AI, Go, and Philosophical Argument

After more than four hours of tight play and a rapid-fire endgame, Google’s artificially intelligent Go-playing computer system has won a second contest against grandmaster Lee Sedol, taking a two-games-to-none lead in their historic best-of-five match in downtown Seoul. The surprisingly skillful Google machine, known as AlphaGo, now needs only one more win to claim victory in the match.

This article in Wired about the artificial intelligence Google is using to play Go is fascinating (via kottke). AlphaGo is coming up with “surprising” moves, and no one knows exactly what it will do next:

With its 19th move, AlphaGo made an even more surprising and forceful play, dropping a black piece into some empty space on the right-hand side of the board. Lee Sedol seemed just as surprised as anyone else. He promptly left the match table, taking an (allowed) break as his game clock continued to run. “It’s a creative move,” Redmond said of AlphaGo’s sudden change in tack. “It’s something that I don’t think I’ve seen in a top player’s game.”

Go board stones

The AI is programmed with thousands of moves, but then engages in machine learning based on that:

Hassabis and his team originally built AlphaGo using what are called deep neural networks, vast networks of hardware and software that mimic the web of neurons in the human brain. Essentially, they taught AlphaGo to play the game by feeding thousands upon thousands of human Go moves into these neural networks.

But then, using a technique called reinforcement learning, they matched AlphaGo against itself. By playing match after match on its own, the system could learn to play at an even higher level—perhaps at a level that eclipses the skills of any human. That’s why it produces such unexpected moves….

Once the system is trained using those machine learning techniques, it plays entirely on its own…

During the match, the commentators even invited DeepMind research scientist Thore Graepel onto their stage to explain the system’s rather autonomous nature. “Although we have programmed this machine to play, we have no idea what moves it will come up with,” Graepel said. “Its moves are an emergent phenomenon from the training. We just create the data sets and the training algorithms. But the moves it then comes up with are out of our hands—and much better than we, as Go players, could come up with.”

Where is the philosophical version of this AI, and when can we have it argue with itself? Will philosophical dialogues—this time the machine version—once again be the source of a new era of philosophy?

(Some previous discussion here.)

UPDATE: AlphaGo won for a third time.

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