On 27 June, 1835, two masters of the ancient Chinese game of Go faced off in a match which was the culmination of a years-long rivalry.
The young prodigy Akaboshi Intetsu dominated the game early on using a secret move developed by his teachers. But a day into the contest a number of ghosts appeared to his opponent, Hon'inbō Jōwa, and showed him three critical moves with which he was able to win back control of the game. At the point when it became clear that Akaboshi would not be able to win the game, the young challenger violently coughed up blood onto the board. He was found dead a few days later. The match between Akaboshi and Jōwa has passed into Go lore as the ‘blood-vomiting game’, and subsequent historians have attributed Akaboshi’s decline to an undiagnosed pulmonary disease. They have been less forthcoming, however, on the matter of ghosts, which may still haunt the game to this day.
On 29 December, 2016, a new player appeared on Tygem, a popular online Go server on which many senior Go professionals trained and tested out new moves. The player was called Master, and immediately they began a blazing winning streak: 60 victories in just seven days, and barely resting between games. Many of the victories were over world champion players. Master’s moves often seemed wild, even impetuous, but they always resulted in a win. After the fifty-ninth game Master was revealed to be – as had been suspected – not a human player, but an Artificial Intelligence (AI). Master was the latest iteration of DeepMind and Google’s AlphaGo programme, which had gained worldwide attention when it defeated Go master Lee Sedol six months earlier.
That game had been close, but the New Year games were already markedly different. When Go players tried to describe the AI’s style of play, they struggled to reconcile it with anything known. One leading Go player said, ‘they’re how I imagine games from far in the future’. Another reported feeling that an ‘alien intelligence’ had landed among them. The machine’s own creator, Dennis Hassabis, said its moves seemed to emanate ‘from another dimension’.
The last great revolution in human-machine competition occurred in 1997, when IBM’s DeepBlue defeated Gary Kasparov at chess, up to that point a game with Go-like status as a bastion of human imagination and mental superiority. But compared to AlphaGo, DeepBlue might as well have belonged to the steam age; immensely powerful, IBM’s machine lacked anything we would call intelligence. It brute-forced Kasparov off the board, calculating games many moves ahead – but merely that: calculating. AlphaGo and its kind perform something more akin to imagination and intuition, and moreover they do so in mathematical realms the human mind cannot comprehend. While we can follow DeepBlue’s line of thought, the thinking behind AlphaGo’s decisions remain unknowable to us – and hence alien and otherworldly.
To call AlphaGo and systems like it an Artificial Intelligence is in some ways an exaggeration. It is a very narrow form of intelligence directed at a particular task, based on one particular computational configuration – neural networks – and a technique called reinforcement learning. These are pieces of software modelled loosely on parts of the human brain, which are trained on a reward system which encourages them to develop their own strategies. Despite this narrow focus, the benefits are generalisable; as well as learning other games, the techniques developed for AlphaGo have been deployed by Google in everything from medical diagnoses to YouTube recommendations. Machine learning is being used by others to screen applicants for jobs, pilot self-driving cars and target military drones. Neural networks are live and connected to the stock market, to distribution systems, to transport infrastructure – to the very social, material, and economic bases of our daily existence. It’s not just AlphaGo’s ‘god-like’ moves we have to contend with, but inscrutable decisions made about jobs and finances, healthcare and road safety – and the sense of mystery, surprise, strangeness and even horror that AlphaGo evokes will become a feature of more and more areas of our lives.
The increasing complexity of the world around us should be cause for political and social concern, as intelligent but unknowable software works its way through society. But it’s also an opportunity to rethink our relationship with the wider world, and to reconsider our place in it. It seems significant that we are investing so much time and energy in building these toy versions of our own minds, just as our ability to control our own destiny and live on the planet sustainably appears to be failing. That failure is in part one of hubris: the belief that we can, as the planet’s dominant species, continue to act selfishly, wastefully and without regard to the future. But with AI comes the sense that we might not be the dominant actor for much longer – and an attendant opportunity to really consider what it means to share the world with other, barely knowable intelligences.