ai – The 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.

December 12, 2025 by Trichordist

There Is No ‘Right to Train’: How AI Labs Are Trying to Manufacture a Safe Harbor for Theft

Every few months, an AI company wins a procedural round in court or secures a sympathetic sound bite about “transformative fair use.” Within hours, the headlines declare a new doctrine of spin: the right to train AI on copyrighted works. But let’s be clear — no such right exists and probably never will. That doesn’t mean they won’t keep trying.

A “right to train” is not found anywhere in the Copyright Act or any other law. It’s also not found in court cases on fair-use that the AI lobby leans on. It’s a slogan and it’s spin, not a statute. What we’re watching is a coordinated effort by the major AI labs to manufacture a safe harbor through litigation — using every favorable fair-use ruling to carve out what looks like a precedent for blanket immunity. Then they’ll get one of their shills in Congress or a state legislature to introduce legislation as though a “right to train” was there all along.

How the “Right to Train” Narrative Took Shape

The phrase first appeared in tech-industry briefs and policy papers describing model training as a kind of “machine learning fair use.” The logic goes like this: since humans can read a book and learn from it, a machine should be able to “learn” from the same book without permission.

That analogy collapses under scrutiny. First of all, humans typically bought the book they read or checked it out from a library. Humans don’t make bit-for-bit copies of everything they read, and they don’t reproduce or monetize those copies at global scale. AI training does exactly that — storing expressive works inside model weights, then re-deploying them to generate derivative material.

But the repetitive chant of the term “right to train” serves a purpose: to normalize the idea that AI companies are entitled to scrape, store, and replicate human creativity without consent. Each time a court finds a narrow fair-use defense in a context that doesn’t involve piracy or derivative outputs (because they lose on training on stolen goods like in the Anthropic and Meta cases), the labs and their shills trumpet it as proof that training itself is categorically protected. It isn’t and no court has ever ruled that it is and likely never will.

Fair Use Is Not a Safe Harbor

Fair use is a case-by-case defense to copyright infringement, not a standing permission slip. It weighs purpose, amount, transformation, and market effect — all of which vary depending on the facts. But AI companies are trying to convert that flexible doctrine into a brand new safe harbor: a default assumption that all training is fair use unless proven otherwise. They love a safe harbor in Silicon Valley and routinely abuse them like Section 230, the DMCA and Title I of the Music Modernization Act.

That’s exactly backward. The Copyright Office’s own report makes clear that the legality of training depends on how the data was acquired and what the model does with it. A developer who trains on pirated or paywalled material like Anthropic, Meta and probably all of them to one degree or another, can’t launder infringement through the word “training.”

Even if courts were to recognize limited fair use for truly lawful training, that protection would never extend to datasets built from pirate websites, torrent mirrors, or unlicensed repositories like Sci-Hub, Z-Library, or Common Crawl’s scraped paywalls—more on the scummy Common Crawl another time. The DMCA’s safe harbors don’t protect platforms that knowingly host stolen goods — and neither would any hypothetical “right to train.”

Yet a safe harbor is precisely what the labs are seeking: a doctrine that would retroactively bless mass infringement like Spotify got in the Music Modernization Act and preempt accountability for the sources they used.

And not only do they want a safe harbor — they want it for free. No licenses, no royalties, no dataset audits, no compensation. What do they want? FREE STUFF. When do they want it? NOW! Just blanket immunity, subsidized by every artist, author, and journalist whose work they ingested without consent or payment.

The Real Motive Behind the Push

The reason AI companies need a “right to train” is simple: without it, they have no reliable legal basis for the data that powers their models and they are too cheap to pay and to careless to take the time to license. Most of their “training corpora” were built years before any licenses were contemplated — scraped from the open web, archives, and pirate libraries under the assumption that no one would notice.

This is particularly important for books. Training on books is vital for AI models because books provide structured, high-quality language, complex reasoning, and deep cultural context. They teach models coherence, logic, and creativity that short-form internet text lacks. Without books, AI systems lose depth, nuance, and the ability to understand sustained argument, narrative, and style.

Without books, AI labs have no business. That’s why they steal books. Very simple, really.

Now that creators are suing, the labs are trying to reverse-engineer legitimacy. They want to turn each court ruling that nudges fair use in their direction into a brick in the wall of a judicially-manufactured safe harbor — one that Congress never passed and rights-holders never agreed to and would never agree to.

But safe harbors are meant to protect good-faith intermediaries who act responsibly once notified of infringement. AI labs are not intermediaries; they are direct beneficiaries. Their entire business model depends on retaining the stolen data permanently in model weights that cannot be erased. The “right to train” is not a right — it’s a rhetorical weapon to make theft sound inevitable and a demand from the richest corporations in commercial history for yet another government-sponsored subsidy of infringement by bad actors.

The Myth of the Inevitable Machine

AI’s defenders claim that training on copyrighted works is as natural as human learning. But there’s nothing natural about hoarding other people’s labor at planetary scale and calling it innovation. The truth is simpler: the “right to train” is a marketing term invented to launder unlawful data practices into respectability.

If courts and lawmakers don’t call it what it is — a manufactured, safe harbor for piracy to benefit some of the biggest free riders who ever snarfed down corporate welfare — then history will repeat itself. What Grokster tried to do with distribution, AI is trying to do with cognition: privatize the world’s creative output and claim immunity for the theft.

