Category: AI Legislation

Your Music, AI, and the Machine Unlearning Research Hub: What Every Musician Should Know

If you’re a recording artists or musician, you have most likely heard some form of this pitch:

“Don’t worry. If you don’t like how your music is used for AI, we can always take it back out later.”

That sounds fair.

The hard part is that, today, it is not that simple. And it’s so not simple, that statement may as well be untrue.

That is why we created the  Machine Unlearning Research Hub  at MusicTechPolicy.com—to help musicians understand what machine unlearning is, what it can do today, and what it may be able to do tomorrow.

Think of it like baking a cake

Suppose you bake a cake with flour, eggs, butter, milk, and sugar. The eggs make the cake what it is.

Once the cake comes out of the oven, you cannot remove just the eggs. AI training works in much the same way.

When an AI developer “trains” a model (often on illegally acquired recordings as we are seeing in the litigation), it does not simply store copies of recordings in a folder. It changes billions—or even trillions—of internal values based on every recording it has been trained on and extracted from those training tracks or its “training pipeline”. Each recording and the values the AI extracts from the recording helps shape the finished model.

That’s why it knows what you mean when you ask it to play an Eric Clapton solo or a John Bonham drum fill. That is also why taking one recording back out later is so difficult.

Surely, you say, they didn’t build a dataset that cannot be corrected and only gets larger with human personal rights and copyrights? Well, they kind of did. Not that different from Google Street View. There’s a long “Hotel California” tradition with these people.

So what is machine unlearning?

Machine unlearning is a field of research that asks a simple question:

Can an AI system forget what it learned from a particular piece of data without rebuilding the entire model from scratch?

The quick answer today is not very easily, no matter what they tell you. Researchers all over the world are working on that question.

The results are a mixed bag. A cynic—who me?—might say they’re not trying very hard. But some techniques show real promise. Others work only under very limited conditions with largely toy datasets.

For today’s largest music models, there is still no widely accepted way to guarantee that every artifact of one recording—or one artist—has been completely removed.

That does not mean machine unlearning will never work. It means it is still a research problem.

How much can it fix today?

The honest answer is:

Some things. Not everything.

Researchers have developed methods that can reduce a model’s reliance on particular data or make it much less likely to produce certain results. That’s not 100% or zero depending on how you look at it. But it’s better every year and those advances matter.

But reducing influence is not the same thing as proving that a recording has been fully removed from a commercial AI model. For musicians, that difference is obviously important.

Will it get better?

Almost certainly.

Machine unlearning is receiving significant attention from universities, technology companies, and governments. Why? Well, for one thing there are countries that have the “right to be forgotten” that Google fought so hard against in Europe and especially Germany. There’s also other privacy laws that all of the AI models are essentially out of compliance with, so it’s only a matter of time until there’s a real effort to do something about it.

Five years from now, today’s methods will almost certainly look primitive. Ten years from now, the tools may be far better still. But no one can honestly promise today that future improvements will solve every problem created by yesterday’s training.

That is why decisions made now still matter. Let’s be honest, the best way to stay out of AI is to never be included in AI.

What does this mean if someone wants to license your music?

Ask yourself one simple question:

If I change my mind in three years, how will my music come back out?

Do not settle for vague promises.

Ask specific questions.

  • Will my recordings be kept in a separate training set?
  • Can they be removed without rebuilding the model?
  • What machine unlearning process will be used?
  • Has that process been independently tested?
  • How will you prove my music was removed?
  • What happens if the technology cannot fully remove it?
  • Who pays to remove it?

If the company cannot answer those questions today, it is worth understanding that they are asking you to rely on technology that may not yet exist in the form they hope it will. Or as Blanche Dubois said in Streetcar Named Desire, “I have always relied on the kindness of strangers.” Feel good yet?

That does not necessarily mean you should refuse every AI license.

It does mean you should know exactly what risk you are accepting.

This is why we built the Machine Unlearning Research Hub

Machine unlearning is moving quickly, and new research papers appear almost every week. Some represent genuine breakthroughs, others improve only narrow parts of the problem.

Our goal is not to tell musicians what decision to make. Our goal is to help musicians make informed decisions based on the best available evidence. If someone asks you to license your music for AI, you deserve to know one thing before you sign:

Can they realistically give it back if you ask?

Today, that question deserves a careful answer—not a marketing slogan. That is what the Machine Unlearning Research Hub is here to explore.

by Trichordist

Europe at the Crossroads: Will the Law Strengthen Authors’ Rights or Surrender the “Crown Jewels” of Human Creativity? @Helienne Lindvall’s ECSA Keynote

[An important keynote from Helienne Lindvall, President of the European Composer and Songwriter Alliance, on why creators’ consent, transparency, and fair remuneration must remain central in the AI era. The keynote was presented as part of the European Composer & Songwriter Alliance (ECSA) conference on “Authors’ Rights and Music Streaming in the Age of AI”, which focused on generative AI and the future of music creators’ rights in Europe

Good afternoon to every one of you, whether you’re here in this room or joining us online. It is a pleasure to welcome you all here today and I want to thank MEDAA, la Maison européenne des Autrices et des Auteurs, for hosting today’s ECSA conference on “Authors’ Rights and Music Streaming in the Age of AI”. ]

I am Helienne Lindvall, songwriter and the President of ECSA, the European Composer and Songwriter Alliance. ECSA represents 57 professional music authors’ associations and more than 30,000 composers across 29 European countries. I am honoured to be here today with fellow composers, songwriters, policymakers, and representatives from Europe’s cultural and creative sectors.

I am particularly grateful to welcome Henna Virkkunen, the Executive Vice-President for Technological Sovereignty, Security, and Democracy at the European Commission. Ms. Virkkunen – thank you again for joining us. We are all looking forward to hearing your opening remarks in just a moment.

