The American Federation of Musicians is drawing a line between the record labels’ AI licensing deals and the musicians whose performances made those deals valuable in the first place.
The American Federation of Musicians (AFM) launched its Human Made, Human Paid campaign this week, calling on the major record labels to recognize a fundamental principle: Musicians should have a say in whether their performances are used to train generative AI systems, and they should be compensated when those performances are exploited.
The campaign comes as the AFM prepares to resume negotiations with Universal Music Group, Sony Music, Warner Music and Disney’s Hollywood Records on November 3 over a new Sound Recording Labor Agreement (SRLA), the collective bargaining agreement governing employment conditions for musicians who perform on recordings.
The union’s demands are straightforward: consent, credit and compensation. Musicians should be able to approve or reject AI uses of their performances, receive appropriate attribution and participate financially when the labels license recordings to AI companies.
But the dispute is about considerably more than another royalty provision. It goes to the heart of who has the authority to license the human performances embedded in sound recordings and whether the owners of recording copyrights can bargain away interests that belong to individual performers.
The record companies originally sued the AI developers for copyright infringement, alleging unauthorized copying of protected sound recordings. But as the companies moved toward settlements and commercial licensing arrangements, the performers whose work was captured in those recordings faced a very different question: Where was their compensation?
AFM International President Tino Gagliardi put the union’s position succinctly: “The record labels cannot pocket profits built on the backs of human artistry while cutting working musicians out of the equation.”
The AFM argues that the labels cannot simply collect AI licensing revenue while disregarding obligations to the session musicians who performed on those records.
The missing rights in the AI licensing debate
The AFM campaign also highlights an important distinction that has been largely overlooked in the AI licensing debate.
A record label may own the copyright in a sound recording, but that does not necessarily mean it owns every right implicated by the use of that recording to train or operate a generative AI system.
Performers may possess independent contractual rights, rights of publicity or other protections relating to their voices, identities and performances. Those interests do not automatically transfer to the record company simply because the performer participated in a recording session.
This becomes particularly important when an AI system can imitate not only a composition or recording but the recognizable characteristics of an individual performer, including vocal timbre, phrasing or instrumental technique.
The AFM’s demand for consent therefore addresses a question that cannot necessarily be resolved by negotiating a copyright license with a record label.
Digital replica protections are a subset of performer identity protections, not a substitute for them. Whether the exploitation involves a digital replica or some other appropriation of a performer’s identity, the underlying rights are distinct from copyright. Ownership of a sound recording, including ownership under a work-for-hire agreement like the SRLA, does not itself convey the performer’s right of publicity. A copyright license is not a license of personal identity.
The Artist Rights Symposium 5 is coming on October 19 at Tweed Recording in Athens, GA hosted by the University of Georgia Terry College of Business Music Certificate Program and the School of Policy and International Affairs, and the Artist Rights Institute. More about the Symposium here and register on Eventbrite here.
As AI companies like Suno and Udio settle copyright lawsuits with record companies and music publishers, they introduce new licensing arrangements. Artists and songwriters may be offered the “opportunity” to “opt in” to the settlements and “new revenue streams”. But not all revenue streams are equal, remember streaming? Remember “Let’s help that plucky startup Spotify”? We have seen this movie before and we know how it ends.
Why a Suno Copyright Settlement Is Different from Spotify, LimeWire—or Even Bartz
The music industry has settled copyright infringement disputes before. Spotify’s mechanical royalty settlements in David Lowery’s class action resolved claims over unpaid or improperly licensed compositions. LimeWire’s settlement addressed unauthorized reproduction and distribution of copyrighted recordings. In both cases, the essential bargain concerned compensation for past copyright infringement, not permission to reproduce the identity of the human beings who created the music. Identity theft never came up.
Suno presents a fundamentally different problem. Its generative AI technology can potentially reproduce not merely copyrighted expression but recognizable characteristics of an artist’s voice, performance and identity—what Chris has called personhood signals. A settlement that licenses recordings for future training may therefore implicate rights that neither the record company nor publisher controls. That’s why they need the “opt in” agreement to waive these rights because the AI platform doesn’t want to pay for the artist’s identify if the artist would even consider that deal. Many artists and songwriters, if not most, will not.
The Bartz v. Anthropic settlement illustrates the limitation of treating AI disputes exclusively as copyright cases. Bartzcompensates copyright owners for specified historical conduct involving pirated books. It settles the claims brought in litigation, so does not expressly resolve the separate problem of extracting and commercializing human identity. That is what a conventional copyright settlement misses.
Settling infringement of the work does not settle exploitation of the person. And no copyright settlement should quietly become consent to commercialize someone’s voice, identity or personhood.
So artists, their managers and lawyers are asking, what exactly are we being asked to agree to this time? Before you even get to the “new revenue stream,” an opt-in for an apparent copyright settlement may also include permission for future AI training, broad releases, perpetual covenants not to sue, or waivers of an artist’s rights in their name, voice and identity. These are fundamentally different transactions, with potentially permanent consequences. Before signing, creators need to understand not only what they will be paid, but what rights they are surrendering, how those rights may be exploited, and whether they can ever get them back.
Chris Castle will lead the closing panel at Artist Rights Symposium 5, that warns “Beware the AI Opt-In: Hidden Right of Publicity Waivers.” The panel brings together four speakers with complementary perspectives on artist advocacy, litigation and music-industry licensing.