November 5, 2025 by thetrichordist

“You don’t need to train on novels and pop songs to get the benefits of AI in science” @ednewtonrex

You Don’t Need to Steal Art to Cure Cancer: Why Ed Newton-Rex Is Right About AI and Copyright

Ed Newton-Rex said the quiet truth out loud: you don’t need to scrape the world’s creative works to build AI that saves lives. Or even beat the Chinese Communist Party.

It’s a myth that AI “has to” ingest novels and pop lyrics to learn language. Models acquire syntax, semantics, and pragmatics from any large, diverse corpus of natural language. That includes transcribed speech, forums, technical manuals, government documents, Wikipedia, scientific papers, and licensed conversational data. Speech systems learn from audio–text pairs, not necessarily fiction; text models learn distributional patterns wherever language appears. Of course, literary works can enrich style, but they’re not necessary for competence: instruction tuning, dialogue data, and domain corpora yield fluent models without raiding copyrighted art. In short, creative literature is optional seasoning, not the core ingredient for teaching machines to “speak.”

Google’s new cancer-therapy paper proves the point. Their model wasn’t trained on novels, lyrics, or paintings. It was trained responsibly on scientific data. And yet it achieved real, measurable progress in biomedical research. That simple fact dismantles one of Silicon Valley’s most persistent myths: that copyright is somehow an obstacle to innovation.

You don’t need to train on Joni Mitchell to discover a new gene pathway. You don’t need to ingest John Coltrane to find a drug target. AI used for science can thrive within the guardrails of copyright because science itself already has its own open-data ecosystems—peer-reviewed, licensed, and transparent.

The companies like Anthropic and Meta insisting that “fair use” covers mass ingestion of stolen creative works aren’t curing diseases; they’re training entertainment engines. They’re ripping off artists’ livelihoods to make commercial chatbots, story generators, and synthetic-voice platforms designed to compete against the very creators whose works they exploited. That’s not innovation—it’s market capture through appropriation.

They do it for reasons old as time—they do it for the money.

The ethical divide is clear:

AI for discovery builds on licensed scientific data.
AI for mimicry plunders culture to sell imitation.

We should celebrate the first and regulate the second. Upholding copyright and requiring provenance disclosures doesn’t hinder progress—it restores integrity. The same society that applauds AI in medical breakthroughs can also insist that creative industries remain human-centered and law-abiding. Civil-military fusion doesn’t imply that there’s only two ingredients in the gumbo of life.

If Google can advance cancer research without stealing art, so can everyone else and so can Google keep different rules for the entertainment side of their business or investment portfolio. The choice isn’t between curing cancer and protecting artists—it’s between honesty and opportunism. The repeated whinging of AI labs about “because China” would be a lot more believable if they used their political influence to get the CCP to release Hong Kong activist Jimmy Lai from stir. We can join Jimmy and his amazingly brave son Sebastian and say “because China”, too. #FreeJimmyLai

October 17, 2025October 17, 2025 by Trichordist

Sir Lucian Grainge Just Drew the Brightest Line Yet on AI

by Chris Castle

Universal Music Group’s CEO Sir Lucian Grainge has put the industry on notice in an internal memo to Universal employees: UMG will not license any AI model that uses an artist’s voice—or generates new songs incorporating an artist’s existing songs—without that artist’s consent. This isn’t just a slogan; it’s a licensing policy, an advocacy position, and a deal-making leverage all rolled into one. After the Sora 2 disaster, I have to believe that OpenAI is at the top of the list.

Here’s the memo:

Dear Colleagues,

I am writing today to update you on the progress that we are making on our efforts to take advantage of the developing commercial opportunities presented by Gen AI technology for the benefit of all our artists and songwriters.

I want to address three specific topics:

Responsible Gen AI company and product agreements; How our artists can participate; and What we are doing to encourage responsible AI public policies.

UMG is playing a pioneering role in fostering AI’s enormous potential. While our progress is significant, the speed at which this technology is developing makes it important that you are all continually updated on our efforts and well-versed on the strategy and approach.

The foundation of what we’re doing is the belief that together, we can foster a healthy commercial AI ecosystem in which artists, songwriters, music companies and technology companies can all flourish together.

NEW AGREEMENTS

To explore the varied opportunities and determine the best approaches, we have been working with AI developers to put their ideas to the test. In fact, we were the first company to enter into AI-related agreements with companies ranging from major platforms such as YouTube, TikTok and Meta to emerging entrepreneurs such as BandLab, Soundlabs, and more. Both creatively and commercially our portfolio of AI partnerships continues to expand.

Very recently, Universal Music Japan announced an agreement with KDDI, a leading Japanese telecommunications company, to develop new music experiences for fans and artists using Gen AI. And we are very actively engaged with nearly a dozen different companies on significant new products and service plans that hold promise for a dramatic expansion of the AI music landscape. Further, we’re seeing other related advancements. While just scratching the surface of AI’s enormous potential, Spotify’s recent integration with ChatGPT offers a pathway to move fluidly from query and discovery to enjoyment of music—and all within a monetized ecosystem.

HOW OUR ARTISTS CAN PARTICIPATE

Based on what we’ve done with our AI partners to date, and the new discussions that are underway, we can unequivocally say that AI has the potential to deliver creative tools that will enable us to connect our artists with their fans in new ways—and with advanced capability on a scale we’ve never encountered.

Further, I believe that Agentic AI, which dynamically employs complex reasoning and adaptation, has the potential to revolutionize how fans interact with and discover music.

I know that we will successfully navigate as well as seize these opportunities and that these new products could constitute a significant source of new future revenue for artists and songwriters.

