by David Shenk
20. Ke2
(White King to e2)
He chose e2.
20….Na6
(Black Knight to a6)
Kieseritzky, unable to find the perfect offensive move to keep Anderssen off balance, instead fell back to defense, developing his Knight to threaten any piece that moved onto the c7 square. Having lost his own momentum, he knew that Anderssen was about to mount a strong attack.
21. N×g7+
(White Knight captures Pawn on g7; check)
Anderssen now began his final assault, putting the Black King in check with his Knight on g7. (He had previously made this square safe by moving his e Pawn to e5, blocking the Queen from a diagonal rescue mission.) A close observer could see that Anderssen was in good attack position, even without his two Rooks. In fact, it was the Rook sacrifices that enabled him to so quickly put such a tight squeeze on the Black King.
21…. Kd8
(Black King to d8)
Kieseritzky escaped check with his only possible move, feeling the vice squeezing tight on his precious King. But how would Anderssen press his attack?
III.
ENDGAME
( Where We Are Going )
HAL: Bishop takes Knight’s Pawn.
FRANK: Lovely move…Rook to King one.
HAL: I’m sorry, Frank, I think you missed it. Queen to Bishop three, Bishop takes Queen, Knight takes Bishop, mate.
FRANK: Yeah, looks like you’re right. I resign.
HAL: Thank you for a very enjoyable game.
—2001: A Space Odyssey
JANUARY 2003. UP ONSTAGE, microphone in hand, former world champion Garry Kasparov was effervescent. He’d just trounced an opponent that, until this day, had not lost to a single person in two years, a player that was beginning to seem invincible—a player that never, ever worries.
This was a new sort of chess match. Only one of the contestants could sweat; only one required sleep or food. Towering over Manhattan’s Central Park, on the twelfth floor of the well-appointed New York Athletic Club, Kasparov was taking on the world computer chess champion, a ruthlessly efficient Israeli software program known as Deep Junior. After months of exhaustive preparation, he had just won the first of six scheduled games in a scant twenty-seven moves. He was ecstatic, not just for his victory, but also for how easily it was accomplished. Though he was careful not to suggest it himself, this rout obviously augured well for the rest of the match. “Computers still have plenty of weaknesses,” a visibly relieved Kasparov told a large crowd of grandmasters, club players, and schoolkids in his rich Azerbaijani-accented English after the game.
Although these two champions had never played an official game together, it was publicly a kind of rematch for Kasparov, who in 1997 became the first world champion ever to be beaten by a chess machine—the customized IBM supercomputer known as Deep Blue. That loss was a humiliation for Kasparov, who later charged that the rules (which he had agreed to) were unfair, and that Deep Blue’s chess-expert operators cheated by giving their machine some human help during the match. (“I do not want to go into legal details,” he said. “I do not want to waste money for the lawyers.”)*29 Now, six years later, came his opportunity to replay history. This contest, recognized as the first official “man-versus-machine” match by the World Chess Federation (also known by its French acronym, FIDE), was Kasparov’s chance not only to revitalize his image but also to cleanse the past. This was, he declared, the first “purely scientific match, because we had fair conditions for both the human player and for the machine.” He wanted history to regard the Deep Blue match as so badly tainted that it could not be taken seriously.
In fact, the Deep Blue win in 1997 was fair and unambiguous. It was also a historic achievement, the culmination of a fifty-year odyssey whose implications went far beyond chess. Since the mid-1940s, scientists had aimed to create a thinking machine, an apparatus that could compete with or even surpass the human brain in logical operations, pattern recognition, problem solving, and even language. Chess was found to be a useful testing ground because of its combination of simple rules and mind-bending complexity. Playing chess was also a goal whose progress could be easily measured: a chess machine could compete against expert players and be ranked according to its wins and losses. Chess was a founding and enduring experimental model for what came to be known as artificial intelligence, or AI.
