Dropping the golden apple

Find the best move! Once upon a time, I sincerely believed that was my overriding goal during a game of chess. Naive, but nowadays I know better. The truth is that dodging banana skins is more fruitful, so to speak, than the pursuit of golden apples.

In part, this is a simple story about experience and humility. After making enough bad moves, one comes to realise that there are always more lurking around the corner. But really, it’s not about me. The past decade or so has seen a fundamental shift in the way that games of chess are perceived, for which the near-omniscient chess computer has been the driving force.

The moves of the world’s best players used to be held in awe. They made mistakes, of course, but identifying them could take a considerable amount of legwork. These days, a chess engine will take just seconds to point out the errors in a game. For every position, the engine shows its preferred move and the resulting evaluation in hundredths of a pawn (e.g. +1.47 signifies a healthy advantage to White). That acts as a benchmark for all the other moves.

The perceptual shift is significant. In chess analysis, thought used to precede truth, and a move that appeared to exhibit a truth would be awarded a ‘!’ signifying ‘good move’. But with the computer by our side, truth precedes thinking, and our moves merely manifest varying degrees of falsity.

But surely one still just has to find the best move? Well, sort of. If those statistics have taught me anything, it’s that ‘satisficing’ wins chess games. Consistently finding suboptimal but decent moves seems more effective than being a perfectionist who blunders intermittently.

Both the big internet chess servers, chess.com and lichess.org, will produce an ‘accuracy’ measure (out of 100) to show how well a game was played by each player overall. It tends to make me feel more chastened than uplifted, but just once in a while, it offers a pleasant surprise.