Jen Jacobsen, Artist Rights Alliance. Friend of the show Jen Jacobsen is a long time artist rights advocate who brings the artist-advocacy perspective, focusing on meaningful consent, transparency and protecting musicians from agreements that may surrender irreversible grants of rights with hidden waivers.
George Zelcs of Korein Tillery. George Zelcs is the lead counsel on the Jason Isbell/David Lowery personhood class action against Suno to help us understand the implications of “opt in” agreements with waivers on rights of publicity and the practical question of what remedies artists should retain.
Gwendolyn Seale — Gwen Seale PLLC. Gwen brings experience representing songwriters and music copyright owners, with particular relevance to licensing authority, co-writer and co-owner interests, compensation and contractual protections.
Tim Kappel — Wells Kappel. Tim is a copyright expert and artist rights advocate who successfully argued in federal trial court and the Fifth Circuit Court of Appeals that his client Cyril Vetter should retain foreign rights as part of a statutory copyright termination— a case now before the U.S. Supreme Court.
The panel is scheduled for 3:00–4:00 p.m. on October 19.
Three Deals Disguised as One?
An AI opt-in may combine three distinct transactions as part of the copyright settlement and go-forward license: compensation for past unauthorized uses (probably not shared by the label, but check), licensing for future model training, and revenue sharing from products built on those models (but don’t hold your breath). But accepting settlement compensation for yesterday’s conduct should not automatically mean consenting to tomorrow’s exploitation.
There may also be a fourth transaction: authorization to use an artist’s name, voice, likeness or other personhood rights which could not have been brought by a record company or music publisher because they do not control those rights.
A copyright license is not permission to commercialize personhood.
The panel will examine how these rights can become entangled, particularly when record companies, publishers or other representatives may not control all the rights an AI company seeks.
What Happens After You Sign?
The panel will address the questions that can be overlooked when attention focuses on the size of a settlement or the promise of future royalties.
What exactly is inside the AI company’s “walled garden”? How are revenues attributed to particular recordings or compositions? Can users generate synthetic voices or prompt an artist’s name? Can artists examine the product before consenting?
And what happens when an artist wants out later when the term expires (if there is a term)? Deleting a source recording does not necessarily remove its influence from an already-trained model. Termination, machine unlearning, continuing model exploitation and rights that survive expiration may determine whether an opt-in becomes a one-way door in an AI Hotel California.
Good afternoon to every one of you, whether you’re here in this room or joining us online. It is a pleasure to welcome you all here today and I want to thank MEDAA, la Maison européenne des Autrices et des Auteurs, for hosting today’s ECSA conference on “Authors’ Rights and Music Streaming in the Age of AI”. ]
I am Helienne Lindvall, songwriter and the President of ECSA, the European Composer and Songwriter Alliance. ECSA represents 57 professional music authors’ associations and more than 30,000 composers across 29 European countries. I am honoured to be here today with fellow composers, songwriters, policymakers, and representatives from Europe’s cultural and creative sectors.
I am particularly grateful to welcome Henna Virkkunen, the Executive Vice-President for Technological Sovereignty, Security, and Democracy at the European Commission. Ms. Virkkunen – thank you again for joining us. We are all looking forward to hearing your opening remarks in just a moment.
I also want to thank three Members of the European Parliament for their participation: Emma Rafowicz, co-rapporteur on the Agora EU programme, Axel Voss, rapporteur on the recent report on copyright and generative AI, and Hélder Sousa Silva, who will draft the forthcoming report on the Cultural and creative sectors in the age of AI.
We would also like to express our deepest gratitude to all the speakers who will contribute their time and expertise today. And remember that this conference would not be possible without the support of the Creative Europe programme.
So, Authors’ Rights and Music Streaming in the Age of AI? Let me first take a step back to 2016. Ten years ago, the European Commission President, Jean-Claude Juncker, called artists and creators “Europe’s crown jewels”. He said their works should be protected and they should be paid fairly.
Three years later, the EU adopted the Directive on Copyright in the Digital Single Market. We applauded it, for enshrining appropriate and proportionate remuneration, for increasing transparency in contracts, and for strengthening author’s rights on content-sharing platforms. Seven years on, where do we stand?
Well, the truth is that the principle of appropriate and proportionate remuneration is still too often circumvented in practice, in particular through buyout practices, but also when it comes to other online exploitation, such as streaming.
And then came generative AI. Adopted at a time when generative AI was barely existing, the Directive does not mention AI anywhere.
But it does include text and data mining exceptions, designed to help universities and researchers, discover new trends and gaining new knowledge. Supposedly with minimal harm to authors and other rightholders.
The reality? When not simply ignoring EU rules, global AI companies have exploited those exceptions far beyond their intended purpose. They’ve scraped and used all our works without consent, without transparency, and without remuneration. The harm to music authors isn’t minimal—it’s maximal. AI-generated content now imitates and substitutes us.
Some say “You could have opted out.” But here’s the truth: AI companies scraped everything – looting the entire history of musical works – before we had a fair chance to opt out and even know how to opt out.
To quote Baroness Beeban Kidron, the director of Bridget Jones The Edge of Reason: “Should shopkeepers have to opt out of shoplifters? Should victims of violence have to opt out of attacks? Should those who use the internet for banking have to opt out of fraud? I struggle to think of another situation where someone protected by law must proactively wrap it around themselves on an individual basis.”
