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

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

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

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

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

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

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

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

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

Her summary states:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

“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

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

  1. Consent as the gate. Voice clones and “new songs” derived from existing songs require affirmative artist approval—full stop.
  2. Provenance as the standard. AI firms that want first-party deals must prove lawful ingestion, audited datasets, and enforceable guardrails against impersonation.
  3. 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.

And YouTube is monetizing Sora videos

[This post first appeared on Artist Rights Watch]

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

 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.

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

Silicon Valley Loses Bigly

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

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

Marsha Blackburn and Maria Cantwell to the Rescue

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

Top Cover from President Trump?

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

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

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

Now what?

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

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

Brava, madam. Well played.

This post first appeared on MusicTechPolicy