ABBA member and CISAC president Björn Ulvaeus took the stage at the United Nations’ AI for Good Global Summit in Geneva on Monday (July 13) to ask a simple question: “Good for whom?”
Kicking off the summit as its opening keynote speaker, Ulvaeus stressed to the crowd to remember the point of view of artists and creatives in the pursuit of AI development: “A technology is good when the human beings whose work made it possible are not erased by it, when they consent to it, when they share in what it creates,” he said. Ulvaeus continued that he hopes “one extra chair will always be reserved at that table for the creators whose work made these systems possible.”
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He added, “These tools are extraordinary, but they could not have been built without us.”
Consent was the focal point of Ulvaeus’ keynote. As he noted in his speech, the ABBA co-founder has never been shy about embracing emerging technology. Just a few years ago, the band used “motion capture and motion learning” to create the groundbreaking virtual ABBA Voyage show in London, which uses technology to de-age and simulate the performances of the four Swedish singers night after night.
“Some people sometimes ask me, ‘How can you lecture the world about AI and human creativity, and then sell tickets to watch a machine perform as you?'” Ulvaeus explained. “The answer is one word: consent. We chose it. We participated in it. We are paid for it. The technology serves the artist because the artists were at the table from the very beginning, and the audiences love it. So, I guess that’s AI for good.”
He continued, “I’m not going to stand here and tell you that machine-made music is cold or soulless, and that audiences will always hear the difference. I know that isn’t true. I am genuinely in awe of the tools that have been built, but awe is not the same as acceptance.”
Ulvaeus also stressed that because creatives’ work “lives inside these models” and is the “foundation on which these tools were built,” this should make creatives “partners, not protesters, not obstacles, not a problem to be managed by lawyers. Partners. And partners deserve a place at the table. Partners deserve a share of the harvest.”
He noted that he does not believe the answer “lies in tracing our work in the outputs…I think it misunderstands how these models work,” explaining that they “don’t sample recordings” but “learn relationships across billions of examples.”
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“What comes out isn’t a copy of any one song,” he added. “It’s a new synthesis built from everything the model has learned.”
“Tracing the output was always the wrong question. The right question is much simpler. It is about the training. Our works went in. We should be paid for what went in, not for every output that comes out the other end, but for the raw material that made the machine what it is,” Ulvaeus continued. He pointed to Spotify as a practical framework for payment, which started by licensing the catalog of works for the platform first, then routing “a percentage of the platform’s revenue…back collectively to rights holders.
“AI can work the same way,” he continued. “A share of AI subscription revenues could flow back to the creators whose work trained these systems. Managed collectively, just as collective licensing has worked for more than a century. The infrastructure already exists.”
Ulvaeus’ words add to mounting concerns from the creative community around AI training and consent. In April, reporting from Billboard revealed that multiple top talent attorneys had learned that labels and publishers could feasibly use common contract language in U.S. record deals related to blanket licensing and exploitation to opt in artists’ works to train their AI partners’ models without seeking individual artist approval. “Some of the labels have already taken the position that they technically don’t need special approvals to train,” Jason Boyarski, founding partner at Boyarski Fritz, told Billboard.
In June, the American Federation of Musicians (AFM) sued Universal Music Group (UMG) and Warner Music Group (WMG), alleging that its members are not sharing in the upside of the major labels’ licensing settlements with AI music firms Suno and Udio. According to the complaint, “the AFM brings this lawsuit because defendants, two of the largest music companies in the world, have licensed sound recordings on which AFM-represented musicians have worked, without compensation or credit, to two AI companies… At the same time, they have refused to provide information to the AFM about which recordings and whose work is being licensed.”
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Later that month, 31 music rights organizations, including Music Artists Coalition and Songwriters of North America, expressed concerns about the AI licensing deals being struck between music companies and AI companies and how they might be leaving artists behind. “Stop the misuse of [our] rights in AI deals,” a press release announcing the letter said, adding, “this is hypocrisy and an injustice which needs to stop now. Labels and publishers rightly argue that AI companies need permission to train on their music catalogue, but will not grant artists and songwriters the same rights.”
Notably, Ulvaeus did not complain in his keynote about how labels and publishers specifically are treating licensed training data. Even so, his address adds to the growing chorus of creatives asking for consensual AI training in 2026. (You can read his full address below.)
The UN’s AI for Good Global Summit also featured the voices of other music industry power players like John Legend, Universal Music Group chief digital officer Michael Nash, NVIDIA vp and general manager of media and entertainment Richard Kerris, Splice CEO Kakul Srivastava, Stability AI CEO Prem Akkaraju and Udio CEO Andrew Sanchez. The group spoke for a session titled The Sound of Intelligence: John Legend and the Leaders Shaping the AI Music Revolution. In it, Legend built on similar sentiments expressed by Ulvaeus, saying, “AI has penetrated into our business and a lot of us are using it in healthy ways…I want us to treasure the role that great art plays in our lives. Treasuring also means requiring policy which protects the creators, so it is a viable career for artists.”
Ulvaeus’ full keynote address:
Good morning,
Last month, I stood on a stage in Paris, marking 100 years of CISAC, the Global Confederation of authors and composers, and this month I stand on a stage here in Geneva, and I find that the journey from one city to the other has a story to tell, because Paris is where the rights of creators were born. In 1791, when France became the first country in the world to write into law that the work of an author belongs to an author. And Geneva is where those rights became universal. The treaty that says a song written in Stockholm is protected in Seoul, in Sao Paulo, and in New York. The Berne Convention has its guardian here at WIPO, just a few kilometers from this stage.
