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.

The AI “License” That Isn’t: A Musician’s Checklist for Spotting a Covenant Not to Sue Censorship Trap in Disguise

If you saw the adverb “forever” in a contract, would it give you pause?  It would me—I would wonder who allowed that to slip through.  As text-to-audio generative AI models desperately try to normalize their shoot-ready-aim ingestion of likely stolen works to support their next round of financing (or in some cases perhaps a VC exit by IPO), it’s likely that we will see some efforts at “licensing” reminiscent of the Napster era. “Licenses” that actually paper over the main act—stop the lawsuit before they start. What will that look like and what should we look for buried in the not so fine print?

Generative AI companies are coming to the negotiating table with “music licensing agreements” (and probably other artists’ too). That sounds encouraging — it suggests they want to do the right thing and pay for the content they use. Trust me, they don’t. What they want is to get away with it.

Not every document titled “license” actually functions like one. Some of these deals are better described as litigation insurance dressed up in licensing language, and if you sign one without reading the small print, you may be giving away far more than you realize. Because as Tom Waits taught us in the classic Step Right Up, the large print giveth and the small print taketh away.

Here’s a practical checklist of red flags to watch for if you want to look past the hype:

☐ Check Whether the “License” Actually Includes a Perpetual “Covenant Not to Sue”

A quick definitional note: a covenant not to sue is a contractual promise in which you agree in advance never to bring a legal claim against the other party — regardless of what happens, regardless of whether you even know you have a claim, and often regardless of whether the conduct at issue would otherwise be something you could sue for or get a court to stop (like with an injunction). Unlike a license, which grants permission and can expire, a covenant not to sue can be a permanent waiver of your right to seek a remedy. It’s the difference between handing someone a key to your house and signing a contract promising you’ll never call the police no matter what they do inside.

A real license gives someone permission to use your work under defined conditions, and when the term ends, so does the permission. Watch out for agreements that include a separate clause in which you irrevocably promise — both during and after the term — never to bring any claim against the company or even its users. If the covenant not only covers copyright, publicity rights, moral rights, defamation, and lawsuits over issues that may not exist yet, you are not licensing your work. You are surrendering your right to enforce your rights, permanently. Or you know, “forever.” Make sure you understand the difference before you sign.

☐ Beware a “Non-Exclusive” License That Binds Your Co-Writers

Remember the 100% licensing debacle back in 2016? Tenants-in-common co-ownership of a copyright means any co-owner can grant a non-exclusive license without the others’ consent — but that principle can be weaponized. If an agreement requires you to represent and warrant that no third-party consent is needed, and that you will not encourage your fellow songwriters to take any position inconsistent with the deal (again with the censorship), you may be dragging your co-writers into an arrangement they never agreed to. Worse, if the covenant not to sue extends to all contributors, your co-writers’ enforcement rights could be compromised by a deal they had no say in. Before you sign, make sure the AI platform isn’t leveraging TIC principles to bind people who aren’t at the table. Here’s why this matters in practice: under TIC co-ownership, a non-exclusive license granted by one co-owner is generally binding on all co-owners, even without their consent. That means if you grant a non-exclusive license — or, more critically, a covenant not to sue — covering the full composition, your co-writer may be unable to bring an infringement claim against the same company for the same use, because the company can point to your grant as a complete defense. The co-writer’s right to sue isn’t technically extinguished, but it’s rendered practically worthless. The result is that one publisher’s signature can neutralize enforcement rights across an entire song’s ownership chain. Ask your lawyer.

☐ Look for a Sweeping Pre-Signing Release

Some agreements bury a broad release of all claims arising before the effective date — known and unknown, suspected and unsuspected. That’s not a license, it’s a preemptive settlement masquerading as a license.  Worse, they may ask you to preemptively waive protections like California Civil Code Section 1542, which exists specifically to protect people in this exact situation. The statute prevents people from accidentally releasing claims they don’t yet know about. If an AI company has been training on your catalog without permission for years, a release like this could function like a contractual safe harbor and eliminate any leverage you had to seek compensation for that unauthorized use, or better yet an injunction. You know, kind of like the Music Modernization Act.  Ask yourself: why does a forward-looking license need a backward-looking release? Aside from wanting a pony.

