artificial intelligence
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Free music streaming shouldn’t be so free, Rob Stringer, CEO of Sony Music Entertainment, suggested Wednesday during a presentation to Sony Corp. analysts and investors.
The value of paid subscription “remains incredible,” said Stringer in prepared remarks during parent company Sony’s Business Segment Meeting 2024. But recent price increases — by Spotify, Apple Music, Amazon Music, YouTube and, most recently, Pandora — have widened what Stringer called the “price gap” between free and paid streaming. Now, Sony wants streaming companies to get more from their free listeners.
“In mature markets, we hope that our partners close that gap by asking consumers using ad-supported services to additionally pay a modest fee,” said Stringer. “This would help develop this segment of the streaming business to be more than just a marketing funnel for paid subscription and still be a tremendous value for users. We have a shared interest in better monetization of free tiers. At Sony Music, we think everyone is willing to pay something for access to virtually the entire universe of music.”
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Free streaming provides an opportunity to attract paying subscribers but returns far less per listener than subscriptions. Even though Spotify has 62% more free listeners than subscribers, advertising accounted for just 10.7% of first-quarter revenue compared to 89.3% from subscriptions. Another round of price increases by Spotify this month in the U.K. and Australia portend additional price increases in the U.S. and other major markets. Further subscription price increases will widen the gap between premium and free streaming, and “even if advertising will become a better part of the story, it’s still a relatively small part of our overall revenue mix,” Spotify CEO Daniel Ek said during the April 23 earnings call.
Charging for ad-supported music would break from a long tradition of providing listeners with a free, on-demand streaming option. YouTube and Spotify are the two largest on-demand, ad-supported platforms that stream music. Amazon Music has a free tier with limited functionality. In the U.S., Pandora has about 39 million monthly active users for its ad-supported internet radio service that has less interactive capabilities than YouTube or Spotify. But paid, ad-supported streaming is common in the video world. Video on-demand services such as Hulu and Netflix offer low-price tiers with advertisements and charge higher prices to eliminate advertising altogether.
Sony Music also wants to extract more revenue from short-form video platforms such as TikTok that command huge audiences but provide relatively few royalties. “Premium-quality artistry drives the appeal of these services, with music being central to approximately 70% of videos created on them,” said Stringer. “These companies play a larger and larger role in music discovery and engagement amongst young listeners. More and more, these are primary consumption sources, and they need to be valued accordingly.”
Stringer, who does not comment during the parent company’s quarterly earnings calls, spoke and answered questions for 40 minutes about Sony Music artists, chart successes, growth opportunities and efforts in emerging markets. After highlighting Sony Music’s efforts in Latin America, India and China, he focused on the newest — and most vexing — technology on the music industry’s horizon. Artificial intelligence, he said, “represents a generational inflection point for music” and Sony Music will take “an active role” in creating a “sustainable business model” that respects the company’s rights.
But Stringer was clear that Sony Music is taking a hard line in the battle to shape AI in music. “We won’t tolerate the illicit training of AI models by reckless and unlicensed misuse of this art,” he warned. “We believe strongly that permission is the only way AI models can be trained with our content, and followed protocols of the EU AI act by sending over 700 letters to AI developers to opt our copyrights out of training.” Sony Music has also issued “over 20,000 takedowns of AI generated soundalikes over the past year,” he added, while working with legislators around the world “to shape policy and rights” on AI issues.
“With the right frameworks in place, innovation will thrive, technology, music will benefit and consumers will enjoy your experiences,” Stringer said. “We have prospered from disruptive market changes before so we are confident we can navigate this chapter successfully.”
When Sabrina Carpenter signed with the Universal Music Publishing Group (UMPG) in October 2023, she was coming off the critical and commercial success of her 2022 Island Records debut Emails I Can’t Send, a project that established her as a formidable pop hitmaker with a distinct voice and a captivating appeal. But since that album’s release, her career has launched into the stratosphere, with a string of singles — “Nonsense” off the original Emails; “Feather,” which was released on the deluxe of Emails in August 2023; and, most recently, April 2024’s “Espresso” — that have each reached higher on the charts than the last, building her into a mainstream dynamo with song-of-the-summer hitmaking potential.
It’s been “Espresso,” however, that has truly captured the zeitgeist. The song zoomed onto the Billboard Hot 100 with a No. 7 debut, eventually reaching No. 4, but has done even better globally, reaching No. 1 on the Billboard Global Excl. U.S. chart — where it spends its second week this week, establishing it as a bona fide international hit. And through the work of her label at Island and her publishing company UMPG, that’s marked the highest chart placement of Carpenter’s career — and help earned UMPG co-head of U.S. A&R and head of UMPG’s global creative group David Gray the title of Billboard’s Executive of the Week.
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Here, Gray discusses the work UMPG has done with Carpenter in the six months since bringing her into the pubco, what sets her apart as a songwriter and the company’s global outlook. “She has always had a vision for herself as an artist and songwriter,” Gray says. “It’s rewarding to see her succeed at a global level and get all of the credit she deserves.”
This week, Sabrina Carpenter’s “Espresso” spends its second week at No. 1 on the Billboard Global Excl. U.S. chart and its fifth week in the top 10 of the Hot 100. What key decision did you make to help make that happen?
