Tag: streaming royalties

The AI Industry Wants Congress to Create the Next 100-Year Radio Loophole

“Formal property’s contribution to mankind is not the protection of ownership… Property’s real breakthrough is that it radically improved the flow of communications about assets and their potential.”

Hernando de Soto, The Mystery of Capital.

Musicians and other creators are unfortunately familiar with many efforts by big business to extract the economic value of their authorship through expansive free-riding copyright loopholes that pretend property rights don’t exist. The current AI crisis did not originate with Big Tech—they learned it from Big Radio.  I distinctly recall having lunch with a Big Tech Washington lobbyist for XM radio (pre-merger) who had just found out that broadcast radio didn’t pay sound recording performances and wanted that same deal for satellite radio.  I had to put the quietus on that pronto.  And they didn’t even know how close they came to disaster. Sheesh.

In case you were wondering, Congress modernized copyright law in 1995 through the Digital Performance Right in Sound Recordings Act.  The 1995 law created the statutory framework that launched licensed webcasting while preserving the archaic terrestrial radio performance loophole—preserved due to lobbying by Big Radio.

For decades, terrestrial AM/FM broadcasters have relied on a statutory copyright exception that allows them to broadcast sound recordings without compensating the featured artists, session musicians, and backup singers whose performances attract listeners, or the record companies who bear the substantial costs of discovering, recording, marketing, and promoting those works. Despite years of bipartisan efforts to end that free ride through legislation like the American Music Fairness Act (AMFA) and its predecessor bills, broadcasters have vigorously defended the exemption with overwhelming money and utilization of the very broadcast license they abuse to feather their nests.  We have put excellent witnesses in front of Congress only to be outspent by smarmy swamp creatures from the National Association of Broadcasters.

AI disputes echo that familiar pattern. In the end, it all comes down to vast wealth accumulated through safe harbors of one kind or another.  Instead of relying on a terrestrial performance exemption, AI companies advance absurd interpretations of fair use and text-and-data-mining doctrines to justify the uncompensated use of stolen works for commercial model training “because China.” They use influence peddlers like White House AI Viceroy David Sacks to try to sneak retroactive safe harbors into the law through Congress in the form of groundless federal preemption of state and local regulation or executive orders that are clearly bought and paid for under the guise of “data center factories” which are not factories at all.   Although the legal theories differ between AI and broadcasting, the economic consequence is remarkably similar: sweeping commercial enterprises seek to build profitable businesses by lobbying or litigating (two sides of the same King’s shilling) to expand exceptions to the exclusive rights Congress granted creators, while forcing artists, musicians, writers, journalists, film makers and photographers to absorb the resulting loss in value.

That concern is no longer theoretical. In a recent Bloomberg podcast, SoundExchange President and CEO Michael Huppe—whose organization distributes more than $1 billion annually in digital performance royalties derived from rights created by that market-making 1995 legislation—described AI as “something that has a lot of danger, but also a lot of potential.” But he cautioned that “we need to make sure that human creators are protected” and that “there need to be guardrails so that [AI] doesn’t steamroll over the whole creative industry.” I couldn’t agree more. Rather than treating property rights as obstacles to AI, Congress should remember Hernando de Soto’s lesson that clearly defined ownership creates wealth—a principle it proved when licensing sound recordings gave birth to the webcasting industry largely thanks to SoundExchange and the infrastructure it brings to the table.

Huppe’s concerns are rooted in measurable economics rather than speculation. Streaming now accounts for approximately 85% of U.S. recorded music revenue, and streaming services distribute a finite, shared royalty pool among eligible recordings. Huppe noted that some services report receiving roughly 75,000 new recordings every day, with reports suggesting that more than 80% are AI-generated.