I also want to thank three Members of the European Parliament for their participation: Emma Rafowicz, co-rapporteur on the Agora EU programme, Axel Voss, rapporteur on the recent report on copyright and generative AI, and Hélder Sousa Silva, who will draft the forthcoming report on the Cultural and creative sectors in the age of AI.

We would also like to express our deepest gratitude to all the speakers who will contribute their time and expertise today. And remember that this conference would not be possible without the support of the Creative Europe programme.

So, Authors’ Rights and Music Streaming in the Age of AI? Let me first take a step back to 2016. Ten years ago, the European Commission President, Jean-Claude Juncker, called artists and creators “Europe’s crown jewels”. He said their works should be protected and they should be paid fairly.

Three years later, the EU adopted the Directive on Copyright in the Digital Single Market. We applauded it, for enshrining appropriate and proportionate remuneration, for increasing transparency in contracts, and for strengthening author’s rights on content-sharing platforms. Seven years on, where do we stand?

Well, the truth is that the principle of appropriate and proportionate remuneration is still too often circumvented in practice, in particular through buyout practices, but also when it comes to other online exploitation, such as streaming.

And then came generative AI. Adopted at a time when generative AI was barely existing, the Directive does not mention AI anywhere.

But it does include text and data mining exceptions, designed to help universities and researchers, discover new trends and gaining new knowledge. Supposedly with minimal harm to authors and other rightholders.

The reality? When not simply ignoring EU rules, global AI companies have exploited those exceptions far beyond their intended purpose. They’ve scraped and used all our works without consent, without transparency, and without remuneration. The harm to music authors isn’t minimal—it’s maximal. AI-generated content now imitates and substitutes us.

Some say “You could have opted out.” But here’s the truth: AI companies scraped everything – looting the entire history of musical works – before we had a fair chance to opt out and even know how to opt out.

To quote Baroness Beeban Kidron, the director of Bridget Jones The Edge of Reason: “Should shopkeepers have to opt out of shoplifters? Should victims of violence have to opt out of attacks? Should those who use the internet for banking have to opt out of fraud? I struggle to think of another situation where someone protected by law must proactively wrap it around themselves on an individual basis.”

And for a songwriter like me—working with co-writers, different CMOs, publishers, and labels—opting out is practically impossible. And even if it was possible, we would be naive to believe it would be respected. How would we even know if it were, when there is no transparency?

The AI Act’s implementation hasn’t helped. Its transparency rules are weak. Trade secrets protect massive theft. Imagine a fast-food manufacturer who had stolen all the ingredients that went into their products, refusing to reveal what the ingredients are or where they came from, calling it a “trade secret”. Then demanding it should be up to the farmers to prove it was their produce that was stolen. That’s what we’re dealing with.

Coca Cola may have a secret recipe, but it still has to display what went into each bottle, and pay its suppliers. It shouldn’t be up to creators to prove AI companies used our works. They should be required to get our consent and to be transparent. Or we should presume — correctly — that they already scraped the entire web.

Yes, a few licensing deals have been signed in the past year — between a couple of major labels and AI companies, usually after litigation, and mostly in the US. But we know next to nothing about the details of those deals – or whether composers and songwriters will benefit in any way, despite it being our works that have been stolen and exploited.

Licensing shouldn’t only be available to those with the muscle to sue. In Europe, where we claim to cherish our artists and cultural diversity, survival of the fittest cannot be the answer. AI companies have ingested ALL the music available online. It makes no sense that only the most powerful get a license and get paid, when they only supplied a fraction of the ingredients. And let me be clear: we are not against AI. It can be a helpful tool in our workflow as creators. We are simply against unlicensed AI.

Generative AI companies must act ethically. They must work with us—not profit from our work without consent and at our expense. That’s the only way to rebuild trust between creators and AI companies. Currently, the AI landscape is like the Wild West, and AI startups that want to act ethically cannot compete when there is a shop next door selling stolen goods.

Let’s be honest, the current framework is misinterpreted and applied far beyond its original purpose. It has created a high level of uncertainty that only benefits global generative AI companies to the detriment of creators. We cannot wait for courts to decide policy. We cannot rely on opaque deals between big corporations where the money rarely trickles down to creators.

This isn’t the time for sticking plasters [or Band Aids] on a wooden leg. It’s time for policymakers to be bold. The good news: not only the Pope but also many EU Member States and the European Parliament are showing the way. The recent Voss report on Copyright and Generative AI recognizes that AI systems rely massively on protected works—exploited without authorization or compensation. It recommends:

• Full transparency for AI training, including a rebuttable presumption of use for any AI service operating in the EU; and

• A new legislative initiative to clarify licensing rules and establish a functioning market.

We fully support this. We need a framework that:

1. Enables fair remuneration for creators

2. Ensures EU copyright law applies to all services operating in the EU.

3. Addresses the substitution and dilution of human creation by AI output

4. Ensures collective management can deliver appropriate and proportionate remuneration to all creators—big and small

The Parliament has also insisted that digital platforms must act against AI fraud and manipulation. And it is not the first time – the European Parliament’s report on music streaming, adopted in 2024, already did so, with many other recommendations to improve the identification of creators on music streaming platforms and ensure more transparency in algorithms and recommendation systems, as well as when it comes to AI generated music.

For composers and songwriters, streaming fraud through AI is a critical issue. In April, Deezer reported that 75,000 fully AI-generated tracks are uploaded daily to the platform – that’s 44% of all uploads. In March, a man in the US pleaded guilty to defrauding streaming platforms with AI-generated tracks, generating millions in royalties. Fraudsters impersonate real artists, upload fake songs to their profiles, and steal their royalties. This isn’t just an economic issue. It’s ethical – it’s a massive violation of moral rights and personal data.