We will be actively engaged in discussing all of these developments with the entire creative community.

While some of the biggest opportunities will require further exploration, we are excited by the compelling AI models we’re seeing emerge.

We will only consider advancing AI products based on models that are trained responsibly. That is why we have entered into agreements with AI developers such as ProRata and KLAY, among others, and are in discussions with numerous additional like-minded companies whose products provide accurate attribution and tools which empower and compensate artists—products that both protect music and enhance its monetization.

And to be clear—and this is very important—we will NOT license any model that uses an artist’s voice or generates new songs which incorporate an artist’s existing songs without their consent.

New AI products will be joined by many other similar ones that will soon be coming to market, and we have established teams throughout UMG that will be working with artists and their representatives to bring these opportunities directly to them.

RESPONSIBLE PUBLIC POLICIES COVERING AI

We remain acutely aware of the fact that large and powerful AI companies are pressuring governments around the world to legitimize the training of AI technology on copyrighted material without owner consent or compensation, among other proposals.

To be clear: all these misguided proposals amount to nothing more than the unauthorized (and, we believe, illegal) exploitation of the rights and property of creative artists.

In addition, we are acting in the marketplace to see our partners embrace responsible and ethical AI policies and we’re proud of the progress being made there. For example, having accurately predicted the rapid rise of AI “slop” on streaming platforms, in 2023 we introduced Artist-Centric principles to combat what is essentially platform pollution. Since then, many of our platform partners have made significant progress in putting in place measures to address the diversion of royalties, infringement and fraud—all to the benefit of the entire music ecosystem.

We commend our partners for taking action to address this urgent issue, consistent with our Artist-Centric approach. Further, we recently announced an agreement with SoundPatrol, a new company led by Stanford scientists that employs patented technology to protect artists’ work from unauthorized use in AI music generators.

We are confident that by displaying our willingness as a community to embrace those commercial AI models which value and enhance human artistry, we are demonstrating that market-based solutions promoting innovation are the answer.

LEADING THE WAY FORWARD

So, as we work to assure safeguards for artists, we will help lead the way forward, which is why we are exploring and finding innovative ways to use this revolutionary technology to create new commercial opportunities for artists and songwriters while simultaneously aiding and protecting human creativity.

I’m very excited about the products we’re seeing and what the future holds. I will update you all further on our progress.

Lucian

Mr. Grainge’s position reframes the conversation from “Can we scrape?” to “How do we get consent and compensate?” That shift matters because AI that clones voices or reconstitutes catalog works is not a neutral utility—it’s a market participant competing with human creators and the rights they rely on.

If everything is “transformative” then nothing is protected—and that guts not just copyright, but artists’ name–image–likeness (NIL), right of publicity and in some jurisdictions, moral rights. A scrape-first, justify-later posture erases ownership, antagonizes creators living and dead, and makes catalogs unpriceable. Why would Universal—or any other rightsholder—partner with a company that treats works and identity as free training fuel? What’s great about Lucian’s statement is he’s putting a flag in the ground: the industry leader will not do business with bad actors, regardless of the consequences.

What This Means in Practice

Consent as the gate. Voice clones and “new songs” derived from existing songs require affirmative artist approval—full stop.
Provenance as the standard. AI firms that want first-party deals must prove lawful ingestion, audited datasets, and enforceable guardrails against impersonation.
Aligned incentives. Where consent exists, there’s room for discovery tools, creator utilities, and new revenue streams; where it doesn’t, there’s no deal.

Watermarks and “AI-generated” labels don’t cure false endorsement, right-of-publicity violations, or market substitution. Platforms that design, market, or profit from celebrity emulation without consent aren’t innovating—they’re externalizing legal and ethical risk onto artists.

Moral Rights: Why This Resonates Globally

Universal’s consent-first stance will resonate in moral-rights jurisdictions where authors and performers hold inalienable rights of attribution and integrity (e.g., France’s droit moral, Germany’s Urheberpersönlichkeitsrecht). AI voice clones and “sound-alike” outputs can misattribute authorship, distort a creator’s artistic identity, or subject their work to derogatory treatment—classic moral-rights harms. Because many countries recognize post-mortem moral rights and performers’ neighboring rights, the “no consent, no license” rule is not just good governance—it’s internationally compatible rights stewardship.

Industry Leadership vs. the “Opt-Out” Mirage

It is absolutely critical that the industry leader actively opposes the absurd “opt-out” gambit and other sleights of hand Big Technocrats are pushing to drive a Mack truck through so-called text-and-data-mining loopholes. Their playbook is simple: legitimize mass training on copyrighted works first, then dare creators to find buried settings or after-the-fact exclusions. That flips property rights on their head and is essentially a retroactive safe harbor,

As Mr. Grainge notes, large AI companies are pressuring governments to bless training on copyrighted material without owner consent or compensation. Those proposals amount to the unauthorized—and unlawful—exploitation of artists’ rights and property. By refusing to play along, Universal isn’t just protecting its catalog; it’s defending the baseline principle that creative labor isn’t scrapable.

Consent or Nothing

Let’s be honest: if AI labs were serious about licensing, we wouldn’t have come one narrow miss away from a U.S. state law AI moratorium triggered by their own overreach. That wasn’t just a safe harbor for copyright infringement, that was a safe harbor for everything from privacy, to consumer protection, to child exploitation, to everything. That’s why it died 99-1 in the Senate, but it was a close run thing,,

And realize, that’s exactly what they want when they are left to their own devices, so to speak. The “opt-out” mirage, the scraping euphemisms, and the rush to codify TDM loopholes all point the same direction—avoid consent and avoid compensation. Universal’s position is the necessary counterweight: consent-first, provenance-audited, revenue-sharing with artists and songwriters (and I would add nonfeatured artists and vocalists) or no deal. Anything less invites regulatory whiplash, a race-to-the-bottom for human creativity, and a permanent breach of trust with artists and their estates.