Whether those estimates ultimately prove higher or lower, the underlying economic principle is unavoidable: every AI-generated recording entering the marketplace competes for listener attention and, if streamed, competes for a share of the same finite, shared royalty pool. Huppe also warned that AI facilitates streaming fraud, allowing bad actors to generate AI recordings, deploy bots to inflate plays, and “siphon away payment from the pipeline that would otherwise go to real artists and real record labels.” His conclusion was unequivocal: “It’s fraud, basically. Straight-up fraud.”

Moreover, generative AI takes legitimate recorded performances to create competing works substituting for the originals themselves. This economic effect echoes Judge Vince Chhabria’s observations in the Kadrey v. Meta books litigation, where he suggested that flooding markets with AI-generated works competing against originals could constitute the type of market harm that would block a fair use defense to copyright infringement.

The explosion of AI-generated music that Mike Huppe cites therefore provides strong evidence of repeatable and measurable market harm identified by Judge Chhabria. Every AI-generated stream competes for listener attention while simultaneously reducing each human artist’s share of a finite, shared royalty pool. Unlike speculative claims of future injury, this dilution can be observed, quantified, and modeled using actual streaming and royalty distributions.

The economics become even more troubling when combined with large-scale scraping. As we have seen litigated in the cases against Udio, Anthropic and Meta (and I think will continue to see proven through all of the AI models including Suno),  AI has trained on enormous quantities of illegally acquired works without obtaining licenses or compensating the creators whose recordings, performances, writings, images, and other expressive works supplied the raw material that makes those models commercially valuable.  Sound familiar?

The same creative ecosystem that furnished the training corpus is then required to compete against a cascading and endless supply of AI-generated outputs while receiving no payment for either the training use or the resulting competition. Worse yet, because nothing says freedom like getting away with it, AI platforms connected to Google, Facebook and Amazon are so used to ignoring copyrights in their day jobs that they clearly planned to ignore our rights.

In music, the effect is especially stark: the recordings that taught music-generation systems how to produce theoretically commercially appealing songs also become the works displaced by those outputs in the marketplace. Creators are effectively asked to finance their own displacement. They suffer a double economic injury—first, uncompensated exploitation of their works to build commercial AI systems, and second, measurable erosion of their share of a finite, shared royalty pool as AI-generated recordings compete for the same listeners and revenues that streamers like Spotify seem unable to stop from invading the ecosystem.

Because of the insane pool allocation formula used for streaming mechanical royalties on interactive services like Spotify, Amazon, Apple and Deezer, songwriters are also subject to the same kind of dilution as artists.  Hopefully the Copyright Royalty Judges will address this new humiliation in the current statutory rate proceeding and clearly state that AI works are not eligible for the statutory license under Section 115.

This measurable dilution also helps illustrate the broader market-flooding concern identified by Judge Chhabria. If AI-generated outputs systematically occupy the same commercial markets as human-created works, reducing revenues through sheer volume rather than direct substitution alone, then streaming provides one of the first empirical laboratories for proving market harm for “the effect of the use upon the potential market for or value of the copyrighted work.”  Because streaming royalties are transparent, pooled, and data-driven, music offers unusually strong evidence that AI-generated competition can inflict repeatable, measurable, and scalable economic injury. If courts follow Judge Chhabria in recognizing this analysis, the same analytical framework could extend beyond music to books, journalism, visual art, film, software, and other creative industries in which AI-generated outputs compete for the same audiences, revenues, and licensing opportunities as human creators.

Against that backdrop, the American Music Fairness Act is no longer simply a current solution to a decades-old copyright reform proposal. If AI companies are correct that generative AI will place unprecedented pressure on the economics of human creativity, then Congress should strengthen—not further weaken—all of the economic foundations supporting human creators. AMFA would finally require terrestrial broadcasters to compensate featured artists, session musicians, and vocalists for the use of their sound recordings, just as streaming and satellite radio already do. It would also unlock reciprocal foreign performance royalties that American performers currently forfeit because the United States remains an international outlier. 