For many decades, chess computers fell woefully (laughably) short of their designers’ ambitions. Then in the 1980s, as computing made important strides, chess engines finally began to sharpen. In the early 1990s, the Carnegie Mellon–trained engineer Feng-Hsiung Hsu emerged with a spare-parts machine called Deep Thought that dominated other machines and even seemed competitive with humans. After taking on IBM sponsorship, Hsu’s newly named Deep Blue played its first match with world champion Kasparov in 1996, losing decisively. With further tinkering, though, it quickly became even stronger, and a year later it won a close rematch.
The victory was a profound and chilling moment whose importance was immediately and intuitively understood around the world: technology was now moving into an ominous new realm. It was one thing to build machines that could move earth or fly over the ocean or even recognize a face. Deep Blue’s victory over Kasparov signaled that we were now making machines that could conceivably compete with us. “We are sharing our world with another species,” Newsweek’s Steven Levy would later write, “one that gets smarter and more independent every year.”
This 2003 rematch of sorts seemed to be yet another important milestone. The world was watching to see if we were yet one more step closer to “Hal,” the highly intelligent and manipulative computer from Stanley Kubrick and Arthur C. Clarke’s film, 2001: A Space Odyssey. Reporters from the New York Times to Pravda to Libya Online were following it game by game. ESPN would be broadcasting the finale—the first live national and international TV coverage of chess since the 1972 Fischer–Spassky match in Reykjavik.
So how did Kasparov pull off such a spectacular win in the first game? “One of the ways to win [against computers] is to find a hole in the opening preparation,” he explained afterward. By mutual agreement, Kasparov and his seconds possessed a copy of the Deep Junior program for six months prior to the match, and they had been relentlessly competing against it ever since, probing it for weaknesses, trying out innumerable different combinations to learn how it “thought.” They also relied on other computers to help them beat this computer: sophisticated new databases like ChessBase, which contained over two million chess games played over the last five hundred years; and spectacular analysis software such as Fritz, which could analyze millions of positions per second and rank them for human consideration. With these advanced tools in place, the pile of collective knowledge increased game by game; players of Kasparov’s (and Deep Junior’s) caliber appeared, game by game, to be doing the unthinkable—mastering chess.
But they weren’t there yet. Even with the enormous electronic database at hand, there were still plenty of new tricks to be discovered. In preparation for Game 1, the Kasparov team unearthed a little-used combination that knocked Deep Junior off balance. It was a surprise Pawn sacrifice on Kasparov’s seventh move. After a fairly conventional opening where the Pawns and Knights jockeyed for control over the center board, Kasparov suddenly thrust out his King’s Knight Pawn two spaces to the g4 square, weakening his Kingside.
GARRY KASPAROV VS. DEEP JUNIOR
JANUARY 26, 2003
NEW YORK
GAME 1
7. g4
(White Pawn to g4)
This was a terrific gamble and could have backfired. “In order to expose [the computer’s weak spot],” said Kasparov after the game, “you have to have a lot of courage. All morning I was saying, ‘Should I play g4 or should I not play g4?’” The strength—and weakness—of this move was in its unpredictability and counterintuitiveness. It left his entire position surprisingly vulnerable on both the Kingside and the Queenside. (Notice ho
w disconnected the White Pawns are across the entire board; disconnected Pawns cannot defend one another.) But that was also precisely the advantage of the move as well. From his practice experience with the Deep Junior program, Kasparov knew that this unusual move, 7. g4, was not included in Junior’s openings database (its “opening book”), and would thus force the computer to start thinking on its own earlier than expected. Every computer has to come “out of book” at some point during the opening. Kasparov knew that it was advantageous to trigger this early, and in an unexpected way.
The most striking thing about this and other Kasparov decisions in Game 1 was that they were both tactical (short-term) and strategic (long-term). Until recently, human masters had successfully thwarted even the best computer programs by carefully avoiding short-term tactical skirmishes. Modern computers’ ability to calculate at blinding speeds made them tactical masters, but strategic advantage still lay with expert human players who could think through long-term strategies in a way that had more to do with spatial perception and planning than mathematics. Whole-game strategies in chess were ideas, not calculable equations. One of the things chess computers still could not do was to grasp an idea.