Reading between the lines, Mr. Grainge has identified AI as both a compelling opportunity and an existential crisis. Let’s see if the others come with him and stare down the bad guys.

[This post first appeared on Artist Rights Watch]

October 16, 2025 by Trichordist Editor

Artist Rights Are Innovation, Too! White House Opens AI Policy RFI and Artists Should Be Heard

The White House has opened a major Request for Information (RFI) on the future of artificial intelligence regulation — and anyone can submit a comment. That means you. This is not just another government exercise. It’s a real opportunity for creators, musicians, songwriters, and artists to make their voices heard in shaping the laws that will govern AI and its impact on culture for decades to come.

Too often, artists find out about these processes after the decisions are already made. This time, we don’t have to be left out. The comment period is open now, and you don’t need to be a lawyer or a lobbyist to participate — you just need to care about the future of your work and your rights. Remember—property rights are innovation, too, just ask Hernando de Soto (Mystery of Capital) or any honest economist.

Here are four key issues in the RFI that matter deeply to artists — and why your voice is critical on each:

1. Transparency and Provenance: Artists Deserve to Know When Their Work Is Used

One of the most important questions in the RFI asks how AI companies should document and disclose the creative works used to train their models. Right now, most platforms hide behind trade secrets and refuse to reveal what they ingested. For artists, that means you might never know if your songs, photographs, or writing were taken without permission — even if they now power billion-dollar AI products.

This RFI is a chance to demand real provenance requirements: records of what was used, when, and how. Without this transparency, artists cannot protect their rights or seek compensation. A strong public record of support for provenance could shape future rules and force platforms into accountability.

2. Derivative Works and AI Memory: Creativity Shouldn’t Be Stolen Twice

The RFI also raises a subtle but crucial issue: even if companies delete unauthorized copies of works from their training sets, the models still retain and exploit those works in their weights and “memory.” This internal use is itself a derivative work — and it should be treated as one under the law.

Artists should urge regulators to clarify that training outputs and model weights built from copyrighted material are not immune from copyright. This is essential to closing a dangerous loophole: without it, platforms can claim to “delete” your work while continuing to profit from its presence inside their AI systems.

3. Meaningful Opt-Out: Creators Must Control How Their Work Is Used

Another critical question is whether creators should have a clear, meaningful opt-out mechanism that prevents their work from being used in AI training or generation without permission. As Artist Rights Institute and many others have demonstrated, “Robots.txt” disclaimers buried in obscure places are not enough. Artists need a legally enforceable system—not another worthless DMCA-style notice and notice and notice and notice and notice and maybe takedown system that platforms must respect and that regulators can audit.

A robust opt-out system would restore agency to creators, giving them the ability to decide if, when, and how their work enters AI pipelines. It would also create pressure on companies to build legitimate licensing systems rather than relying on theft.

4. Anti-Piracy Rule: National Security Is Not a License to Steal

Finally, the RFI invites comment on how national priorities should shape AI development and it’s vital that artists speak clearly here. There must be a bright-line rule that training AI models on pirated content is never excused by national security or “public interest” arguments. This is a real thing—pirate libraries are clearly front and center in AI litigation which have largely turned into piracy cases because the AI lab “national champions” steal books and everything else.

If a private soldier stole a carton of milk from a chow hall, he’d likely lose his security clearance. Yet some AI companies have built entire models on stolen creative works and now argue that government contracts justify their conduct. That logic is backwards. A nation that excuses intellectual property theft in the name of “security” corrodes the rule of law and undermines the very innovation it claims to protect. On top of it, the truth of the case is that the man Zuckerberg is a thief, yet he is invited to dinner at the White House.

A clear anti-piracy rule would ensure that public-private partnerships in AI development follow the same legal and ethical standards we expect of every citizen — and that creators are not forced to subsidize government technology programs with uncompensated labor. Any “AI champion” who steals should lose or be denied a security clearance.

Your Voice Matters — Submit a Comment

The White House needs to hear directly from creators — not just from tech companies and trade associations. Comments from artists, songwriters, and creative professionals will help shape how regulators understand the stakes and set the boundaries.

You don’t need legal training to submit a comment. Speak from your own experience: how unauthorized use affects your work, why transparency matters, what a meaningful opt-out would look like, and why piracy can never be justified by national security.

👉 Submit your comment here before the October 27 deadline.

2025-18737 Download

October 3, 2025 by thetrichordist

Senator Josh @HawleyMO Throws Down on Big Tech’s Copyright Theft

Senator Josh Hawley (@HawleyMO) says that if the AI revolution continues to proceed unchecked, it will lead to extreme power concentration.

"It is undermining many of our cherished ideals, and if that keeps on, AI will work to undermine America." pic.twitter.com/OLY0G4F7dw
— ControlAI (@ai_ctrl) September 18, 2025

I believe Americans should have the ability to defend their human data, and their rights to that data, against the largest copyright theft in the history of the world.

Millions of Americans have spent the past two decades speaking and engaging online. Many of you here today have online profiles and writings and creative productions that you care deeply about. And rightly so. It’s your work. It’s you.