☐ Make Sure “Training Rights” Aren’t Irrevocable in Practice

A license to include your works in a training corpus sounds civilized, but look closely at the removal mechanics (and take a class in “machine unlearning“). If the company is only required to retrain its model a limited number of times per year — say, twice — then even if you pull your catalog, your works may remain embedded in the AI model for months or even “forever”. There are no guarantees that “retraining” will actually remove your works from the model and, in fact, the literature suggests it won’t. And if the covenant not to sue survives the term for anything created while the deal was active (or before the deal was active), the training that already happened is effectively locked in. You may be inadvertently granting a right for yourself and maybe your co-writers that you can never meaningfully take back.

☐ Don’t Pre-Approve a Statutory Streaming License They May Not Be Entitled To

Some AI music platforms aspire to become full on-demand streaming services — and their agreements may include language contemplating exactly that expansion, with provisions stating the company will simply obtain a blanket mechanical license from the Mechanical Licensing Collective under 17 U.S.C. § 115(d). But whether a generative AI platform that creates synthetic music qualifies for the statutory compulsory license designed for traditional on-demand streaming is a genuinely open legal question. If you agree to terms that treat this expansion as a foregone conclusion — or worse, if your covenant not to sue or conditional authorization greenlights streaming functionality by default — you may be conceding the argument before it’s ever litigated. Don’t let an agreement’s assumptions about statutory eligibility become your assumptions. That question should be tested, not waived.

There’s a deeper problem here, too. The Section 115 compulsory license has always contained an anti-piracy prerequisite: you cannot obtain a compulsory license to use a musical composition if the sound recording you’re working from was not lawfully fixed or authorized by the sound recording’s copyright owner. If an AI platform trained its model on sound recordings it ingested without authorization (as is currently being litigated), its entire statutory license theory may be built on a foundation of infringement. The compulsory license was never designed to launder unauthorized use of sound recordings into lawful use of the compositions they embody. By agreeing to terms that treat the platform’s eligibility as settled, you may be implicitly conceding that the platform’s use of those sound recordings was authorized — a concession likely worth far more than anyone is probably paying for it and that can get you sideways with the sound recording owners.

☐ Scrutinize “Guardrail Failure” Safe Harbors

Technical safeguards — input filters, output filters, vocal classifiers — are only as good as the consequences for failure. Be wary of provisions that excuse the AI company from breach liability when its guardrails fail, so long as the failures are characterized as “inadvertent” and “de minimis” which are in the eye of the beholder and just buying a lawsuit.  If the agreement treats guardrail failures as non-breaches by default, you’ve effectively agreed that the company can produce unauthorized outputs of your works without meaningful accountability, as long as it promises to try to fix the problem after the fact with no stick if it fails.

☐ Watch Who Owns the AI Model — and Learned “Insights”

Ownership clauses in AI agreements often go further than you’d expect. The company may claim ownership not just of the AI model, but of all “insights” it learns which can be damn near anything. That “learning” is including those developed using your content. That language could be read to mean that everything the AI extracts, learns, or derives from your catalog belongs to the platform. Make sure you are not inadvertently ceding ownership of the creative intelligence embedded in your works.

☐ Don’t Let a Third Party’s Binding Calculation Determine Your Payment

I am no fan of market share revenue share deals, particularly when the revenue pool is a fixed number. Some revenue pool deals delegate the calculation of your market share — and therefore your payment — to a third party, and then declare that calculation to be binding on you, even if you had nothing to do with calculating either your market share (under the “license” not in general) or your share of the revenue or minimum guarantee. If you have no right to challenge the methodology or the math, or to audit that third party, you could be found to have agreed to be paid whatever someone else decides you’re owed, with no recourse if they get it wrong.

☐ Trace the Revenue Through Every Deduction Before Celebrating the Rate

A headline royalty rate means nothing if it’s applied to a revenue base that has already been carved down by layers of deductions including off the top fees, advertising costs, technical fees, inference compute costs, app-store commissions, performance royalties, and more. Each deduction may sound reasonable in isolation, but stacked together, they can reduce the revenue pool to a fraction of what you’d expect. Always model your actual payout, not just the stated percentage.

☐ Beware Conditional Authorizations That Expand the Deal Without Your Active Consent

Some agreements include provisions for future features such as API access, enterprise customer pricing, new product versions, downloads, or interactive streaming that automatically activate once a majority of other rightsholders sign on. If the trigger is what other labels or publishers do rather than what you approve, you may find that the scope of the license has expanded well beyond what you agreed to, without any additional negotiation or compensation.  And remember what they say about if everyone else was running off a cliff.