Overall at UMPG, we work to support our songwriters’ ideas and decisions in any way we can, whether putting together strategic writing sessions or working to secure great synch opportunities globally.
Sabrina signed with UMPG last October. What were your first conversations like with her about her music and where she wanted to go?
Sabrina talked about how the Emails I Can’t Send album was a step up from where she was before and she was ready to take it up to the next level from there. She has always had a vision for herself as an artist and songwriter. It’s rewarding to see her succeed at a global level and get all of the credit she deserves.
What sets Sabrina apart from other pop stars as a songwriter, and how have you helped to emphasize that?
Sabrina has such a unique and brilliant songwriting voice, both lyrically and melodically. All the years of doing sessions, working hard, taking songwriting very seriously and perfecting her craft has made her not only the artist in the writing session… but she is also an A-list-level songwriter talent-wise.
For the past two years you’ve headed up UMPG’s global creative group. How has that changed how you work with songwriters, and in what ways does it help your global reach?
At UMPG, we have always recognized that there are amazing writing opportunities for songwriters outside of their own territories. The number and quality of these writing opportunities has accelerated in the last few years. The communication between territories that the Global Creative Group provides is essential to making sure our writers get the best of these opportunities.
How are you preparing to deal with AI in the publishing world?
It’s still nascent in the broader creative community, but we know AI offers opportunities and risks. We embrace AI, just as we have other technology innovations in the past, but only AI technology that is ethical and artist-centric — in other words, only if it supports songwriters and protects their rights.
Voice-Swap, an ethically-trained AI voice company, and BMAT Music Innovators, a company that indexes music usage and ownership data using machine learning, have partnered to launch a new technical certification for AI voice and music models. It is designed to verify that the audio content used to train voice models does not infringe on any […]
NASHVILLE — Ahead of the 2024 Music Biz conference, Music Business Association president Portia Sabin predicted that artificial intelligence would be the most hotly-discussed topic.
“AI is the big one that everyone’s talking about,” she told Billboard.
That premonition proved true during the current conference (held in Nashville May 13-16), as dozens of speakers across the spectrum of music, tech, legal and more discussed AI’s uncertain future in the space, and its current impact on the industry.
One such panel was “How AI and Tech Are Shaping the Business of Music” on Monday (May 13). Moderated by Elizabeth Brooks, managing partner at Better Angels Venture, the panelists—head of artist marketing and digital strategy at Friends At Work, Jeremy Gruber; senior vp of product and technology at MAX, Jeff Rosenfeld; MADKAT founder Maddy Sundquist; and singer-songwriter Stephen Day — discussed the emergence of AI in music, some of the concerns surrounding its potential impact on artist creativity, and how artists can maintain an authentic connection to their fans.
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As the sole artist on the panel, Day kicked off the AI portion of the discussion and countered that, despite the recent uptick in the use of generative AI in popular music — most recently with Drake on “Taylor Made Freestyle,” the diss track in which he uses AI to recreate Snoop Dogg and the late Tupac Shakur’s voices, which has since been taken down after the Shakur estate threatened to take legal action — he’s not concerned about generative AI’s emergence. “Overall, I’m not really scared about it because technology has always advanced,” he said. “The human with the heart and the soul is what makes it important.”
Rosenfeld agreed, adding that “technology continually upends the business of music,” pointing to social media as an example of something that changed digital marketing strategies for artists and labels. One group that could be at risk though, he said, are artists that people don’t have a direct connection with, like film/TV composers. “It’s the personal connection [that fans are after]. It is the person and their story behind the music that people relate to,” he said. “And that’s why it’s important to have a relationship with your fans.”
Rosenfeld isn’t the first exec to note that risk for artists who make instrumental music. In a 2023 Billboard story, Oleg Stavitsky, co-founder/CEO of AI-driven functional sound company Endel, pointed to “functional music” (that is, a type of audio “not designed for conscious listening”) as an area of focus for their firm. While the company isn’t in the business of making hits, it’s focused on making music that promotes sleep or relaxation (lo-fi music, ambient electronics, etc.) with help from AI tools. Another company, LifeScore, which uses AI to “create unique, real-time soundtracks for every journey,” recruited James Blake to create an AI ambient soundtrack titled Wind Down.
While that’s a threat to that corner of the market, the panelists were largely optimistic, albeit cautiously, about AI’s future impact.
“AI is not our overlord today,” Brooks said. Added Rosenfeld, “It’s enabled small businesses to expand… It’s destabilizing, but at the same time empowering.”
At a separate panel on Wednesday (May 15) titled “How AI Is Changing the Way We Market, Promote & Sell Music,” the speakers also had a positive outlook on AI in the industry. Moderated by co-founder and CEO of 24/7 Artists, Yudu Gray, Jr., the panel featured chief product officer of SymphonyOS, Chuka Chase; head of communications & creator insights at BandLab Technologies, Dani Deahl; and Visionary Rising founder LaTecia Johnson.
Chase said that his company has used AI to streamline the process of finding and growing an audience for artists. One way has been to use AI to build a setlist for an emerging artist’s first tour. Chase explained that his team was able to harness AI by sending out emails and putting out polls in order to gain insight into what that artist should perform in each city. “We went into the CRM and blasted emails to put out polls, a microsite asking what songs [that artist] should perform. After a couple hours we got around 20,000 responses,” he said, adding that he could then plug that data into GPT and make a setlist based on the most-requested songs.
