Earlier this year, an amateur Go player was one of the game’s top ranked AIs. They did this using a strategy developed with the help of a program researcher designed to examine systems like KataGo for weaknesses. As it turns out, the win is just part of a wider Go renaissance that has seen human players become more creative ever since
In a recent study published in the journal , researchers from the City University of Hong Kong and Yale found that human Go players have become less predictable in recent years. As the the researchers came to that conclusion by analyzing a dataset of more than 5.8 million Go moves made during professional play between 1950 and 2021. Using a “superhuman” Go AI, a program that can play the game and increase the quality from every single move, they created a metric called a “decision quality index,” or DQI for short.
After assigning a DQI score to each move in their data set, the team found that prior to 2016, the quality of professional play improved relatively little from year to year. At most, the team saw a positive median annual DQI change of 0.2. In some years, the overall quality of the game actually dropped. However, since the emergence of superhuman AIs in 2018, median DQI values have changed at a rate of more than 0.7. During the same period, professional players have adopted more new strategies. In 2018, 88 percent of games, up from 63 percent in 2015, saw players mount a combination of plays not seen before.
“Our findings suggest that the development of superhuman AI programs may have prompted human players to break traditional strategies and push them to explore new moves, which in turn may have improved their decision-making,” the team writes.
That’s an interesting change, but not exactly unintuitive when you think about it. As Professor Stuart Russell at the University of California, Berkeley told me New scientist“It’s not surprising that players who train against machines tend to make more moves that machines approve.”
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