☐ Censorship Clauses: Don’t Agree to Never Contradict the Deal

Representation and warranty sections sometimes include a covenant that you will not take, or encourage your artists or songwriters to take, any position at any time (whether during or after the term and whether or not truthful) that is inconsistent with the hoorah narrative about AI or the applicable license. Read that carefully. It could be interpreted to prevent you — or your writers — from ever publicly criticizing the deal, advocating for stronger protections, or supporting legislation that conflicts with the agreement’s framework, even years after it expires even if the AI platform is in breach.  Aside from censoring your freedom of speech, this has nothing, and I mean nothing, to do with a license.

☐ Understand What Walled Garden Actually Means for Your Writers

A service that restricts AI-generated content to a “walled garden” with no downloads sounds contained. But if users can generate unlimited content using your works, share tracks or links to tracks across social media, and the company retains the right to expand into other product lines (including non-AI product lines like an on-demand streaming service) all within the same agreement, any “walled garden” may be pretty ephemeral.

☐ Confirm That Your Minimum Guarantee Is Actually Guaranteed

A minimum guarantee that is “fully recoupable” against future royalties is not a floor — it’s an advance. If the service underperforms, you keep the advance, but if it succeeds, the guarantee is just an interest-free loan. Make sure you understand whether the guarantee represents real minimum compensation or simply front-loaded royalties you would have earned anyway. Also, plan for both failure and success—if you’re a publisher or label, how on earth are you going to be able to account to your songwriters or artists while you’re recouping any minimum guarantee or afterwards?

☐ Demand Flow-Down Protections in the Platform’s Terms of Service

An AI platform’s Terms of Service are where your contractual protections actually meet the end user — and if the ToS doesn’t carry your rights forward, your rights may exist only on paper, if at all. Before you sign, confirm that the agreement requires the platform’s user-facing ToS to include, at a minimum:

  • An ownership disclaimer — users must acknowledge they acquire no copyright or ownership interest in AI outputs that embody your works.
  • A reverse-engineering prohibition — users must be prohibited from extracting, reconstructing, or isolating your works from the model’s outputs.
  • A downstream training restriction — users must be barred from using AI-generated outputs containing your works to train their own AI models.
  • User indemnification that flows to you — if a user misuses your works, you shouldn’t have to rely solely on the platform to make you whole.
  • A meaningful commercial-use definition and enforcement mechanism — if the deal says “personal, non-commercial use only,” the ToS needs to define what that means and impose real consequences for violations, not just account revocation. Remember, “non-commercial” has been used for text and data mining exceptions in various countries that are huge and unintended exceptions to copyright.
  • An anti-circumvention clause — users should be explicitly prohibited from attempting to bypass input/output filters and guardrails, not just prevented by technology that may fail.
  • Publisher review and approval rights over ToS language — if the agreement references ToS protections as part of your deal, you should have the right to review and approve the actual language implementing them.

If the platform isn’t required to flow these protections down to users, then the guardrails in your agreement are a ceiling, not a floor.

☐ Ask Whether Any Other Rightsholders Are Getting Equity — and Whether You Are, Too

If the agreement includes an MFN clause promising you’ll receive the “most favorable economic terms” offered to any other licensor, ask the obvious follow-up: are large rightsholders receiving equity stakes in the AI platform as part of their deals like the majors and Merlin did with Spotify? We’ve seen this movie before. When streaming platforms launched, labels negotiated equity positions that dramatically increased the total value of their agreements — value that was never shared with publishers or songwriters. If an AI company is offering stock, warrants, or other equity consideration to labels while offering publishers only cash royalties and a minimum guarantee, then the MFN clause is cosmetic. The “most favorable economic terms” aren’t favorable at all if they exclude the most valuable component of the deal. Before you accept the premise that you’re being treated equally, ask what the royalty rate would look like if nobody were getting equity. That’s the number that tells you whether the cash terms are fair on their own — or whether they’re subsidized by equity you’ll never see.

Now What: When an AI company presents you with a “licensing agreement,” read it like a litigator, not a dealmaker. (When presented with a contract, dealmakers look at the money, litigators look at the remedies.). The title of the document matters far less than what’s inside it. If the agreement includes a perpetual covenant not to sue, a retroactive release of claims, and an ownership clause that captures everything the AI learns from your work, what you’re being offered isn’t a license — it’s capitulation with a royalty attached.

