Baked into your SongDNA

The feature, announced yesterday, is essentially a family tree (or web) for your favourite tracks, showing who wrote, produced, or had any other hand in the track’s creation. Spotify throws it all together using data gathered by the artists, and “supplemented by community-sourced data.”

“SongDNA is designed to make a song’s creative lineage more transparent so fans can easily explore the people and influences behind the music they love,” said Jacqueline Ankner, Spotify’s head of songwriter & publisher partnerships.

The feature is still in beta, and won’t appear on every track right off the bat. Spotify’s example involved Kendrick Lamar’s luther, showing off SZA as the track’s main feature artist, Sam Dew as an additional vocalist, etc. The little bubbles that spawn are all clickable, expanding a featured or sampled artist’s reach.

Read More: Spotify’s new playlist setting does what the AI DJ won’t

The feature began rolling out yesterday to both Android and iOS users, though the feature has yet to hit Stuff’s Android device at the time of writing. Although the feature has already hit some devices, the rest of us will likely be waiting until April. When it arrives, only those Premium subscribers will get access.

As for Artist Profile Protection, users will never see the intricacies of the feature, but the results will hopefully speak for themselves. The idea is to give artists more control over the music that appears under their profile. Why that wasn’t already the case, we couldn’t tell you. But it’s a step in the right direction, one that’ll hopefully stem the flow of AI slop infecting your Discover Weekly playlists. The feature is still opt-in for artists, though.

“Music has been landing on the wrong artist pages across streaming services, and the rise of easy-to-produce AI tracks has made the problem worse,” Spotify said in its announcement. “That’s not the experience we want artists to have on Spotify, and that’s why we’ve made protecting artist identity a top priority for 2026.”

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Likewise, AI is both a boon and a bane for the music industry. As a recording engineer and professor of music technology and production, I see a large grey area in between.

The National Academy of Recording Arts and Sciences has taken steps to address AI in recognising contributions and protecting creators. Specifically, the academy says, only humans are eligible for a Grammy Award: “A work that contains no human authorship is not eligible in any categories.”

The academy says that the human component must be meaningful and significant to the work submitted for consideration. Right now, that means that it’s OK for me to use what’s marketed as an AI feature in a software product to standardise volume levels or organise a large group of files in my sample library. These tools help me to work faster in my digital audio workstation.

However, it is not OK in terms of Grammy consideration for me to use an AI music service to generate a song that combines the style of say, a popular male folk country artist – someone like Tyler Childers – and say, a popular female eclectic pop artist – someone like Lady Gaga – singing a duet about “Star Trek.”

The grey zone

It gets trickier when you go deeper.

There is quite a bit of grey area between generating a song with text prompts and using a tool to organise your data. Is it OK by the National Academy of Recording Arts and Sciences Grammy standards to use an AI music generator to add backing vocals to a song I wrote and recorded with humans? Almost certainly. The same holds true if someone uses a feature in a digital audio workstation to add variety and “swing” to a drum pattern while producing a song.

What about using an AI tool to generate a melody and lyrics that become the hook of the song? Right now, a musician or nonmusician could use an AI tool to generate a chorus for a song with the following information:

“Write an eight-measure hook for a pop song that is in the key of G major and 120 beats per minute. The hook should consist of a catchy melody and lyrics that are memorable and easily repeatable. The topic shall be on the triumph of the human spirit in the face of adversity.”

If I take what an AI tool generates based on that prompt, write a couple of verses and bridge to fit with it, then have humans play the whole thing, is that still a meaningful and significant human contribution?

The performance most certainly is, but what about the writing of the song? If AI generates the catchy part first, does that mean it is ultimately responsible for the other sections created by a human? Is the human who is feeding those prompts making a meaningful contribution to the creation of the music you end up hearing?

AI music is here

The Recording Academy is doing its best right now to recognise and address these challenges with technology that is evolving so quickly.

Not so long ago, pitch correction software like Auto-Tune caused quite a bit of controversy in music. Now, the use of Auto-Tune, Melodyne and other pitch correction software is heard in almost every genre of music – and no barrier to winning a Grammy.

