Summary of the Core Content
This article takes AlphaGo’s victory over Lee Sedol as a starting point to discuss how AI is reshaping the world of Go. It explains how AI has shattered humanity’s millennia-old understanding of the game, changing the language used by players to discuss Go (from vague descriptions to precise data), the style of play (from individualistic approaches to the pursuit of perfection akin to AI), and the authority within the Go community (from top human players to AI). At the same time, it highlights positive developments: professional Go players are transitioning into roles of “interpreters” for AI and humans; female players have gained more opportunities due to AI’s impact on traditional power structures. The article also raises questions about technological fairness, urging us to consider the distribution of power behind these advancements and who might be excluded.
Detailed Analysis
1. AlphaGo’s “Divine Move”:千年-Old Go Conventions Overthrown by a Machine
In the second game against Lee Sedol in 2016, AlphaGo made move 37, which humans considered a poor choice—opening up an unprofitable corner for the opponent. Lee was puzzled and even chuckled at the time, with commentators questioning the move’s validity. However, AlphaGo won decisively. Post-game analysis showed that the probability of humans making such a move was less than one in ten thousand; AI chose it because it only slightly reduced the chances of losing compared to the optimal strategy. This “divine move” demonstrated that machines can create new Go tactics, a privilege previously reserved for humans.
2. The Language of Go Discussions Has Changed: From Vague Descriptions to Precise Numbers
Before the advent of AI, players used vague terms like “Black is slightly ahead” or “This move feels risky” to describe their moves. With AI, discussions have shifted to more precise numerical data, such as “Black’s chances of winning at 49.5%.” This change reflects a shift in thinking: while humans focus on achieving local goals (such as capturing territory or attacking), AI aims solely for victory, using win rates as the sole criterion.
3. Have Players Lost Their Unique Styles?
The charm of professional Go players once lay in their distinctive playing styles—Nie Weiping’s strategic vision, Gu Li’s aggressiveness, Lee Sedol’s calmness. However, with AI, players now strive for perfection, adopting its standard approaches. For example, the current world champion, Shin Jinhyuk, is praised for his AI-like precision but lacks the personal charisma of traditional players. The optimal moves suggested by AI make creativity redundant, as either the player has already thought of those moves or they are deemed incorrect.
4. Authority Has Shifted from Humans to AI
In the past, top human Go players held the authority; their decisions were unquestioned. But with AI, this power structure has been disrupted. Players no longer discuss moves with each other during retrospectives but instead rely on AI’s recommendations. Even top players like Gu Li are cautious when discussing moves publicly and use smartphones to consult AI in real-time during broadcasts for fear of making mistakes. AI has become the new “referee,” diminishing the influence of human experts.
5. Not All Changes Are Negative: Players Transforming into “AI Interpreters,” and Female Players Finding New Opportunities
While AI brings challenges, it also presents opportunities:
- Professional Players as Interpreters: Professional players now act as interpreters, explaining complex strategies in language understandable to humans. Some have realized that pursuing perfect win rates (often suggested by AI) is not always beneficial; moves that differ by 5% from the optimal strategy may actually lead to better outcomes, as human opponents can also make mistakes.
- Breakthrough for Female Players: The traditionally male-dominated Go community has seen more female players advancing to high ranks in recent years. For instance, Choi Jeong-ju became the first female player to qualify for the Samsung Cup in 2022, thanks to AI’s role in opening up new opportunities for women.
Conclusion: Technology Is Not Neutral
The article concludes with an analogy from the Low Bridge on Long Island, New York—designed too low for buses to pass, it only serves wealthy white motorists. This illustrates that technology is never neutral; its design reflects who benefits and who is excluded. Similarly, the standards set by tech companies for Go AI may favor those who are good at logic and diligence. As we embrace AI, we must ask whether these standards truly benefit everyone.
In Go, AI makes the moves, but in life, we must decide for ourselves where to “place our pieces” (i.e., how to use technology).