What if I told you that AI models have already been trained on enough copyrighted works to fill the Library of Congress 22 times over? For me, that makes it very simple: We need a legal mechanism that allows Americans to freely defend those creations. I say let’s empower human beings by protecting the very human data they create. Assign property rights to specific forms of data, create legal liability for the companies who use that data and, finally, fully repeal Section 230. Open the courtroom doors. Let the people sue those who take their rights, including those who do it using AI.

Third, we must add sensible guardrails to the emergent AI economy and hold concentrated economic power to account. These giant companies have made no secret of their ambitions to radically reshape our economic life. So, we ought to require transparency and reporting each time they replace a working man with a machine.

And the government should inspect all of these frontier AI systems, so we can better understand what the tech titans plan to build and deploy.

Ultimately, when it comes to guardrails, protecting our children should be our lodestar. You may have seen recently how Meta green-lit its own chatbots to have sensual conversations with children—yes, you heard me right. Meta’s own internal documents permitted lurid conversations that no parent would ever contemplate. And most tragically, ChatGPT recently encouraged a troubled teenager to commit suicide—even providing detailed instructions on how to do it.

We absolutely must require and enforce rigorous technical standards to bar inappropriate or harmful interactions with minors. And we should think seriously about age verification for chatbots and agents. We don’t let kids drive or drink or do a thousand other harmful things. The same standards should apply to AI.

Fourth and finally, while Congress gets its act together to do all of this, we can’t kneecap our state governments from moving first. Some of you may have seen that there was a major effort in Congress to ban states from regulating AI for 10 years—and a whole decade is an eternity when it comes to AI development and deployment. This terrible policy was nearly adopted in the reconciliation bill this summer, and it could have thrown out strong anti-porn and child online safety laws, to name a few. Think about that: conservatives out to destroy the very concept of federalism that they cherish … all in the name of Big Tech. Well, we killed it on the Senate floor. And we ought to make sure that bad idea stays dead.

We’ve faced technological disruption before—and we’ve acted to make technology serve us, the people. Powered flight changed travel forever, but you can’t land a plane on your driveway. Splitting the atom fundamentally changed our view of physics, but nobody expects to run a personal reactor in their basement. The internet completely recast communication and media, but YouTube will still take down your video if you violate a copyright. By the same token, we can—and we should—demand that AI empower Americans, not destroy their rights . . . or their jobs . . . or their lives.

September 22, 2025 by thetrichordist

If you got one of these emails from Spotify, you might be interested

Spotify failed to consult any of the people who drive fans to the data abattoir: the musicians, artists, podcasters and authors.

Spotify has quietly tightened the screws on AI this summer—while simultaneously clarifying how it uses your data to power its own machine‑learning features. For artists, rightsholders, developers, and policy folks, the combination matters: Spotify is making it harder for outsiders to train models on Spotify data, even as it codifies its own first‑party uses like AI DJ and personalized playlists.

Spotify is drawing a bright line: no training models on Spotify; yes to Spotify training its own. If you’re an artist or developer, that means stronger contractual leverage against third‑party scrapers—but also a need to sharpen your own data‑governance and licensing posture. Expect other platforms in music and podcasting to follow suit—and for regulators to ask tougher questions about how platform ML features are audited, licensed, and accounted for.

Below is a plain‑English (hopefully) breakdown of what changed, what’s new or newly explicit, and the practical implications for different stakeholders.

Explicit ban on using Spotify to train AI models (third parties).

Spotify’s User Guidelines now flatly prohibit “crawling” or “scraping” the service and, crucially, “using any part of the Services or Content to train a machine learning or AI model.” That’s a categorical no for bots and bulk data slurps. The Developer Policy mirrors this: apps using the Web API may not “use the Spotify Platform or any Spotify Content to train a machine learning or AI model.” In short: if your product ingests Spotify data, you’re in violation of the rules and risk enforcement and access revocation.

Spotify’s own AI/ML uses are clearer—and broad.

The Privacy Policy (effective August 27, 2025) spells out that Spotify uses personal data to “develop and train” algorithmic and machine‑learning models to improve recommendations, build AI features (like AI DJ and AI playlists), and enforce rules. That legal basis is framed largely as Spotify’s “legitimate interests.” Translation: your usage, voice, and other data can feed Spotify’s own models.

The user content license is very broad.

If you post “User Content” (messages, playlist titles, descriptions, images, comments, etc.), you grant Spotify a worldwide, sublicensable, transferable, royalty‑free, irrevocable license to reproduce, modify, create derivative works from, distribute, perform, and display that content in any medium. That’s standard platform drafting these days, but the scope—including derivative works—has AI‑era consequences for anything you upload to or create within Spotify’s ecosystem (e.g., playlist titles, cover images, comments).

Anti‑manipulation and anti‑automation rules are baked in.

The User Guidelines and Developer Policy double down on bans against bots, artificial streaming, and traffic manipulation. If you’re building tools that touch the Spotify graph, treat “no automated collection, no metric‑gaming, no derived profiling” as table stakes—or risk enforcement, up to termination of access.

Data‑sharing signals to rightsholders continue.

Spotify says it can provide pseudonymized listening data to rightsholders under existing deals. That’s not new, but in the ML context it underscores why parallel data flows to third parties are tightly controlled: Spotify wants to be the gateway for data, not the faucet you can plumb yourself.

What this means by role:

• Artists & labels: The AI‑training ban gives you a clear contractual hook against services that scrape Spotify to build recommenders, clones, or vocal/style models. Document violations (timestamps, IPs, payloads) and send notices citing the User Guidelines and Developer Policy. Meanwhile, assume your own usage and voice interactions can be used to improve Spotify’s models—something to consider for privacy reviews and internal policies.