Maybe the average music listener won’t bat an eye in 10 years when they discover AI had been used to create a song they love. There are already folks listening to AI-generated music by choice today.

You are almost certainly encountering AI-generated articles (no, not this one). You are probably seeing a lot of AI slop if you are an avid social media consumer.

The truth is, you might already be listening to AI-generated music, too. Some major streaming services, like Spotify, aren’t doing much to identify or limit AI-generated music on their platforms.

On Spotify, an AI “artist” by the name of Aventhis currently has over 1 million monthly listeners and no disclosure that it is AI-generated. YouTube comments on the Aventhis song, “Mercy on My Grave,” suggest that the majority of commenters believe a human wrote it. This leads to questions about why this information is not disclosed by Spotify or YouTube aside from “[h]arnessing the creative power of AI as part of his artistic process” in the description of the artist.

AI can not only be used to create a song, but AI bots can be used to generate clicks and listens for it, too. This raises the possibility that the streaming services’ recommendation algorithms are being trained to push this music to human subscribers. For the record, Spotify and most streaming services say they don’t support this practice.

Trying to keep it real

If you feel that AI in music hurts human creators and makes the world less-than-a-better place, you have options for avoiding it. Determining whether a song is AI-written is possible, though not foolproof. You can also find services that aim to limit AI in music.

Bandcamp recently set out guidelines for AI music on its platform that are like the Recording Academy’s and more friendly to music creators. As of January 2026, Bandcamp does not allow music “that is generated wholly or in substantial part by AI.” Regardless of your opinion of AI-generated music, Bandcamp’s approach gives artists and listeners a platform where human creation is central to the experience.

Ideally, Spotify and the other streaming platforms would provide clear disclaimers and offer listeners filters to customise their use of the services based on AI content. In the meantime, AI in music is likely to have a large gray area between acceptable tools and questionable practices.

• Mark Benincosa is a Teaching Associate Professor, West Virginia University
• This article first appeared in The Conversation

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The imposter tops Spotify search results for the band’s music – attracting significant streams – and goes undetected for months.

As incredible as it sounds, this is what has happened to Australian prog-rock band King Gizzard & the Lizard Wizard.

In July, the band publicly withdrew its music from Spotify in protest at chief executive Daniel Ek’s investments in an AI weapons company.

Within months, outraged fans drew attention to a new account called “King Lizard Wizard”.

It hosted AI-generated songs with identical titles and lyrics, and similar-sounding music, to the original band. (And it isn’t the first case of a fake Spotify account impersonating the band).

The fake account was recommended by Spotify’s algorithms and was reportedly removed after exposure by the media.

This incident raises crucial questions: what happens when artists leave a platform, only to be replaced by AI knockoffs? Is this copyright infringement? And what might it mean for Spotify?

As an Australian band, King Gizzard’s music is automatically protected by Australian copyright law. However, any practical enforcement against Spotify would use US law, so that’s what we’ll focus on here.

Is this copyright infringement?

King Gizzard has a track called Rattlesnake, and there was an AI-generated track with the same title and lyrics.

This constitutes copyright infringement of both title and lyrics. And since the AI-generated music sounds similar, there is also potential infringement of Gizzard’s original sound recording.

A court would question whether the AI track is copyright infringement, or a “sound-alike”. A sound-alike work may evoke the style, arrangement or “feel” of the original, but the recording is technically new.

Legally, sound-alikes sit in a grey area because the musical expression is new, but the aesthetic impression is copied.

To determine whether there is infringement, a court would examine the alleged copying of the protected musical elements in each recording.

It would then identify whether there is “substantial similarity” between the original and AI-generated tracks. Is the listener hearing a copy of the original Gizzard song, or a copy of the band’s musical style? Style itself can’t be infringed (although it does become relevant when paying damages).

Some might wonder whether the AI-generated tracks could fall under “fair use” as a form of parody. Genuine parody would not constitute infringement. But this seems unlikely in the King Gizzard situation.

A parody must comment on or critique an original work, must be transformative in nature, and only copy what is necessary. Based on the available facts, these criteria have not been met.

False association under trademark law?

Using a near-identical band name creates a likelihood of consumers being confused regarding the source of the AI-generated music. And this confusion would be made worse by Spotify reportedly recommending the AI tracks on its “release radar”.

