AI Music: ‘Theft machines’?

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0:33Dust on the wind Boots on the ground

0:37Ludovic Hunter-Tilney: Smoke in the sky That's the mellow sound of Dust on the Wind, a song by the band The Velvet Sundown. They play classic rock in the style of 1970s bands like Kansas and the Eagles. It's all very FM radio, but retooled for the age of streaming and playlists. Don't look away The Velvet Sundance debut album, Floating on Echoes, came out in June. It racked up a million streams on Spotify in less than a month, catapulting the band to fame. But people noticed something strange about this quartet of retro rockers. Velvet Sundance were oddly elusive. There were no interviews with them, no tour dates, no website.

1:23Ludovic Hunter-Tilney: And there was something even more peculiar about their publicity photos. Four airbrushed Californian dudes with eerily perfect faces and identical hands, holding hamburgers in a celebratory meal as though they had never seen a griddled patty before. So who exactly are Velvet Sundown? The answer is no one. Or at least not the people they claimed to be. It turns out Velvet Sundown and their hit songs are totally AI generated. The Velvet Sundown is a band that gets more than a million monthly listens. Turns out their music is generated by AI. The band changed its profile on Spotify to say the project is guided by human creative direction and then composed, voiced and visualised with the support of artificial intelligence.

2:21Ludovic Hunter-Tilney: The Velvet Sundown was an elaborate deception. Everything from the band's lyrics to the melodies to the artwork were made by generative artificial intelligence. And their success on streaming platforms has thrown up a lot of questions. How did they get so many streams? Why weren't they flagged as AI by music platforms? And how did the Velvet Sundown's music get so precise, So convincing that they were able to pass as a real band in the first place.

2:59Ludovic Hunter-Tilney: This is Techtonic from the Financial Times. I'm Ludwig Hunter-Tilney, the FT's pop critic. And in this two-part series, we're looking at how AI is impacting the music industry. In the last episode, we explored how AI technology has evolved, whether it has the potential to take people's jobs, and if it could present a threat to the very practice of music making itself. But AI music generators may have an Achilles heel. They're trained on literally millions of songs harvested from the internet. And campaigners, record labels, and artists say that includes stealing songs that should be protected by copyright law.

3:42Ludovic Hunter-Tilney: The AI companies behind the music generators are coming up against an age-old music industry adage. Where there's a hit, there's a writ. This is part two, Theft Machines.

3:59Ludovic Hunter-Tilney: Every new piece of music contains traces of other pieces of music that came before it. But AI song generators take this recycling process to an extreme The Velvet Sundown are a case in point Their sound accurately mimics an analogue era of vinyl and guitars Long hair and a thick fog of marijuana smoke The song you were just listening to, Dust on the Wind Has the vibe of Kansas' hit Dust in the Wind And that feeling of familiarity isn't just because of the almost indistinguishable titles It also comes from the way these AI models learn. To train today's AI models in a given domain, you need tons of examples of that thing to learn from.

4:47So you need tons of real music.

4:49Ludovic Hunter-Tilney: That's Ed Newton-Rex, who you heard in the previous episode. He's a composer and the CEO of Fairly Trained, a non-profit that advocates for ethical AI models. But he worked in generative AI for more than a decade. So AI companies, they either go and send out their own web crawler that will kind of crawl tons and tons of websites, find links to music files. Ultimately, they'll scrape them, they'll download them, or they will go and get access to some other library that someone else has already done that for. And then essentially, the way these training algorithms work is these models try to recreate what they hear, right?

5:31So you'll stop the music at like five seconds and you'll try to get it to replicate kind of what comes next. You can think of it like this. And if the next kind of sound that outputs is the next one in the original song, you essentially give it a good mark. And you do this just untold numbers of times with untold numbers of pieces of music. So what this does is it builds up this model that has this understanding of music such that it can then essentially generate its own music.

6:00Ludovic Hunter-Tilney: This learning, according to Newton-Rex, is on a totally unprecedented scale. Is it at all analogous to the sort of processes that you would do as a composer if you were to go and, let's say, listen to lots of music by Benjamin Britten and then go and compose something which was clearly influenced by it? Is this really like a sort of computer equivalent at what it's capable of being able to assimilate and reproduce? It's really not. The ways that these processes work are totally different. As a simple example, you know, basically to train one of these models, you need billions of data points. That is not how we learn music.

6:36I do not go and consume the entire canon of Western music and learn its intricacies and copy it repeatedly and then output something fresh that, by the way, every so often might quote something I've learned. That's a simple example of how these processes are totally different.