Know what you’re signing. Read it yourself, don’t buy the hoorah.

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

@RickBeato on AI Artists

Is it at thing or is it disco? Our fave Rick Beato has a cautionary tale in this must watch video: AI can mimic but not truly create art. As generative tools get more prevalent, he urges thoughtful curation, artist-centered policies, and an emphasis on emotionally rich, human-driven creativity–also known as creativity. h/t Your Morning Coffee our favorite podcast.

Senator Cruz Joins the States on AI Safe Harbor Collapse— And the Moratorium Quietly Slinks Away

Silicon Valley Loses Bigly

In a symbolic vote that spoke volumes, the U.S. Senate decisively voted 99–1 to strike the toxic AI safe harbor moratorium from the vote-a-rama for the One Big Beautiful Bill Act (HR 1) according to the AP. Senator Ted Cruz, who had previously actively supported the measure, actually joined the bipartisan chorus in stripping it — an acknowledgment that the proposal had become politically radioactive.

To recap, the AI moratorium would have barred states from regulating artificial intelligence for up to 10 years, tying access to broadband and infrastructure funds to compliance. It triggered an immediate backlash: Republican governors, state attorneys general, parents’ groups, civil liberties organizations, and even independent artists condemned it as a blatant handout to Big Tech with yet another rent-seeking safe harbor.

Marsha Blackburn and Maria Cantwell to the Rescue

Credit where it’s due: Senator Marsha Blackburn (R–TN) was the linchpin in the Senate, working across the aisle with Sen. Maria Cantwell to introduce the amendment that finally killed the provision. Blackburn’s credibility with conservative and tech-wary voters gave other Republicans room to move — and once the tide turned, it became a rout. Her leadership was key to sending the signal to her Republican colleagues–including Senator Cruz–that this wasn’t a hill to die on.

Top Cover from President Trump?

But stripping the moratorium wasn’t just a Senate rebellion. This kind of reversal in must-pass, triple whip legislation doesn’t happen without top cover from the White House, and in all likelihood, Donald Trump himself. The provision was never a “last stand” issue in the art of the deal. Trump can plausibly say he gave industry players like Masayoshi Son, Meta, and Google a shot, but the resistance from the states made it politically untenable. It was frankly a poorly handled provision from the start, and there’s little evidence Trump was ever personally invested in it. He certainly didn’t make any public statements about it at all, which is why I always felt it was such an improbable deal point that it was always intended as a bargaining chip whether the staff knew it or not.

One thing is for damn sure–it ain’t coming back in the House which is another way you know you can stick a fork in it despite the churlish shillery types who are sulking off the pitch.

One final note on the process: it’s unfortunate that the Senate Parliamentarian made such a questionable call when she let the AI moratorium survive the Byrd Bath, despite it being so obviously not germane to reconciliation. The provision never should have made it this far in the first place — but oh well. Fortunately, the Senate stepped in and did what the process should have done from the outset.

Now what?

It ain’t over til it’s over. The battle with Silicon Valley may be over on this issue today, but that’s not to say the war is over. The AI moratorium may reappear, reshaped and rebranded, in future bills. But its defeat in the Senate is important. It proves that state-level resistance can still shape federal tech policy, even when it’s buried in omnibus legislation and wrapped in national security rhetoric.

Cruz’s shift wasn’t a betrayal of party leadership — it was a recognition that even in Washington, federalism still matters. And this time, the states — and our champion Marsha — held the line. 

Brava, madam. Well played.

This post first appeared on MusicTechPolicy

@human_artistry Campaign Letter Opposing AI Safe Harbor Moratorium in Big Beautiful Bill HR 1

Artist Rights Institute is pleased to support the Human Artistry Campaign’s letter to Senators Thune and Schumer opposing the AI safe harbor in the One Big Beautiful Bill Act. ARI joins with:

Opposition is rooted in the most justifiable reasons:

By wiping dozens of state laws off the books, the bill would undermine public safety, creators’ rights, and the ability of local communities to protect themselves from a fast-moving technology that is being rushed to the market by tech giants. State laws protecting people from invasive AI deepfakes would be at risk, along with a range of proposals designed to eliminate discrimination and bias in AI. For artists and creators, preempting state laws requiring Big tech to disclose the material they used to train their models, often to create new products that compete with the human creators’ originals, would make it difficult or impossible to prove this theft has occurred. As the Copyright Office’s Fair Use Report recently reaffirmed, many forms of this conduct are illegal under longstanding federal law. 