For Deahl, who’s also a DJ and music producer, AI has helped with delegating various administrative tasks. “One of the biggest hurdles that artists now have to overcome is they don’t have to just worry about the creative components… They have to worry about all these different facets of their business.” She argues that any tool that gives her the ability to “cut out the BS” and give her the time to focus on the creative process is the best way to help her amplify her work. “Not every artist is built to be an entrepreneur,” she said.
Several companies are beginning to launch similar “AI assistants” for these kinds of admin roles. Last month, for example, Venice Music launched a new tool called Co-Manager “to educate artists on the business and marketing of music, so artists can spend more time focused on their creative vision,” Suzy Ryoo, co-founder and president of the company, said in a statement at the time. The idea is to, as Deahl said, give artists more time to be artists.
To that end, as AI tools become more prominent, the humans on an artist’s team are now more crucial than ever. While AI tools perhaps shrink the size of an artist’s team due to their functionality, Deahl doesn’t envision a world in which human roles are fully replaced. “I don’t worry about replacement when it comes to the people I engage with,” she said. “It would be a really lonely road for me as an artist if the only things that I relied on were AI chatbots or tools that tell me what my strategy should be. I need human feedback.”
Sony Music warned tech companies not to mine its recordings, compositions, lyrics and more “for any purposes, including in relation to training, developing, or commercializing any [artificial intelligence] system,” in a declaration published on the company’s website on Thursday (May 16).
In addition, according to a letter obtained by Billboard, Sony Music is in the process of reaching out to hundreds of companies developing generative AI tech, as well as streaming services, to drive home this message directly.
The pointed letter notes that “unauthorized use of SMG Content in the training, development or commercialization of AI systems deprives SMG Companies and SMG Talent of control over and appropriate compensation for the uses of SMG Content, conflicts with the normal exploitation of those works, unreasonably prejudices our legitimate interests, and infringes our intellectual property and other rights.”
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GenAI models require “training” — “a computational process of deconstructing existing works for the purpose of modeling mathematically how [they] work,” as Google explained last year in comments to the U.S. Copyright Office in October. “By taking existing works apart, the algorithm develops a capacity to infer how new ones should be put together.” Through inference, these models eventually can generate credible-sounding hip-hop beats, for example.
Whether a company needs permission before undertaking the training process on copyrighted works is already the subject of a fierce debate, leading to lawsuits in several industries. In October, Universal Music Group (UMG) was among the music companies that sued AI startup Anthropic, alleging that “in the process of building and operating AI models, [the company] unlawfully copies and disseminates vast amounts of copyrighted works.”
Although these cases will likely set precedent for AI training practices in the U.S., the courts typically move at a glacial pace. In the meantime, some technology companies seem set on training their genAI tools on large troves of recordings without permission.
“Based on recent Copyright Office filings it is clear that the technology industry and speculative financial investors would like governments to believe in a very distorted view of copyright,” Dennis Kooker, Sony Music’s president of global digital business, said during the Artificial Intelligence Insight Forum in Washington, D.C. in November. “One in which music is considered fair use for training purposes and in which certain companies are permitted to appropriate the entire value produced by the creative sector without permission, and to build huge businesses based on it without paying anything to the creators concerned.”
While Kooker was adamant during his testimony that training for genAI music tools “cannot be without consent, credit and compensation to the artists and rightsholders,” he also pointed out that Sony has “roughly 200 active conversations taking place with start-ups and established players about building new products and developing new tools.”
“These discussions range from tools for creative or marketing assistance, to tools that potentially give us the ability to better protect artist content or find it when used in an unauthorized fashion, to brand new products that have never been launched before,” he continued.
Sony’s letter to genAI companies this week ended on a similar note: “We invite you to engage with us and the music industry stakeholders we represent to explore how your AI Act copyright policy may be developed in a manner that ensures our and SMG Talent’s rights are respected.”
For the last two years, I’ve poured my angst, joy, wonder and grief into a musical project called Current Dissonance.
I read the news voraciously, and every few days, a story resonates with particular thunder. I sit with that story in mind, as inspiration and intention, and then record a piece of solo piano music, composed on the spot, in reaction. Most often, Current Dissonance subscribers receive the new track within minutes of its completion.
I love engaging with this project. It’s become a cathartic practice and wordless diary, connective tissue when so much around us seems to be fracturing, something full of guts and blood and soul that feels deeply personal and unapologetically human.
Given all that, I find it both thrilling and jarring that AI music creation has advanced to a point where well-crafted algorithms could largely take my place as the brain, heart and fingers behind this project.
At its core, the fusion of AI and music creation isn’t new, and its evolution from tweaky curiosity to full-on cultural juggernaut has been fascinating to watch. My first exposure came via Digital Audio Workstations (DAWs) — the complex software suites used to produce nearly all new music. Years ago, I experimented with an early AI feature that allowed virtual drummers to bang out rudimentary grooves tailored to my songs-in-progress; another utility let me stretch and distort audio samples in subtle or grotesque ways. Later, I wrote coverage of a startup that used machine learning to auto-generate soundtracks for video.
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Some of those legacy AI utilities felt promising but imperfect, others inelegant to the point of unusability. But they all showed the potential of what was to come. And it’s not hard to see that what was coming has now arrived — with the force of a freight train.