6:52Ludovic Hunter-Tilney: The result is, you've got these models that have mined the internet for millions of songs. For Newton-Rex and other musicians, the problem is not just that these models are so powerful, it's that they may have been trained on those musicians' music, without their knowledge, without their permission. Given that this music belongs to other people, is being taken without their permission, is being copied huge numbers of times in this process, which is ultimately where copyright is infringed. What is happening here is basically theft dressed up as competition. You know, you have this model at the end, and the AI company will say, you know, it's just like a human competing with you.

7:36But actually, it's very, very different, because they've stolen this music.

7:40Ludovic Hunter-Tilney: Newton Rex says that it wasn't always like this. Back in 2010, when he started working in generative AI, AI companies stuck to training models on music that either wasn't copyrighted or that they'd paid for. But then in 2022, across the whole AI industry, you suddenly had this moment where what had previously been happening behind closed doors, where people had been sort of researching what would happen if you just took more work to train on without asking, suddenly people started releasing these models commercially, which was unheard of. And at that point, the whole AI industry almost overnight shifted.

8:19And you got this huge shift towards basing these models on what's essentially theft. You know, it's going and just gathering whatever work you can to train your models on and ignoring the rights of the people who own that work.

8:32Ludovic Hunter-Tilney: To be clear, AI companies don't deny that they've trained their models on vast swathes of music gathered from the internet. Suno, one of the most advanced AI generators, has said that training includes all musical files of reasonable quality that are available on the internet. It also acknowledges that lots of the music available is copyrighted. But both Suno and Udio, another leading AI generator, say their use of this music to train their models would fall under an exception to copyright law called fair use. And fair use has a pretty broad definition allowing for copyrighted material to be used in circumstances like criticism, commentary, education, or in some cases, for there to be some creative and transformative use.

9:19Ludovic Hunter-Tilney: The idea that AI companies should be allowed to use copyrighted music, seemingly with such ease, is causing controversy. Suno and Udio are both facing lawsuits from copyright holders in the US and Europe. And in the UK, the government is considering taking things one step further. Currently, an AI company taking your work and training on it in this way in the UK is illegal. The government wants to legalise it. The government is actively trying to legalise the theft of people's creative labour. What the British government is proposing is an amendment to the law that would actually give AI companies special rights to use copyrighted music.

10:04Ludovic Hunter-Tilney: We got in touch with a government spokesperson who rejected the idea that they were legalizing theft, as Newton-Rex describes it, and added that, quote, no decisions have been taken, but our focus will always be on enhancing the ability of rights holders to be compensated and paid fairly, while enabling access to high-quality material to train leading AI models in the UK. I first came across Newton-Rex's name earlier this year because he put together an album I reviewed. It featured a surreally impressive supergroup. Hans Zimmer, Damon Albarn, Annie Lennox, Kate Bush, the Pet Shop Boys, and about a thousand other artists.

10:46Ludovic Hunter-Tilney: Here's a snippet of what it sounded like. Yes, that is indeed the sound of silence. The album, called Is This What We Want?, is a protest album, a silent protest album. It was designed to illustrate what the artists say will happen if proposed changes to UK copyright law go ahead. Empty studios, muted musicians, the end of songs sung by the human voice. And this isn't just a UK issue. A lot of governments around the world are eager to accommodate AI. No one wants to miss out on this revolutionary technology. i think in general lots of governments right now feel a lot of pressure i live in the u.s and the standard line here is um you know we got to compete with china and you hear that in the uk as well this idea that like there's ai race and if we don't allow ai companies to steal all the musicians work we will somehow lose the ai race but i think this is this lacks so much nuance i mean you know Firstly, you have AI companies talking about curing cancer and AI solving disease and making scientific discoveries.

11:58And let's be clear, they haven't done any of this yet. But ultimately, even if you think that that's possible, you don't need Ed Sheeran's songs if you want to cure cancer. Like, with respect to Ed Sheeran, you only need people's music if you want to build AI models that will compete with them.

12:19Ludovic Hunter-Tilney: Copyright infringement is complicated and while AI music companies might currently claim fair use in training their models they're cautious when it comes to reproducing real artists When I tried out Udeo in the first episode of this series it seemed quite effective at producing songs in a certain style death metal, say, or reggaeton But when I asked it to copy specific artists it seemed to misfire Take the Britpop song I asked it to make in the style of Oasis.

12:56It sounded nothing like Oasis, but did sound a bit like Guns N' Roses.

13:02Ludovic Hunter-Tilney: This happened a lot with UDO, who say they don't generate artist likeness without permission. If I asked it to copy the style of a specific artist, it would remove the name from the prompt and often make something that sounded completely different. Like when I asked it to make a song in the style of Madonna. Song like Ray of Light by Madonna is what I'm asking it.

