Month: October 2025

Less Than Zero: The Significance of the Per Stream Rate and Why It Matters

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.

Too Dynamic to Question, Too Dangerous to Ignore

When Ed Newton-Rex left Stability AI, he didn’t just make a career move — he issued a warning. His message was simple: we’ve built an industry that moves too fast to be honest.

AI’s defenders insist that regulation can’t keep up, that oversight will “stifle innovation.” But that speed isn’t a by-product; it’s the business model. The system is engineered for planned obsolescence of accountability — every time the public begins to understand one layer of technology, another version ships, invalidating the debate. The goal isn’t progress; it’s perpetual synthetic novelty, where nothing stays still long enough to be measured or governed, and “nothing says freedom like getting away with it.”

We’ve seen this play before. Car makers built expensive sensors we don’t want that fail on schedule; software platforms built policies that expire the moment they bite. In both cases, complexity became a shield and a racket — “too dynamic to question.” And yet, like those unasked-for, but paid for, features in the cars we don’t want, AI’s design choices are too dangerous to ignore. (Like what if your brakes really are going out, not just the sensor is malfunctioning.)

Ed Newton-Rex’s point — echoed in his tweets and testimony — is that the industry has mistaken velocity for virtue. He’s right. The danger is not that these systems evolve too quickly to regulate; it’s that they’re designed that way designed to fail just like that brake sensor. And until lawmakers recognize that speed itself is a form of governance, we’ll keep mistaking momentum for inevitability.

SB 683: California’s Quiet Rejection of the DMCA—and a Roadmap for Real AI Accountability

When Lucian Grainge drew a bright line—“UMG will not do business with bad actors regardless of the consequences”—he did more than make a corporate policy statement.  He threw down a moral challenge to an entire industry: choose creators or choose exploitation.

California’s recently passed SB 683 does not shout as loudly, but it answers the same call. By refusing to copy Washington’s bureaucratic NO FAKES Act and its DMCA-style “notice-and-takedown” maze, SB 683 quietly re-asserts a lost principle: rights are vindicated through courts and accountability, not compliance portals.

What SB 683 actually does

SB 683 amends California Civil Code § 3344, the state’s right-of-publicity statute for living persons, to make injunctive relief real and fast.  If someone’s name, voice, or likeness is exploited without consent, a court can now issue a temporary restraining order or preliminary injunction.  If the order is granted without notice, the defendant must comply within two business days.  

That sounds procedural—and it is—but it matters. SB 683 replaces “send an email to a platform” with “go to a judge.”   It converts moral outrage into enforceable law.

The deeper signal: a break from the DMCA’s bureaucracy

For twenty-seven years, the Digital Millennium Copyright Act (DMCA) has governed online infringement through a privatized system of takedown notices, counter-notices, and platform safe harbors.  When it was passed, Silicon Valley came alive with schemes to get around copyright infringement through free riding schemes that beat a path to Grokster‘s door.

But the DMCA was built for a dial-up internet and has aged about as gracefully as a boil on cow’s butt.

The Copyright Office’s 2020 Section 512 Study concluded that whatever Solomonic balance Congress thought it was making has completely collapsed:

“[T]he volume of notices demonstrates that the notice-and-takedown system does not effectively remove infringing content from the internet; it is, at best, a game of whack-a-mole.”

“Congress’ original intended balance has been tilted askew.”  

“Rightsholders report notice-and-takedown is burdensome and ineffective.”  

“Judicial interpretations have wrenched the process out of alignment with Congress’ intentions.” 
 
“Rising notice volume can only indicate that the system is not working.”  

Unsurprisingly, the Office concluded that “Roughly speaking, many OSPs spoke of section 512 as being a success, enabling them to [free ride and] grow exponentially and serve the public without facing debilitating lawsuits [or one might say, paying the freight]. Rightsholders reported a markedly different perspective, noting grave concerns with the ability of individual creators to meaningfully use the section 512 system to address copyright infringement and the “whack-a-mole” problem of infringing content re-appearing after being taken down. Based upon its own analysis of the present effectiveness of section 512, the Office has concluded that Congress’ original intended balance has been tilted askew.”