• Publishers and collecting societies: The combination of “no third‑party training” + “first‑party ML training” is a policy trend to watch across platforms. It raises familiar questions about derivative data, model outputs, and whether platform machine learning features create new accounting categories—or require new audit rights—in future licenses.

• Policymakers: Read this as another brick in the “closed data/open model risk” wall. Platforms restrict external extraction while expanding internal model claims. That asymmetry will shape future debates over data‑access mandates, competition remedies, and model‑audit rights—especially where platform ML features may substitute for third‑party discovery tools.

Practical to‑dos

1) For rights owners: Add explicit “no platform‑sourced training” language in your vendor, distributor, or analytics contracts. Track and log known scrapers and third‑party tools that might be training off Spotify. Consider notice letters that cite the specific clauses.

2) For privacy and legal teams: Update DPIAs and data maps. Spotify’s Privacy Policy identifies “User Data,” “Usage Data,” “Voice Data,” “Message Data,” and more as inputs for ML features under legitimate interest. If you rely on Spotify data for compliance reports, make sure you’re only using permitted, properly aggregated outputs—not raw exports.

3) For users: I will be posting a guideline to how to clawback your data. I may not hit everything so always open to suggestions about whatever else that others spot.

Spotify’s terms give it very broad rights to collect, combine, and use your data (listening history, device/ads data, voice features, third-party signals) for personalization, ads, and product R&D. They also take a broad license to user content you upload (e.g., playlist art).

Key cites

• User Guidelines: prohibition on scraping and on “using any part of the Services or Content to train a machine learning or AI model.”

• Developer Policy (effective May 15, 2025): “Do not use the Spotify Platform or any Spotify Content to train a machine learning or AI model…” Also bans analyzing Spotify content to create new/derived listenership metrics or user profiles for ad targeting.

• Privacy Policy (effective Aug. 27, 2025): Spotify uses personal data to “develop and train” ML models for recommendations, AI DJ/AI playlists, and rule‑enforcement, primarily under “legitimate interests.”

• Terms & Conditions of Use: very broad license to Spotify for any “User Content” you post, including the right to “create derivative works” and to use content by any means and media worldwide, irrevocably.

[A version of this post first appeared on MusicTechPolicy]

September 3, 2025 by thetrichordist

The AI Safe Harbor is an Unconstitutional Violation of State Protections for Families and Consumers

By Chris Castle

The AI safe harbor slavered onto President Trump’s “big beautiful bill” is layered with intended consequences. Not the least of these is the affect on TikTok.

One of the more debased aspects of TikTok (and that’s a long list) is their promotion through their AI driven algorithms of clearly risky behavior to their pre-teen audience. Don’t forget: TikTok’s algorithm is not just any algorithm. The Chinese government claims it as a state secret. And when the CCP claims a state secret they ain’t playing. So keep that in mind.

One of these risky algorithms that was particularly depraved was called the “Blackout Challenge.” The TikTok “blackout challenge” has been linked to the deaths of at least 20 children over an 18-month period. One of the dead children was Nylah Anderson. Nylah’s mom sued TikTok for her daughter because that’s what moms do. If you’ve ever had someone you love hang themselves, you will no doubt agree that you live with that memory every day of your life. This unspeakable tragedy will haunt Nylah’s mother forever.

Even lowlifes like TikTok should have settled this case and it should never have gotten in front of a judge. But no–TikTok tried to get out of it because Section 230. Yes, that’s right–they killed a child and tried to get out of the responsibility. The District Court ruled that the loathsome Section 230 applied and Nylah’s mom could not pursue her claims. She appealed.

The Third Circuit Court of Appeals reversed and remanded, concluding that “Section 230 immunizes only information ‘provided by another’” and that “here, because the information that forms the basis of Anderson’s lawsuit—i.e., TikTok’s recommendations via its FYP algorithm—is TikTok’s own expressive activity, § 230 does not bar Anderson’s claims.”

So…a new federal proposal threatens to slam the door on these legal efforts: the 10-year artificial intelligence (AI) safe harbor recently introduced in the House Energy and Commerce Committee. If enacted, this safe harbor would preempt state regulation of AI systems—including the very algorithms and recommendation engines that Nylah’s mom and other families are trying to challenge.

Section 43201(c) of the “Big Beautiful Bill” includes pork, Silicon Valley style, entitled the “Artificial Intelligence and Information Technology Modernization Initiative: Moratorium,” which states:

no State or political subdivision thereof may enforce any law or regulation regulating artificial intelligence models, artificial intelligence systems, or automated decision systems during the 10-year period beginning on the date of the enactment of this Act.

The “Initiative” also appropriates “$500,000,000, to remain available until September 30, 2035, to modernize and secure Federal information technology systems through the deployment of commercial artificial intelligence, the deployment of automation technologies, and the replacement of antiquated business systems….” So not only did Big Tech write themselves a safe harbor for their crimes, they also are taking $500,000,000 of corporate welfare to underwrite it courtesy of the very taxpayers they are screwing over. Step aside Sophocles, when it comes to tragic flaws, Oedipus Rex got nothing on these characters.

Platforms like TikTok, YouTube, and Instagram use AI-based recommendation engines to personalize and optimize content delivery. These systems decide what users see based on a combination of behavioral data, engagement metrics, and predictive algorithms. While effective for keeping users engaged, these AI systems have been implicated in promoting harmful content—ranging from pro-suicide material to dangerous ‘challenges’ that have directly resulted in injury or death.

