down on the board. His initial reaction matched everyone else’s: shock. And then he began to realise: ‘It’s not a human move. I’ve never seen a human play this move,’ he said. ‘So beautiful. Beautiful. Beautiful. Beautiful.’
Beautiful and deadly it turned out to be. Not a mistake but an extraordinarily insightful move. Some fifty moves later, as the black and white stones fought over territory from the lower left-hand corner of the board, they found themselves creeping towards the black stone of move 37. It was joining up with this stone that gave AlphaGo the edge, allowing it to clock up its second win. AlphaGo 2 Humans 0.
Sedol’s mood in the press conference that followed was notably different. ‘Yesterday I was surprised. But today I am speechless … I am in shock. I can admit that … the third game is not going to be easy for me.’ The match was being played over five games. This was the game that Sedol needed to win to be able to stop AlphaGo claiming the match.
The human fight-back
Sedol had a day off to recover. The third game would be played on Saturday, 12 March. He needed the rest, unlike the machine. The first game had been over three hours of intense concentration. The second lasted over four hours. You could see the emotional toll that losing two games in a row was having on him.
Rather than resting, though, Sedol stayed up till 6 a.m. the next morning analysing the games he’d lost so far with a group of fellow professional Go players. Did AlphaGo have a weakness they could exploit? The machine wasn’t the only one who could learn and evolve. Sedol felt he might learn something from his losses.
Sedol played a very strong opening to game 3, forcing AlphaGo to manage a weak group of stones within his sphere of influence on the board. Commentators began to get excited. Some said Sedol had found AlphaGo’s weakness. But then, as one commentator posted: ‘Things began to get scary. As I watched the game unfold and the realisation of what was happening dawned on me, I felt physically unwell.’
Sedol pushed AlphaGo to its limits but in so doing he revealed the hidden powers that the program seemed to possess. As the game proceeded, it started to make what commentators called lazy moves. It had analysed its position and was so confident in its win that it chose safe moves. It didn’t care if it won by half a point. All that mattered was that it won. To play such lazy moves was almost an affront to Sedol, but AlphaGo was not programmed with any vindictive qualities. Its sole goal was to win the game. Sedol pushed this way and that, determined not to give in too quickly. Perhaps one of these lazy moves was a mistake that he could exploit.
By move 176 Sedol eventually caved in and resigned. AlphaGo 3 Humans 0. AlphaGo had won the match. Backstage, the DeepMind team was going through a strange range of emotions. They’d won the match, but seeing the devastating effect it was having on Sedol made it hard for them to rejoice. The million-dollar prize was theirs. They’d already decided to donate the prize, if they won, to a range of charities dedicated to promoting Go and science subjects as well as to Unicef. Yet their human code was causing them to empathise with Sedol’s pain.
AlphaGo did not demonstrate any emotional response to its win. No little surge of electrical current. No code spat out with a resounding ‘YES!’ It is this lack of response that gives humanity hope and is also scary at the same time. Hope because it is this emotional response that is the drive to be creative and venture into the unknown: it was humans, after all, who’d programmed AlphaGo with the goal of winning. Scary because the machine won’t care if the goal turns out to be not quite what its programmers had intended.
Sedol was devastated. He came out in the press conference and apologised:
I don’t know how to start or what to say today, but I think I would have to express my apologies first. I should have shown a better result, a better outcome, and better content in terms of the game played, and I do apologize for not being able to satisfy a lot of people’s expectations. I kind of felt powerless.
But he urged people to keep watching the final two games. His goal now was to try to at least get one back for humanity.
Having lost the match, Sedol started game 4 playing far more freely. It was as if the heavy burden of expectation had been lifted, allowing him to enjoy his game. In sharp contrast to the careful, almost cautious play of game 3, he launched into a much more extreme strategy called ‘amashi’. One commentator compared it to a city investor who, rather than squirrelling away small gains that accumulate over time, bet the whole bank.
Sedol and his team had stayed up all of Saturday night trying to reverse-engineer from AlphaGo’s games how it played. It seemed to work on a principle of playing moves that incrementally increase its probability of winning rather than betting on the potential outcome of a complicated single move. Sedol had witnessed this when AlphaGo preferred lazy moves to win game 3. The strategy they’d come up with was to disrupt this sensible play by playing the risky single moves. An all-or-nothing strategy might make it harder for AlphaGo to score so easily.
AlphaGo seemed unfazed by this line of attack. Seventy moves into the game, commentators were already beginning to see that AlphaGo had once again gained the upper hand. This was confirmed by a set of conservative moves that were AlphaGo’s signal that it had the lead. Sedol had to come up with something special if he was going to regain the momentum.
If move 37 of game 2 was AlphaGo’s moment of creative genius, move 78 of game 4 was Sedol’s retort. He’d sat there for thirty minutes staring at the board, staring at defeat, when he suddenly placed a white stone in an unusual position, between two of AlphaGo’s black stones. Michael Redmond, who was commentating on the YouTube channel, spoke for everyone: ‘It took me by surprise. I’m sure that it would take most opponents by surprise. I think it took AlphaGo by surprise.’
It certainly seemed to. AlphaGo appeared to completely ignore the play, responding with a strange move. Within several more moves AlphaGo could see that it was losing. The DeepMind team stared at their screens behind the scenes and watched their creation imploding. It was as if move 78 short-circuited the program. It seemed to cause AlphaGo to go into meltdown as it made a whole sequence of destructive moves. This apparently is another characteristic of the way Go algorithms are programmed. Once they see that they are losing they go rather crazy.
Silver, the chief programmer, winced as he saw the next move AlphaGo was suggesting: ‘I think they’re going to laugh.’ Sure enough, the Korean commentators collapsed into fits of giggles at the moves AlphaGo was now making. Its moves were failing the Turing Test. No human with a shred of strategic sense would make them. The game dragged on for a total of 180 moves, at which point AlphaGo put up a message on the screen that it had resigned. The press room erupted with spontaneous applause.
The human race had got one back. AlphaGo 3 Humans 1. The smile on Lee Sedol’s face at the press conference that evening said it all. ‘This win is so valuable that I wouldn’t exchange it for anything in the world.’ The press cheered wildly. ‘It’s because of the cheers and the encouragement that you all have shown me.’
Gu Li, who was commentating on the game in China, declared Sedol’s move 78 as the ‘hand of god’. It was a move that broke the conventional way to play the game and that was ultimately the key to its shocking impact. Yet this is characteristic of true human creativity. It is a good example of Boden’s transformational creativity, whereby breaking out of the system you can find new insights.
At the press conference, Hassabis and Silver could not explain why AlphaGo had lost. They would need to go back and analyse why it had made such a lousy move in response to Sedol’s move 78. It turned out that AlphaGo’s experience in playing humans had led it to totally dismiss such a move as something not worth thinking about. It had assessed that this was a move that had only a one in 10,000 chance of being played. It seems as if it just had not bothered to learn a response to such a move because it had prioritised other moves as more likely and therefore more worthy of response.
Perhaps Sedol just needed to get to know his opponent. Perhaps over a longer match he would have turned the tables on AlphaGo. Could he maintain the momentum into the fifth and final game? Losing 3–2 would be very different