The moratorium is so vague that it is unclear whether it would actually prohibit states from addressing construction of data centers or the vast drain on the power grid to implement AI placement in states. This is a safe harbor on steroids and terrible for all creators.

@ArtistRights Institute Newsletter 5/5/25

The Artist Rights Watch podcast returns for another season! This week’s episode features Chris Castle on An Artist’s Guide to Record Releases Part 2. Download it here or subscribe wherever you get your audio podcasts.

New Survey for Songwriters: We are surveying songwriters about whether they want to form a certified union. Please fill out our short Survey Monkey confidential survey here! Thanks!

Texas Scalpers Bill of Rights Legislation

Can this Texas House bill help curb high ticket prices? Depends whom you ask (Marcheta Fornoff/KERA News)

Texas lawmakers target ticket fees and resale restrictions in new legislative push (Abigail Velez/CBS Austin)

@ArtistRights Institute opposes Texas Ticketing Legislation the “Scalpers’ Bill of Rights” (Chris Castle/Artist Rights Watch)

Streaming

Spotify’s Earnings Points To A “Catch Up” On Songwriter Royalties At Crb For Royalty Justice (Chris Castle/MusicTechPolicy)

Streaming Is Now Just As Crowded With Ads As Old School TV (Rick Porter/Hollywood Reporter)

Spotify Stock Falls On Music Streamer’s Mixed Q1 Report (Patrick Seitz/Investors Business Daily)

Economy

The Slowdown at Ports Is a Warning of Rough Economic Seas Ahead (Aarian Marshall/Wired)

What To Expect From Wednesday’s Federal Reserve Meeting (Diccon Hyatt/Investopedia)

Spotify Q1 2025 Earnings Call: Daniel Ek Talks Growth, Pricing, Superfan Products, And A Future Where The Platform Could Reach 1bn Subscribers (Murray Stassen/Music Business Worldwide)

Artist Rights and AI

SAG-AFTRA National Board Approves Commercials Contracts That Prevent AI, Digital Replicas Without Consent (JD Knapp/The Wrap)

Generative AI providers see first steps for EU code of practice on content labels (Luca Bertuzzi/Mlex)

A Judge Says Meta’s AI Copyright Case Is About ‘the Next Taylor Swift’ (Kate Knibbs/Wired)

Antitrust

Google faces September trial on ad tech antitrust remedies (David Shepardson and Jody Godoy/Reuters)

TikTok

Ireland fines TikTok 530 million euros for sending EU user data to China (Ryan Browne/CNBC)

@ArtistRights Newsletter 4/14/25

The Artist Rights Watch podcast returns for another season! This week’s episode features AI Legislation, A View from Europe: Helienne Lindvall, President of the European Composer and Songwriter Alliance (ECSA) and ARI Director Chris Castle in conversation regarding current issues for creators regarding the EU AI Act and the UK Text and Data Mining legislation. Download it here or subscribe wherever you get your audio podcasts.

New Survey for Songwriters: We are surveying songwriters about whether they want to form a certified union. Please fill out our short Survey Monkey confidential survey here! Thanks!

AI Litigation: Kadrey v. Meta

Law Professors Reject Meta’s Fair Use Defense in Friend of the Court Brief

Ticketing
Viagogo failing to prevent potentially unlawful practices, listings on resale site suggest that scalpers are speculatively selling tickets they do not yet have (Rob Davies/The Guardian)

ALEC Astroturf Ticketing Bill Surfaces in North Carolina Legislation

ALEC Ticketing Bill Surfaces in Texas to Rip Off Texas Artists (Chris Castle/MusicTechPolicy)

International AI Legislation

Brazil’s AI Act: A New Era of AI Regulation (Daniela Atanasovska and Lejla Robeli/GDPR Local)

Why robots.txt won’t get it done for AI Opt Outs (Chris Castle/MusicTechPolicy)

Feature TranslationHow has the West’s misjudgment of China’s AI ecosystem distorted the global technology competition landscape (Jeffrey Ding/ChinAI)

Unethical AI Training Harms Creators and Society, Argues AI Pioneer (Ed Nawotka/Publishers Weekly) 

AI Ethics

Céline Dion Calls Out AI-Generated Music Claiming to Feature the Iconic Singer Without Her Permission (Marina Watts/People)

Splice CEO Discusses Ethical Boundaries of AI in Music​ (Nilay Patel/The Verge)