Families across the country have sued these companies, alleging that the AI-driven algorithms knowingly promoted hazardous content to vulnerable users. In many cases, the claims are based on state consumer protection laws, negligence, or wrongful death statutes. Plaintiffs argue that the companies failed in their duty to design safe systems or to warn users about foreseeable dangers. These cases are not attacks on free speech or user-generated content; they focus specifically on the design and operation of proprietary AI systems.

If you don’t think that these platforms are depraved enough to actually raise safe harbor defenses, just remember what they did to Nylah’s mom–raised the exceptionally depraved Section 230 as a defense to their responsibility in the death of a child.

The AI safe harbor would prohibit states from enacting or enforcing any law that regulates AI systems or automated decision-making technologies for the next 10 years. This sweeping language could easily be interpreted to cover civil liability statutes that hold platforms accountable for the harms their AI systems cause. This is actually even worse than the vile Section 230–the safe harbor would be expressly targeting actual state laws. Maybe after all the appeals, say 20 years from now, we’ll find out that the AI safe harbor is unconstitutional commandeering, but do we really want to wait to find out?

Because these wrongful death lawsuits rely on arguments that an AI algorithm caused harm—either through its design or its predictive content delivery—the companies could argue that the moratorium shields them from liability. They might claim that the state tort claims are an attempt to “regulate” AI in violation of the federal preemption clause. If courts agree, these lawsuits could be dismissed before ever reaching a jury.

This would create a stunning form of corporate immunity even beyond the many current safe harbors for Big Tech: tech companies would be free to deploy powerful, profit-driven AI systems with no accountability in state courts, even when those systems lead directly to preventable deaths.

The safe harbor would be especially devastating for families who have already suffered tragic losses and are seeking justice. These families rely on state wrongful death laws to hold powerful platforms accountable. Removing that path to accountability would not only deny them closure, but also prevent public scrutiny of the algorithms at the center of these tragedies.

States have long held the authority to define standards of care and impose civil liability for harms caused by negligence or defective products. The moratorium undermines this traditional role by barring states from addressing the specific risks posed by AI systems, even in the context of established tort principles. It would represent one of the broadest federal preemptions of state law in modern history—in the absence of federal regulation of AI platforms.

• In Pennsylvania, the parents of a teenager who committed suicide alleged that Instagram’s algorithmic feed trapped their child in a cycle of depressive content.
• Multiple lawsuits filed under consumer protection and negligence statutes in states like New Jersey, Florida, and Texas seek to hold platforms accountable for designing algorithms that systematically prioritize engagement over safety.
• TikTok faced multiple class action multidistrict litigation claims it illegally harvested user information from its in-app browser.

All of such suits could be in jeopardy if courts interpret the AI moratorium as barring state laws that impose liability on algorithm-driven systems and you can bet that Big Tech platforms will litigate the bejeezus out of the issue. Even if the moratorium was not intended to block wrongful death and other state law claims, its language may be broad enough to do so in practice—especially when leveraged by well-funded corporate legal teams.

Even supporters of federal AI regulation should be alarmed by the breadth of this safe harbor. It is not a thoughtful national framework based on a full record, but a shoot-from-the-hip blanket prohibition on consumer protection and civil justice. By freezing all state-level responses to AI harms, the AI safe harbor is intent on consolidating power in the hands of federal bureaucrats and corporate lobbyists, leaving ordinary Americans with fewer options for recourse, not to mention a clear violation of state police powers and the 10th Amendment.

To add insult to injury, the use of reconciliation to pass this policy—without full hearings, bipartisan debate, or robust public input—only underscores the cynical nature of the strategy. It has nothing to do with the budget aside from the fact that Big Tech is snarfing down $500 million of taxpayer money for no good reason just so they can argue their land grab is “germane” to shoehorn it into reconciliation under the Byrd Rule. It’s a maneuver designed to avoid scrutiny and silence dissent, not to foster a responsible or democratic conversation about how AI should be governed.

At its core, the AI safe harbor is not about fostering innovation—it is about shielding tech platforms from accountability just like the DMCA, Section 230 and Title I of the Music Modernization Act. By preempting state regulation, it could block families from using long-standing wrongful death statutes to seek justice for the loss of their children and laws protecting Americans from other harms. It undermines the sovereignty of states, the dignity of grieving families, and the public’s ability to scrutinize the AI systems that increasingly shape our lives.

Congress must reject this overreach, and the American public must remain vigilant in demanding transparency, accountability, and justice. The Initiative must go.

[A version of this post first appeared on MusicTechPolicy]

May 16, 2025 by Trichordist Editor

Big Beautiful AI Safe Harbor asks If David Sacks wants to Make America Screwed Again?

In a dramatic turn of events, Congress is quietly advancing a 10-year federal safe harbor for Big Tech that would block any state and local regulation of artificial intelligence (AI). That safe harbor would give Big Tech another free ride on the backs of artists, authors, consumers, all of us and our children. It would stop cold the enforcement of state laws to protect consumers like the $1.370 billion dollar settlement Google reached with the State of Texas last week for grotesque violations of user privacy. The bill would go up on Big Tech’s trophy wall right next to the DMCA, Section 230 and Title I of the Music Modernization Act.