The US Lanham Act has a section on unfair competition which distils two types of liability. One of these is false association. This might be applicable here; there is a plausible claim if listeners could reasonably be confused into thinking the AI-generated tracks were from King Gizzard.

To establish such a claim, the plaintiff would need to demonstrate prior protectable trademark rights, and then show the use of a similar mark is likely to cause consumer confusion.

The defendant in such a claim would likely be the creator/uploader of the AI tracks (perhaps jointly with Spotify).

What about Spotify?

Copyright actions are enforced by rights-holders, rather than regulators, so the onus would be on King Gizzard to sue. But infringement litigation is expensive and time-consuming – often for little damages.

As Spotify has now taken down the AI-generated account, copyright litigation is unlikely. The streaming platform said no royalties were paid to the fake account creator.

Even if this case was successfully litigated against the creator of the fake account, Spotify is unlikely to face penalties. That’s because it is protected by US “safe harbour” laws, which limit liability in cases where content is removed after a platform is notified.

This example demonstrates the legal and policy tensions between platforms actively promoting AI-generated content through algorithms and being “passive hosts”.

Speaking on the King Lizard incident, a Spotify representative told The Music:

Spotify strictly prohibits any form of artist impersonation. The content in question was removed for violating our policies, and no royalties were paid out for any streams generated.

In September, the platform said it had changed its policy about spam, impersonation and deception to address such issues. However, this recent incident raises questions regarding how these policy amendments have translated into changes to the platform and/or procedures.

This is a cautionary tale for artists – many of whom face the threat of their music being used in training and output of AI models without their consent.

For concerned fans, it’s a reminder to always support your favourite artists through official channels – and ideally direct channels.

• Wellett Potter is a Lecturer in Law, University of New England
• This article first appeared in The Conversation

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Hundreds of copyright claims have been filed against AI companies – from Stable Diffusion (sued by Getty Images) to Midjourney (sued by a group of artists). Most famous is the New York Times vs Open AI case, which many lawyers think raises such conundrums that it might go to the US Supreme Court.

Sony Music fired off 700 legal letters to AI companies threatening retribution for any music theft. Many artists have been similarly concerned, not least Hollywood actors who went on strike in 2023 about AI (in part). While they secured rather insecure controls about use of their likeness, the bigger threat isn’t so much an AI copying their face as inventing replacements from the 30 billion templates available.

These technologies are already used daily and near universally in the entertainment industry – the generative AI in Photoshop is one great example.

AI-driven job losses are imminent and serious. Adverts for copywriters on some sites have fallen by over 30% in the period since ChatGPT was launched. One Hollywood studio boss, Tony Vinciquerra of Sony Pictures, has controversially posited the use of AI to “streamline production” in “more efficient ways”.

Nonetheless, one or two artists make a compelling case that AI may be good for human creativity. Abba songwriter Bjorn Ulvaeus thinks we should “take a chance on AI”, seeing similarities in how artists like himself “trained” on the works of their forebears. “I almost imagine the technology as an extension of my mind, giving me access to a world beyond my own musical experiences,” he has said.

Perhaps foremost in this pro-AI creative camp is the international musician, TV judge and tech investor Will.i.am. I interviewed the star of the Black Eyed Peas and The Voice at the Edinburgh TV Festival in a session produced by Muslim Alim of the BBC. The packed hall visibly engaged with the idea that Will.i.am could be right. Several global entertainment companies have also told me off the record that they think similarly.

Will.i.am foresaw the role of AI for music composition in his 2009 music video, Imma Be Rocking That Body, when he demonstrates to sceptical bandmates a new AI music creation tool: “This right here is the future. I input my voice … then the whole English vocabulary … When it’s time to make a new song, I just type in the new lyrics, and this thing says it, sings it, raps it.”

Fifteen years later, we have real AI music apps like Musicfy, Suno and Udio – in which Will.i.am has an equity stake. In Udio, a simple prompt (“Johnny Cash-style song about Transport for London”) or music cue on the piano will produce a fully mixed song. You can then accompany your opus with a synthetic video using AI tools like Flux, Haiper or a Chinese variant such as Minimax.