Welcome To The New A(I)ge
Examples of AI’s growth spurt permeate the music world. For cringe-worthy fun, check out There I Ruined It, where AI Simon & Garfunkel sing lyrics from “Baby Got Back” and “My Humps” to the melody of “Sound of Silence.” Then visit Suno, where single-sentence prompts yield remarkably realistic songs — fully-produced, with customized lyrics — in electronica, folk, metal and beyond. Open up Logic Pro and hear just how big and vivid its AI mastering utility can make a track sound in seconds. These developments are just the overture, and there’s no technical reason why a vast array of musical projects — including my own — couldn’t be AI-ified in the movements to come.
For example, I’ve created 154 short piano pieces for Current Dissonance, as of the writing of this article. Hours more of my piano work are publicly accessible. An AI model could be trained on those recordings to look for patterns in the notes I play, the chord voicings I choose, the ways I modulate volume and manipulate rhythms — all the subtle choices that make me sound like me, as opposed to anyone else sitting at a piano.
The algorithm would also need to learn the relationship between each Current Dissonance movement and the news article it reinterprets, building a map of correlations between facets of the written story and recorded music. Do Locrian-mode motifs in 7/8 permeate my playing when I’m reflecting on South Asian politics — and are C#s twice as likely to appear when I reimagine headlines that are less than four words long? I have no idea, but a well-trained AI model would parse those potential patterns and more.
In the end, my hypothetical AI Current Dissonance would function like Suno does for popular music formats. To hear a Michael Gallant-style piano reaction to anything, type in your prompt and see what erupts.
While this may sound like a daydream, the key technical bedrock exists right now, or will exist soon. Following a similar development pathway, I doubt it’ll be long before we can also hear how Tchaikovsky might have reacted symphonically to war in Ukraine, or how McCoy Tyner could have soloed over “Vampire,” “Believer,” or any other tune written after his death. Elvis Presley reimagining Elvis Costello, Billie Holiday reinterpreting Billie Eilish, John Philip Sousa composing marches to honor nations that didn’t exist when he did — the possibilities are stunning.
But where does all of this innovation leave today’s music professionals?
Old Theme, New Variations
Recent conversations with fellow music-makers have yielded gallows humor, dark jokes about obsolescence at the hands of the robots — but also a sense of resilience, the feeling that we’ve heard this tune before.
Take for example the advancement of synthesizer technology, which has certainly constricted market demand for musicians who make their living playing in recording sessions. And the ubiquitousness of affordable, powerful DAWs like Pro Tools, Ableton Live and GarageBand has snuffed out a generation of commercial studios and their engineers’ careers. Those losses are real and devastating, but they’re only part of the story.
Inventing, programming and performing with synthesizers has become a thriving musical specialty of its own, creating new professional opportunities amidst ashes of the old. The same can be said for the brilliant minds who make every new bit of music software even more amazing. And democratized music production due to GarageBand and its ilk has made possible the global ascent of DIY artists who could never have afforded to work in traditional studios.
As the duality of loss and regrowth takes hold in the AI era, everyone involved in music must amplify the latter, while keeping the former as muted as possible. There are key steps that communities and countries alike can take to ensure that AI music technology boosts existing creators and inspires new ones — that it enhances human creativity more than it cuts us down.
Shedding for the Future
The biggest error music-makers can commit is pretending that nothing will change. When it comes to AI, willful ignorance will lead to forced irrelevance. Let’s avoid that future.
Instead, I encourage all music-makers to learn as much about AI music technology as possible. These tools are not secret weapons, siloed away for the rich and privileged; with an internet connection and a few hours, any music-maker can gain at least a high-level look at what’s going on. It’s incumbent on all of us to learn the landscape, learn the tools and see how they can make our human music-making better.
Music-makers must also double down on human connections. For artists with followings large or small, this means rededicating ourselves to building meaningful relationships with audiences, strengthening the human connection that AI can only approximate. Taking time to greet listeners at each performance, making space to bond with superfans — just as in-person concerts will grow in meaning as fiction and reality become increasingly indistinguishable in the digital world, so will the importance of face-to-face conversations, handshakes and high-fives, hugs between artists and those who see beauty in their music.
For music-makers who spend their time in studio settings, reinforcing connections with clients and collaborators will also be key. While I currently rely on AI-fueled music tools in some contexts, I cherish every opportunity to team up with fellow humans, because I’m blessed to work with great people who elevate and inspire me. That’s another vital connection that AI cannot now — or hopefully ever — replace.
It Takes a Movement
Music-makers, those who support them in commerce and industry, and those who weave music into their lives as listeners — all of us must help build a movement that cherishes human creativity lifted through technology.
There’s already hard evidence that protecting artists’ digital integrity is an all-too-rare consensus issue within American politics; check out Tennessee’s bipartisan ELVIS Act for more. Music-makers in any community can push their local and national leaders to ride Tennessee’s momentum and reproduce its successes against AI abuse. As a voting member of the Recording Academy, I’m proud of the organization’s pro-human activism efforts when it comes to federal copyright law and other vital issues. Every music-related entity should make noise in favor of similar protections.
Granted, even the smartest laws will only go so far. AI music technology is so accessible that trolls and bad actors will likely be able to manipulate musicians’ voices, privately and anonymously, without suffering real consequences — a dynamic unlikely to change anytime soon. But the more our culture brands such exploitative recordings as tasteless and taboo, the better. We cultivate respect for human creators when we marginalize the consumption of non-consensual, AI-smelted musical plastic.