Against Deep Junior, Kasparov was signaling something new. He was not employing classic anticomputer chess. Rather, he played it as he would play another human grandmaster. It was the highest compliment he could pay to Junior’s programmers: they had developed a machine with true strategic ability. They had developed a machine that appeared to be thinking.
This was not much consolation in the immediate wake of such a powerful defeat of the computer program. Kasparov’s performance left many experts in the observation hall wondering aloud whether he would not merely win the match but crush Deep Junior and humiliate its creators. Perhaps the fearsome computers weren’t as advanced as many had thought. Perhaps human players possessed the ability to adapt and improve even more quickly than machines.
Amir Ban and Shay Bushinsky, the Israeli creators of Deep Junior, were fearing the exact same thing. As Kasparov departed for his New York victory dinner, the vanquished programmers shuffled onto the stage looking pale and somewhat embarrassed. They had expected much more of a fight from their baby. “If Kasparov does this to Junior every game, then we don’t deserve to be here,” Ban admitted. He shook a few hands and quietly headed down to Fifty-eighth Street to smoke a cigarette.
GARRY KIMOVICH KASPAROV was born in 1963 in the ancient port city of Baku, Azerbaijan, on the western edge of the Caspian Sea. In the ninth century chess migrated directly through Baku on its way from Baghdad to Kiev. The game came to be known in the region as shahmaty, after the Persian term shah-mat, which later evolved into the English checkmate—shah (the King) mat (is defeated). The eleventh-century Azerbaijani poet Khagani wrote that “time checkmates shahs like elephants gone far astray” and made a reference to “Ne’eman, the great master of chess.” Over time, chess in Baku became like ice fishing in Norway, an indelible part of the culture stretching back more generations than anyone could count.
When Kasparov was six, he shocked his family by solving a difficult endgame puzzle from the newspaper. “Since Garry knows how the game ends,” his father remarked, “we ought to teach him how it begins.” Sixteen years and many thousands of training hours later, Kasparov became the youngest-ever world chess champion at twenty-two. His greatness was also enduring. Kasparov held the world championship from 1985 to 2000, and even after losing the title he retained the highest ranking in the world. Perhaps more significantly, as he neared middle age at the dawn of the twenty-first century, Kasparov was one of the few human beings left who could effectively compete with the top chess computers.
Now, in Game 2 of the 2003 match, he had the unenviable task of proving he could beat Junior again—and this time as Black, which always has the inherent disadvantage of moving second. But Kasparov did not come to the table to fight for a draw. From the start, he surprised expert onlookers with another aggressive game, an unorthodox version of one of his specialties, the Sicilian Defense. Just as in the first game, he boldly took on the computer in tactical play. And he seemed in command for much of the game. Now there was no doubt about it: tactical play—trying to achieve short-term gain—was clearly an emerging theme in this match. In recent years, it had become axiomatic: Humans cannot win tactical battles against computers. A squishy and vulnerable human brain cannot compete move by move with a computer that analyzes millions of moves per second. In New York, Kasparov was challenging this widely held belief, and in Game 2 he again took on Deep Junior both strategically and tactically. Specifically in this game, explained commentator John Fernandez, “Kasparov’s wrinkle was to employ a rare development of his dark-squared Bishop on the square a7, where it controls many squares in the heart of Deep Junior’s position from the protective bunker of the corner of the board.”
DEEP JUNIOR VS. GARRY KASPAROV
JANUARY 28, 2003
NEW YORK
GAME 2
Commentators noted that Kasparov had successfully played this exact Bishop move in a recent exhibition match. It worked this time too, for a while. But then on move 25 he was outfoxed. Deep Junior offered Kasparov the chance to check with his Queen. Kasparov had been planning another move, but the check was too tempting to pass up. At the least, he couldn’t see how taking the check could do any harm.
“It was a human move,” he said later. “You see a check like that and you simply play it. But I immediately realized that I had let [Junior] off the hook.”
The game ended in a draw—all in all, not a bad deal for Kasparov, who as Black had avoided a loss. The ambassador for human intelligence was still doing humans proud, still winning the match against an inexhaustible and savvy machine. At the same time, Deep Junior was surprising the experts with its humanity. “Its play has been almost completely indistinguishable from that of a human master…it hasn’t made any obvious computer-like moves,” commented popular American chess columnist Mig Greengard.
