From Aeon:
When IBM’s Deep Blue chess computer defeated the world champion Garry Kasparov in 1997, humanity let out a collective sigh, recognising the loss of an essential human territory to the onslaught of thinking machines. Chess, that inscrutably challenging game, with more possible game states than there are atoms in the Universe, was no longer a canvas for individual human achievement. Newsweek called it ‘The Brain’s Last Stand’.
Why was the loss so upsetting to so many? Not because chess is complicated, per se – calculating differential equations is complicated, and we are happy to cede the work to computers – but because chess is creative. We talk about the personality, the aesthetics of chess greats such as Kasparov and Bobby Fischer, seeing a ‘style of play’ in the manipulation of pieces on a grid. Chess was a foil, a plane of endeavour, for storytellers as diverse as Vladimir Nabokov and Satyajit Ray, and we celebrate its grandmasters as remarkable synthesisers of logic and creativity. It was particularly galling, then, for Kasparov to lose to a machine based not on its creativity but its efficiency at analysing billions of possible moves. Deep Blue wasn’t really intelligent at all, but it was very good at avoiding mistakes in chess. One might argue that its victory not only knocked humanity down a peg but demonstrated that chess itself is not, or does not have to be, the aesthetic space we imagined it.
And yet Kasparov, after having lost to what he later called ‘a $10 million alarm clock’, continued to play against machines, and to reflect on the consequences of computation for the game of kings. And not just against them: for the past two decades, Kasparov has been exploring an idea he calls ‘Advanced Chess’, where humans collaborate with computer chess programs against other hybrid teams, sometimes called ‘Centaurs’. The humans maintain strategic control of the game while automating the memorisation and basic calculation on which great chess depends.
. . . .
Kasparov argues that the introduction of machine intelligence to chess did not diminish but enhanced the aesthetics of the game, creating a new space for creativity at the game’s highest levels. Today, players of ‘freestyle’ chess work with high-end chess systems, databases of millions of games and moves, and often other human collaborators too. Freestyle teams can easily defeat both top grandmasters and chess programs, and some of the best centaur teams are made up of amateur players who have created better processes for combining human and machine intelligence.
. . . .
We are all centaurs now, our aesthetics continuously enhanced by computation. Every photograph I take on my smartphone is silently improved by algorithms the second after I take it. Every document autocorrected, every digital file optimised. Musicians complain about the death of competence in the wake of Auto-Tune , just as they did in the wake of the synthesiser in the 1970s. It is difficult to think of a medium where creative practice has not been thoroughly transformed by computation and an attendant series of optimisations. The most profound changes have occurred in fields such as photography, where the technical knowledge required to produce competent photographs has been almost entirely eclipsed by creative automation. Even the immediacy of live performance gets bracketed by code through social media and the screens we watch while recording events that transpire right before our eyes.
. . . .
Sociologists such as Pierre Bourdieu painstakingly mapped the deeply social dimensions of cultural judgment in the 20th century, but today the deeply intersubjective nature of taste is not just obvious but almost subliminal. Algorithms are shaping the reception of works at the forefront, but also the periphery. The entire horizon of our cultural perspectives is shaped by the filtering mechanisms that populate our news feeds, prioritise our inboxes and rank our search results. And they are, of course, built out of our own collective responses to prior stimuli, modelling a collective aesthetic project that we (often unknowingly) participate in with every click and purchase.
Link to the rest at Aeon
Unlike a ‘game’ art can have too many variables for a machine to try to work with.
Then there’s the small problem of people often not being able to explain why they like one thing over another – so how can you program for it?
As for their ‘centaurs’ thingy, the team is only as good as its weakest link; be that the programming, or the human not being able to keep their ‘ride’ in check.
I think us solo organic units are safe for a while yet.
Sorry, but I have to disagree:
People often can’t explain what they like or why they like it. But Amazon and other advertisers cope with that every day in sending you directed advertising based on what you have liked before. Look also at services like Pandora as an example of algorithms figuring out patterns by matching hidden variables against past behaviors.
“Only as good as the weakest link”? It all depends on how the “links” are organized. Steel cables are far, far stronger than their individual strands, and stronger even than those same strands would be if they were not twisted together. Much of civil engineering is about combining components in ways that are stronger than the individual components themselves. No single steel girder could support an entire skyscraper.
Amazon and the like can compare to what has gone before and guess what the general public will like/dislike. The problem though is until something is made/written/played they have no idea if it’ll be a shooting star – or a dud.
And on the ‘advertisers’? Please, most of them just throw everything the customer is willing to spend at the wall in the hopes that something might stick.