Consent is one key; control is another. While industry executives, music-makers of all shapes and flavors, influencers and lawmakers must collectively insist that musicians remain masters of their own voices, I recommend we go further by empowering artists themselves to take the lead.
It would be brilliant, and fair, for Madonna or Janelle Monáe, Juanes or Kendrick Lamar, to release interactive AI albums that they, the artists, control. Such properties could allow fans to create custom AI tracks from raw material exclusively recorded for that purpose. Under no circumstances should AI assets be leveraged for any use without the explicit permission — and compensation — of the humans responsible for the music on which those algorithms were trained.
…And I Feel Fine
In the face of AI’s explosion, we must remember to stay curious, hungry and optimistic. Investors, inventors and tech companies must look beyond novelty song creation as the technology’s highest musical goal; I can’t imagine how far AI will go when applied to creating new instruments, for example. Much of the music I make is improvisational, formed in my brain milliseconds before it’s realized by my fingers. How amazing would it be to jam with live band members — as well as an AI algorithm trained to create instant orchestrations, in real time as I play, using a never-before-heard chimera of Les Paul overdrive, volcanic glass vibraphone and a grizzly bear roaring?
AI presents massive challenges to human creators of any sort, but if we proceed with thoughtfulness and respect, new innovations will lift music-making communities everywhere. I for one will be thrilled to learn who the first Beethoven, Beyoncé and Robert Johnson of the AI era will be, and to hear the masterpieces they create.
Michael Gallant is a musician, composer, producer, and writer living in New York City.
A bipartisan group of four senators led by Majority Leader Chuck Schumer is recommending that Congress spend at least $32 billion over the next three years to develop artificial intelligence and place safeguards around it, writing in a new report released Wednesday that the U.S. needs to “harness the opportunities and address the risks” of the quickly developing technology.
The group of two Democrats and two Republicans said in an interview Tuesday that while they sometimes disagreed on the best paths forward, it was imperative to find consensus with the technology taking off and other countries like China investing heavily in its development. They settled on a raft of broad policy recommendations that were included in their 33-page report.
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While any legislation related to AI will be difficult to pass, especially in an election year and in a divided Congress, the senators said that regulation and incentives for innovation are urgently needed.
“It’s complicated, it’s difficult, but we can’t afford to put our head in the sand,” said Schumer, D-N.Y., who convened the group last year after AI chatbot ChatGPT entered the marketplace and showed that it could in many ways mimic human behavior.
The group recommends in the report that Congress draft “emergency” spending legislation to boost U.S. investments in artificial intelligence, including new research and development and new testing standards to try and understand the potential harms of the technology. The group also recommended new requirements for transparency as artificial intelligence products are rolled out and that studies be conducted into the potential impact of AI on jobs and the U.S. workforce.
Republican Sen. Mike Rounds, a member of the group, said the money would be well spent not only to compete with other countries who are racing into the AI space but also to improve Americans’ quality of life — supporting technology that could help cure some cancers or chronic illnesses, he said, or improvements in weapons systems could help the country avoid a war.
“This is a time in which the dollars we put into this particular investment will pay dividends for the taxpayers of this country long term,” he said.
The group came together a year ago after Schumer made the issue a priority — an unusual posture for a majority leader — and brought in Democratic Sen. Martin Heinrich of New Mexico, Republican Sen. Todd Young of Indiana and Rounds of South Dakota.
As the four senators began meeting with tech executives and experts, Schumer said in a speech over the summer that the rapid growth of artificial intelligence tools was a “moment of revolution” and that the government must act quickly to regulate companies that are developing it.
Young said the development of ChatGPT, along with other similar models, made them realize that “we’re going to have to figure out collectively as an institution” how to deal with the technology.
“In the same breath that people marveled at the possibilities of just that one generative AI platform, they began to hypothesize about future risks that might be associated with future developments of artificial intelligence,” Young said.
While passing legislation will be tough, the group’s recommendations lay out the first comprehensive road map on an issue that is complex and has little precedent for consideration in Congress. The group spent almost a year compiling the list of policy suggestions after talking privately and publicly to a range of technology companies and other stakeholders, including in eight forums to which the entire Senate was invited.
The first forum in September included Elon Musk, CEO of Tesla and owner of X, Meta’s Mark Zuckerberg, former Microsoft CEO Bill Gates and Google CEO Sundar Pichai.
Schumer said after the private meeting that he had asked everyone in the room — including almost two dozen tech executives, advocates and skeptics — whether government should have a role in the oversight of artificial intelligence, and “every single person raised their hand.”
The four senators are pitching their recommendations to Senate committees, which are then tasked with reviewing them and trying to figure out what is possible. The Senate Rules Committee is already moving forward with legislation, voting on Wednesday on three bills that would ban deceptive AI content used to influence federal elections, require AI disclaimers on political ads and create voluntary guidelines for state election offices that oversee candidates.
Schumer, who controls the Senate’s schedule, said those election bills were among the chamber’s “highest priorities” this year. He also said he planned to sit down with House Speaker Mike Johnson, who has expressed interest in looking at AI policy but has not said how he would do that.
