How AI impacts today’s music — and what that means for the industry

Terms like “machine learning” and “generative AI” can conjure up some extreme ideas of today’s technological capabilities, especially for anyone who doesn’t regularly engage with that type of tech. But machine learning (ML) and generative AI solutions can’t generate original content out of thin air; their creations come from the materials they’re trained on.

For instance, Spotify recommends songs based on individual user selections. User preferences are studied on the back end, and AI takes this information and basically says, “If X user listens to X artist, they might like this other artist based on these shared characteristics,” using data input from humans.

But AI’s mark on the music industry goes far beyond helping music lovers find their next favorite artist. Keep reading to learn more about generative AI’s influence on the music industry and why artists and insiders are cautious about its creative potential.

How AI Already Appears in Your Favorite Songs

AI’s presence in music isn’t a brand new concept. Singers, songwriters, producers, composers, and other industry insiders use different forms of ML and generative AI tools to help them with both creative and relatively mundane tasks. Here’s a brief compilation to show what today’s state-of-the-art technology is capable of:

• ML software was used to draw out usable vocals from a previously hard-to-hear, lo-fi recording of John Lennon singing “Now and Then,” now considered to be the last recorded Beatles song.
• Songwriters can prompt tools like ChatGPT to help generate ideas for lyrics or more interesting interpretations of song ideas.
• Producers use AI to correct a vocalist’s pitch in final edits, while engineers can mix recordings quickly and thus, less expensively.
• AI can be used to generate different musical sounds, including specific instruments, which provides greater creative access to artists who may not be able to afford multiple musicians or the studio hours needed to produce their ideal compositions.

These examples range from neutral to creatively freeing in terms of how AI currently impacts the music we listen to. However, some pathways to innovation require creators to proceed more cautiously, especially when it comes to respecting an artist’s voice, likeness, and body of work.

What’s Next — and Why the Industry Is Concerned

As more people use ML and AI in music creation, the technology will become increasingly intelligent due to the increased amount of data it’s being trained on. The more data it is trained on, the closer the technology gets to replicating human behavior. This development becomes tricky to navigate when considering the potential to replicate any artist’s voice with relative ease.

Copyright brings into question artistic ownership. Ola Sars, a veteran in the music technology space, explains, “The issue that rights holders, artists, or songwriters have with that is that [these companies are] using their art to train the machines to produce music based on their music.” In many cases, it’s hard to discern between a true vocal and a generated one.

Sars continued, “Labels and publishers are worried that there's going to be a whole robot army replicating their music, and consumers won't understand that it's produced by a machine. [The labels and publishers will] lose their revenue, and they'll be replaced by machines.”

Without some type of regulatory policies in place, artists and other members of the music industry worry that the unchecked use of ML and genAI tools could lead to confusion as to what’s real and what’s not, not just in a musical sense but in terms of the artist’s actual image, branding, and reputation.

Tennessee has taken steps to help protect artists against AI-generated imitations. According to NPR, “The Ensuring Likeness Voice and Image Security Act, or ELVIS Act, is an updated version of the state's old right of publicity law. While the old law protected an artist's name, photograph or likeness, the new legislation includes AI-specific protections.”

ML and AI can provide greater access to music production software, making musical expression more affordable and accessible to a wider audience than ever before. Keeping ethics and legal considerations in mind when using or further developing this technology is essential to protecting creative integrity and creating future opportunities.