Which is a genteel way of saying the DMCA is an abject failure for creators and halcyon days for venture-backed online service providers. So why would anyone who cared about creators want to continue that absurd process?

SB 683 flips that logic. Instead of creating bureaucracy and rewarding the one who can wait out the last notice standing, it demands obedience to law.  Instead of deferring to internal “trust and safety” departments, it puts a judge back in the loop. That’s a cultural and legal break—a small step, but in the right direction.

The NO FAKES Act: déjà vu all over again

Washington’s proposed NO FAKES Act is designed to protect individuals from AI-generated digital replicas which is great. However—NO FAKES recreates the truly awful DMCA’s failed architecture: a federal registry of “designated agents,” a complex notice-and-takedown workflow, and a new safe-harbor regime based on “good-faith compliance.”    You know, notice and notice and notice and notice and notice and notice and…..

If NO FAKES passes, platforms like Google would again hold all the procedural cards: largely ignore notices until they’re convenient, claim “good faith,” and continue monetizing AI-generated impersonations.  In other words, it gives the platforms exactly what they wanted because delay is the point.  I seriously doubt that Congress of 1998 thought that their precious DMCA would be turned into a not so funny joke on artists, and I do remember Congressman Howard Berman (one of the House managers for DMCA) looking like he was going to throw up during the SOPA hearings when he found out how many millions of DMCA notices YouTube alone receives.  So why would we want to make the same mistake again thinking we’ll have a different outcome?  With the same platforms now richer beyond category? Who could possibly defend such garbage as anything but a colossal mistake?

The approach of SB 683 is, by contrast, the opposite of NO FAKES. It tells creators: you don’t need to find the right form—you need to find a judge.  It tells platforms: if a court says take it down, you have two days, not two months of emails, BS counter notices and a bad case of learned helplessness.  True, litigation is more costly than sending a DMCA notice, but litigation is far more likely to be effective in keeping infringing material down and will not become a faux “license” like DMCA has become.  

The DMCA heralded twenty-seven years of normalizing massive and burdensome copyright infringement and raising generations of lawyers to defend the thievery while Big Tech scooped up free rider rents that they then used for anti-creator lobbying around the world.  It should be entirely unsurprising that all of that litigation and lobbying has lead us to the current existential crisis.

Lucian Grainge’s throw-down and the emerging fault line

When Mr. Grainge spoke, he wasn’t just defending Universal’s catalog; he was drawing a perimeter around normalizing AI exploitation, and not buying into an even further extension of “permissionless innovation.”

Universal’s position aligns with what California just did. While Congress toys with a federal opt-out regime for AI impersonations, Sacramento quietly passed a law grounded in judicial enforcement and personal rights.  It’s not perfect, but it’s a rejection of the “catch me if you can” ethos that has defined Silicon Valley’s relationship with artists for decades.

A job for the Attorney General

SB 683 leaves enforcement to private litigants, but the scale of AI exploitation demands public enforcement under the authority of the State.  California’s Attorney General should have explicit power to pursue pattern-or-practice actions against companies that:

– Manufacture or distribute AI-generated impersonations of deceased performers (like Sora 2’s synthetic videos).
– Monetize those impersonations through advertising or subscription revenue (like YouTube does right now with the Sora videos).
– Repackage deepfake content as “user-generated” to avoid responsibility.

Such conduct isn’t innovation—it’s unfair competition under California law. AG actions could deliver injunctions, penalties, and restitution far faster than piecemeal suits. And as readers know, I love a good RICO, so let’s put out there that the AG should consider prosecuting the AI cabal with its interlocking investments under Penal Code §§ 186–186.8, known as the California Control of Profits of Organized Crime Act (CCPOCA) (h/t Seeking Alpha).