Some experts warn that the U.S. is behind many other countries on the issue, including the EU which took the lead in March when they gave final approval to a sweeping new law governing artificial intelligence in the 27-nation bloc. Europe’s AI Act sets tighter rules for the AI products and services deemed to pose the highest risks, such as in medicine, critical infrastructure or policing. But it also includes provisions regulating a new class of generative AI systems like ChatGPT that have rapidly advanced in recent years.
“It’s time for Congress to act,” said Alexandra Reeve Givens, CEO of the Center for Democracy & Technology. “It’s not enough to focus on investment and innovation. We need guardrails to ensure the responsible development of AI.”
The senators emphasized balance between those two issues, and also the urgency of action.
“We have the lead at this moment in time on this issue, and it will define the relationship between the United States and our allies and other competing powers in the world for a long time to come,” Heinrich said.
When Drake dismissively told Metro Boomin to go and “make some drums” in one of his recent diss tracks during his beef with Kendrick Lamar, the superproducer went off and did just that — and the result marked a turning point for the use of AI in music production.
The beat, titled “BBL Drizzy,” pairs a vintage-sounding soul vocalist over some 808 drums. The producer released it to SoundCloud on May 5, encouraging his fans to record their own bars over it for the chance to win a free beat, and it swiftly went viral.
But soon after, it was revealed that the singer from the “BBL Drizzy” beat didn’t exist — the voice was AI-generated, as was the song itself. The vocals, melody and instrumental of the sample were generated by Udio, an AI music startup founded by former Google Deep Mind engineers. Though Metro was not aware of the source of the track when he used it, his tongue-in-cheek diss became the first notable use case of AI-generated sampling, proving the potential for AI to impact music production. (A representative for Metro Boomin did not respond to Billboard’s request for comment).
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As with all AI tracks, however, a human being prompted it. King Willonius, a comedian, musician and content creator, had put together the Udio-generated song on April 14, pulling inspiration from a recent Rick Ross tweet — in which the rapper joked that Drake looks like he got a Brazilian Butt Lift — to write the lyrics. “I think it’s a misconception that people think AI wrote ‘BBL Drizzy,’” Willonius told Billboard in an interview about the track. “There’s no way AI could write lyrics like ‘I’m thicker than a Snicker and I got the best BBL in history,’” he adds, laughing.
There are a lot of issues — legal, philosophical, cultural and technical — that are still to be sorted out before this kind of sampling hits the mainstream, but it’s not hard to imagine a future where producers turn to AI to create vintage-sounding samples to chop up and use in beats given that sample clearances are notoriously complicated and can drag on for months or years, even for big name producers like Metro Boomin.
“If people on the other side [of sample clearance negotiations] know they’re probably going to make money on the new song, like with a Metro Boomin-level artist, they will make it a priority to clear a sample quickly, but that’s not how it is for everyone,” says Todd Rubenstein, a music attorney and founder of Todd Rubenstein Law. Grammy-winning writer/producer Oak Felder says clearing a sample for even a high-profile track is still a challenge for him. “I’ll be honest, I’m dealing with a tough clearance right now, and I’ve dealt with it before,” he says. “I had trouble clearing an Annie Lennox sample for a Nicki Minaj record once… It’s hard.”
Many smaller producers are not able to sample established songs because they know that it could get them into legal trouble. Others go ahead without permission, causing massive legal headaches, like when bedroom producer Young Kio sampled an undisclosed Nine Inch Nails song in an instrumental he licensed out on BeatStars. The beat was used by then-unknown Lil Nas X and resulted in the Billboard Hot 100 No. 1 “Old Town Road.” When the sample was discovered, Nas was forced to give up a large portion of his publishing and master royalties to the band.
Udio’s co-founder, David Ding, tells Billboard that he believes AI samples “could simplify a lot of the rights management” issues inherent to sampling and explains that Udio’s model is particularly adept at making realistic songs in the vein of “Motown ‘70s soul,” perhaps the most common style of music sampled in hip-hop today, as well as classical, electronic and more. “It’s a wide-ranging model,” Ding says.
Willonius believes AI samples also offer a solution for musicians in today’s relentless online news cycle. While he has made plenty of songs from scratch before, Willonius says AI offered him the chance to respond in real-time to the breakneck pace of the feud between Drake and Kendrick. “I never could’ve done that without AI tools,” he says. Evan Bogart, a Grammy-winning songwriter and founder of Seeker Music, likens it to a form of digital crate digging. “I think it’s super cool to use AI in this way,” he says. “It’s good for when you dig and can’t find the right fit. Now, you can also try to just generate new ideas that sound like old soul samples.”
There’s a significant financial impact incurred from traditional sampling that could also be avoided with AI. To use the melody of “My Favorite Things” in her hit song “7 Rings,” for example, Ariana Grande famously had to cede 90% of her publishing income for the song to “My Favorite Things” writers Rodgers and Hammerstein — and that was just an interpolation rather than a full sample, which entails both the use of compositional elements, like melody, and a portion of the sound recording.
“It certainly could help you having to avoid paying other people and avoid the hassle,” says Rubenstein, who has often dealt with the complications of clearing songs that use samples and beats from marketplaces like BeatStars. But he adds that any user of these AI models must use caution, saying it won’t always make clearances easier: “You really need to know what the terms of service are whenever you use an AI model, and you should know how they train their AI.”
