Monday, January 25, 2010

What Kind of Smart?

Gary Kasparov on the differences between AI and human intelligence as applied to chess.

Before 1994 and after 2004 these duels held little interest. The computers quickly went from too weak to too strong. But for a span of ten years these contests were fascinating clashes between the computational power of the machines (and, lest we forget, the human wisdom of their programmers) and the intuition and knowledge of the grandmaster.

In what Rasskin-Gutman explains as Moravec's Paradox, in chess, as in so many things, what computers are good at is where humans are weak, and vice versa. This gave me an idea for an experiment. What if instead of human versus machine we played as partners? My brainchild saw the light of day in a match in 1998 in León, Spain, and we called it "Advanced Chess." Each player had a PC at hand running the chess software of his choice during the game. The idea was to create the highest level of chess ever played, a synthesis of the best of man and machine.

Although I had prepared for the unusual format, my match against the Bulgarian Veselin Topalov, until recently the world's number one ranked player, was full of strange sensations. Having a computer program available during play was as disturbing as it was exciting. And being able to access a database of a few million games meant that we didn't have to strain our memories nearly as much in the opening, whose possibilities have been thoroughly catalogued over the years. But since we both had equal access to the same database, the advantage still came down to creating a new idea at some point.

Having a computer partner also meant never having to worry about making a tactical blunder. The computer could project the consequences of each move we considered, pointing out possible outcomes and countermoves we might otherwise have missed. With that taken care of for us, we could concentrate on strategic planning instead of spending so much time on calculations. Human creativity was even more paramount under these conditions. Despite access to the "best of both worlds," my games with Topalov were far from perfect. We were playing on the clock and had little time to consult with our silicon assistants. Still, the results were notable. A month earlier I had defeated the Bulgarian in a match of "regular" rapid chess 4–0. Our advanced chess match ended in a 3–3 draw. My advantage in calculating tactics had been nullified by the machine.


At the level of complexity represented by chess, no single capability has achieved dominance. A combination of capabilities is necessary, all of which are the result of trade-offs.

The "freestyle" result, though startling, fits with my belief that talent is a misused term and a misunderstood concept. The moment I became the youngest world chess champion in history at the age of twenty-two in 1985, I began receiving endless questions about the secret of my success and the nature of my talent. Instead of asking about Sicilian Defenses, journalists wanted to know about my diet, my personal life, how many moves ahead I saw, and how many games I held in my memory.

I soon realized that my answers were disappointing. I didn't eat anything special. I worked hard because my mother had taught me to. My memory was good, but hardly photographic. As for how many moves ahead a grandmaster sees, Russkin-Gutman makes much of the answer attributed to the great Cuban world champion José Raúl Capablanca, among others: "Just one, the best one." This answer is as good or bad as any other, a pithy way of disposing with an attempt by an outsider to ask something insightful and failing to do so. It's the equivalent of asking Lance Armstrong how many times he shifts gears during the Tour de France.

The only real answer, "It depends on the position and how much time I have," is unsatisfying. In what may have been my best tournament game at the 1999 Hoogovens tournament in the Netherlands, I visualized the winning position a full fifteen moves ahead—an unusual feat. I sacrificed a great deal of material for an attack, burning my bridges; if my calculations were faulty I would be dead lost. Although my intuition was correct and my opponent, Topalov again, failed to find the best defense under pressure, subsequent analysis showed that despite my Herculean effort I had missed a shorter route to victory. Capablanca's sarcasm aside, correctly evaluating a small handful of moves is far more important in human chess, and human decision-making in general, than the systematically deeper and deeper search for better moves—the number of moves "seen ahead"—that computers rely on.

There is little doubt that different people are blessed with different amounts of cognitive gifts such as long-term memory and the visuospatial skills chess players are said to employ. One of the reasons chess is an "unparalleled laboratory" and a "unique nexus" is that it demands high performance from so many of the brain's functions. Where so many of these investigations fail on a practical level is by not recognizing the importance of the process of learning and playing chess. The ability to work hard for days on end without losing focus is a talent. The ability to keep absorbing new information after many hours of study is a talent. Programming yourself by analyzing your decision-making outcomes and processes can improve results much the way that a smarter chess algorithm will play better than another running on the same computer. We might not be able to change our hardware, but we can definitely upgrade our software.

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