13:40Ludovic Hunter-Tilney: so udia's really botched this one because it's created what sounds to me like a really bad copy of a kylie track it's got nothing to do with madonna's ray of light there it's even quoting spinning around you got me spinning round and round which i mean that has to be a little bit like, I don't want to get myself mired in all of the thickets of legal tangles that are taking place now, but a bit cheeky, really. It looked like it was time to talk to a real lawyer. I met up with Greg Orpryor, an entertainment lawyer at the firm Reed Smith. He's been in the industry for more than two decades and has been involved in some landmark disputes around music.

14:15I think about generative AI and what's happening right now as the next big legal frontier for the music industry.

14:24Ludovic Hunter-Tilney: In the US last year, the world's biggest record labels, Warner Records, Sony Music and Universal Music Group, launched a legal battle against Suno and Udeo, claiming copyright infringement on an almost unimaginable scale. So the music industry comes together, particularly on the recorded music side, and they say, right, okay, this is non. And they join together to sue two companies, Suno and Udeo, early stage startups, innovators disruptors, you might argue. And the music industry says, hey, you are not allowed, or you should not be allowed, to copy my music and store it and use it for the purposes of training your machine to create new music.

15:07Ludovic Hunter-Tilney: This is not, for what it's worth, the only case currently levelled against UDO and Suno. Earlier this year, the aptly named country musician Tony Justice, launched a lawsuit representing the interests of independent artists. And there's been a class action lawsuit against Suno specifically from the German Copyright Society, GEMA. The music industry is well-versed in fighting tech innovation. After the CD boom of the 1990s, the music business was riding high. Then suddenly, at the end of the decade, file-sharing services like Napster began proliferating. And then all of a sudden, wow, you can get your music anywhere for free from some unknown actor.

15:55And so the music industry embarked on a big campaign of litigation, a campaign for the public's attention and sympathy for this bad behaviour.

16:05Ludovic Hunter-Tilney: The record companies successfully sued file-sharing platforms like Napster and LimeWire. But it was like a game of whack-a-mole. Other platforms popped up to replace them. Eventually, the labels ended up doing deals with streaming companies like Spotify to put their catalogs online. Spotify is what changed the game, where they said to the music industry, well, your music is available for free everywhere now. What if I charge people a certain amount per month? That was the big sea change. And all of a sudden, you were able to get all the world's music for 10 bucks a month. That's a huge bargain.

16:45Ludovic Hunter-Tilney: That was a long time ago. Two decades on, the balance of power between the music industry and big tech is much more one-sided. Today's tech industry is bigger and more powerful than it's ever been. The music industry in relative terms is incredibly small. It tends to be very cohesive and powerful because it's newsworthy, captures the public's attention, everyone identifies with music. So it's got a lot of other strengths, but in relative terms, it's absolutely dwarfed by the tech industries. So it is a David and Goliath-style battle. So, can the music industry strike another deal? Suno and Udio are now reported to be in talks with the labels.

17:29The narrative at the moment is that the companies are negotiating. Right. I think there's a fear on both sides. You know, it's a win or lose case. Either the courts say it's permitted, in which case the record labels have lost, and that's very bad news for them. Or they say it isn't permitted and Suno and Udiya lose, and the investors lose a lot of their money. So because it's such a febrile and difficult case, a win or lose case, then the parties are inclined to negotiate. Which leads to settlements. Or a license. Right. Or a license, and most likely and a license. So if things go the way that I suspect they will go, The record labels will take some money in return for this training that they haven't permitted.

18:11And they'll license these services moving forward.

18:14Ludovic Hunter-Tilney: You can imagine a world in which record labels and the AI industry come to some kind of arrangement, where the AI companies get to keep training better and better models. And the labels, in theory at least, get a slice of that pie. They can make a bit of money off the AI boom. But where does this leave the artists? Even if a deal is reached, it still won't remove their big fear that they'll be competing with AI music generators for listeners.

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19:31and how they may affect your finances and portfolio. Listen at schwapp.com slash Washington Wise.

19:51Ludovic Hunter-Tilney: I want to go back to the Velvet Sundown, who you heard at the beginning of this episode. They're the AI-generated band posing as a groovy 70s soft rock outfit. Their songs accrued millions of streams and turned up in Spotify's Discover Weekly playlists, all without any indication that the band was AI. And The Velvet Sundown is far from the only example of AI music on streaming platforms. It's impossible to know the exact numbers. Deezer, one of the smaller platforms, says it's dealing with 20 ,000 AI uploads every day. A recent report by music industry analysts Luminate puts the figure for the whole streaming industry at nearly 100 ,000 AI songs daily.