Often, music-making AI models train on copyrighted material without the consent or compensation of its rights holders, a practice that is largely condemned by the music business — even those who are excited about the future of AI tools. Though these AI companies argue this is “fair use,” the legality of this practice is still being determined in the United States. The New York Times has launched a lawsuit against OpenAI for training on its copyrighted archives without consent, credit or compensation, and UMG, Concord, ABKCO and other music publishers have also filed a lawsuit against Anthropic for using their lyrics to train the company’s large language model. Rep. Adam Schiff (D-CA) has also introduced a new bill called the Generative AI Copyright Disclosure Act to require transparency on this matter.
Udio’s terms of service puts the risk of sharing its AI songs on users, saying that users “shall defend, indemnify, and hold the company entities harmless from and against any and all claims, costs, damages, losses, liabilities and expenses” that come from using whatever works are generated on the platform. In an interview with Billboard, Udio co-founder Ding was unable to answer what works were specifically used in its training data. “We can’t reveal the exact source of our training data. We train our model on publicly available data that we obtained from the internet. It’s basically, like, we train the model on good music just like how human musicians would listen to music,” says Ding. When pressed about copyrights in particular, he replies, “We can’t really comment on that.”
“I think if it’s done right, AI could make things so much easier in this area. It’s extremely fun and exciting but only with the proper license,” says Diaa El All, CEO/founder of Soundful, another AI music company that generates instrumentals specifically. His company is certified by Fairly Trained, a non-profit that ensures certified companies do not use copyrighted materials in training data without consent. El All says that creating novel forms of AI sampling “is a huge focus” for his company, adding that Soundful is working with an artist right now to develop a fine-tuned model to create AI samples based on pre-existing works.
“I can’t tell you who it is, but it’s a big rapper,” he says. “His favorite producer passed away. The rapper wants to leverage a specific album from that producer to sample. So we got a clearance from the producer’s team to now build a private generative AI model for the rapper to use to come up with beats that are inspired by that producer’s specific album.”
While this will certainly have an impact on the way producers work in the future, Felder and Bogart say that AI sampling will never totally replace the original practice. “People love nostalgia; that’s what a sample can bring,” says Felder. With the success of sample-driven pop songs at the top of the Hot 100 and the number of movie sequels hitting box office highs, it’s clear that there is an appetite for familiarity, and AI originals cannot feed that same craving.
“BBL Drizzy” might’ve been made as a joke, but Felder believes the beat has serious consequences. “I think this is very important,” he says. “This is one of the first successful uses [AI sampling] on a commercial level, but in a year’s time, there’s going to be 1,000 of these. Well, I bet there’s already a thousand of these now.”
This story is included in Billboard‘s new music technology newsletter, Machine Learnings. To subscribe to this and other Billboard newsletters, click here.
It has been more than a decade since Randy Travis has recorded new music. But on Friday (May 3) the country legend released the gentle “Where That Came From,” an emotional ballad featuring his signature warm baritone and lovestruck lyrics.
In an interview with CBS News Sunday Morning‘s Lee Cowan slated to air this weekend Travis’ longtime producer describes how the singer’s team constructed the track using artificial intelligence in the wake of the near-fatal 2013 stroke that took away the Grammy-winning country star’s voice.
“It’s Randy Travis. Randy’s on the other side of the microphone … It’s still his vocal,” says Cris Lacey, co-chair/president of Warner Music Nashville in the interview. “There’s no reason he shouldn’t be able to make music … And to deprive him of that, if he still wants to do that, that’s unconscionable to me.”
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While Lacey acknowledges the “chatter about all the negative sides of AI,” he says that when the Travis team began thinking about recording “Where That Came From” using AI they wondered what that would look like for them. “And the first thing that came to mind… was we would give Randy Travis his voice back,” Lacey says.
According to the piece, when Travis suffered the stroke doctors gave him a 2% chance of surviving after discovering that in addition to paralysis the brain attack caused damage to the area of his brain controlling speech and language that had left it nearly beyond repair.
Cowan also spoke with Travis, 64, and wife Mary for the piece that takes viewers behind-the-scenes for a look at how longtime producer Kyle Lehning pieced together the song with the singer’s blessing using old audio tracks of his voice as a launching pad. With another singer pitching in, a custom AI program overlaid Travis’ voice on the new recording, with Lehning using the country legend’s input to “painstakingly” mold the AI-generated vocals into a song that felt authentically Travis.
“It’s not about how it sounds. It’s about how it feels,” Lehning says. “Him being here and him being able to be, you know, a vital part of the decision-making process makes all the difference to me.” If he’s being honest, though, Lehning says when he first realized that the AI experiment was working it, “freaked me out… when I played it back it was like, ‘oh my!’ And I immediately thought, ‘this might work.’”
The more he listened and dug into the nuance, Lehning says the song clearly needed more “massaging,” which required him to approach it “syllable-by-syllable.”
Cowan also observed the moment when Travis’ fellow country music friends and family heard the song for the first time, with stepdaughter Cavanaugh Mauch commenting, “It’s so weird to try and explain everything that goes through your head when you’re listening to it.”
In the wake of the stroke, Travis’ manager Tony Conway cooked up the idea for The Music of Randy Travis tour, which features the singer’s eight-piece band fronted by James Dupré, who played Travis’ son in the 2015 movie The Price. The latest iteration of that show, the More Life tour, is currently on the road, with the next date slated for May 23 at The Paramount in Abilene, Texas.