And it threatens citizens’ trust in the authenticity of digital content. That’s one of the many reasons why we welcome MEPs Rafowicz and Kuhnke’s draft report on AgoraEU, which rightly prioritizes human creativity over AI-generated works.

We also warmly welcome this proposal for a dedicated music strand that can address the concrete challenges and structural imbalances impacting the sector, such as increasing market concentration, artistic freedom, fair remuneration and the growing dominance of digital service providers.

Today, 26 organisations from across the European music sector published a statement to support this draft report and encourage all MEPs to give the music sector the support it deserves.

Now, let me conclude: Our plea today is simple: The promise made to Europe’s crown jewels in 2016 remains unfulfilled: The exceptions designed to help researchers and generate information now fuel billion-dollar companies that exploit us. The transparency we were promised is hidden behind trade secrets. The licensing market that should exist is reserved for those who can afford the most expensive lawyers in the US. This must change.

We call on European policymakers to act with courage. With the European Parliament, we call for an additional legal framework, one that can finally uphold the key principles of transparency, consent and remuneration and encourage a well-functioning licensing market. This is not about adding more regulation This is to rebalance a framework that is fundamentally flawed, far from its intended purpose and Europe’s most fundamental values.

Europe must decide: will it stand with its creators, or stand by while our works are taken without consent? Let us become once again Europe’s crown jewels.

Please. Let’s make this true. Thank you.

by thetrichordist

The Growing Backlash Against AI Data Centers: Local Resistance and the Infrastructure Crunch

As we’ve reported many times, communities across the US are increasingly pushing back against the explosive growth of AI-driven data centers. Major concerns include skyrocketing electricity demand, massive water consumption for cooling, noise pollution from giant fans, loss of prime agricultural and residential land, and rising utility bills passed on to local residents. As of May 2026, independent trackers report approximately 69–78 U.S. jurisdictions that have enacted bans, restrictions, or moratoriums on new data centers. Many of these measures also target the new high-voltage transmission lines required to power them.

This wave of resistance highlights a deepening tension between the rapid expansion of AI infrastructure and local priorities around quality of life, sustainability, and community control.

1. Michigan: The Epicenter of Local Moratoriums

I think you could safely say that Michigan currently leads the nation in local opposition to data center construction, largely triggered by the controversial $16+ billion OpenAI-Oracle Stargate AI data center project in Saline Township, Washtenaw County. Despite a 4-1 township planning commission vote against rezoning and strong resident protests, the Stargate construction project advanced through legal channels, igniting widespread defensive actions across the state.

  • More than 50 communities (cities and townships) have enacted temporary moratoriums, covering roughly 1,500 square miles — an area comparable to the size of Rhode Island.
  • Between 25 and 51 active local moratoriums are in place as of early 2026.
  • State lawmakers have introduced bills (HB 5594–5596) calling for a one-year statewide pause on new hyperscale data centers, along with stricter rules on water and electricity connections.
  • Some utilities, such as Ypsilanti, have imposed their own 12-month bans on water hookups for large AI facilities—but that will eventually expire.

Key issues in Michigan should sound familiar: massive water usage, strain on the electrical grid, and the loss of local zoning authority.

2. Virginia: Transmission Line Battles in “Data Center Alley”

Virginia is home to the highest concentration of data centers in the United States (over 550 facilities), particularly in Northern Virginia. Opposition here focuses heavily on both the data centers and the extensive transmission lines needed to support them.

  • Strong protests in Loudoun, Prince William, Hanover, and other counties against new projects and expansions.
  • Major conflicts over high-voltage lines such as the Valley Link and Joshua Falls projects, which cross multiple counties and impact neighborhoods, historic sites, and conserved rural land.
  • Dominion Energy has faced repeated legal and community challenges regarding route selections.
  • Legislative debates continue over ending billions in tax incentives and studies projecting residential electricity rate increases of up to $37 per month by 2040.
Breakfast at Buck’s of Woodside—if you’re not at the table you are on the menu

3. Georgia: Statewide Pause Efforts Amid High Project Volume

Georgia has seen hundreds of announced data center projects, prompting both local and statewide responses.

  • Bills such as HB 1059 and HB 1012 propose temporary statewide pauses on new permitting (potentially until 2027–2028) to allow time for impact studies.
  • Several counties, including DeKalb and Camden, have passed moratoriums ranging from several months to a year while updating zoning ordinances.
  • Residents voice concerns about energy costs, water consumption, loss of land, and whether tax incentives truly benefit local communities.

Georgia’s combination of legislative proposals and county-level actions reflects growing resistance in a rapidly developing market.

4. North Carolina: Rising Local and Policy Pushback

North Carolina ranks among the top states for new moratorium activity as data center developers expand beyond traditional East Coast hubs.

  • Multiple counties and municipalities have passed restrictions or temporary moratoriums citing infrastructure strain, zoning issues, and community impacts.
  • Policy proposals such as HB 1063 seek to require hyperscale developers to fully cover the costs of power, water, and grid upgrades rather than passing them to ratepayers.
  • Growing focus on the environmental and visual effects of both data centers and supporting transmission lines.

North Carolina represents an emerging hotspot where early local actions may shape future statewide policy.

5. Indiana: County-Level Resistance and High-Stakes Conflicts

Indiana has seen intense localized opposition, particularly in rural counties.

  • Counties such as White and Fulton have enacted 6-to-12-month moratoriums to study impacts and strengthen local ordinances.
  • Trackers show at least 6 formal actions, with several others in discussion.
  • Primary concerns include the conversion of prime agricultural land, rising utility rates, and the industrialization of rural communities.