20:36Ludovic Hunter-Tilney: And this is already starting to impact artists. I had WhatsApp messages. I had emails, lots of Instagram messages saying, I think something's gone wrong with your Spotify. there seems to be someone who sounds like Phil Collins singing on your page with a terrible, terrible artwork. Is this you? Hannah Stratton is a singer-songwriter based in Australia, and she's had a successful career on streaming platforms. Some of her songs have gone viral, like this 2016 track, The Thrill of Loneliness, which has been streamed 17.6 million times on Spotify.

21:27It's like folk music kind of set, like on a windy day, really.

21:33Ludovic Hunter-Tilney: Dretton makes most of her income from streaming, predominantly Spotify, and she spent most of this year working on a new album. But in August, something strange happened. She woke up to see that a song she had never heard of had landed on her profile, alongside accompanying artwork of an airbrushed guitar lying on a bed of poppies. All listed under her name. Where did you go, my friends of both? I don't yet... This is the song. It's called Where Do You Go? And I think you'll agree it sounds pretty different from Hannah's usual music. I don't want to know what it's done. I mean, I don't think it sounds anything like me.

22:16I think they've used Phil Collins. It sounds like him. It sounds like his voice. It's quite a generic sort of 70s sound.

22:24Ludovic Hunter-Tilney: It turns out that the song is AI generated and had been uploaded without her knowledge by someone who had managed to override her profile. It's not clear exactly why they did this, but there have been similar instances of streaming fraud reported with bad actors attempting to hijack artists' revenues. Concerned about both her reputation and her revenue stream, Stretton tried to get the song taken down, contacting both Spotify and the company who appeared to have made it. But it remained on her profile for a whole week. During that time, the income from those streams was going to someone else. And she was getting more messages from bemused fans.

23:07Did you hit your head is one that I got. Did you hit your head, this is terrible. Or just dot, dot, dot, what's going on? We waited three years for an album and this is what we're getting.

23:22Ludovic Hunter-Tilney: Eventually, Stretton was able to get the song removed. But she says this is happening all the time. This is such a widespread problem. This is actually not the first time this has happened to me. There's a reason why someone like me is targeted. I do have very good streaming numbers for someone who doesn't have any promo and I'm independent. So I don't have a label or a team behind me, you know, with lawyers coming out of my ears to be able to really protect myself. And I think it's just upsetting if it tarnishes your good name. You know, I've been working for 10 years to build this independent career.

24:05And it's very sad to have it so easily taken away.

24:10Ludovic Hunter-Tilney: There are lots of problems that arise as a result of AI not being labelled. And it isn't just limited to hijacking artists' profiles. AI-generated music might just appear in people's playlists without warning. And even where music is identified as AI, streaming platforms such as Spotify don't necessarily take it down. There are tens of thousands of generative AI tracks delivered to streaming services every day. I think that a lot of actors in the music business who are hoping to capitalize on the wave of generative AI content are really just hoping that people won't notice it. That's music journalist Liz Pelley.

24:51Ludovic Hunter-Tilney: She spent years looking into Spotify's business model and is the author of Mood Machine, The Rise of Spotify and the Costs of the Perfect Playlist. Pelley says that Spotify doesn't seem to do much to stop AI from appearing on its platform. or even being pushed to listeners. Take the example of the Velvet Sundown. One piece of the puzzle of how those tracks sort of like went viral on streaming had to do with the fact that they were appearing in Discover Weekly playlists on Spotify. So algorithmic personalized playlists. Spotify is the world's biggest streaming platform with almost 700 million users.

25:29Ludovic Hunter-Tilney: And it works by pushing algorithmic recommendations. It's not just a repository of the world's music. it tries to tailor music to your taste so that you can sit back and listen continuously, like listening to your favorite radio station. Its Discover Weekly playlists are a huge part of how the platform works. Listeners have streamed songs featured on these playlists more than 100 billion times. A lot of those algorithmic recommendations are based on listening patterns across the platform. And I think the Velvet Sundown song, it had been added to like a third party playlist called Vietnam War Songs or something like that, that had, you know, hundreds of thousands of followers.

26:13And clearly they had some sort of strategy for juicing these tracks in algorithmic recommendations. And then what happens is like if certain tracks that fit a user's taste profile are gaining lots of traction, it'll boost the chances that it might end up in one of their algorithmic recommendations.