Spotify’s Bold AI Gamble Could Disrupt The Entire Music Industry (Bernard Marr/Forbes)

Books

Apple in China: The Capture of the World’s Greatest Company by Patrick McGee (Coming May 13)

PRESS RELEASE: @Human_Artistry Campaign Endorses NO FAKES Act to Protect Personhood from AI

For Immediate Release

HUMAN ARTISTRY CAMPAIGN ENDORSES NO FAKES ACT

Bipartisan Bill Reintroduced by Senators Blackburn, Coons, Tillis, & Klobuchar and Representatives Salazar, Dean, Moran, Balint and Colleagues

Create New Federal Right for Use of Voice and Visual Likeness
in Digital Replicas

Empowers Artists, Voice Actors, and Individual Victims to Fight Back Against
AI Deepfakes and Voice Clones

WASHINGTON, DC (April 9, 2025) – Amid global debate over guardrails needed for AI, the Human Artistry Campaign today announced its support for the reintroduced “Nurture Originals, Foster Art, and Keep Entertainment Safe Act of 2025” (“NO FAKES Act”) – landmark legislation giving every person an enforceable new federal intellectual property right in their image and voice. 

Building off the original NO FAKES legislation introduced last Congress, the updated bill was reintroduced today by Senators Marsha Blackburn (R-TN), Chris Coons (D-DE), Thom Tillis (R-NC), Amy Klobuchar (D-MN) alongside Representatives María Elvira Salazar (R-FL-27), Madeleine Dean (D-PA-4), Nathaniel Moran (R-TX-1), and Becca Balint (D-VT-At Large) and bipartisan colleagues.

The legislation sets a strong federal baseline protecting all Americans from invasive AI-generated deepfakes flooding digital platforms today. From young students bullied by non-consensual sexually explicit deepfakes to families scammed by voice clones to recording artists and performers replicated to sing or perform in ways they never did, the NO FAKES Act provides powerful remedies requiring platforms to quickly take down unconsented deepfakes and voice clones and allowing rights​​holders to seek damages from creators and distributors of AI models designed specifically to create harmful digital replicas.

The legislation’s thoughtful, measured approach preserves existing state causes of action and rights of publicity, including Tennessee’s groundbreaking ELVIS Act. It also contains carefully calibrated exceptions to protect free speech, open discourse and creative storytelling – without trampling the underlying need for real, enforceable protection against the vast range of invasive and harmful deepfakes and voice clones.

Human Artistry Campaign Senior Advisor Dr. Moiya McTier released the following statement in support of the legislation:

​“The Human Artistry Campaign stands for preserving essential qualities of all individuals – beginning with a right to their own voice and image. The NO FAKES Act is an important step towards necessary protections that also support free speech and AI development. The Human Artistry Campaign commends Senators Blackburn, Coons, Tillis, and Klobuchar and Representatives Salazar, Dean, Moran, Balint, and their colleagues for shepherding bipartisan support for this landmark legislation, a necessity for every American to have a right to their own identity as highly realistic voice clones and deepfakes become more pervasive.

Dr. Moiya McTier, Human Artistry Campaign Senior Advisor

By establishing clear rules for the new federal voice and image right, the NO FAKES Act will power innovation and responsible, pro-human uses of powerful AI technologies while providing strong protections for artists, minors and others. This important bill has cross-sector support from Human Artistry Campaign members and companies such as OpenAI, Google, Amazon, Adobe and IBM. The NO FAKES Act is a strong step forward for American leadership that erects clear guardrails for AI and real accountability for those who reject the path of responsibility and consent.

Learn more & let your representatives know Congress should pass NO FAKES Act here.

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ABOUT THE HUMAN ARTISTRY CAMPAIGN: The Human Artistry Campaign is the global initiative for the advancement of responsible AI – working to ensure it develops in ways that strengthen the creative ecosystem, while also respecting and furthering the indispensable value of human artistry to culture. Across 34 countries, more than 180 organizations have united to protect every form of human expression and creative endeavor they represent – journalists, recording artists, photographers, actors, songwriters, composers, publishers, independent record labels, athletes and more. The growing coalition champions seven core principles for keeping human creativity at the center of technological innovation. For further information, please visit humanartistrycampaign.com

@human_artistry Calls Out AI Voice Cloning

Here’s just one reason why we can’t trust Big Tech for opt out (or really any other security that stops them from doing what they want to do)