And for a songwriter like me—working with co-writers, different CMOs, publishers, and labels—opting out is practically impossible. And even if it was possible, we would be naive to believe it would be respected. How would we even know if it were, when there is no transparency?
The AI Act’s implementation hasn’t helped. Its transparency rules are weak. Trade secrets protect massive theft. Imagine a fast-food manufacturer who had stolen all the ingredients that went into their products, refusing to reveal what the ingredients are or where they came from, calling it a “trade secret”. Then demanding it should be up to the farmers to prove it was their produce that was stolen. That’s what we’re dealing with.
Coca Cola may have a secret recipe, but it still has to display what went into each bottle, and pay its suppliers. It shouldn’t be up to creators to prove AI companies used our works. They should be required to get our consent and to be transparent. Or we should presume — correctly — that they already scraped the entire web.
Yes, a few licensing deals have been signed in the past year — between a couple of major labels and AI companies, usually after litigation, and mostly in the US. But we know next to nothing about the details of those deals – or whether composers and songwriters will benefit in any way, despite it being our works that have been stolen and exploited.
Licensing shouldn’t only be available to those with the muscle to sue. In Europe, where we claim to cherish our artists and cultural diversity, survival of the fittest cannot be the answer. AI companies have ingested ALL the music available online. It makes no sense that only the most powerful get a license and get paid, when they only supplied a fraction of the ingredients. And let me be clear: we are not against AI. It can be a helpful tool in our workflow as creators. We are simply against unlicensed AI.
Generative AI companies must act ethically. They must work with us—not profit from our work without consent and at our expense. That’s the only way to rebuild trust between creators and AI companies. Currently, the AI landscape is like the Wild West, and AI startups that want to act ethically cannot compete when there is a shop next door selling stolen goods.
Let’s be honest, the current framework is misinterpreted and applied far beyond its original purpose. It has created a high level of uncertainty that only benefits global generative AI companies to the detriment of creators. We cannot wait for courts to decide policy. We cannot rely on opaque deals between big corporations where the money rarely trickles down to creators.
This isn’t the time for sticking plasters [or Band Aids] on a wooden leg. It’s time for policymakers to be bold. The good news: not only the Pope but also many EU Member States and the European Parliament are showing the way. The recent Voss report on Copyright and Generative AI recognizes that AI systems rely massively on protected works—exploited without authorization or compensation. It recommends:
• Full transparency for AI training, including a rebuttable presumption of use for any AI service operating in the EU; and
• A new legislative initiative to clarify licensing rules and establish a functioning market.
We fully support this. We need a framework that:
1. Enables fair remuneration for creators
2. Ensures EU copyright law applies to all services operating in the EU.
3. Addresses the substitution and dilution of human creation by AI output
4. Ensures collective management can deliver appropriate and proportionate remuneration to all creators—big and small
The Parliament has also insisted that digital platforms must act against AI fraud and manipulation. And it is not the first time – the European Parliament’s report on music streaming, adopted in 2024, already did so, with many other recommendations to improve the identification of creators on music streaming platforms and ensure more transparency in algorithms and recommendation systems, as well as when it comes to AI generated music.
For composers and songwriters, streaming fraud through AI is a critical issue. In April, Deezer reported that 75,000 fully AI-generated tracks are uploaded daily to the platform – that’s 44% of all uploads. In March, a man in the US pleaded guilty to defrauding streaming platforms with AI-generated tracks, generating millions in royalties. Fraudsters impersonate real artists, upload fake songs to their profiles, and steal their royalties. This isn’t just an economic issue. It’s ethical – it’s a massive violation of moral rights and personal data.
And it threatens citizens’ trust in the authenticity of digital content. That’s one of the many reasons why we welcome MEPs Rafowicz and Kuhnke’s draft report on AgoraEU, which rightly prioritizes human creativity over AI-generated works.
We also warmly welcome this proposal for a dedicated music strand that can address the concrete challenges and structural imbalances impacting the sector, such as increasing market concentration, artistic freedom, fair remuneration and the growing dominance of digital service providers.
Today, 26 organisations from across the European music sector published a statement to support this draft report and encourage all MEPs to give the music sector the support it deserves.
Now, let me conclude: Our plea today is simple: The promise made to Europe’s crown jewels in 2016 remains unfulfilled: The exceptions designed to help researchers and generate information now fuel billion-dollar companies that exploit us. The transparency we were promised is hidden behind trade secrets. The licensing market that should exist is reserved for those who can afford the most expensive lawyers in the US. This must change.
We call on European policymakers to act with courage. With the European Parliament, we call for an additional legal framework, one that can finally uphold the key principles of transparency, consent and remuneration and encourage a well-functioning licensing market. This is not about adding more regulation This is to rebalance a framework that is fundamentally flawed, far from its intended purpose and Europe’s most fundamental values.
Europe must decide: will it stand with its creators, or stand by while our works are taken without consent? Let us become once again Europe’s crown jewels.
As we’ve reported many times, communities across the US are increasingly pushing back against the explosive growth of AI-driven data centers. Major concerns include skyrocketing electricity demand, massive water consumption for cooling, noise pollution from giant fans, loss of prime agricultural and residential land, and rising utility bills passed on to local residents. As of May 2026, independent trackers report approximately 69–78 U.S. jurisdictions that have enacted bans, restrictions, or moratoriums on new data centers. Many of these measures also target the new high-voltage transmission lines required to power them.
