‘Cheat!” One of the worst call-outs in human life. Yet with the screaming progress of artificial intelligence, and particularly its growing facility in language, art and games, are we at the end of cheating? And the beginning of something else?

This is best illustrated at the moment by what has become known on social media as #ChessDrama. Last month, the Norwegian chess grandmaster Magnus Carlsen accused fellow grandmaster (and teenage enfant terrible), America’s Hans Niemann, of being an inveterate cheat.

How do you cheat at chess? The wider world has had fun imagining how winning advice might be communicated to players. Buzzing shoe inserts (or anal beads), strategic facial tics from audience members, looking at your phone in a toilet break … But it’s the entities giving the advice that are the core of the cheating. These are “chess engines”, made of software, that right now are effortlessly better than any human, no matter how grand their mastery, will ever be.

Online chess games and competitions have become huge, post-Covid. According to one of the major networks, Chess.com, having analysed his gameplay on their platform, it charges that Hans Niemann has availed himself of “illegal assistance” more than 100 times. They also identified three current grandmasters who had also AI-cheated with chess engines.

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To me, it seems easy enough to use the superintelligent software while playing digitally from home – just position a hooked-up device, out of sight of your webcam. But Niemann actually beat Carlsen in a physically co-present game, where they’d passed all kinds of detection and suffered constant surveillance.

Carlsen still asserted that something fishy was going on. He noted that after his victory, Niemann was poor at post-rationalising his game moves, as if he didn’t quite understand the thinking that produced them.

The #ChessDrama rages on, waiting for its next moves, which will be made media interview by media interview, rather than knight on rook. But I am more interested in what it reveals about our future.

How will we live with artificial intelligences that, in specific areas (but eventually in general), will calculate answers to data-rich problems more deeply and quickly than humans could ever do?

Going by the reactions of the chess world, with a mixture of pragmatism, curiosity, grumpiness and insouciance. Pragmatically, chess players have always practiced with their fellows, and anticipated their opponents’ game styles.

Now they do both with a super-genius on their laptops, one that always knows the ultimate winning move and can simulate the strategy of the other contestant.

Grandmasters have complained that creativity and surprise are disappearing from the human game: gameplay becomes about memorising the optimal moves that their infallible computers have already shown them. This drives proposals that the rules of chess might be changed – a bigger board, more powerful pawns – to keep things interesting.

However, the AI is above and beyond all that. Something like Deep Mind’s AlphaGo Zero programme would master any new changes in a matter of days or even hours. It would use its neuronal-like learning powers – playing itself incessantly and massively – in order to discover the winning moves coming out of any new rule set.

I wonder whether the tension between Niemann (18 and Gen A) and Carlsen (31 and Gen Z) is between the stubbornly human and the relaxedly post-human. Niemann expects to learn from powerful algorithms in his life while Carlsen still clings to some possibility of human expertise and mastery.

Niemann is already in a partnership with artificial intelligence. He assumes that the more he engages with it, the more it will take his unassisted game to new levels. (Maybe it has, given his surprise victory over Carlsen).

CARLSEN, like some hapless legal clerk automated away by smart machines that crunch case law, perhaps looks at his years of chess practise and intuition – and sees so much grind and wasted labour, effortlessly transcended by mere software. Understandably enraging.

What about AI and other human competitions? Take the recent story about the winner of the Colorado State Fair’s art prize (digital category), which was precisely accredited to “Jason Allen via Midjourney”.

Jason is a human, but Midjourney is an AI that can turn a text prompt (for example, “Gordon Brown as a mouldy banana, in the style of Roy Lichtenstein”) into an image. The title of the winning piece is “Theatre D’opera Spatial” (Space Opera Theatre). It’s pretty groovy, like an opening scene from a sci-fi Netflix special.

But it caused a fuss, with some art competitions and artist groups’ calling for AI-made art to be banned. I predict this won’t last long. There’s one thing I know about contemporary arts: if a new tool is easy to use and richly generative of possibilities, it will be quickly adapted, used and (best of all) abused.

We don’t know what will come from a new relationship between text and image – maybe something as startling and subverting as comics once were. But I doubt “cheating” will pertain, as criterion for judging its artistic worth.

I guess some reader will see my sanguinity about all this, and say “just you wait till the machines come for the journalists and the musicians!” Again, that battle is already here and interestingly lost.

The Google engineer who recently claimed the company’s top chatbot, LaMDA, was already sentient and conscious, has gone to ground. But the prose that the algorithm generated in its exchanges with Blake Lemoine was, at the very least, on its way to being a serviceable op-ed.

Schoolkids in the USA are also confessing to using these “large language model” AI to get them, and their pals, A-grade scores in their school exams. Does this judge the AI or does it judge the formulaic and routine nature of education?

I do know of AIs that are already composing admirable classical and modern musical works.

Intelligent software is even feeding on the vast archives of popular music, claiming to come up with parameters that steer artists to success. (Good luck with that – pop is always mud against a wall.) I predict that what these powerful creative algorithms will do is drive our human aesthetics in the opposite direction – towards the flaky and the fragile, the unpredictable and unrepeatable, the sweaty and the all-too-human.

To be clear, this doesn’t mean being against the machine, but maybe sometimes choosing what machines to work with, and in what ways.

My brother and I have been making a dance record over the last few years, and we have come to love something called an “arpeggiator”.

This is indeed a dreaded and relentless machine – though not comprised of zeros and ones, but full of valves and transistors, making wave patterns.

These boxes produce cascading scales of notes, arpeggios recognisable to the classical greats. But those patterns are unique, every time you fire up the box (and sometimes it depends on whether the studio heating’s been on).

Greg and I have, in a sense, been jamming with these unpredictable machines, as fellow musicians.

Songs – indeed, veritable bangers – have sprouted out of every engagement we’ve had.

These arpeggiations can subsequently be digitally manipulated – but they first make a unique contribution, as granular as breath through a saxophone.

So can the human-machine relationship be more fruitful?

The American theologian James Carse makes a distinction between “finite games” (sports with winners and losers, like chess or capitalism), and “infinite games” (cultures that seek to extend outwards, that change the rules in order to include others).

Perhaps it matters what kind of tech we bring to what kinds of games. #ChessDrama won’t be the first of these stushies between humans and superintelligent AIs.

But we can learn, in a cautionary way, from its high-browed hysteria.