Travis — who was inducted into the Country Music Hall of Fame in 2016 — has also released a trio of albums post-stroke, including two volumes of covers, Influence Vol. 1: The Man I Am and Influence Vol. 2: The Man I Am, as well as 2020’s Precious Memories (Worship & Faith), a collection of worship songs recorded in Feb. 2003 at the Calvary Assembly of God in Orlando.
The CBS News piece will run on Sunday (May 5) at 9 a.m. ET on CBS and Paramount+. Listen to “Where That Came From” and watch a preview of the CBS segment below.
“It freaked me out.” In 2013 country music star @randytravis suffered a stroke that robbed him of his singing voice. Travis’ longtime producer, Kyle Lehning, gives Lee Cowan an exclusive inside look at how cutting-edge AI enabled Travis to once again raise his voice in song. pic.twitter.com/vxzXQ5k2OK— CBS Sunday Morning 🌞 (@CBSSunday) May 3, 2024
Drake’s track with an AI 2Pac verse didn’t last long. A day after the Tupac Shakur estate threatened to sue Drake for using an AI imitation of the later rapper’s voice on “Taylor Made Freestyle,” he took down the recording. In using 2Pac’s voice, though, Drake opened yet another important debate about generative AI that reveals just how risky the business is — and how rightsholders may have more power to shape it than they realize.
So let’s get legal! In the cease-and-desist letter he sent on behalf of the Shakur estate, lawyer Howard King referenced both Shakur’s personality rights, which encompasses publicity rights, or what some states refer to as likeness rights, plus the copyrights to the rapper’s recordings and songs. Most coverage of this focused on the former issue, since personality rights are relatively straightforward — Shakur’s estate controls the rights to the rapper’s distinctive style. The second gets complicated, since the recording copyrights — and potentially the song copyrights — have less to do with Drake’s use of 2Pac-style vocals than how he was able to create them in the first place.
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To create such a convincing imitation of 2Pac, an AI model would almost certainly have to ingest — and, in the course of doing so, copy — a significant number of Shakur’s recordings. So King, in his letter, demanded from Drake “a detailed explanation for how the sound-alike was created and the persons or company that created it, including all recordings and other data ‘scraped’ or used.” Any answer Drake gave would have taken the issue into legal terra incognita — an AI’s ingestion of recordings and songs would implicate copyright, although it’s not clear if this could be done without a license under fair use. The stakes would be high, though. As opposed to a California right of publicity violation, which would be relatively easy to prove and incur limited damages, copyright infringement is federal and comes with statutory damages of up to $150,000 per work infringed. That means a company that ingests 20 works to create one would be liable a maximum of $3 million.
For the last year, music creators and rightsholders have been talking about generative AI as something that’s coming — the deals they’ll negotiate, the terms they’ll set, the business they’ll do — once they negotiate the right deals. But technology companies tend to beg forgiveness rather than ask permission, and it seems some of them have already ingested a considerable amount of music for AI without a license. Think about it: None of the major labels have announced deals for AI companies to ingest their catalogs of recordings, but enough recordings have been ingested to make AI vocal imitations of Drake, 2Pac, Snoop — even Frank Sinatra doing Lil Jon’s “Skeet skeet.” That means that a company or companies could be in big trouble. Or that they have a first-mover advantage over their rivals. Or both.
Part of the reason technology companies forge ahead is that deals that involve new technology get complicated. In this case, how do you value a license you’re not sure you need? If you think that companies need a license to ingest music for the purposes of allowing users to make AI vocal imitations — as seems likely — the price for that license is going to be relatively high, with complicated terms, because rightsholders would presumably want to be compensated on an ongoing basis. (It’s insanely difficult to create a fair one-time license to ingest a catalog of music: first, since copyright law controls copying, the licensor would forfeit any control not specified in the contract; second, it would be hard for a potential buyer to raise the kind of money a seller might want, so the economics of ongoing payments make more sense.) If you think that ingestion would fall under fair use — which is very possible in some edge cases but much less so generally — why would you pay a high fee, much less constrain yourself with complicated terms?
The legal cases that will tip the scales in one direction or the other will proceed at the speed of litigation, which moves slower than culture, much less technology. The first big case will be against Anthropic, which Universal Music, Concord, ABKCO and other music publishers sued in October for training an AI on lyrics to compositions they control. (Universal’s agreement with YouTube on AI principles might make a ruling that this is fair use somewhat less likely, since it shows that major labels are willing to license their music.) There are already other cases in other parts of the media business — The New York Times sued OpenAI and Microsoft in December, for example — and one of them could set an important precedent.
Until that happens — and maybe after, too — there will be settlements. Very few rightsholders have much of an interest in stopping AI — some could in some cases, but it’s a losing battle. What they really want to do is leverage the power they have to destroy, or at least delay, a nascent business in order to shape it. (“The power to destroy a thing is the absolute control over it,” in the words of Paul Atreides, Padishah Emperor of the Known Universe, who might be exaggerating but certainly has a point.) That will give them real power — not only to monetize music with AI but to shape the terms of engagement in a way that, let’s face it, is likely to favor big companies with big catalogs. It will be interesting to see what they do with it.