Introduced through the House Energy and Commerce Committee as part of a broader legislative package branded with President Trump’s economic agenda, this safe harbor would prevent states from enforcing or enacting any laws that address the development, deployment, or oversight of AI systems. While couched as a measure to ensure national uniformity and spur innovation, this proposal carries serious consequences for consumer protection, data privacy, and state sovereignty. It threatens to erase hard-fought state-level protections that shield Americans from exploitative child snooping, data scraping, biometric surveillance, and the unauthorized use of personal and all creative works. This post unpacks how we got here, why it matters, and what can still be done to stop it.

The Origins of the New Safe Harbor

The roots of the latest AI safe harbor lie in a growing push from Silicon Valley-aligned political operatives and venture capital influencers, many of whom fear a patchwork of state-level consumer protection laws that would stop AI data scraping. Among the most vocal proponents is tech entrepreneur-turned White House crypto czar David Sacks, who has advocated for federal preemption of state AI rules in order to protect startup innovation from what he and others call regulatory overreach also known as state “police powers” to protect state residents.

If my name was “Sacks” I’d probably be a bit careful about doing things that could get me fired. His influence reportedly played a role in shaping the safe harbor’s timing and language, leveraging connections on Capitol Hill to attach it to a larger pro-business package of legislation. That package—marketed as a pillar of President Trump’s economic plan—was seen as a convenient vehicle to slip through controversial provisions with minimal scrutiny. You know, let’s sneak one past the boss.

Why This Is Dangerous for Consumers and Creators

The most immediate danger of the AI safe harbor is its preemption of state protections at a time when AI technologies are accelerating unchecked. States like California, Illinois, and Virginia have enacted—or are considering—laws to limit how companies use AI to analyze facial features, scan emails, extract audio, or mine creative works from social media. The AI mantra is that they can snarf down “publicly available data” which essentially means everything that’s not behind a paywall. Because there is no federal AI regulation yet, state laws are crucial for protecting vulnerable populations, including children whose photos and personal information are shared by parents online. Under the proposed AI safe harbor, such protections would be nullified for 10 years–and don’t think it won’t be renewed.

Without the ability to regulate AI at the state level, we could see our biometric data harvested without consent. Social media posts—including photos of babies, families, and school events—could be scraped and used to train commercial AI systems without transparency or recourse. Creators across all copyright categories could find their works ingested into large language models and generative tools without license or attribution. Emails and other personal communications could be fed into AI systems for profiling, advertising, or predictive decision-making without oversight.

While federal regulation of AI is certainly coming this AI safe harbor includes no immediate substitute. Instead, it freezes state level regulatory development entirely for a decade—an eternity in the technology world—during which time the richest companies in the history of commerce can entrench themselves further with little fear of accountability. And it likely will provide a blueprint for federal legislation when it comes.

A Strategic Misstep for Trump’s Economic Agenda: Populism or Make America Screwed Again?

Ironically, attaching the moratorium to a legislative package meant to symbolize national renewal may ultimately undermine the very populist and sovereignty-based themes that President Trump has championed. By insulating Silicon Valley firms from state scrutiny, the legislation effectively prioritizes the interests of data-rich corporations over the privacy and rights of ordinary Americans. It hands a victory to unelected tech executives and undercuts the authority of governors, state legislators, and attorney generals who have stepped in where federal law has lagged behind. So much for that states are “laboratories of democracy” jazz.

Moreover, the manner in which the safe harbor was advanced legislatively—slipped into what is supposed to be a reconciliation bill without extensive hearings or stakeholder input—is classic pork and classic Beltway maneuvering in smoke filled rooms. Critics from across the political spectrum have noted that such tactics cheapen the integrity of any legislation they touch and reflect the worst of Washington horse-trading.

What Can Be Done to Stop It

The AI safe harbor is not a done deal. There are several procedural and political tools available to block or remove it from the broader legislative package.

1. Committee Intervention – Lawmakers on the House Energy and Commerce Committee or the Rules Committee can offer amendments to strip or revise the moratorium before it proceeds to the full House.
2. House Floor Action – Opponents of the moratorium can offer floor amendments during debate to strike the provision. This requires coordination and support from members across both parties.
3. Senate “Byrd Rule” Challenge and Holds – Because reconciliation bills must be budget-related, the Senate Parliamentarian can strike the safe harbor if it’s deemed “non-germane” which it certainly seems to be. Senators can formally raise this challenge.
4. Conference Committee Negotiation – If different versions of the legislation pass the House and Senate, the final language will be hashed out in conference. There is still time to remove the moratorium here.
5. Public Advocacy – Artists, parents, consumer advocates, and especially state officials can apply pressure through media, petitions, and direct outreach to lawmakers, highlighting the harms and democratic risks of federal preemption. States may be able to sue to block the safe harbor as unconstitutional (see Chris’s discussion of constitutionality) but let’s not wait to get to that point. It must be said that any such litigation poses a threat to Trump’s “Big Beautiful Bill” courtesy of David Sacks.

Conclusion

The AI safe harbor may have been introduced quietly, but there’s a growing backlash from all corners. Its consequences would be anything but subtle. If enacted, it would freeze innovation in AI accountability, strip states of their ability to protect residents, and expose Americans to widespread digital exploitation. While marketed as pro-innovation, the safe harbor looks more like a gift to data-hungry monopolies at the expense of federalist principles and individual rights.

It’s not too late to act, but doing so requires vigilance, transparency, and an insistence that even the most powerful Big Tech oligarchs remain subject to democratic oversight.

May 15, 2025May 15, 2025 by thetrichordist

@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

gov.uscourts.cand_.415175.525.0 Download

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 Translation: How 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