While AI platforms complain of “burdensome” and “unproductive” litigation, that’s simply not true of enterprises like the AI cabal—litigation is exactly what was required in order to reveal the truth about massive piracy powering the circular AI bubble economy. Litigation has revealed that the scale of infringement by AI platforms like Anthropic and Meta is so vast that private damages are meaningless. It is increasingly clear these companies are not alone—they have relied on pirate libraries and torrent ecosystems to ingest millions of works across every creative category. Rather than whistle past the graveyard while these sites flourish, government must confront its failure to enforce basic property rights. When theft becomes systemic, private remedies collapse, and enforcement becomes a matter for the state. Even Anthropic’s $1.5 billion settlement feels hollow because the crime is so immense. Not just because statutory damages in the US were also established in 1999 to confront…CD ripping.

AI regulation as the moment to fix the DMCA

The coming wave of AI legislation represents the first genuine opportunity in a generation to rewrite the online liability playbook.  AI and the DMCA cannot peacefully coexist—platforms will always choose whichever regime helps them keep the money.

If AI regulation inherits the DMCA’s safe harbors, nothing changes. Instead, lawmakers should take the SB 683 cue:
– Restore judicial enforcement.  
– Tie AI liability to commercial benefit. 
– Require provenance, not paperwork.  
– Authorize public enforcement.

The living–deceased gap: California’s unfinished business


SB 683 improves enforcement for living persons, but California’s § 3344.1 already protects deceased individuals against digital replicas.  That creates an odd inversion: John Coltrane’s estate can challenge an AI-generated “Coltrane tone,” but a living jazz artist cannot.   The Legislature should align the two statutes so the living and the dead share the same digital dignity.

Why this matters now

Platforms like YouTube host and monetize videos generated by AI systems such as Sora, depicting deceased performers in fake performances.  If regulators continue to rely on notice-and-takedown, those platforms will never face real risk.   They’ll simply process the takedown, re-serve the content through another channel, and cash another check.

The philosophical pivot

The DMCA taught the world that process can replace principle. SB 683 quietly reverses that lesson.  It says: a person’s identity is not an API, and enforcement should not depend on how quickly you fill out a form.

In the coming fight over AI and creative rights, that distinction matters. California’s experiment in court-centered enforcement could become the model for the next generation of digital law—where substance defeats procedure, and accountability outlives automation.

SB 683 is not a revolution, but it’s a reorientation. It abandons the DMCA’s failed paperwork culture and points toward a world where AI accountability and creator rights converge under the rule of law.

If the federal government insists on doubling down with the NO FAKES Act’s national “opt-out” registry, California may once again find itself leading by quiet example: rights first, bureaucracy last.

Ghosts in the Machine: How AI’s “Future” Runs on a 1960s Grid

The smart people want us to believe that artificial intelligence is the frontier and apotheosis of human progress. They sell it as transformative and disruptive. That’s probably true as far as it goes, but it doesn’t go that far. In practice, the infrastructure that powers it often dates back to a different era and there is the paradox: much of the electricity to power AI’s still flows through the bones of mid‑20th century engineering. Wouldn’t it be a good thing if they innovated a new energy source before they crowd out the humans?

The Current Generation Energy Mix — And What AI Adds

To see that paradox, start with the U.S. national electricity mix:

In 2023 , the U.S. generated about 4,178 billion kWh of electricity at utility-scale facilities. Of that, 60% came from fossil fuels (coal, natural gas, petroleum, other gases), 19% came from nuclear, and 21% from renewables (wind, solar, hydro). 
– Nuclear power remains the backbone of zero-carbon baseload: it supplies around 18–19% of U.S. electricity, and nearly half of all non‑emitting generation. 
– In 2025, clean sources (nuclear + renewables) are edging upward. According to Ember, in March 2025 fossil fuels fell below 50% of U.S. electricity generation for the first time (49.2%), marking a historic shift.
– Yet still, more than half of US power comes from carbon-emitting sources in most months.