At a moment when AI is intensifying the struggle for creative labor to survive even while platforms seek broad legal exceptions for uncompensated training through lobbying and executive orders, eliminating one of copyright law’s oldest uncompensated uses would send an important signal: the future of artificial intelligence should not be financed by the continued erosion of the livelihoods of human creators.

The AI industry’s habit of predicting existential harm while aggressively commercializing the same technology presents a profound ethical contradiction that Professor Cal Newport calls “doom trolling” in a recent New York Times post.  This leads to a conclusion that AI companies cannot credibly claim their technology poses existential risks while continuing to accelerate its commercialization without meaningful restraint.

Newport gives this example reminiscent of my personal favorite, the exploding gas tank in Ford Pintos (not to pick on Ford):

Imagine if the Ford Motor Company put out a report saying that it feared its popular F-150 trucks might soon start bursting into flames, but that there was nothing the company could do about it because automotive technology was too inevitable and important to slow down. You’re probably struggling to picture this scenario because no reasonable consumer product company would ever act like this. 

The A.I. companies could start behaving the same way. To do so would require that they stop treating A.I. like some inevitable force that they’re struggling to steward. It’s not. It’s a collection of specific tools that these companies are choosing to design and sell according to specific business plans. Accordingly, they need to talk about their offerings like any other consumer product. This means explaining clearly whom these products are for, justifying their benefits and, critically, taking full responsibility for any harm they might cause. Just because A.I. currently enjoys a high-tech sheen doesn’t make it exceptional with respect to common-sense safety standards.

If these A.I. companies insist on continuing to pretend that they’re merely stoic observers of an unavoidable dystopian future, then perhaps it’s time to force the issue. As consumers, we can refuse to play the doom-trolling game. Next time Anthropic releases a dire report, or Sam Altman’s voice cracks as he imagines the disruption that OpenAI is unleashing, we can pivot back to the pragmatic: “OK, but what benefits am I getting by spending $1,000 a month on tokens?” If they continue to ratchet up the doom, then perhaps it’s time to transform dread into ridicule: The earnest pseudoscience of Anthropic’s white papers already borders on satire. The current zeitgeist surrounding A.I. encourages a fretful submission to these tech leaders, but this could rapidly change.

The AI industry cannot have it both ways. It cannot warn that generative AI will fundamentally transform—or even eliminate—millions of creative jobs while simultaneously insisting that the law should expand uncompensated access to the very works that make those systems possible. If AI companies genuinely believe their own predictions, then the appropriate public policy response is not to weaken copyright, broaden fair use, or create new exceptions for commercial training. It is to reinforce every remaining economic support for human creativity. 

The evidence emerging from music streaming already demonstrates why. AI-generated works are not merely theoretical substitutes; they compete for attention, streams, and revenue, measurably reducing each creator’s share of a finite, shared royalty pool. That provides some of the clearest real-world evidence yet of repeatable market harm from generative AI at commercial scale. Congress should take note. The question is no longer whether creators deserve compensation for their work. It is whether the United States will choose to finance the AI economy by systematically eroding the economic incentives that have sustained human creativity for generations—or whether it will insist that technological progress, like every other successful industry before it, pays its own way.

Perhaps the greatest lesson of the American Music Fairness Act is not about radio at all. It is about refusing to repeat yesterday’s policy mistakes in tomorrow’s technology. As Mike Huppe observed on Bloomberg, Congress should not be creating new copyright exceptions while it is still trying to fix old ones. That warning applies with even greater force to artificial intelligence. If policymakers know that generative AI is likely to place extraordinary pressure on the economics of human creativity—as many AI companies themselves readily acknowledge—then the answer cannot be to expand uncompensated uses of creative works in the name of innovation and unintended consequences be damned.

The webcasting revolution showed what Hernando de Soto long argued: respecting property rights doesn’t kill innovation—it gives innovators the legal foundation to build sustainable markets. AMFA is a cautionary tale: a narrow copyright exception adopted decades ago has deprived generations of American performers of compensation and remains difficult to unwind. Congress should learn from that history, not repeat it. The AI economy should be built by paying for the creative works that make it possible and respecting the rights of all creators—not by creating another exception that future generations will spend decades trying to reverse and an entrenched bureaucracy of the richest corporations in commercial history will oppose with all the resources they can muster.