This wave of resistance highlights a deepening tension between the rapid expansion of AI infrastructure and local priorities around quality of life, sustainability, and community control.
1. Michigan: The Epicenter of Local Moratoriums
I think you could safely say that Michigan currently leads the nation in local opposition to data center construction, largely triggered by the controversial $16+ billion OpenAI-Oracle Stargate AI data center project in Saline Township, Washtenaw County. Despite a 4-1 township planning commission vote against rezoning and strong resident protests, the Stargate construction project advanced through legal channels, igniting widespread defensive actions across the state.
More than 50 communities (cities and townships) have enacted temporary moratoriums, covering roughly 1,500 square miles — an area comparable to the size of Rhode Island.
Between 25 and 51 active local moratoriums are in place as of early 2026.
State lawmakers have introduced bills (HB 5594–5596) calling for a one-year statewide pause on new hyperscale data centers, along with stricter rules on water and electricity connections.
Some utilities, such as Ypsilanti, have imposed their own 12-month bans on water hookups for large AI facilities—but that will eventually expire.
Key issues in Michigan should sound familiar: massive water usage, strain on the electrical grid, and the loss of local zoning authority.
2. Virginia: Transmission Line Battles in “Data Center Alley”
Virginia is home to the highest concentration of data centers in the United States (over 550 facilities), particularly in Northern Virginia. Opposition here focuses heavily on both the data centers and the extensive transmission lines needed to support them.
Strong protests in Loudoun, Prince William, Hanover, and other counties against new projects and expansions.
Major conflicts over high-voltage lines such as the Valley Link and Joshua Falls projects, which cross multiple counties and impact neighborhoods, historic sites, and conserved rural land.
Dominion Energy has faced repeated legal and community challenges regarding route selections.
Legislative debates continue over ending billions in tax incentives and studies projecting residential electricity rate increases of up to $37 per month by 2040.
Breakfast at Buck’s of Woodside—if you’re not at the table you are on the menu
3. Georgia: Statewide Pause Efforts Amid High Project Volume
Georgia has seen hundreds of announced data center projects, prompting both local and statewide responses.
Bills such as HB 1059 and HB 1012 propose temporary statewide pauses on new permitting (potentially until 2027–2028) to allow time for impact studies.
Several counties, including DeKalb and Camden, have passed moratoriums ranging from several months to a year while updating zoning ordinances.
Residents voice concerns about energy costs, water consumption, loss of land, and whether tax incentives truly benefit local communities.
Georgia’s combination of legislative proposals and county-level actions reflects growing resistance in a rapidly developing market.
They are bulldozing my family home on August 1st! We do not want to sell! STOP THE TRANSMISSION LINES AND STOP THE DATA CENTERS THEY ARE SUPPORTING. https://t.co/XFSDRoKBuY
4. North Carolina: Rising Local and Policy Pushback
North Carolina ranks among the top states for new moratorium activity as data center developers expand beyond traditional East Coast hubs.
Multiple counties and municipalities have passed restrictions or temporary moratoriums citing infrastructure strain, zoning issues, and community impacts.
Policy proposals such as HB 1063 seek to require hyperscale developers to fully cover the costs of power, water, and grid upgrades rather than passing them to ratepayers.
Growing focus on the environmental and visual effects of both data centers and supporting transmission lines.
North Carolina represents an emerging hotspot where early local actions may shape future statewide policy.
5. Indiana: County-Level Resistance and High-Stakes Conflicts
Indiana has seen intense localized opposition, particularly in rural counties.
Counties such as White and Fulton have enacted 6-to-12-month moratoriums to study impacts and strengthen local ordinances.
Trackers show at least 6 formal actions, with several others in discussion.
Primary concerns include the conversion of prime agricultural land, rising utility rates, and the industrialization of rural communities.
Indiana illustrates how even mid-sized proposals can trigger strong community responses and political tension.
Broader Implications and the Path Forward
The five most active states — Michigan, Virginia, Georgia, North Carolina, and Indiana — capture the national picture. Resistance is bipartisan, spans urban and rural areas, and increasingly includes opposition to the massive transmission lines that accompany data center projects.
Common themes include fears that data centers consume disproportionate amounts of power and water while shifting costs onto existing residents. Proponents argue these facilities bring jobs, tax revenue, and are essential for America’s AI competitiveness. Critics insist that growth must be responsible, with full cost recovery, better siting practices, efficiency standards, and genuine community input.
As AI demand continues to surge, this local “revolt” tests whether the physical infrastructure can scale fast enough without compromising quality of life and environmental goals. I think the national consensus is a big no.
Expect more moratoriums, ballot initiatives, legal battles, and negotiations in the coming months. The outcome will significantly influence not only the future of AI but also national energy policy and land-use planning for years to come.
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.
David is pointing to a quiet but serious problem hiding behind the rush to use generative AI in advertising, film, and television: copyright law protects authorship, not outputs. AI muddies or even erases authorship altogether in some cases
Under current U.S. Copyright Office guidance, works generated primarily by AI are often not registrable in the Copyright Office because they lack a human author exercising creative control. That means a brand that relies on AI to generate a commercial may not actually own exclusive rights in the finished work. If someone copies, remixes, or repurposes that ad, even in a way that damages the brand, the company may have little or no legal recourse under copyright law.
