Musicians, Machines, and the AI-Powered Future of Sound

Musicians have also reacted to the general unease generated by ChatGPT and Bing’s AI chatbot. Bogdan Raczynski, reading transcripts of the chatbots’ viral discussions with humans, says over email that he detected “fright, confusion, regret, guardedness, backtracking, and so on” in the model’s responses. It isn’t that he thinks the chatbot has feelings, but that “the emotions it evokes in humans are very real,” he says. “And for me those feelings have been concern and sympathy.” In response, he has released a “series of comforting live performances for AI” (emphasis mine).

Ben-Tal says his work presents an alternative to “the human-versus-machine narrative.” He admits that generative AI can be unsettling because, on a superficial level at least, it exhibits a kind of creativity normally ascribed to humans, but he adds that it is also just another technology, another instrument, in a lineage that goes back to the bone flute. For him, generative AI isn’t unlike turntables: When artists discovered they could use them to scratch records and sample their sounds, they created whole new genres.

In this vein, copyright may need a substantial rethink: Google has refrained from releasing its MusicLM model, which turns text into music, because of the “the risks associated with music generation, in particular, the potential misappropriation of creative content.” In a 2019 paper, Ben-Tal and other researchers asked readers to imagine a musician holodeck, an endpoint for music AI, that has archived all recorded music and can generate or retrieve any possible sound on request. Where do songwriters fit into this future? And before then, can songwriters defend themselves against plagiarism? Should audiences be told, as WIRED does in its articles, when AI is used?

Yet these models still present attractive creative capabilities. In the short term, Ben-Tal says, musicians can use an AI, as he did, to improvise with a pianist outside of their skill set. Or they can draw inspiration from an AI’s compositions, perhaps in a genre they are not familiar with, like Irish folk music. 

And in the longer term, AI might fulfill a wilder (albeit controversial) fantasy: It could effortlessly realize an artist’s vision. “Composers, you know, we come up with ideas of what music we would like to create, but then translating these into sounds or scores, realizing those ideas, is quite a laborious task,” he says. “If there was a wire that we could plug in and get this out, that could be very fantastic and wonderful.” 

More urgently, mundane and pervasive algorithms are already mangling the industry. Author Cory Doctorow has written about Spotify’s chokehold on music—how playlists, for instance, encourage artists to abandon albums for music that fits into “chill vibes” categories, and train audiences to let Spotify tell them what to listen to. Introduced into this situation, AI will be the enemy of musicians. What happens when Spotify unleashes its own AI artists and promotes those? 

Raczynski hopes he will catch the wave rather than be consumed by it. “Perhaps in a roundabout way, like it or not, I am acknowledging that short of going off the grid, I have no choice but to develop a relationship with AI,” he says. “My hope is to build a reciprocal relationship over a self-centered one.”