Indiana illustrates how even mid-sized proposals can trigger strong community responses and political tension.

Broader Implications and the Path Forward

The five most active states — Michigan, Virginia, Georgia, North Carolina, and Indiana — capture the national picture. Resistance is bipartisan, spans urban and rural areas, and increasingly includes opposition to the massive transmission lines that accompany data center projects.

Common themes include fears that data centers consume disproportionate amounts of power and water while shifting costs onto existing residents. Proponents argue these facilities bring jobs, tax revenue, and are essential for America’s AI competitiveness. Critics insist that growth must be responsible, with full cost recovery, better siting practices, efficiency standards, and genuine community input.

As AI demand continues to surge, this local “revolt” tests whether the physical infrastructure can scale fast enough without compromising quality of life and environmental goals. I think the national consensus is a big no.

Expect more moratoriums, ballot initiatives, legal battles, and negotiations in the coming months. The outcome will significantly influence not only the future of AI but also national energy policy and land-use planning for years to come.

by thetrichordist

A Subtle Shift in US AI Policy and Why Artists Should Pay Attention

Something is moving in Washington.

A recent report suggests that the Trump administration is considering a new executive order on artificial intelligence. On its face, that might sound like more of the same—another round of AI policy chatter promoted by David Sacks, the Silicon Valley lobbyist and billionaire investor who has been pushing a “don’t slow it down” approach.

But this time feels different.

Sacks appears to have gotten pushed out at least a bit. Don’t count the chickens just yet. But the shift in tone matters. And the timing matters even more. The order is reportedly being weighed ahead of Trump’s visit to China, where AI development has become a central axis of geopolitical competition.

That context changes the story. For the past several years, the dominant policy posture around AI has been simple: don’t slow down innovation. Because China.

That argument has been doing a lot of work. It has been used to wave away concerns about training data, to discourage state and local oversight of data center buildouts, and to greenlight massive infrastructure commitments—including dedicated nuclear power for AI campuses run by Google, Microsoft, Meta, and Amazon.

In other words: build the machine first. Deal with the consequences later.

Artists have been the raw material for that strategy.

Musicians, book authors, visual artists—these are not just inputs. They are the training ground for systems that are now capable of producing substitutive outputs that overwhelm creators and flood markets. And until now, the White House policy conversation has largely treated that massive theft as an acceptable cost of staying ahead led by David Sacks, R Street Institute and the hyperscalers.

What makes this potential executive order interesting is that it suggests a shift away from that posture. If the administration is preparing to meet with China on AI, it has an incentive to show that the United States takes control, governance, and strategic resources seriously. And in this context, creative works start to look less like “free fuel” and more like national assets.

That may matter for artists.

Because once you recognize that AI systems derive value from the signals embedded in creative works—voice, tone, style, expression—you start to see those works differently. They are not just content. They are repositories of identity and cultural value.

And they are being extracted at scale.

A more protective policy framework—whether it focuses on model review, training data standards, or provenance—creates an opening. It creates space for the idea that artists are not just upstream contributors, but stakeholders whose work underpins the entire system.

This doesn’t mean the executive order, if it comes, will solve the problem. It won’t.

But it could mark an inflection point.

If policymakers begin to treat AI not just as a technology race but as a resource competition, then the role of creators becomes harder to ignore. You can’t claim to lead in AI while simultaneously disregarding the human material that makes those systems work.

That contradiction is starting to surface. The industry allowed artists and even copyright itself to be lumped in with zoning boards as “bureaucracy” which in turn allowed David Sacks and his ilk to try to create an alternate universe where “innovation” ran wild to “beat China” while also selling chips to China out the back door.

For artists, the takeaway is simple: pay attention to the shift in tone. Policy signals often precede legal ones. What gets framed as a national priority today can become a regulatory framework tomorrow.

For the first time in a while, there are signs that the conversation may be moving—however slightly—toward recognizing the value that artists bring to the AI ecosystem.

Sacks may not be gone. Silicon Valley rarely loses outright, just look at the MLC. But even a partial shift away from the “move fast and ingest everything” playbook is meaningful.

Because for artists, the question has never been whether AI will be built.

The question is whether it will be built on you or with you.

by Trichordist

@RonanFarrow and @AndrewMarantz: Sam Altman May Control Our Future—Can He Be Trusted?

Ronan Farrow and Andrew Marantz investigate Sam Altman’s leadership of OpenAI, based on internal documents and more than 100 interviews. They center on a core tension: Altman has positioned himself as a steward of humanity’s most powerful technology, yet many colleagues and insiders question whether he can be trusted with that responsibility. Internal memos compiled by senior figures—including chief scientist Ilya Sutskever—allege a pattern of misleading statements and evasiveness, particularly around AI safety and governance.  Shocking, ain’t it?

The piece traces OpenAI’s evolution from a nonprofit founded to prioritize safety over profit into a commercially driven company pursuing massive scale and valuation. Along the way, Altman is portrayed as highly ambitious, politically savvy, and willing to push boundaries—sometimes at the expense of transparency or institutional safeguards. 

It also situates these concerns within the broader stakes of artificial general intelligence: if such systems emerge, the individuals controlling them could wield unprecedented global power. The article ultimately raises an unresolved question—whether the rapid centralization of technological authority in a single leader and company is compatible with the level of trust and accountability that such power demands.

Read it on the New Yorker.

by thetrichordist

Say No to Suno

Late last year, thieves disguised as construction workers broke into the Louvre during broad daylight, grabbed more than $100 million worth of crown jewels, and roared off on their motorbikes into the busy streets of Paris. While some of those thieves were later arrested, the jewelry they stole has yet to be recovered, and many fear those historic works of artistry have already been recut, reset, and resold.