Phonorecords V and the “39 Steps” Problem: Time for the CRB to Fix Streaming Mechanicals

As we head back into the next Phonorecords proceeding, there is an issue hiding in plain sight inside the existing and ancient streaming mechanical royalty rate structure that we fondly call “the 39 steps” in honor of John Buchan, Alfred Hitchcock and Richard Hannay. Despite the blood lust for complexity from the ancien régime that clings to its one sided royalty pool, there is one part of this unfair business practice that the Copyright Royalty Board (CRB) can and should address this time around.

Start with the basics. The part 385 streaming mechanical formula—the so-called “39 steps”—is built on a simple premise: we are calculating royalties for the use of musical works protected by the Copyright Act. The inputs and deductions in that formula are not abstract accounting categories. They are supposed to reflect real payments for real statutory rights.

That premise is now under pressure.

The rise of generative AI has introduced a new category of output that does not fit neatly within the Copyright Act. The U.S. Copyright Office has made clear that works generated entirely by AI are not copyrightable, and that protection exists only to the extent of meaningful human authorship in a proportion yet to be determined. Courts have moved in the same direction, and the Supreme Court’s denial of cert in Thaler v. Perlmutter leaves that framework intact.

Yet the part 385 formula has no explicit mechanism to deal with this category of material. That creates a risk on two fronts.

We have to consider the royalty pool itself. Section 115 applies when the exclusive rights of a copyright owner in a musical work are implicated. If a so-called “AI track” is not a protected musical work, then there is a serious question whether it belongs in the section 115 system at all. Treating non-copyrightable output as if it were a statutory musical work risks diluting the pool for actual rightsholders.

And then, of course, we have the Step 2 deduction for performance royalties. The regulation allows services to subtract payments for the public performance of musical works before calculating the payable pool. But what happens if a service characterizes payments to a platform like AIMPRO as “performance royalties”? If those payments are not, in fact, for the public performance of a protected musical work, they should not reduce the pool. Otherwise, the formula becomes a vector for leakage.

Moreover, if the U.S. Copyright Office ultimately articulates a workable “human authorship” framework for AI-assisted works during the Phonorecords V rate period, the downstream impact on the section 115 system could be profound: for the first time, the part 385 “39 steps” calculation may have to accommodate fractional copyrightability within a single work. Instead of treating a musical work as a binary input (in or out), services and the MLC could be forced to parse which portions of a track are attributable to human authorship and therefore eligible for royalties, and which are not. That would introduce a new layer of allocation on top of an already complex formula—effectively embedding micro-level authorship determinations into macro-level royalty calculations—and raising the administrative, evidentiary, and dispute-resolution burdens across the entire system.

The key point is that the CRB does not need to resolve all questions of AI copyrightability to act here for purposes of the 39 Steps. It can simply clarify what is already in the statute and the regulation: The part 385 formula applies only to payments that correspond to rights in nondramatic musical works, and deductions are limited to payments that genuinely compensate the public performance of such works. That is not a policy innovation. It is a classification rule.

If there is doubt about whether a category of material such as purely generative AI output qualifies as a “musical work” for these purposes, that is a question the CRB can refer to the Register of Copyrights in a pinch. But the CRB should not leave the door open for the mechanical royalty pool to be diluted by payments for things that fall outside the Copyright Act altogether.