“Deep Junior,” he declared, “has so far passed the chess Turing Test.”
IN THE WORLD of computer professionals, Greengard’s remark was equivalent to declaring that someone had just landed on Mars. Passing the Turing test was an extraordinary feat of engineering. It meant that machines were now crossing the threshold into the realm of human intelligence—or at least the appearance of intelligence.
Trained as a mathematical logician in the 1930s, British computer pioneer Alan Turing was recruited by British Intelligence in World War II. At the Bletchley Park military intelligence campus north of London, he led a team that cracked the vexing Enigma encryption code used by German U-boats. (Field Marshal “Monty” Montgomery thanked Turing’s squad for letting him “know what the Jerries are having for breakfast.”) They also helped the Allies create uncrackable encryptions of their own so that commanders and leaders, including Roosevelt and Churchill, could talk to one another in confidence.
After the war, Turing introduced concepts necessary for the invention of digital computing. Among other things, explains Andrew Hodges in his biography Alan Turing: The Enigma, Turing contributed “the crucial twentieth-century insight that symbols representing instructions are no different in kind from symbols representing numbers.” That meant that computers could potentially do much more than calculate—they could also take on a wide variety of other tasks involving the manipulation of data, patterns, and even decision making. Building on that and other Turing insights, the first generation of primitive computers (including the famous ENIAC and UNIVAC machines) was built in the late 1940s and early 1950s. The early history of computing is nearly impossible to imagine without him.
His legendary Turing test came in response to the giant question that he posed in a 1950 article for the journal Mind: “Can machines think?” After considering the technological, cognitive, philosophical, and theological implications of that question, Turing argued that yes, a true thinking machine could eventually be built—and
he expressed confidence that one day it would happen.
But how to tell? How could anyone properly determine if a machine was engaged in humanlike thought? Turing concluded that there would never be a satisfactory objective standard. Instead, he proposed, it was ultimately a matter of human perception. If, in response to human questions, a computer could consistently provide answers indistinguishable from human answers—answers that would fool a human on the other side of a curtain—then that machine would ipso facto be demonstrating thought. The Turing test was born.
In chess, the equivalent question was whether a computer player might someday fool people into thinking it was a human player. Any computer could be programmed to respond to certain moves with other moves, or to value certain pieces above other pieces. But could humanlike play involving intuition, creativity, risk taking, and opponent psychology ever be convincingly mimicked by a machine?
Alan Turing loved chess and played all the time, though he wasn’t nearly as adept on the chessboard as he was on the chalkboard. At Bletchley Park he was fortunate to be surrounded by accomplished players, and the chess pieces were always handy. The onetime British champion Conel Hugh O’Donel Alexander was Turing’s deputy. Future British champion Harry Golombek was also on the staff; Golombek’s chess superiority over Turing was such that he could overwhelm Turing in a chess game, force Turing’s resignation, and then turn the board around to play Turing’s pieces against his own original pieces—and win.
Turing and his colleagues played not just for the diversion, but also because chess was such a useful tool. It helped them work through ideas and problems, explore logic and mathematics, and experiment with mechanical instructions. Contrary to what one might have supposed, the busy nexus of chess and mathematics had not diminished as mathematics itself became more nuanced in the modern age. One might expect that highly advanced concepts like cycloids, primary decomposition, and transcendental numbers would render the medieval chessboard an obsolete tool. On the contrary, the game seemed only to become more and more entrenched in classrooms, journals, blackboards, and, eventually, on Web sites. In the late nineteenth century, number theory pioneer Edmund Landau wrote two books on mathematical problems inherent in chess. (More than a century later, the connection would still be vibrant: in 2004 Harvard University offered the course “Chess and Mathematics,” whose aim was to “illustrate the interface between chess problems and puzzles on the one hand, and mathematical theory and computation on the other.” Chess, it seemed, would never lose relevance, since its vitality was based not on any particular set of ideas, but on its symbolic power.)