Closer to home, but no less nefarious, is the brazen rip-off of artists enabled by irresponsible AI, whose profiteers are recutting, remixing, and reselling original works of artistry as something new.  The hijacking of the world’s entire treasure-trove of music floods platforms with AI slop and dilutes the royalty pools of legitimate artists from whose music this slop is derived. 

Meanwhile, those who are promoting this new business model are operating in broad daylight, too – minus the yellow safety vests.  That is AI music company Suno, the brazen “smash and grab” platform whose “Make it Music” ad campaign suggests that the most personal and meaningful forms of music can now be fabricated by their unauthorized AI platform machinery trained on human artists’ work. 

How significant is this activity?  Publicly revealed data says Suno is used to generate 7 million tracks a day, a massive quantity that suggests a dominant market share of AI tracks.  According to recent reports, Deezer “deems 85% of streams of fully AI-generated tracks [on its service] to be fraudulent,” and that such tracks include outputs from major generative models.  As JP Morgan’s analysts said, Deezer’s data “should be indicative of the broader market.”  Suno has yet to demonstrate persuasively that its platform does not, in practice, serve as a scalable input into streaming-fraud schemes — raising a serious concern that Suno has, in effect, become a fraud-fodder factory on an industrial scale.

In a February 2 LinkedIn post, Paul Sinclair, Suno’s Chief Music Officer, claims that his company’s platform is about “empowerment” that enables “billions of fans to create and play with music.”  He argues that closed systems are “walled gardens” that deny people access to the full joy of music.

Ironically, Sinclair’s choice of analogy undermines his own argument.  Ask yourself: just why are most gardens surrounded by fences or walls?  To keep out rabbits, deer, raccoons and wild pigs seeking a free lunch.  We cultivate, nurture and protect our gardens precisely because that makes them much more productive over the long run.

While Sinclair may be loath to admit it, AI is fundamentally different from past disruptive innovations in the music industry.  The phonograph, cassettes, CDs, MP3s, downloads, streaming – all these technologies were about the reproduction and distribution of creative work.  By contrast, irresponsible AI like Suno appropriates and plunders such creative work while undermining the commercial ecosystem for artists.

Think back to the days of Napster.  What brought the music industry back from the ruinous abyss of unfettered digital piracy?  It was the very “closed systems” that Sinclair derides as exclusionary.  At least streaming platforms maintain access controls and content management systems that enable creator compensation, even if the economic outcomes for many creators remain inadequate.  Should we be against Apple Music, Spotify, Deezer, YouTube Music, and Amazon Music?  What about Netflix, Disney+ and HBO, too, while we’re at it?

At its core, Sinclair’s argument is just a tired remix of the old trope that “information wants to be free.”  What that really means is: “We want your music for free.”

Artists need to understand Suno’s game.  They are not putting technology in the service of artists; they are putting artists in the service of their technology.  Every time artists’ creations are used by the platform, those creations have just unwittingly been contributed to the creation of endless derivatives of artists’ own work, not to mention AI slop, with limited or no remuneration back to the human creators.  Suno built its business on our backs, scraping the world’s cultural output without permission, then competing against the very works exploited.

It’s also important to keep in mind that using Suno to generate audio output calls into question the copyrightability of whatever Suno creates.  Most countries around the world including the US Copyright Office have been clear that generative AI outputs are largely ineligible for a copyright – meaning the economic value of the Suno creation lies solely with Suno, not with the artist using it.  The only ones gaining empowerment from Suno are Suno themselves.

Many in our community are embracing responsible AI as a tool for creation, and as a means for fans to explore and interact with our artistry.  That’s wonderful.  But it’s not the same as creating an environment where AI-generated works sourced from our music are mass distributed to dilute our royalties or, worse yet, reward those actively seeking to commit fraud.  Artists need to know the difference – all AI platforms are not the same, and Suno, which is being sued for copyright infringement, is not a platform artists should trust.

Responsible AI-generated music must evolve within a framework that respects and remunerates artists, enhances human creativity rather than supplants it, and empowers fans to engage with the music they love.  At the same time, AI services must preclude mass distribution of slop and prevent fraudsters from destroying the very ecosystem that has been built to reward and sustain artists and audiences alike.

All of us, including billions of music fans, share an urgent, deep and abiding interest in protecting and rewarding human genius, even as AI continues to change our industry and the world in unimaginable ways.  So in 2026, even as the Louvre continues to revamp its own approach to security, we in the arts must rise to confront those who would “smash-and-grab” our creativity for their own benefit.

Together, while embracing innovation, we must work to establish more effective safeguards – both legal and technological – that better promote and protect all creative artists, our intellectual property, and the spark of human genius.

Say no to Suno. Say yes to the beauty and bounty of the gardens that feed us all.

Signed: 

Ron Gubitz, Executive Director, Music Artist Coalition

Helienne Lindvall, Songwriter and President, European Composer and Songwriter Alliance

David C. Lowery, Artist and Editor The Trichordist

Tift Merritt artist, Practitioner in Residence, Duke University and Artist Rights Alliance Board Member

Blake Morgan, artist, producer, and President of ECR Music Group.

Abby North, President, North Music Group

Chris Castle, Artist Rights Institute

by Trichordist Editor

Stealing Isn’t Innovation!

Don’t let the so-called “AI czar” sell you the idea that changing the law to legalize taking artists’ work without consent is innovation. It isn’t.

Innovation creates new value. The AI boondoggle takes existing value from creators and communities and hands it to a small number of tech companies—without permission, without payment, and without accountability but with a nuclear reactor next to your house.

Artists aren’t raw material. They’re rights-holders under U.S. law. Rewriting those rights to subsidize AI business models isn’t progress—it’s a policy choice to reward theft at scale.

