‘Players now train to replicate AI’s moves as closely as they can rather than inventing their own, even when the machine’s thinking remains mysterious to them.’
This is a fascinating look at how AI is reshaping how the best Go players in the world improve their skills using AI. After AlphaGo defeated Lee Sedol ten years ago (with moves that no human would make at the time) it’s now almost impossible to compete professionally in the game without using AI.
There are some positives to this (like democratising access to training, particularly for female players) but also some arguably less positive consequences. It’s completely changed the way in which the game is played: ‘The crux of the game has shifted to the middle moves, where raw calculation matters more than creativity.’
It has led to a homogenisation of playing styles, with players trying to replicate moves that AI would make without necessarily understanding the reasoning behind the moves. It’s taken something of the art out of key parts of the game, and the areas that fans still revel in are those where human judgement needs to take over, mistakes are made, and player personality shines.
As Marshall McLuhan once said: ‘We shape our tools and thereafter our tools shape us.’ It makes me wonder about other contexts in which we might end up following AI directions without quite knowing why. When the human ceases to be the driver in these more complex scenarios we could well find that we’re losing the art of good decision-making.
I write a weekly Substack of AI and digital trends, and transformation insights. To join our community of over thirteen thousand subscribers you can sign up to that here.
To get posts like this delivered straight to your inbox, drop your email into the box below.
Photo by Elena Popova on Unsplash
Leave a Reply