The Copyright Office guidance says:
In the Office’s view, it is well-established that copyright can protect only material that is the product of human creativity. Most fundamentally, the term “author,” which is used in both the Constitution and the Copyright Act, excludes non-humans. The Office’s registration policies and regulations reflect statutory and judicial guidance on this issue….If a work’s traditional elements of authorship were produced by a machine, the work lacks human authorship and the Office will not register it For example, when an AI technology receives solely a prompt from a human and produces complex written, visual, or musical works in response, the “traditional elements of authorship” are determined and executed by the technology—not the human user
David has not identified a theoretical risk. Copyright is the backbone of brand control in media. It’s what allows companies to stop misuse, dilution, parody-turned-weapon, or hostile appropriation. In the US, a copyright registration is required to protect those rights. Remove that protection, and brands are left relying on weaker tools like trademark or unfair competition law, which are narrower, slower, and often ill-suited to digital remix culture.
David’s warning extends beyond ads. Film and TV studios experimenting with AI-generated scripts, scenes, music, or visuals may be undermining their own ability to control, license, or defend those works. In trying to save money upfront, they may be giving up the legal leverage that protects their brand, reputation, and long-term value.
Congress is considering several legislative packages to regulate AI. AI is a system that was launched globally with no safety standards, no threat modeling, and no real oversight. A system that externalized risk onto the public, created enormous security vulnerabilities, and then acted surprised when criminals, hostile states, and bad actors exploited it.
After the damage was done, the same companies that built it told governments not to regulate—because regulation would “stifle innovation.” Instead, they sold us cybersecurity products, compliance frameworks, and risk-management services to fix the problems they created.
Yes, artificial intelligence is a problem. Wait…Oh, no sorry. That’s not AI.
That’s was Internet. And it made the tech bros the richest ruling class in history.
And that’s why some of us are just a little skeptical when the same tech bros are now telling us: “Trust us, this time will be different.” AI will be different, that’s for sure. They’ll get even richer and they’ll rip us off even more this time. Not to mention building small nuclear reactors on government land that we paid for, monopolizing electrical grids that we paid for, and expecting us to fill the landscape with massive power lines that we will pay for.
The topper is that these libertines want no responsibility for anything, and they want to seize control of the levers of government to stop any accountability. But there are some in Congress who are serious about not getting fooled again.
Senator Marsha Blackburn released a summary of legislation she is sponsoring that gives us some cause for hope (read it here courtesy of our friends at the Copyright Alliance). Because her bill might be effective, that means Silicon Valley shills will be all over it to try to water it down and, if at all possible, destroy it. That attack of the shills has already started with Silicon Valley’s AI Viceroy in the Trump White House, a guy you may never have heard of named David Sacks. Know that name. Beware that name.
Senator Blackburn’s bill will do a lot of good things, including for protecting copyright. But the first substantive section of Senator Blackburn’s summary is a game changer. She would establish an obligation on AI platforms to be responsible for known or predictable harm that can befall users of AI products. This is sometimes called a “duty of care.”
Her summary states:
Place a duty of care on AI developers in the design, development, and operation of AI platforms to prevent and mitigate foreseeable harm to users. Additionally, this section requires:
• AI platforms to conduct regular risk assessments of how algorithmic systems, engagement mechanics, and data practices contribute to psychological, physical, financial, and exploitative harms.
• The Federal Trade Commission (FTC) to promulgate rules establishing minimum reasonable safeguards.
At its core, Senator Blackburn’s AI bill tries to force tech companies to play by rules that most other industries have followed for decades: if you design a product that predictably harms people, you have a responsibility to fix it.
That idea is called “products liability.” Simply put, it means companies can’t sell dangerous products and then shrug it off when people get hurt. Sounds logical, right? Sounds like what you would expect would happen if you did the bad thing? Car makers have to worry about the famous exploding gas tanks. Toy manufacturers have to worry about choking hazards. Drug companies have to test side effects. Tobacco companies….well, you know the rest. The law doesn’t demand perfection—but it does demand reasonable care and imposes a “duty of care” on companies that put dangerous products into the public.
Blackburn’s bill would apply that same logic to AI platforms. Yes, the special people would have to follow the same rules as everyone else with no safe harbors.
Instead of treating AI systems as abstract “speech” or neutral tools, the bill treats them as what they are: products with design choices. Those choices that can foreseeably cause psychological harm, financial scams, physical danger, or exploitation. Recommendation algorithms, engagement mechanics, and data practices aren’t accidents. They’re engineered. At tremendous expense. One thing you can be sure of is that if Google’s algorithms behave a certain way, it’s not because the engineers ran out of development money. The same is true of ChatGPT, Grok, etc. On a certain level of reality, this is very likely not guess work or predictability. It’s “known” rather than “should have known.” These people know exactly what their algorithms do. And they do it for the money.
The bill would impose that duty of care on AI developers and platform operators. A duty of care is a basic legal obligation to act reasonably to prevent foreseeable harm. “Foreseeable” doesn’t mean you can predict the exact victim or moment—it means you can anticipate the type of harm that flows to users you target from how the system is built.
To make that duty real, the bill would require companies to conduct regular risk assessments and make them public. These aren’t PR exercises. They would have to evaluate how their algorithms, engagement loops, and data use contribute to harms like addiction, manipulation, fraud, harassment, and exploitation.
