Artistry in the Algorithms: Music in the Age of AI

Artistry in the Algorithms: Music in the Age of AI Berklee alumni and professors speak to Berklee Today about the promise and peril of making music with AI.

By

Michael Blanding

November 13, 2023

A few months ago, Associate Professor Ben Camp, who teaches in Berklee's Songwriting Department, was working with a recent graduate on a tricky lyric for a new album. She wanted to convey the sense that she could create magic, and to urge listeners to get in touch with their own inner powers instead of being afraid of them, recalls Camp (they/them). And the context for this line was like the mood of the witches that open Macbeth. Later, Camp sent her a potential lyric: In the witching hour's hold / Do you hear the stories told? / Do you fear the magic yet to unfold?

I read it to her and she loved it, says Camp, who says she only changed one word- unfold to unfurl. Camp then revealed that they actually hadn't come up with the line-it was generated by ChatGPT, the large language model trained by artificial intelligence (AI). She was like, Oh my God, I hate you,' Camp says, chuckling.

The anecdote captures the ambivalence songwriters and musicians are feeling about artificial intelligence, says Camp, who has begun introducing ChatGPT and other AI tools into their classes. I've gotten everything from I need to go home and throw out my computer,' to It's okay, but it doesn't have the spirit and soul a human has,' to Thank you for making me use AI. I did a way better job than I would have without it.'

Associate Professor Ben Camp

Image by Kelly Davidson

As generative AI and machine learning get better and better at mimicking human creativity-and at making original music-the technologies have been greeted by musicians and music fans alike with mixed emotions, including a healthy dose of fear. This spring, when an anonymous composer released the song Heart on My Sleeve, claiming they used AI to generate passable versions of the voices of Drake and the Weeknd, the so-called Fake Drake alarmed musicians everywhere, who feared that their talents could simply be ripped off.

It was the second time in a matter of months that AI had crossed the line into what had been exclusively the territory of musicians and songwriters. In February, DJ David Guetta created a song using AI to generate lyrics along with the voice of Eminem. Getting ahead of the trend, in April Grimes gamely told creators they could freely use her voice in compositions without penalty. (That's easy enough when you're a multimillion-dollar artist who has children with the richest man in the world.) So far, such experiments seem little more than musical pranks. But as the technology continues to improve, it's quickly forcing musicians and songwriters, including Berklee faculty and alumni, to grapple with its implications.

These are still early days. But there are a number of startups right now in an arms race to productize AI technology for music that we'll start to see in six months to a year.

- Jonathan Bailey '08, former chief technology officer of iZotope

Democratizing or Dumbing Down? These are still early days, says Jonathan Bailey '08, former chief technology officer of iZotope, a company using machine learning in part to create software for recording, mixing, and mastering music. But there are a number of startups right now in an arms race to productize AI technology for music that we'll start to see in six months to a year. One of iZotope's big breakthroughs was using AI to remove background noise from an audio recording-a feat that is normally hard to do.

Separating out the speech content from noise is really difficult, but it's actually a pretty easy problem to solve using deep learning, Bailey says. The same principles that can label sounds as speech or noise are now being applied to identify drums, guitars, and other instruments-and will eventually be able to generate those sounds, Bailey says.

If you're a singer-songwriter, you can record your voice and guitar in your bedroom and then automatically enhance the quality to sound like you recorded it in a professional studio. Then what if you could add a bass track and drums to that? Right now, it seems in the realm of fantasy, but this could become more and more possible.

In a sense, such technologies are an extension of the democratization of music recording, continuing the trend of software such as GarageBand or Autotune that have made advanced tools more accessible to amateur musicians. It used to cost a million dollars to create an album, then $10,000, and now $1,000, Bailey says. To me, generative AI is just a point on that curve, the next evolution of enabling more people to be creative.

That democratizing trend in AI doesn't bother Mark Simos, an assistant professor in Berklee's Songwriting Department. It's part of a whole progression of technologies to help nonskilled musicians to be able to write songs, he says. That's not likely to fundamentally change the nature of the industry. On the other hand, he does see a danger in professional musicians using AI to generate songs out of whole cloth.

Assistant Professor Mark Simos

Image by Louise Bichan

Decades ago, Simos worked in software with expert systems, a precursor to AI. More recently, he's judged several AI songwriting contests, and has noticed a disturbing trend of musicians using AI as a shortcut to creativity. When you ask ChatGPT to spit out a song on a certain topic in a certain study, that's not how real songwriting works, Simos says. Much of real songwriting is nonlinear; it's not just reaching into some oracular space in your head and out pops the song.

What AI can't replicate-at least not yet-is the combination of music and lyrics that make

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