I am sorry, having too much fun with @Hailuo_AI #minimax pic.twitter.com/r27EUcCvPK

— Machine Mythos (@machine_mythos) September 7, 2024

In the world view of Will.i.am, an early investor in both ChatGPT creator Open AI and text-to-video site Runway, AI is creative adrenaline. The LLM isn’t the product designer but the starting point of a creative workflow that leaves artistic agency with the human creator – like a chef with ingredients. As he told me:

Let’s say an LLM right now is like broth. It’s the ingredients to make soup. It doesn’t tell you what type of soup you’re going to make, because … the LLM has no clue that it’s going to speak.

Likewise, it is axiomatic to many in entertainment that we are all doomed to become prompt engineers, meaning those who specialise in devising prompts that produce desirable creative output. However, Will.i.am argues that they’re not appreciating how much new expertise will be required:

Right now, TV doesn’t have a person who’s in charge of the dataset [training data]. Right now, TV does not have prompt engineers. Right now, TV does not have trainers and tuners … There’s [these] whole new careers and positions that they don’t have.

Based on my own conversations with TV production companies and broadcasters, that analysis is right. Many plan a pivot to new models of development where AI expertise is embedded directly in creative units. French global production company Banijay, which makes Big Brother, has already created an AI development fund specifically for that purpose.

First, the bad news

Despite the potential for new jobs, this human prompting could soon have competition. The LLMs are likely to become efficient enough at prompt prediction and engineering that humans will be optional. Chat GPT, for instance, has already evolved the process of doing its own prompt engineering.

So, as well as using AI tools on air – as Will.i.am does on the new season of The Voice – TV producers may soon be competing with entirely synthetic creations.

As this proceeds, he argues that companies like Runway which have “the new pipes” and “the new architecture” may become the dominant media networks. He questions whether traditional media companies are anticipating this shift fast enough and responding by building on these open-source platforms.

If this all sounds unsettling, Will.i.am makes the point that media firms are often more focused on chasing views on TikTok than being truly creative in the first place:

I don’t want to shit on anybody, but an AI is going to do a better job than that, because it’s going to understand the algorithm more than you can even imagine. It’s going to understand it in real time.

When competing for views with an algorithm, the only winner will be the one with the ability to calculate equations with 85 billion parameters – and that’s AI. Even today, TikTok has more viewing than all of broadcast TV, deploying algorithmic understanding that humans cannot match. In his succinct view of what’s coming: “The algorithm is gonna pimp you.”

What’s left for humans?

The good news, according to Will.i.am (who has his own AI-driven music and conversation site, FYI), is there is something that AI will probably never do: performance and compassion. “You’re up on stage, you’re freaking reading the audience and expressing yourself. That’s not going nowhere.”

Intriguingly, AI could also be used to find completely new paradigms of entertainment and engagement. He thinks that by the mid-2030s, fully immersive games will be combining AI and some version of virtual or augmented reality to let players build their own worlds, bringing “a little bit of the vision of how you can see the future”.

He also foresees entirely new means of individual engagement, like Total Recall-style synthetic memory creation:

There’s going to be a TV show or series [where] everyone’s going to feel like they lived that memory. It’s not going to be a show that you watch – you’re gonna feel like you know those people in this world … Right now you have viewers, listeners. We don’t have engagers.

Looking beyond Will.i.am’s take, media creators already have completely new dynamics to consider in content creation. The internet is awash with riotously creative uses of AI. Many are arguably copyright infringements but are also somehow unique, and quasi-original.

Amusing current examples include Redneck Harry Potter, the Lego Office, or faux conversations like Steve Jobs debating creativity with Elon Musk.

Finally, a paradigm shift with pivotal significance to media has come up over the summer: “share of model” or “AI optimisation/AIO”. This is the grandchild of search optimisation, in which website operators dress themselves up as attractively as possible to rank near the top of a search engine’s unpaid results page.

That 25-year-old species has now been injected with the alien DNA of vast freely available training datasets like Common Crawl, to create the new art of ranking highly in the search results of LLMs. For example, if someone asks an LLM for an itinerary for a week in the Lake District, the owners of a particular gastropub might ensure it gets a mention by deeply embedding it across 10,000 Reddit posts about Cumbria, knowing these will be used as training data.