AI can thrive without gutting creative rights. But that requires consent, licensing, and fair compensation—not retroactive immunity dressed up as innovation.

Stealing isn’t innovation. It’s just stealing, with a press strategy.

Find out more at Stealing Isn’t Innovation and @human_artistry

by Trichordist

2026 Music Predictions: The Legal and Policy Fault Lines Ahead

By Chris Castle

I was grateful to Hypebot for publishing my 2026 music‑industry predictions, which focused on the legal and structural pressures already reshaping the business. For regular readers, I’m reposting those predictions here—and adding a few more that follow directly from the policy work, regulatory engagement, and royalty‑system scrutiny we’ve been immersed in over the past year with the Artist Rights Institute. These additional observations are less about trend‑spotting and more about where the underlying legal and institutional logic appears to be heading next.

1. AI Copyright Litigation Will Move From Abstract Theory to Operational Discovery

In 2026, the center of gravity in AI‑copyright cases will shift toward discovery that exposes how models are trained, weighted, filtered, and monetized. Courts will increasingly treat AI systems as commercial products rather than research experiments, and discovery fights for the good of humanity…ahem…rather than summary judgment rhetoric. The result will be pressure on platforms to settle, license, or restructure before full disclosure occurs particularly since it’s becoming increasingly likely that every frontier AI lab as ripped off the world’s culture the old fashioned way—they stole it off the Internet.

The next round of AI copyright litigation will come from fans: As more deals are done with AI like the Disney/Sora deal, fans who use Sora or other AI to create separatable rights with AI (like new characters, new story lines) or even new universes with old story lines (like maybe new versions of the Luke/Darth/Hans/Leia arc in the Old West) will start to get the idea that their IP is…well…their IP. If it’s used without compensating them or getting their permission, that whole copyright thing is going to start to get real for them.

2. Streaming Platforms Will Face Structural Payola Scrutiny, Not Just Royalty Complaints

Minimum‑payment thresholds, bundled offerings, and “greater‑of” formulas will no longer be treated as isolated business choices. Regulators and courts will begin to examine how these mechanisms function together to shift risk onto artists while preserving platform margins. Antitrust, consumer‑protection, and unfair‑competition theories will increasingly converge around the same conduct. Due to Spotify’s market dominance and intimidation factor for majors and big to medium sized independent labels, these cases will have to come from independent artists.

3. The Copyright Office Will Approve a Conditional Redesignation of the MLC

Rather than granting an unconditional redesignation of the Mechanical Licensing Collective, the Copyright Office is likely to impose conditions tied to governance, transparency, and financial stewardship. This approach allows continuity for licensees while asserting supervisory authority grounded in the statute. The message will be clear: designation is provisional, not permanent.

Digital-Licensing-Coordinator-to-USCO-2-Sept-22-2025Download

4. The MLC’s Gundecked Investment Policy Will Be Unwound or Materially Rewritten

The practice of investing unmatched royalties as a pooled asset is becoming legally and politically indefensible. In 2026, expect the investment policy to be unwound or rewritten by new regulations to require pass‑through of gains, or strict capital‑preservation limits. Once framed as a fiduciary issue rather than a finance strategy, the current model cannot survive intact.

It’s also worth noting that the MLC’s investment portfolio has grown so large ($1.212 billion) that its investment income reported on its 2023 tax return has also grown to an amount in excess of its operating costs as measured by the administrative assessment paid by licensees.

5. An MLC Independent Royalty‑Accounting and Systems Review Will Become Inevitable

As part of a conditional redesignation, the Copyright Office may require an end‑to‑end operational review of the MLC by a top‑tier royalty‑accounting firm. Unlike a SOC report, such a review would examine whether matching, data logic, and distributions actually produce correct outcomes. Once completed, that analysis would shape litigation, policy reform, and future oversight.

6. Foreign CMOs Will Push Toward Licensee‑Pays Models

Outside the U.S., collective management organizations face rising technology costs and political scrutiny over compensation. In response, many will explore shifting more costs to licensees rather than members, reframing CMOs as infrastructure providers. Ironically, the U.S. MLC experiment may accelerate this trend abroad given the MLC’s rich salaries and vast resources for developing poorly implemented tech.

These developments are not speculative in the abstract. They follow from incentives already in motion, records already being built, and institutions increasingly unable to rely on deference alone.

7.  Environmental Harms of AI Become a Core Climate Issue

We will start to see the AI labs normalize the concept of private energy generation on a massive scale to support data centers built in current green spaces.  If they build or buy electric plants they do not intend to share.  This whole thing about they will build small nuclear reactors and sell excess back to the local grid is crazy—there won’t be any excess and what about their behavior over the last 25 years makes you think they’ll share a thing?

So some time after Los Angeles rezones Griffith Park commercial and sells the Greek Theater to Google for a new data center and private nuclear reactor and Facebook buys the Diablo Canyon reactor, the Music Industry Climate Collective will formally integrate AI’s ecological footprint into their national and international policy agendas. After mounting evidence of data‑center water depletion, aquifer stress, and grid destabilization — particularly in drought‑prone regions — climate coalitions will conceptually reclassify AI infrastructure as a high‑impact industrial activity.

This will become acute after people realize they cannot expect the state or federal government to require new state permitting regimes because of the overwhelming political influence of Big Tech in the form of AI Viceroy-for-Life David Sacks. (He’s not going anywhere in a post-Trump era.). This will lead to environmental‑justice litigation over siting decisions and pressure to require reporting of AI‑related energy, water, and land use.

