How AI-Based Training Affected the Performance of Professional Go Players

In this study, we analyzed how the performance of professional Go players has changed since the advent of AlphaGo, the first artificial intelligence (AI) application to defeat a human world Go champion. We interviewed and surveyed professional Go players and found that AI has been actively introduced into the Go training process since the advent of AlphaGo. The significant impact of AI-based training was confirmed in a subsequent analysis of 6,292 games in Korean Go tournaments and Elo rating data of 1,362 Go players worldwide. Overall, the tendency of players to make moves similar to those recommended by AI has sharply increased since 2017. The degree to which players' expected win rates fluctuate during a game has also decreased significantly since 2017. We also found that AI-based training has provided more benefits to senior players and allowed them to achieve Elo ratings higher than those of junior players.

Automated summary

This study analyzes the performance changes of professional Go players since the introduction of AlphaGo, the first AI application to defeat a human world Go champion. It is found that AI has been actively incorporated into Go training since AlphaGo's appearance, with significant impact observed in game analysis and player rating data. Player tendency to follow AI-recommended moves and the fluctuation of expected win rates have both increased since 2017. Additionally, AI-based training benefits senior players more, leading to higher Elo ratings compared to junior players.