Meanwhile, AI’s demand is surging:

– The Department of Energy estimates that data centers consumed 4.4% of U.S. electricity in 2023 (176 TWh) and projects this to rise to 6.7–12% by 2028 (325–580 TWh) according to the Department of Energy.
– An academic study of 2,132 U.S. data centers (2023–2024) found that these facilities accounted for more than 4% of national power consumption, with 56% coming from fossil sources, and emitted more than 105 million tons of CO₂e (approximately 2.18% of U.S. emissions in 2023). 
– That study also concluded: data centers’ carbon intensity (CO₂ per kWh) is 48% higher than the U.S. average.

So: AI’s power demands are no small increment—they threaten to stress a grid still anchored in older thermal technologies.

Global Data Centers https://www.datacentermap.com

Why “1960s Infrastructure” Isn’t Hyperbole

When I say AI is running on 1960s technology, I mean several things:

1. Thermal generation methods remain largely unchanged according to the EPA.  Coal-fired steam turbines and natural gas combined-cycle plants still dominate.

2. Many plants are old and aging.  The average age of coal plants in the U.S. is about 43 years; some facilities are over 60. Transmission lines and grid control systems often date from mid-to late-20th century planning.

3. Nuclear’s modern edge is historical.  Most U.S. nuclear reactors in operation were ordered in the 1960s–1970s and built over subsequent decades. In other words: The commercial installed base is old.

The Rickover Motif: Nuclear, Legacy, and Power Politics

To criticize AI’s reliance on legacy infrastructure, one powerful symbol is Admiral Hyman G. Rickover, the man often called the “Father of the Nuclear Navy.” Rickover’s work in the 1950s and 1960s not only shaped naval propulsion but also influenced the civilian nuclear sector.

Rickover pushed for rigorous engineering standards , standardization, safety protocols, and institutional discipline in building reactors. After the success of naval nuclear systems, Rickover was assigned by the Atomic Energy Commission to influence civilian nuclear power development.

Rickover famously required applicants to the nuclear submarine service to have “fixed their own car.” That speaks to technical literacy, self-reliance, and understanding systems deeply, qualities today’s AI leaders often lack. I mean seriously—can you imagine Sam Altman on a mechanic’s dolly covered in grease?

As the U.S. Navy celebrates its 250th anniversary, it’s ironic that modern AI ambitions lean on reactors whose protocols, safety cultures, and control logic remain deeply shaped by Rickover-era thinking from…yes…1947. And remember, Admiral Rickover had to transfer the hidebound Navy to nuclear power which at the time was just recently discovered and not well understood—and away from diesel. Diesel. That’s innovation and required a hugely entrepreneurial leader.

The Hypocrisy of Innovation Without Infrastructure

AI companies claim disruption but site data centers wherever grid power is cheapest — often near legacy thermal or nuclear plants. They promote “100% renewable” branding via offsets, but in real time pull electricity from fossil-heavy grids. Dense compute loads aggravate transmission congestion. FERC and NERC now list hyperscale data centers as emerging reliability risks. 

The energy costs AI doesn’t pay — grid upgrades, transmission reinforcement, reserve margins — are socialized onto ratepayers and bondholders. If the AI labs would like to use their multibillion dollar valuations to pay off that bond debt, that’s a conversation. But they don’t want that, just like they don’t want to pay for the copyrights they train on.

Innovation without infrastructure isn’t innovation — it’s rent-seeking. Shocking, I know…Silicon Valley engaging in rent-seeking and corporate welfare.

The 1960s Called. They Want Their Grid Back.

We cannot build the future on the bones of the past. If AI is truly going to transform the world, its promoters must stop pretending that plugging into a mid-century grid is good enough. The industry should lead on grid modernization, storage, and advanced generation, not free-ride on infrastructure our grandparents paid for.

Admiral Rickover understood that technology without stewardship is just hubris. He built a nuclear Navy because new power required new systems and new thinking. That lesson is even more urgent now.

Until it is learned, AI will remain a contradiction: the most advanced machines in human history, running on steam-age physics and Cold War engineering.