They do this already, believe it. What’s different is that they don’t make it public, anymore than Ford made public the internal research that the Pinto’s gas tank was likely to explode. In other words, platforms would have to look honestly at what their systems actually do in the world—not just what they claim to do.
The bill also directs the Federal Trade Commission (FTC) to write rules establishing minimum reasonable safeguards. That’s important because it turns a vague obligation (“be responsible”) into enforceable standards (“here’s what you must do at a minimum”). Think of it as seatbelts and crash tests for AI systems.
So why do tech companies object? Because many of them argue that their algorithms are protected by the First Amendment—that regulating how recommendations work is regulating speech. Yes, that is a load of crap. It’s not just you, it really is BS.
Imagine Ford arguing that an exploding gas tank was “expressive conduct”—that drivers chose the Pinto to make a statement, and therefore safety regulation would violate Ford’s free speech rights. No court would take that seriously. A gas tank is not an opinion. It’s an engineered component with known risks and risks that were known to the manufacturer.
AI platforms are the same. When harm flows from design decisions—how content is ranked, how users are nudged, how systems optimize for engagement—that’s not speech. That’s product design. You can measure it, test it, audit it, which they do and make it safer which they don’t.
This part of Senator Blackburn’s bill matters because platform design shapes culture, careers, and livelihoods. Algorithms decide what gets seen, what gets buried, and what gets exploited. Blackburn’s bill doesn’t solve every problem, but it takes an important step: it says tech companies can’t hide dangerous products behind free-speech rhetoric anymore.
If you build it, and it predictably hurts people, you’re responsible for fixing it. That’s not censorship. It’s accountability. And people like Marc Andreessen, Sam Altman, Elon Musk and David Sacks will hate it.
The moratorium would block states from enforcing their own laws on AI accountability, deepfakes, consumer protection, energy policy, discrimination, and data rights. Tennessee’s ELVIS Act is a prime example. For ten years — or five years in the “softened” version — the federal government would force states to stand down while some of the most richest and powerful monopolies in commercial history continue deploying models trained on unlicensed works, scraped data, personal information, and everything in between. Regardless of whether it is ten years or five years, either may as well be an eternity in Tech World. Particularly since they don’t plan on following the law anyway with their “move fast and skip things” mentality.
Ted Turns Texas Glowing
99-1/2 just won’t do—Remember the AI moratorium that was defeated 99-1 in the Senate during the heady days of the One Big Beautiful Bill Act? We said it would come back in the must-pass National Defense Authorization Act and sure enough that’s exactly where it is courtesy of Senator and 2028 Presidential hopefull Ted Cruz (fundraising off of the Moratorium no doubt for his “Make Texas California Again” campaign) and other Big Tech sycophants according to a number of sources including Politico and the Tech Policy Press:
It…remains to be seen when exactly the moratorium issue may be taken up, though a final decision could still be a few weeks away.
Congressional leaders may either look to include the moratorium language in their initial NDAA agreement, set to be struck soon between the two chambers, or take it up as a separate amendment when it hits the floor in the House and Senate next month.
Either way, they likely will need to craft a version narrow enough to overcome the significant opposition to its initial iterations. While House lawmakers are typically able to advance measures with a simple majority or party-line vote, in the Senate, most bills require 60 votes to pass, meaning lawmakers must secure bipartisan support.
The pushback from Democrats is already underway. Sen. Brian Schatz (D-HI), an influential figure in tech policy debates and a member of the Senate Commerce Committee, called the provision “a poison pill” in a social media post late Monday, adding, “we will block it.”
Still, the effort has the support of several top congressional Republicans, who have repeatedly expressed their desire to try again to tuck the bill into the next available legislative package.
In Washington, must-pass bills invite mischief. And right now, House leadership is flirting with the worst kind: slipping a sweeping federal moratorium on state AI laws into the National Defense Authorization Act (NDAA).
This idea was buried once already — the Senate voted 99–1 to strike it from Trump’s earlier “One Big Beautiful Bill.” But instead of accepting that outcome, Big Tech trying to resurrect it quietly, through a bill that is supposed to fund national defense, not rewrite America’s entire AI legal structure.
The NDAA is the wrong vehicle, the wrong process, and the wrong moment to hand Big Tech blanket immunity from state oversight. As we have discussed many times the first time around, the concept is probably unconstitutional for a host of reasons and will no doubt be immediately challenged.
AI Moratorium Lobbying Explainer for Your Electric Bill
Here are the key shilleries pushing the federal AI moratorium and their backers:
Promote ‘uniform national standards’ in Congressional meetings
Operate through and alongside trade groups
PARASITES GROW IN THE DARK: WHY THE NDAA IS THE ABSOLUTE WRONG PLACE FOR THIS
The National Defense Authorization Act is one of the few bills that must pass every year. That makes it a magnet for unrelated policy riders — but it doesn’t make those riders legitimate.
An AI policy that touches free speech, energy policy and electricity rates, civil rights, state sovereignty, copyright, election integrity, and consumer safety deserves open hearings, transparent markups, expert testimony, and a real public debate. And that’s the last thing the Big Tech shills want.
THE TIMING COULD NOT BE MORE INSULTING
Big Tech is simultaneously lobbying for massive federal subsidies for compute, federal preemption of state AI rules, and multi-billion-dollar 765-kV transmission corridors to feed their exploding data-center footprints.