26:32Ludovic Hunter-Tilney: Spotify, unlike some other streamers, does not flag when content is AI generated. And it doesn't take AI music down unless it violates its terms and conditions, like impersonating an existing artist. We asked Spotify about this, and they didn't get back to us. We also spoke to Deezer, a French streaming platform, who told us that tagging AI tracks and excluding them from playlists isn't impossible. They say they are so far the only platform that does this. But by comparison to Spotify, Deezer is really small, with about 9 million subscribers. And in the meantime, more and more AI music is appearing across streaming platforms generally.

27:17Ludovic Hunter-Tilney: And the burden is mostly on us, the listener, to figure out whether or not the song is made by a machine or by a human. Even now, something that I experience is this dynamic of people sharing a link with me and saying, is this AI? Is this a real artist? Do you know if this is made a genre of AI? And I just don't feel like people should have those questions. Like that almost is like right now feels more urgent to me is like making sure that people have the tools to know when they're being served a generative AI track. A big anxiety about AI music is that it will start seeping into daily life, slowly saturating the musical landscape.

27:55Ludovic Hunter-Tilney: Like the figurative frog being boiled, we won't notice until it's too late. At least if we're told what's AI and what's not, then we can decide for ourselves whether we want to listen to it. And that might be good for artists too. If we listeners have an informed choice, then maybe we'll decide we actually want real human-made music, no matter how accomplished the AI music becomes. But will we? I think the public will determine what they want. So if people decide that they really want music that was written by writers' camps rather than algorithms, then that is what people will listen to. Holly Herndon is the pioneering musician I spoke to in part one of this series.

28:38Ludovic Hunter-Tilney: She's been experimenting with generative AI for a decade. And she says, so much of popular music is already a production line, so why not automate it? Often on the biggest hits that we'll hear, people will go to a writer's camp and there will be 50 different writing credits on a single song. So in a way, it's already a kind of collective intelligence perfectly crafting the song to meet the conditions of the invisible algorithm that Spotify is setting. So there's already so much manipulation to the craft there that I see no issue in that being kind of fully automated. And I also just don't think that all musics have to follow the same logic.

29:18I think it's okay to have subcultures. You know, different music can have different functions in our world.

29:24Ludovic Hunter-Tilney: What function will AI music fulfill in the future? I began this series feeling skeptical about claims that AI could seriously threaten the music industry. I'm less sceptical now. While I remain doubtful about dystopian fantasies of the charts becoming flooded by AI songs, I am convinced that AI will increasingly play an everyday part in the making of music, either as aid or rival. But this whole process has also made me reconsider the role music plays in our lives. It is the art formed most closely and also mysteriously linked with our emotions. And the deeper I've delved into the world of AI, the more I found myself thinking about human-made music.

30:14Ludovic Hunter-Tilney: What it is and what we value in it.

30:21Ludovic Hunter-Tilney: I went back to Dan Tarbuck. You'll remember him from part one. He's the composer and musician whose studio I went to visit. His company makes high-quality production music. In response to the threat of AI, Tarbuck has decided to double down on the thing that he believes makes music so distinctive. It's humanness. You know, we make some really authentic things here where people can bounce ideas off each other, and we're really capturing that, and that's what we're really leaning into now. Human-made music and the most human possible way where everyone's improvising and just making things up on the spot.

30:57There's mistakes in it. You might not even notice them, but you'd notice if they weren't there. That's part of the charm. It's never going to be perfect, whereas AI, I think, maybe is trying to be.

31:07Ludovic Hunter-Tilney: So you really are taking a bet then that the desire for flesh and blood musicians creating things in a room such as this through moments of inspiration, which can't be predicted, is going to continue to be very important. I think it'd be foolish to think that it's not going to affect us and that it isn't affecting us. And I think it's going to affect every single industry. but we have to adapt and be able to offer something that we think is valuable. And hopefully other people will see the value in that. Music will always be a human thing at heart. You could even argue that AI music isn't really music because it might sound like it on the surface, but there's no meaning behind it.

31:41I just hope that people will always find the value in something which has been made by someone with feelings and with a story to tell, which at this point AI doesn't have.

31:54Ludovic Hunter-Tilney: Thank you for listening to Techtonic with me, Ludovic Hunter-Tilney. The producers are Lulu Smith and Josh Gabbard-Doyon. The senior producer is Edwin Lane. The executive producer is Flo Phillips. Sound design by Breen Turner and Samantha Giavinko. Original, not AI music, by Metaphor Music. Manuela Saragoza is the FT's acting co-head of audio. Our fact-checkers are Megan Hill and Miata Embriwa.

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