This may also be the moment to ask a more fundamental question: whether the industry should abandon the “39 steps” construct altogether. Whatever its historical justification—particularly in Phonorecords I, where publishers were trying to shield early services like MusicNet from crushing retroactive exposure—the current formula has outlived its usefulness. Today, it functions less as a fair pricing mechanism and more as a constraint, allowing services to use their complementary oligopoly power to effectively cap mechanical royalties by anchoring them to total content costs. The result is a structurally odd feedback loop in which sound recording deals influence the value of adjacent musical works. A cleaner alternative would be a flat, escalating penny-rate framework, akin to what the Judges adopted for both Subpart B mechanical royalties (physical and downloads) as well as section 114 royalties—simpler, more transparent, and far less susceptible to strategic manipulation.

We have been here before. The history of section 115 is, in many ways, the history of closing gaps between statutory language and market behavior.

Phonorecords V presents another such moment.

The CRB should take it.

The Elusive Obelus: Streaming’s Problem With Denominators

“How did you go bankrupt?” Bill asked.
“Two ways,” Mike said. “Gradually and then suddenly.”

Ernest Hemingway, The Sun Also Rises.

No matter how much people would like to deflect it, the unvarnished per stream rate is an ever diminishing income stream.  Given the number of calculations involved for both sound recording and song, it is likely that the total end-to-end cost of rendering the accountings for the streams costs more than the royalty earned on that stream by any one royalty participant.  Solving this problem is the difference between a short-term stock-fueled sugar high and a long-term return of shareholder value for all concerned.  So now what?

If you’re someone who receives or calculates streaming royalties, you’re already familiar with the  problem of the ever-decreasing per-stream rate.  The Trichordist’s definitive “Streaming Price Bible” for 2018 confirms this trend yet again, but simple math explains the problem of the revenue share allocation.

Remember that the way streaming royalties are calculated in voluntary agreements (aka “direct deals”) revolves around a simple formula (Formula A):

(Payable Revenue ÷ Total Service Streams) x Your Streams = Per Stream Rate

Which may also be expressed as Formula B:

Payable Revenue x (Your Streams ÷ Total Service Streams) = Your share of revenue

(Formula A and B are also known as “the big pool” in the user-centric or Ethical Pool models.)

Here’s the trick–it’s in the correlation of the rate of increase over time of the numerator and the denominator.  If you focus on any single calculation you won’t see the problem.  You have to calculate the rate of change over time.  Simply put, if the numerator in either Formula A or Formula B increases at a lower rate than the denominator, then the quotient, or the result of the division, will always decline as long as those conditions are met.  That’s why the Streaming Price Bible shows a declining per-stream rate–a contrarian fact among the hoorah from streaming boosters that sticks in the craw.

Services make these accounting calculations monthly for the most part, and they are calculated a bit differently depending on the service.  This is why the Streaming Price Bible has different rates for different services, rates that vary depending on the terms of the contract and also the amount of “Payable Revenue” that the service attributes to the particular sound recordings.

The quotient will also vary depending on the copyright owner’s deal.  If you add downside protection elements such as contractual per stream or per subscriber minimums, then you can cushion the decline.

This is also true of non-recoupable payments (such as direct payments that are deemed to be recoupable but not returnable, or “breakage”).  Nonrecoupable payments are just another form of nominal royalty payable to the copyright owner, and increase the overall payout.  And of course, the biggest nonrecoupable payment is stock which sometimes pays off as we saw with Spotify.  These payments may or may not be shared with the artist.  (See the WIN Fair Digital Deals Pledge.)

So each of the elements of both Formula A and Formula B are a function of other calculations. We’re not going to dive into those other elements too deeply in this post–but we will note that there are some different elements to the formulas depending on the bargaining power of the rights owner, in this case the owner of sound recordings.

So how is it that the per-stream rate declines over time in the Streaming Price Bible?

Putting the Demon in the Denominator

Back to Formula B, you’ll note that the function “Your Streams ÷ Total Service Streams” looks a lot like a market share allocation.  In fact, if the relevant market is limited to the service calculating the revenue share allocation, it is a market share allocation of service revenue by another name.  When you consider that the customary method of calculating streaming royalties across all services is a similar version of Formula B, it may as well be an allocation of the total market on a market share basis.