And who pays for those high-voltage lines? Ratepayers do. Utilities that qualify as political subdivisions in the language of the moratorium—such as municipal utilities, public power districts, and cooperative systems—set rates through their governing boards rather than state regulators. These boards must recover the full cost of service, including new infrastructure needed to meet rising demand. Under the moratorium’s carve-outs, these entities could be required to accept massive AI-driven load increases, even when those loads trigger expensive upgrades. Because cost-of-service rules forbid charging AI labs above their allocated share, the utility may have no choice but to spread those costs across all ratepayers. Residents, not the AI companies, would absorb the rate hikes.
States must retain the power to protect their citizens. Congress has every right to legislate on AI. But it does not have the right to erase state authority in secret to save Big Tech from public accountability.
A CALL TO ACTION
Tell your Members of Congress: No AI moratorium in the NDAA. No backroom preemption. No Big Tech giveaways in the defense budget.
When White House AI Czar David Sacks tweets confidently that “there will be no federal bailout for AI” because “five major frontier model companies” will simply replace each other, he is not speaking as a neutral observer. He is speaking as a venture capitalist with overlapping financial ties to the very AI companies now engaged in the most circular investment structure Silicon Valley has engineered since the dot-com bubble—but on a scale measured not in millions or even billions, but in trillions.
Sacks is a PayPal alumnus turned political-tech kingmaker who has positioned himself at the intersection of public policy and private AI investment. His recent stint as a Special Government Employee to the federal government raised eyebrows precisely because of this dual role. Yet he now frames the AI sector as a robust ecosystem that can absorb firm-level failure without systemic consequence.
The numbers say otherwise. The diagram circulating in the X-thread exposes the real structure: mutually dependent investments tied together through cross-equity stakes, GPU pre-purchases, cloud-compute lock-ins, and stock-option-backed revenue games. So Microsoft invests in OpenAI; OpenAI pays Microsoft for cloud resources; Microsoft books the revenue and inflates its stake OpenAI. Nvidia invests in OpenAI; OpenAI buys tens of billions in Nvidia chips; Nvidia’s valuation inflates; and that valuation becomes the collateral propping up the entire sector. Oracle buys Nvidia chips; OpenAI signs a $300 billion cloud deal with Oracle; Oracle books the upside. Every player’s “growth” relies on every other player’s spending.
This is not competition. It is a closed liquidity loop. And it’s a repeat of the dot-bomb “carriage” deals that contributed to the stock market crash in 2000.
And underlying all of it is the real endgame: a frantic rush to secure taxpayer-funded backstops—through federal energy deals, subsidized data-center access, CHIPS-style grants, or Department of Energy land leases—to pay for the staggering infrastructure costs required to keep this circularity spinning. The singularity may be speculative, but the push for a public subsidy to sustain it is very real.
Call it what it is: an industry searching for a government-sized safety net while insisting it doesn’t need one.
In the meantime, the circular investing game serves another purpose: it manufactures sky-high paper valuations that can be recycled into legal war chests. Those inflated asset values are now being used to bankroll litigation and lobbying campaigns aimed at rewriting copyright, fair use, and publicity law so that AI firms can keep strip-mining culture without paying for it.
The same feedback loop that props up their stock prices is funding the effort to devalue the work of every writer, musician, actor, and visual artist on the planet—and to lock that extraction in as a permanent feature of the digital economy.
Spotify’s insistence that it’s “misleading” to compare services based on a derived per-stream rate reveals exactly how out of touch the company has become with the very artists whose labor fuels its stock price. Artists experience streaming one play at a time, not as an abstract revenue pool or a complex pro-rata formula. Each stream represents a listener’s decision, a moment of engagement, and a microtransaction of trust. Dismissing the per-stream metric as irrelevant is a rhetorical dodge that shields Spotify from accountability for its own value proposition. (The same applies to all streamers, but Spotify is the only one that denies the reality of the per-stream rate.)
Spotify further claims that users don’t pay per stream but for access as if that negates the artist’s per stream rate payments. It is fallacious to claim that because Spotify users pay a subscription fee for “access,” there is no connection between that payment and any one artist they stream. This argument treats music like a public utility rather than a marketplace of individual works. In reality, users subscribe because of the artists and songs they want to hear; the value of “access” is wholly derived from those choices and the fans that artists drive to the platform. Each stream represents a conscious act of consumption and engagement that justifies compensation.
Economically, the subscription fee is not paid into a vacuum — it forms a revenue pool that Spotify divides among rights holders according to streams. Thus, the distribution of user payments is directly tied to which artists are streamed, even if the payment mechanism is indirect. To say otherwise erases the causal relationship between fan behavior and artist earnings.
The “access” framing serves only to obscure accountability. It allows Spotify to argue that artists are incidental to its product when, in truth, they are the product. Without individual songs, there is nothing to access. The subscription model may bundle listening into a single fee, but it does not sever the fundamental link between listener choice and the artist’s right to be paid fairly for that choice.
Less Than Zero Effect: AI, Infinite Supply and Erasing Artist
In fact, this “access” argument may undermine Spotify’s point entirely. If subscribers pay for access, not individual plays, then there’s an even greater obligation to ensure that subscription revenue is distributed fairly across the artists who generate the listening engagement that keeps fans paying each month. The opacity of this system—where listeners have no idea how their money is allocated—protects Spotify, not artists. If fans understood how little of their monthly fee reached the musicians they actually listen to, they might demand a user-centric payout model or direct licensing alternatives. Or they might be more inclined to use a site like Bandcamp. And Spotify really doesn’t want that.
