the province of the grandmasters and international masters. Every one of these boards has at least one player with a Russian or East European name. Off the main stage, from right to left in the tournament hall, follow the masters, the experts, and the category players from class A down to D and E.

The meritocracy is aided and abetted by a rating system that would horrify politically correct academics. Long after IQs fell into disrepute and aptitude tests began to attract suspicion, the measurement of intelligence is alive and flourishing in chess. The Elo rating system, designed by statistician Arpad Elo in the 1950s, quantifies every player’s skill with a number (usually between 100 and 2800, though there are no fixed upper and lower limits). The system is accurate to a sometimes spooky extent. In the first round at Reno, the favored player won every single game in the master section: 26 victories in 26 games, a statistical implausibility that would have sent Professor Elo scurrying back to his blackboard. The combination of numbers and psychology is a potent mix. The lower-rated player becomes afraid of phantoms, believing the opponent has hatched deep schemes that he can’t see. The higher-rated player bears down extra hard, expecting his opponent to make a mistake eventually. In this way, the rating system becomes a self-fulfilling prophecy.

In the final round I am playing on board eleven, just offstage, and my opponent is David Pruess. He is a genial 24-year-old international master, and the only person in America who draws a full-time salary for playing chess. He is the recipient of this year’s Samford Fellowship, which provides $32,000 and intensive chess training for one gifted young player a year.

According to our ratings, it is a complete mismatch. I know it and Pruess knows it. According to the rating system I should be at least a seven-to-one underdog, but that doesn’t take into account the psychological effect of ratings. But in this game, the psychology proves to be Pruess’s undoing. He unknowingly assumes the role of the infallible computer, while the two of us go through the opening sequence I have already played so many times. Pawn to e4. Pawn to c5. Pawn to f4. Pawn to d5. Knight to f3. Pruess pauses when he sees this unusual move, the gauntlet landing at his feet. Something is not right—he senses a trap. But still, the best move is the best move; it must be played. It’s a matter of professionalism. He takes my pawn. Knight to g5. Knight to f6. Bishop to c4. And now…

Pruess thinks for five minutes, ten minutes, fifteen. Later, after the game, he will explain, “I wasn’t going to be intimidated into playing a move that wasn’t the best, just because my opponent might have some threats.” In his blog on the U.S. Chess Federation website, his friend and now grandmaster, Josh Friedel, wrote, “David’s need to refute everything that looks fishy to him took over common sense.” Pruess reaches for his bishop and plants it on g4. He has played the same move that the computer plays, and ironically for roughly the same reasons. The computer knows no fear because it is built that way. Pruess knows no fear because he has such a huge rating handicap… and because he is built that way.

The bishop remains there for less than five seconds. Under some circumstances I might have let it stay there longer, pretended to think about the position in order to disguise the fact that I have already prepared this opening at home. But not today. I am too excited, too impatient. I have been playing this position and dreaming about this moment for two years. I slide my queen three squares diagonally to g4 and capture the bishop. The queen’s life is forfeit. The battle is on!


The third, and most important, player in this chess drama is not a human at all. It is a chess-playing entity that resides on a compact disk inside my computer. This entity is called Fritz 9, the most recent in a long line of chess-playing machines and chess-playing programs that have utterly transformed the world of chess.

By happenstance, my career has almost exactly coincided with the rise of chess computers. In the 1970s, when chess calculators first came out, they played laughable chess. A “computer move” was a move that made no sense, a move that no human would play because it demonstrated utter cluelessness about the game. But by the early 1980s, the top computers were beginning to defeat serious players. In 1982 a computer called Belle, named after Bell Laboratories and programmed by Ken Thompson, the creator of the UNIX operating system, became the first machine ever to achieve a master rating.

In 1983, I actually had a chance to play Belle in the U.S. Amateur Team Championship. Thompson himself sat at the board across from me, keying the moves into the computer. In the end the computer lost, making what at the time was a very typical “computer move.” Where a human would have kept both queens on the board to preserve some chance of drawing the game, the computer allowed me to trade queens. It was a slave to its evaluation function, a part of the program that assigns a numerical value to every position: a 0.5-pawn advantage, a 0.8-pawn disadvantage. Humans do not do such precise calculations; they use intuition and experience to guide them. To the computer, the queen trade marginally improved its position. In my view, it was trading a murky position for a clearly hopeless one. However, “clearly hopeless” was not a concept that the computer understood.