8.  Criminal RICO Case Against StubHub and Affiliated Resale Networks

By late 2026, the Department of Justice brings a landmark criminal RICO indictment targeting StubHub‑linked reseller networks and individual reseller financiers for systemic ticketing fraud and money laundering. The enterprise theory alleges that major resellers, platform intermediaries, lenders, and bot‑operators coordinated to engage in wire fraud, market manipulation, speculative ticketing, and deceptive consumer practices at international scale. Prosecutors present evidence of an organized structure that used bots, fabricated scarcity, misrepresentation of seat availability, and price‑fixing algorithms to inflate profits.

This becomes the first major criminal RICO prosecution in the secondary‑ticketing economy and triggers parallel state‑level investigations and civil RICO suits. Public resellers like StubHub will face shareholder lawsuits and securities fraud allegations.

Just another bright sunshiny day.

[A version of this post first appeared on MusicTechPolicy]




by thetrichordist

Meet the New AI Boss, Worse Than the Old Internet Boss

Congress is considering several legislative packages to regulate AI. AI is a system that was launched globally with no safety standards, no threat modeling, and no real oversight. A system that externalized risk onto the public, created enormous security vulnerabilities, and then acted surprised when criminals, hostile states, and bad actors exploited it.

After the damage was done, the same companies that built it told governments not to regulate—because regulation would “stifle innovation.” Instead, they sold us cybersecurity products, compliance frameworks, and risk-management services to fix the problems they created.

Yes, artificial intelligence is a problem. Wait…Oh, no sorry. That’s not AI.

That’s was Internet. And it made the tech bros the richest ruling class in history.

And that’s why some of us are just a little skeptical when the same tech bros are now telling us: “Trust us, this time will be different.” AI will be different, that’s for sure. They’ll get even richer and they’ll rip us off even more this time. Not to mention building small nuclear reactors on government land that we paid for, monopolizing electrical grids that we paid for, and expecting us to fill the landscape with massive power lines that we will pay for.

The topper is that these libertines want no responsibility for anything, and they want to seize control of the levers of government to stop any accountability. But there are some in Congress who are serious about not getting fooled again.

Senator Marsha Blackburn released a summary of legislation she is sponsoring that gives us some cause for hope (read it here courtesy of our friends at the Copyright Alliance). Because her bill might be effective, that means Silicon Valley shills will be all over it to try to water it down and, if at all possible, destroy it. That attack of the shills has already started with Silicon Valley’s AI Viceroy in the Trump White House, a guy you may never have heard of named David Sacks. Know that name. Beware that name.

Senator Blackburn’s bill will do a lot of good things, including for protecting copyright. But the first substantive section of Senator Blackburn’s summary is a game changer. She would establish an obligation on AI platforms to be responsible for known or predictable harm that can befall users of AI products. This is sometimes called a “duty of care.”

Her summary states:

Place a duty of care on AI developers in the design, development, and operation of AI platforms to prevent and mitigate foreseeable harm to users. Additionally, this section requires:

• AI platforms to conduct regular risk assessments of how algorithmic systems, engagement mechanics, and data practices contribute to psychological, physical, financial, and exploitative harms.

• The Federal Trade Commission (FTC) to promulgate rules establishing minimum reasonable safeguards.

At its core, Senator Blackburn’s AI bill tries to force tech companies to play by rules that most other industries have followed for decades: if you design a product that predictably harms people, you have a responsibility to fix it.

That idea is called “products liability.” Simply put, it means companies can’t sell dangerous products and then shrug it off when people get hurt. Sounds logical, right? Sounds like what you would expect would happen if you did the bad thing? Car makers have to worry about the famous exploding gas tanks. Toy manufacturers have to worry about choking hazards. Drug companies have to test side effects. Tobacco companies….well, you know the rest. The law doesn’t demand perfection—but it does demand reasonable care and imposes a “duty of care” on companies that put dangerous products into the public.

Blackburn’s bill would apply that same logic to AI platforms. Yes, the special people would have to follow the same rules as everyone else with no safe harbors.

Instead of treating AI systems as abstract “speech” or neutral tools, the bill treats them as what they are: products with design choices. Those choices that can foreseeably cause psychological harm, financial scams, physical danger, or exploitation. Recommendation algorithms, engagement mechanics, and data practices aren’t accidents. They’re engineered. At tremendous expense. One thing you can be sure of is that if Google’s algorithms behave a certain way, it’s not because the engineers ran out of development money. The same is true of ChatGPT, Grok, etc. On a certain level of reality, this is very likely not guess work or predictability. It’s “known” rather than “should have known.” These people know exactly what their algorithms do. And they do it for the money.

The bill would impose that duty of care on AI developers and platform operators. A duty of care is a basic legal obligation to act reasonably to prevent foreseeable harm. “Foreseeable” doesn’t mean you can predict the exact victim or moment—it means you can anticipate the type of harm that flows to users you target from how the system is built.

To make that duty real, the bill would require companies to conduct regular risk assessments and make them public. These aren’t PR exercises. They would have to evaluate how their algorithms, engagement loops, and data use contribute to harms like addiction, manipulation, fraud, harassment, and exploitation.

They do this already, believe it. What’s different is that they don’t make it public, anymore than Ford made public the internal research that the Pinto’s gas tank was likely to explode. In other words, platforms would have to look honestly at what their systems actually do in the world—not just what they claim to do.

The bill also directs the Federal Trade Commission (FTC) to write rules establishing minimum reasonable safeguards. That’s important because it turns a vague obligation (“be responsible”) into enforceable standards (“here’s what you must do at a minimum”). Think of it as seatbelts and crash tests for AI systems.

So why do tech companies object? Because many of them argue that their algorithms are protected by the First Amendment—that regulating how recommendations work is regulating speech. Yes, that is a load of crap. It’s not just you, it really is BS.