And to anticipate Spotify’s typical deflection—that low payments are the label’s fault—that’s not correct either. Spotify sets the revenue pool, defines the accounting model, and negotiates the rates. Labels may divide the scraps, but it’s Spotify that decides how small the pie is in the first place either through its distribution deals or exercising pricing power.
Three Proofs of Intention
Daniel Ek, the Spotify CEO and arms dealer, made a Dickensian statement that tells you everything you need to know about how Spotify perceives their role as the Streaming Scrooge—“Today, with the cost of creating content being close to zero, people can share an incredible amount of content”.
That statement perfectly illustrates how detached he has become from the lived reality of the people who actually make the music that powers his platform’s market capitalization (which allows him to invest in autonomous weapons). First, music is not generic “content.” It is art, labor, and identity. Reducing it to “content” flattens the creative act into background noise for an algorithmic feed. That’s not rhetoric; it’s a statement of his values. Of course in his defense, “near zero cost” to a billionaire like Ek is not the same as “near zero cost” to any artist. This disharmonious statement shows that Daniel Ek mistakes the harmony of the people for the noise of the marketplace—arming algorithms instead of artists.
Second, the notion that the cost of creating recordings is “close to zero” is absurd. Real artists pay for instruments, studios, producers, engineers, session musicians, mixing, mastering, artwork, promotion, and often the cost of simply surviving long enough to make the next record or write the next song. Even the so-called “bedroom producer” incurs real expenses—gear, software, electricity, distribution, and years of unpaid labor learning the craft. None of that is zero. As I said in the UK Parliament’s Inquiry into the Economics of Streaming, when the day comes that a soloist aspires to having their music included on a Spotify “sleep” playlist, there’s something really wrong here.
Ek’s comment reveals the Silicon Valley mindset that art is a frictionless input for data platforms, not an enterprise of human skill, sacrifice, and emotion. When the CEO of the world’s dominant streaming company trivializes the cost of creation, he’s not describing an economy—he’s erasing one.
While Spotify tries to distract from the “per-stream rate,” it conveniently ignores the reality that whatever it pays “the music industry” or “rights holders” for all the artists signed to one label still must be broken down into actual payments to the individual artists and songwriters who created the work. Labels divide their share among recording artists; publishers do the same for composers and lyricists. If Spotify refuses to engage on per-stream value, what it’s really saying is that it doesn’t want to address the people behind the music—the very creators whose livelihoods depend on those streams. In pretending the per-stream question doesn’t matter, Spotify admits the artist doesn’t matter either.
Less Than Zero or Zeroing Out: Where Do We Go from Here?
The collapse of artist revenue and the rise of AI aren’t coincidences; they’re two gears in the same machine. Streaming’s economics rewards infinite supply at near-zero unit cost which is really the nugget of truth in Daniel Ek’s statements. This is evidenced by Spotify’s dalliances with Epidemic Sound and the like. But—human-created music is finite and costly; AI music is effectively infinite and cheap. For a platform whose margins improve as payout obligations shrink, the logical endgame is obvious: keep the streams, remove the artists.
Two-sided market math. Platforms sell audience attention to advertisers and access to subscribers. Their largest variable cost is royalties. Every substitution of human tracks with synthetic “sound-alikes,” noise, functional audio, or AI mashup reduces royalty liability while keeping listening hours—and revenue—intact. You count the AI streams just long enough to reduce the royalty pool, then you remove them from the system, only to be replace by more AI tracks. Spotify’s security is just good enough to miss the AI tracks for at least one royalty accounting period.
Perpetual content glut as cover. Executives say creation costs are “near zero,” justifying lower per-stream value. That narrative licenses a race to the bottom, then invites AI to flood the catalog so the floor can fall further.
Training to replace, not to pay. Models ingest human catalogs to learn style and voice, then output “good enough” music that competes with the very works that trained them—without the messy line item called “artist compensation.”
Playlist gatekeeping. When discovery is centralized in editorial and algorithmic playlists, platforms can steer demand toward low-or-no-royalty inventory (functional audio, public-domain, in-house/commissioned AI), starving human repertoire while claiming neutrality.
Investor alignment. The story that scales is not “fair pay”; it’s “gross margin expansion.” AI is the lever that turns culture into a fixed cost and artists into externalities.
Where does that leave us? Both streaming and AI “work” best for Big Tech, financially, when the artist is cheap enough to ignore or easy enough to replace. AI doesn’t disrupt that model; it completes it. It also gives cover through a tortured misreading through the “national security” lens so natural for a Lord of War investor like Mr. Ek who will no doubt give fellow Swede and one of the great Lords of War, Alfred Nobel, a run for his money. (Perhaps Mr. Ek will reimagine the Peace Prize.) If we don’t hard-wire licensing, provenance, and payout floors, the platform’s optimal future is music without musicians.
Plato conceived justice as each part performing its proper function in harmony with the whole—a balance of reason, spirit, and appetite within the individual and of classes within the city. Applied to AI synthetic works like those generated by Sora 2, injustice arises when this order collapses: when technology imitates creation without acknowledging the creators whose intellect and labor made it possible. Such systems allow the “appetitive” side—profit and scale—to dominate reason and virtue. In Plato’s terms, an AI trained on human art yet denying its debt to artists enacts the very disorder that defines injustice.
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