Thompson more or less retired from the computer chess field after that year, but computers kept getting better and better. First they beat masters, then international masters, then grandmasters. After a while, the only question was when (not whether) they would beat the human world champion. That day arrived sooner than anyone expected—on May 11, 1997, when IBM’s Deep Blue humiliated Garry Kasparov in the last game of a six-game match.

For some people, Kasparov’s loss was a tragic event, the day that humans lost their ascendancy over their silicon creations. In fact, it has not worked out that way. Deep Blue represented a harnessing of human brainpower: the combined knowledge of the people who designed the chips, the people who did the programming, and the chess masters who provided guidance on chess principles. It was only natural that an entity that combined the mental powers of many human brains would eventually defeat a human who could only tap the power of one.

The real question, which everyone missed at the time, was not “What will happen when one computer beats the best human?” The question we should have asked was “What will happen when every chess player can own a computer that can beat the best human?” The arrival of commercial programs of world-championship caliber, such as Fritz, has transformed the chess world far more than the one-shot accomplishment of Deep Blue. Chess players are the first group of humans to fully confront the implications of artificial intelligence, the future envisioned in Stanley Kubrick’s 2001: A Space Odyssey.

What has the computer wrought? It has both liberated and enslaved us. First, it has overturned decades of chess wisdom. In position after position, game after game, it has demonstrated that “computer moves” are quite playable, and sometimes better than the human conventional wisdom. It has opened our eyes to possibilities that we did not know existed. It has done so not by virtue of some special insight, but because the computer examines every move without prejudice. Many of our beloved principles of chess, it turns out, were merely prejudices. Some writers, notably English grandmaster John Watson, have argued that there are no principles left in chess—only a bewildering thicket of individual moves and variations.

But at the same time, the computer poses a real danger for the ordinary player. If we are not careful, we can be enslaved by it. I have already seen middle-of-the-road players who are afraid to trust their own judgement, who will play the “computer moves” no matter whether they are too reckless or too conservative. The computer’s numbers appear precise, objective, inarguable. It takes a conscious effort of will to detach ourselves from them. Do you trust Fritz when it says, “White is 0.67 pawns ahead”? Or do you trust Jonathan Rowson when he writes, “Ask the [pawn] on b3 if he feels proud of himself”? If you listen to the computer too much, you can no longer hear your pieces.

And there’s one other thing that the computer cannot do. It absolutely cannot appreciate beauty. And yet, for me, chess without beauty is not worth playing.

I noticed this for the first time when I would let Fritz, the computer program, annotate its own games. It virtually never gave any exclamation points. “Exclams,” as players call them, have a long and honorable history in chess. They are the annotator’s way of pointing out a brilliancy: a move that is subtle, witty, difficult to find. In a word, beautiful. Especially remarkable moves get two exclamation points. I remember, as a teen-ager, poring through Irving Chernev’s 1000 Best Short Games of Chess and looking for moves with three exclamation points. And yes, there were some—the two or three moves that Chernev considered the greatest in chess history.

As I thought about Fritz’s inability to award exclams, I realized that exclamation points make absolutely no sense to a computer. From the computer’s point of view, it is the player’s obligation to find the best move, every time. There is no such thing as a brilliancy. There is only the correct move, and everything else is a blunder. What does subtle, witty, unexpected mean to a computer? The categories are too subjective. Even humans can’t agree on them. And yet without them, there is no beauty in chess. It is nothing but a zero-sum game. It is no longer an art form.

It is one thing to say that a computer cannot appreciate the beauty of chess moves. It is quite another to use that inability to defeat it. In fact, most “anti-computer” strategies developed by humans have done exactly the opposite. They recommend that the human should play ugly moves, in order to reach a constipated position where the computer cannot find a plan.

My solution, in contrast, was to play the most romantic of all chess moves, a queen sacrifice. A move the computer could not understand. I believed that this move was too complex to be reduced by an evaluation function to a single number. It was a move like a quantum wave function in physics, pregnant with a trillion possibilities, which would give birth to a trillion different realities. Only in the game itself will the trillion possibilities collapse into one certainty.

Watch closely! The queen slides three spaces over to g4, taking the Black bishop off the board. The queen’s life is forfeit, but her spirit will linger on.

To be continued…

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