Top-ranked Go player Shin Jin-seo achieved victory against the advanced AI program KataGo in a three-game match, winning two consecutive games after an initial loss. This comeback is significant, as Go has been viewed as a domain where AI has surpassed human players since Lee Sedol's match against AlphaGo in 2016. A decade later, humans are facing AI with new strategies and conditions.
However, this victory should not be interpreted as humans surpassing AI. In direct matches, AI's strength is already far superior to that of human players. In this match, Shin started with a two-stone handicap, while KataGo made its moves within 20 seconds each time, compared to Shin's five hours plus one 30-second overtime. Shin's achievement lies not in being stronger than AI, but in accurately assessing the conditions and executing a winning strategy.
In the first game, Shin maintained an early advantage but faced a setback in the middle game, ultimately losing by resignation after 245 moves. He quickly adjusted his strategy for the second game, sacrificing three stones in the center to regain control and winning by 4.5 points after 290 moves.
In the final game, Shin focused on securing territory while minimizing risky confrontations. After building a strong position on the right side around the 80th move, he maintained his lead and won by 11.5 points after 221 moves, turning the series around.
The three games did not follow a single tactic against AI. Shin acknowledged the issues from the first game and varied his strategies for each match. Instead of directly competing with AI's calculation power, he made choices suited to the situation. The victory resulted from prudent decision-making that minimized risks and maintained advantages, rather than from flashy moves.
Notably, Shin did not reject AI; he has regularly used AI analysis to refine his judgment. He embraced technology, understanding and utilizing it to develop his own strategies.
This has significant implications in the age of generative AI. While AI can write, create art, and analyze vast amounts of data, it cannot replace the human role. The responsibility for what questions to ask and which answers to choose remains with humans. The gap will widen between those who accept AI results blindly and those who verify errors and context.
Governments and businesses should not focus solely on computational power and investment in AI. Education should foster the ability to redefine problems and validate results rather than just finding quick answers. Companies and public institutions must not attribute AI errors and biases to mere 'machine mistakes.' We must prevent a structure where responsibility is relinquished to machines.
Shin's comeback does not imply that humans are superior to AI. In the AI era, competitiveness does not stem from simply defeating machines. It arises from understanding the capabilities and limitations of technology and applying it to human objectives. While AI can calculate, it cannot determine direction. Ultimately, competitiveness in the technological age comes from human strategy, judgment, and responsibility. This is the most significant takeaway from Shin's remarkable victory.
However, this victory should not be interpreted as humans surpassing AI. In direct matches, AI's strength is already far superior to that of human players. In this match, Shin started with a two-stone handicap, while KataGo made its moves within 20 seconds each time, compared to Shin's five hours plus one 30-second overtime. Shin's achievement lies not in being stronger than AI, but in accurately assessing the conditions and executing a winning strategy.
In the first game, Shin maintained an early advantage but faced a setback in the middle game, ultimately losing by resignation after 245 moves. He quickly adjusted his strategy for the second game, sacrificing three stones in the center to regain control and winning by 4.5 points after 290 moves.
In the final game, Shin focused on securing territory while minimizing risky confrontations. After building a strong position on the right side around the 80th move, he maintained his lead and won by 11.5 points after 221 moves, turning the series around.
The three games did not follow a single tactic against AI. Shin acknowledged the issues from the first game and varied his strategies for each match. Instead of directly competing with AI's calculation power, he made choices suited to the situation. The victory resulted from prudent decision-making that minimized risks and maintained advantages, rather than from flashy moves.
Notably, Shin did not reject AI; he has regularly used AI analysis to refine his judgment. He embraced technology, understanding and utilizing it to develop his own strategies.
This has significant implications in the age of generative AI. While AI can write, create art, and analyze vast amounts of data, it cannot replace the human role. The responsibility for what questions to ask and which answers to choose remains with humans. The gap will widen between those who accept AI results blindly and those who verify errors and context.
Governments and businesses should not focus solely on computational power and investment in AI. Education should foster the ability to redefine problems and validate results rather than just finding quick answers. Companies and public institutions must not attribute AI errors and biases to mere 'machine mistakes.' We must prevent a structure where responsibility is relinquished to machines.
Shin's comeback does not imply that humans are superior to AI. In the AI era, competitiveness does not stem from simply defeating machines. It arises from understanding the capabilities and limitations of technology and applying it to human objectives. While AI can calculate, it cannot determine direction. Ultimately, competitiveness in the technological age comes from human strategy, judgment, and responsibility. This is the most significant takeaway from Shin's remarkable victory.
* This article has been translated by AI.
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