Paris made the promise, Geneva made it universal, and I’m here to ask this summit to do the same thing one more time, for the age of AI. The name of this summit is AI for Good. It’s an inspiring name. This week, the United Nations launched a new AI for Good Commission, bringing government scientists and technology companies together to help shape the future of AI. I hope one extra chair will always be reserved at that table for the creators whose work made these systems possible, because the title of this summit contains a question: Good for whom?
I want to suggest a simple test. A technology is good when the human beings whose work made it possible are not erased by it, when they consent to it, when they share in what it creates. By that test, AI for good already exists. I know because I’m standing inside an example of it every night in London. Some of you may have seen ABBA Voyage, four digital avatars, myself among them, 40 years younger. I can recommend that. Performing usually to a full house, six shows a week, made possible by motion capture and machine learning.
Some people sometimes ask me, “How can you lecture the world about AI and human creativity, and then sell tickets to watch a machine perform as you?” The answer is one word: consent. We chose it. We participated in it. We are paid for it. The technology serves the artist because the artists were at the table from the very beginning, and the audiences love it. So, I guess that’s AI for good. It isn’t a slogan; it is a contract.
But there’s another version, one without the contract. Somewhere in the world today, a generative model is producing music. It produces more songs in a day than every member of CISAC will write in a lifetime. It can do this for one reason only. It was trained on our work, on a century of human songs, including, I have no doubt, mine. Ingested without agreed permission, without payment, and without so much as a postcard.
I’m not going to stand here and tell you that machine-made music is cold or soulless, and that audience will always hear the difference. I know that isn’t true. I am genuinely in awe of the tools that have been built, but awe is not the same as acceptance. The tools are extraordinary, but they could not have been built without us — the artists, the songwriters, the musicians, the producers, every person who has written a melody, recorded a performance, found the words to something that perhaps had never been said before. Their work lives inside these models. It is the foundation on which these tools were built. It is the reason they sound like they sound, move the way they move, and feel the way they feel. That makes us partners, not protesters, not obstacles, not a problem to be managed by lawyers. Partners. And partners deserve a place at the table. Partners deserve a share of the harvest.
Now, what does that actually mean in practice? Because I’m not here only to make moral argument. I’m here to propose one. Some people argue that the answer lies in tracing our work in the outputs, and I understand that instinct. But I think it misunderstands how these models work.
As we all know, they don’t sample recordings; they learn relationships across billions of examples, how melodies move, how harmony resolves, how rhythm, timbre, and language combine. What comes out isn’t a copy of any one song. It is a new synthesis built from everything the model has learned.
Now, let me give you an example of how I work with AI. I’m writing a new musical at the moment, and I’m using it almost every day. I record myself singing and playing a song or a part of one, which I’ve written; I’m playing it on my guitar. I’ll upload it to the AI model, and I ask it to give me a cover because I want to hear the song roughly as it’s going to sound when I someday hopefully record it with a human artist, so I simply prompt, I ask it to give me pop ballad, female vocal, strings, and suddenly I have a full-blown demo. Weaknesses I couldn’t hear before suddenly become obvious. A bridge that doesn’t quite do the job, words that don’t sound right, a melody that needs another turn. Then I rewrite, and I do it again and again. I challenge anyone to trace that back. You can’t.
For me, tracing the output was always the wrong question. The right question is much simpler. It is about the training. Our works went in. We should be paid for what went in, not for every output that comes out the other end, but for the raw material that made the machine what it is.
We’ve solved problems like this before. When Spotify emerged, we didn’t try to measure the value of every individual listen before paying creators. We licensed the catalog. A percentage of the platform’s revenue flowed back collectively to rights holders. AI can work the same way. A share of AI subscription revenues could flow back to the creators whose work trained these systems. Managed collectively, just as collective licensing has worked for more than a century. The infrastructure already exists. The principle is already established. What is missing is the political will to require it for everyone, not just those powerful enough to sue.
And that is what I’m asking this room for today. This is not simply about protecting today’s artists. It is about making sure there are artists tomorrow. If human creators cannot earn a living, fewer people will devote years to mastering an instrument, finding their voice, or writing songs that matter, and if that happens, AI itself will eventually have less original, new human creativity from which to learn. Fairness is not just morally right. It is how we keep the well from running dry.
We are sitting right now at a fork in the road. The legal cases now moving through courts around the world will help determine whether licensing becomes the foundation of this new industry, or whether free extraction does. The decisions made over the next few years will shape the creative economy for decades and decades. I’m not pessimistic. I have lived through the cassette, CD, the MP3, Napster, streaming. Every time our industry found a way to embrace new technology while protecting the human creator. Every time people had to make difficult decisions. And every time the decisions that lasted were reasonable ones.
Human creativity is not just content; it is not just data. It is testimony, a life lived, a grief that became a lyric, a love that became a melody, a specific, unrepeatable experience of a human being in a particular time and place, transformed into something another human can feel. That is what trained these models, and the people whose life’s work became part of those models deserve to share in what they have made possible.
So I say to the companies building these extraordinary systems: you have built remarkable things. You could not have built them without us. That makes us partners. We deserve a place at the table. We deserve a share of the harvest.
Human creativity is not the enemy of artificial intelligence. It is the reason artificial intelligence exists. The future does not require us to choose between creators and technology. It requires us to decide whether creators remain partners in the future they help build.
Paris made the promise. Geneva made it universal.
The people in this room have the opportunity to renew that promise for the age of AI.
I believe we will.
Thank you.
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