Imagine Ford arguing that an exploding gas tank was “expressive conduct”—that drivers chose the Pinto to make a statement, and therefore safety regulation would violate Ford’s free speech rights. No court would take that seriously. A gas tank is not an opinion. It’s an engineered component with known risks and risks that were known to the manufacturer.

AI platforms are the same. When harm flows from design decisions—how content is ranked, how users are nudged, how systems optimize for engagement—that’s not speech. That’s product design. You can measure it, test it, audit it, which they do and make it safer which they don’t.

This part of Senator Blackburn’s bill matters because platform design shapes culture, careers, and livelihoods. Algorithms decide what gets seen, what gets buried, and what gets exploited. Blackburn’s bill doesn’t solve every problem, but it takes an important step: it says tech companies can’t hide dangerous products behind free-speech rhetoric anymore.

If you build it, and it predictably hurts people, you’re responsible for fixing it. That’s not censorship. It’s accountability. And people like Marc Andreessen, Sam Altman, Elon Musk and David Sacks will hate it.

by Trichordist

Trump’s Historic Kowtow to Special Interests: Why Trump’s AI Executive Order Is a Threat to Musicians, States, and Democracy

There’s a new dance in Washington—it’s called the KowTow

Most musicians don’t spend their days thinking about executive orders. But if you care about your rights, your recordings, your royalties, or your community, or even the environment, you need to understand the Trump Administration’s new executive order on artificial intelligence. The order—presented as “Ensuring a National Policy Framework for AI”—is not a national standard at all. It is a blueprint for stripping states of their power, protecting Big Tech from accountability, and centralizing AI authority in the hands of unelected political operatives and venture capitalists. In other words, it’s business as usual for the special interests led by an unelected bureaucrat, Silicon Valley Viceroy and billionaire investor David Sacks who the New York Times recently called out as a walking conflict of interest.

You’ll Hear “National AI Standard.” That’s Fake News. IT’s Silicon valley’s wild west

Supporters of the EO claim Trump is “setting a national framework for AI.” Read it yourself. You won’t find a single policy on:
– AI systems stealing copyrights (already proven in court against Anthropic and Meta)
– AI systems inducing self-harm in children
– Whether Google can build a water‑burning data center or nuclear plant next to your neighborhood 

None of that is addressed. Instead, the EO orders the federal government to sue and bully states like Florida and Texas that pass AI safety laws and threatens to cut off broadband funding unless states abandon their democratically enacted protections. They will call this “preemption” which is when federal law overrides conflicting state laws. When Congress (or sometimes a federal agency) occupies a policy area, states lose the ability to enforce different or stricter rules. There is no federal legislation (EOs don’t count), so there can be no “preemption.”

Who Really Wrote This? The Sacks–Thierer Pipeline

This EO reads like it was drafted directly from the talking points of David Sacks and Adam Thierer, the two loudest voices insisting that states must be prohibited from regulating AI.  It sounds that way because it was—Trump himself gave all the credit to David Sacks in his signing ceremony.

– Adam Thierer works at Google’s R Street Institute and pushes “permissionless innovation,” meaning companies should be allowed to harm the public before regulation is allowed. 
– David Sacks is a billionaire Silicon Valley investor from South Africa with hundreds of AI and crypto investments, documented by The New York Times, and stands to profit from deregulation.

Worse, the EO lards itself with references to federal agencies coordinating with the “Special Advisor for AI and Crypto,” who is—yes—David Sacks. That means DOJ, Commerce, Homeland Security, and multiple federal bodies are effectively instructed to route their AI enforcement posture through a private‑sector financier.

The Trump AI Czar—VICEROY Without Senate Confirmation

Sacks is exactly what we have been warning about for months: the unelected Trump AI Czar

He is not Senate‑confirmed. 
He is not subject to conflict‑of‑interest vetting. 
He is a billionaire “special government employee” with vast personal financial stakes in the outcome of AI deregulation. 

Under the Constitution, you cannot assign significant executive authority to someone who never faced Senate scrutiny. Yet the EO repeatedly implies exactly that.

Even Trump’s MOST LOYAL MAGA Allies Know This Is Wrong

Trump signed the order in a closed ceremony with sycophants and tech investors—not musicians, not unions, not parents, not safety experts, not even one Red State governor.

Even political allies and activists like Mike Davis and Steve Bannon blasted the EO for gutting state powers and centralizing authority in Washington while failing to protect creators. When Bannon and Davis are warning you the order goes too far, that tells you everything you need to know. Well, almost everything.

And Then There’s Ted Cruz

On top of everything else, the one state official in the room was U.S. Senator Ted Cruz of Texas, a state that has led on AI protections for consumers. Cruz sold out Texas musicians while gutting the Constitution—knowing full well exactly what he was doing as a former Supreme Court clerk.

Why It Matters for Musicians

AI isn’t some abstract “tech issue.” It’s about who controls your work, your rights, your economic future. Right now:

– AI systems train on our recordings without consent or compensation. 
– Major tech companies use federal power to avoid accountability. 
– The EO protects Silicon Valley elites, not artists, fans or consumers. 

This EO doesn’t protect your music, your rights, or your community. It preempts local protections and hands Big Tech a federal shield.

It’s Not a National Standard — It’s a Power Grab

What’s happening isn’t leadership. It’s *regulatory capture dressed as patriotism*. If musicians, unions, state legislators, and everyday Americans don’t push back, this EO will become a legal weapon used to silence state protections and entrench unaccountable AI power.

What David Sacks and his band of thieves is teaching the world is that he learned from Dot Bomb 1.0—the first time around, they didn’t steal enough. If you’re going to steal, steal all of it. Then the government will protect you.


by Trichordist