Earlier this week, a fan named Mark for reasons that are not entirely clear, sent Nick Cave some lyrics written “in the style of Nick Cave” by the ChatGPT AI system.
Suffice to say, Cave was not happy with the algorithmic imitation.
“With all the love and respect in the world, this song is bullshit, a grotesque mockery of what it is to be human, and well, I don’t like it very much.”
Fair enough: why should he?
But Cave’s comment on his Red Hand Files blog raises issues relevant to all of us as we reflect on what the AI revolution means for our own lives and careers.
Before Cave, ChatGPT couldn’t write a ‘real song’, but only ‘a replication, a kind of burlesque’. That’s because, he says, real songs emerge from “the complex, internal human struggle of creation”:
This is what we humble people can offer that only AI can emulate, the transcendent journey of the artist forever struggling with his or her own shortcomings. This is where human genius resides, deeply entrenched in, yet reaching beyond, those limitations.”
Now artists have been concerned about the suffocating effects of technology since time immemorial.
In 1906, the composer John Philip Sousa polemicized, in very famous terms, against a futuristic invention called the phonograph.
“Hitherto the whole course of music, from the first day until now,” said Sousa, “has been to make it the expression of soul states. Now, in this twentieth century, these talking and playing machines, and again offer to reduce the expression of music to a mathematical system of megaphones, wheels, gears, discs, cylinders.
You’ll find similar charges against electric guitars, synthesizers, drum machines, Auto-Tune, and almost any new development in song making or recording.
Yet time and again people have discovered ways to use the technology in exciting, creative ways.
Think of the golden age of hip-hop: how producers used sampling – a technique many have denounced as pure plagiarism – to create an entirely new kind of music.
That example – particularly the subsequent legal restrictions on sampling – also illustrates how the capabilities of a particular technology depend on the social and economic context in which it emerges.
After all, most pop songs aren’t the result of individual geniuses, and that hasn’t been the case for a long time now. As early as 1910, The New York Times could publish a piece titled “How popular song factories make a hit”.
“Today,” it explained, “the consumption of songs by the masses in America is as constant as their consumption of shoes, and demand is similarly met by factory production.”
Then, as now, in a cutthroat business, companies applied all methods to make the most money as quickly as possible.
To disrupt pop music – and many other areas as well – AI does not have to show genius. It just has to be good enough so that the low price relative to human labor overrides any perceived decline in quality.
A few years ago, in his book The singing machine, John Seabrook wrote about how Swedish producers like Denniz Pop, Max Martin, Dr Luke and others transformed contemporary music. To create iconic songs for the likes of Taylor Swift, Rihanna, Katy Perry and Beyoncé, production wizards start with simple chord progressions on laptops, distribute the files to a wide variety of singers, melody makers, hook writers, lyricists and taste makers, then mix digital recordings of multiple contributors into a seamless whole.
David Hajdu of The Nation describes the method as not so much industrial as post-industrial, as it involves “mining the vast digital repository of past recordings, either by imitating or referencing them through synthesis, and then manipulating and putting them together add.”
AI suits this kind of songwriting perfectly.
Famously, Max Martin gave Britney Spears the alarming text “Hit me baby one more time” because, as a non-native English speaker, he misunderstood teen slang for texting. But, as songwriter Ulf Ekberg explained, “it was to our advantage that English wasn’t our native language because we can treat English very disrespectfully and just find the word that sounded right with the tune”.
Does anyone really think Martin and his team wouldn’t have used ChatGPT if the software existed back then?
None of this implies that AI itself is an obstacle to musical creation. The problem is not so much with the technology as with a social system that converts any innovation directly into profit, regardless of the consequences for art or society.
If there’s money to be made from AI-generated “Nick Cave-style” songs, we’ll get it, no matter how subpar the results.
That probably won’t affect Cave himself much, given the loyalty of his fanbase. But the same logic applied elsewhere threatens devastating consequences for ordinary people.
After all, an AI doesn’t have to be a genius to make you unemployed. It just has to be enough – and a little cheaper.