Note that this is very different from setting a wholesale price for your goods that implies a retail price.  A wholesale price is a function of what you think a consumer would or should pay.  When a service agrees to a minimum per stream or per subscriber rate, they are essentially accepting a price term that behaves like a wholesale price.

For most artists and indie labels, the price is set by your market share of the subscription fees or ad rates that the service thinks the market will bear based on the service’s business goals—not based on your pricing decision.

Why is this important?  A cynic might say it’s because Internet companies are in the free lunch crowd–they would give everything away for free since their inflated salaries and sky-high rents are paid by venture capitalists who don’t understand a thing about breaking artists and investing in talent.  You know, the kind of people who would give Daniel Ek a million dollar bonus when he hadn’t met his performance targets, stiffed songwriters for years and gotten the company embroiled in multimillion dollar lawsuits.  But had met the only performance target that mattered which was to put some cosmetics on that porker and push it out the door into a public stock offering.  (SPOT F-1 at p. 133: “In February 2018, our board of directors determined to pay Mr. Ek the full $1,000,000 bonus based on the Company’s 2017 performance though certain performance goals were not achieved…”)

But long-term, it’s important because one way that royalties will rise is if the service can only acquire its only product at a higher price.  Or not.  The other way that royalties will rise is if services are required to pay a per-stream rate that is higher than the revenue share rate.  How that increase is passed to the consumer is up to them.  Maybe a move from World Trade Center to Poughkeepsie would help.

The Streaming Price Bible is based on revenue for an indie label that did not have the massive hits we see on Spotify.  In this sense, it is the unvarnished reality of streaming without the negotiated downside protection goodies, unrecoupable or nonreturnable payments, and of course shares of stock.  While some may say the Bible lacks hits, that’s kind of the point–hits mask a thousand sins.  Ask any label accountant.

Will Consumption Eat Your Free Lunch?

Let’s say again: The simple explanation for the longitudinal decline of streaming royalties measured by the Streaming Price Bible is that the rate of change across accounting periods in the “Payable Revenue” must be greater than the rate of change in the total number of streams in order for the per-stream rate to increase–otherwise the per-stream rate will always decrease.  Another way to think of it is that revenue has to increase faster than consumption, or consumption will eat your lunch.

What if you left the formula the same and just increased the revenue being allocated?  Services will probably resist that move.  After all, when artists complain about their per-stream rate, the services often answer that the problem is not with them, it is with the artist’s labels because the services pay hundreds of millions to the labels.

We don’t really have much meaningful control over what goes in the monthly payable revenue number (i.e., the mathematical “dividend” or numerator).  What kinds of revenue should be included?  Here are a few:

–all advertising revenue from all sources
–e-commerce transactions
–bounties or referral fees, including  recoupable or non-refundable guarantees
–sponsorships
–subscription income
–traffic or tariff charges paid by telcos
–revenue from the sale of data

Services will typically deduct “small off the tops” which would include
–VAT or sales tax
–ad commissions paid to unaffiliated third parties (usually subject to a cap)

Indie labels and independent artists may not have the leverage to negotiate some of these revenue elements such as revenue from the sale of data for starters.  Other elements of the revenue calculation for indie labels and artists will also likely not include the downside protections, subscriber target top up fees and the like.

And of course the biggest difference is that indie labels (at least not in the Merlin group who may) typically do not get nonreturnable advances,  nonrecoupable payments, or stock.

Is That All There Is?

Why should we care about all this?  There is a story that is told of negotiations to settle a lawsuit against a well-known pirate site.  One of the venture capitalists backing the pirates told one of the label negotiators that he could make them all richer through an IPO than any settlement they’d ever be able to negotiate.

The label executive asked, lets’ say we did that, but then what happens?  You say we should adapt, but you’re still destroying the industry ecosystem so that there’s nothing left to adapt to.  The most we could make from an IPO would cover our turnover for a year at best.  And we would be dependent on your success, not our artists’ success.

Then what?