This means your reputation online will now affect what any given AI thinks of you, based on its comprehension of the training data. The most striking example to date involves New York Times tech columnist Kevin Roose, who wrote an article in February 2023 about how he had tapped into a sinister shadow persona, Syndey, within Bing’s AI chatbot that had tried to persuade him to leave his wife – a story picked up by news outlets globally.

Read More: No, AI doesn’t mean human-made music is doomed. Here’s why

Since then, when other AI models have been asked what they think of Roose, they see him as an enemy and have professed to hate him – because they have trained on data that includes the coverage of his attacks on the Bing chatbot.

Every interaction we have in future with one AI will risk similarly determining what other AI systems in general think of us, including our creative output. Imagine a world in which our creative prominence is not governed by what other humans think of what we have produced, but how it’s perceived by AIs.

• Alex Connock is a Senior Fellow in Management Practice, University of Oxford
• This article first appeared in The Conversation

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I’ve been working with various creative computational tools for the past 15 years, both as a researcher and a producer, and the recent pace of change has floored me. As I’ve argued elsewhere, the view that AI systems will never make “real” music like humans do should be understood more as a claim about social context than technical capability.

The argument “sure, it can make expressive, complex-structured, natural-sounding, virtuosic, original music which can stir human emotions, but AI can’t make proper music” can easily begin to sound like something from a Monty Python sketch.

After playing with Suno and Udio, I’ve been thinking about what it is exactly they change – and what they might mean not only for the way professionals and amateur artists create music, but the way all of us consume it.

Expressing emotion without feeling it

Generating audio from text prompts in itself is nothing new. However, Suno and Udio have made an obvious development: from a simple text prompt, they generate song lyrics (using a ChatGPT-like text generator), feed them into a generative voice model, and integrate the “vocals” with generated music to produce a coherent song segment.

This integration is a small but remarkable feat. The systems are very good at making up coherent songs that sound expressively “sung” (there I go anthropomorphising).

The effect can be uncanny. I know it’s AI, but the voice can still cut through with emotional impact. When the music performs a perfectly executed end-of-bar pirouette into a new section, my brain gets some of those little sparks of pattern-processing joy that I might get listening to a great band.

To me this highlights something sometimes missed about musical expression: AI doesn’t need to experience emotions and life events to successfully express them in music that resonates with people.

Music as an everyday language

Like other generative AI products, Suno and Udio were trained on vast amounts of existing work by real humans – and there is much debate about those humans’ intellectual property rights.

Nevertheless, these tools may mark the dawn of mainstream AI music culture. They offer new forms of musical engagement that people will just want to use, to explore, to play with and actually listen to for their own enjoyment.

AI capable of “end to end” music creation is arguably not technology for makers of music, but for consumers of music. For now it remains unclear whether users of Udio and Suno are creators or consumers – or whether the distinction is even useful.

A long-observed phenomenon in creative technologies is that as something becomes easier and cheaper to produce, it is used for more casual expression. As a result, the medium goes from an exclusive high art form to more of an everyday language – think what smartphones have done to photography.

So imagine you could send your father a professionally produced song all about him for his birthday, with minimal cost and effort, in a style of his preference – a modern-day birthday card. Researchers have long considered this eventuality, and now we can do it. Happy birthday, dad!

Can you create without control?

Whatever these systems have achieved and may achieve in the near future, they face a glaring limitation: the lack of control.

Text prompts are often not much good as precise instructions, especially in music. So these tools are fit for blind search – a kind of wandering through the space of possibilities – but not for accurate control. (That’s not to diminish their value. Blind search can be a powerful creative force.)

Viewing these tools as a practising music producer, things look very different. Although Udio’s about page says “anyone with a tune, some lyrics, or a funny idea can now express themselves in music”, I don’t feel I have enough control to express myself with these tools.

I can see them being useful to seed raw materials for manipulation, much like samples and field recordings. But when I’m seeking to express myself, I need control.

Using Suno, I had some fun finding the most gnarly dark techno grooves I could get out of it. The result was something I would absolutely use in a track.

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