The Game Is Not over Yet—Go in the Post-AlphaGo Era
Level 5 - mechanism / opinion, no new human data
Level 5 by design analogy; conceptual perspective and theoretical analysis without new empirical data.
OpenAlex W3101697314 · doi:10.3390/philosophies5040037
What was done
The authors provide a conceptual and theoretical examination of the board game Go in the era following superhuman AI systems like AlphaGo. They evaluate theoretical questions concerning proximity to perfect play, human capacity to learn from AI, compressibility of game knowledge, computational complexity, and the energy requirements of optimal play.
What was found
The abstract reports no quantitative measurements or empirical findings. It outlines a conceptual inquiry into how Go's combinatorial complexity and game dynamics model broader issues in human-AI interaction, explainability, and AI utility.
Why it matters
The paper frames the cultural and computational aftermath of AI mastering complex games as a case study for understanding future human collaboration with and reliance on superhuman AI systems.
Limits
The work is a non-empirical perspective paper and narrative analysis. It does not provide experimental benchmarks, algorithmic models, or quantitative datasets to evaluate the theoretical questions posed.
Cited by
- supports The AI program AlphaGo defeated the world champion in the board game Go.