JENNIFER WOLFE

Los Angeles-based media strategist & technology storyteller

AI Copyright Law Is Complete Chaos But It Doesn’t Have to Be



TL;DR

  • There may be an existential element to the strikes, but they are actually the age-old concerns of labor fighting against what it sees as an unjust division of power and capital.
  • The law has not kept pace with the speed of AI but that’s not to say that existing protections can’t be extended and adapted to solve issues.
  • It almost requires an AI to compute all the possible consequences of how the technology might be used, and that use is being interpreted by humans with feelings and emotions and fears and values which in some ways are not predictable nor consistent with cold logical math.


READ MORE: Generative AI and the media sector: Preliminary thoughts on a legal and policy agenda (The Platform Law Blog)

No issue exercises more minds in the industry just now than AI but as legendary scriptwriter William Goldman once said, “Nobody knows nothing.”

That’s because AI is a runaway train, speeding ahead of existing protections such as those around copyright and in contract law, which actors and writer’s are demand rewriting to account for their own personal data being rewarded in perpetuity. AI tools like ChatGPT are also black boxes even to the folk at OpenAI, who developed them — no one seems sure of how it actually works, let alone what it is capable of.

It feels like a maelstrom right now although more than one commentator has pointed out that what is actually happening is a good old-fashioned fight for rights between labor and capital.

In which case, a good deal of what is being played out in the name of AI is a continuation of existing trends and inequalities that could be dealt with by existing law, or extensions of same.

Competition law specialists Geradin Partners writes in a blog post, “many of the problems experienced by media organizations are neither new nor specific to GenAI. Therefore, in many cases, the solution may not necessarily consist in adopting new rules, but in sensibly revising and extending the scope of existing rules.”

Another lawyer, Gregor Pryor of Reed Smith, explained, “AI is pushing existing legal concepts to their limits, inventing new ones and generally questioning the relationship between our legal systems and machines in an unprecedented manner.”

READ MORE: Reed Smith publishes guide exploring AI in the entertainment and media industry (Reed Smith)

A factor determining the economic impact of generative AI, for example, is who owns data and models. Geradin Partners notes that ownership of data and models are often highly centralized, leading to market concentration.

At a recent government hearing Senator Cory Booker said, “One of my biggest concerns about this space is what I’ve already seen in the space of Web2, Web3 is this massive corporate concentration. It is really terrifying to see how few companies now control and affect the lives of so many of us. And these companies are getting bigger and more powerful.”

Alarmingly, OpenAI boss Sam Altman confirmed at the Senate hearing: “What’s happening in the open source community is amazing, but there will be a relatively small number of providers that can make models at the cutting edge.”

Given the monopoly of such power, it is likely that concerns about abuses of dominance and “gatekeeping” will arise,” thinks Geradin Partners, adding that practices such as tying/bundling, self-preferencing, default settings, and refusal to grant access to data may be employed to strengthen existing ecosystems. Examples include bundling search or social networks with generative AI tools, tying cloud services packages to AI services, etc.

Ensuring that generative AI evolves in a manner that is conducive to intellectual property rights (IPR) protection is arguably one of the greatest challenges to address from the perspective of the media and creative industries.

“It is widely accepted that inadequate IPR protection chills content creativity and innovation,” says the law firm. There are established rules for text and data mining but Geradin wonders as generative AI services proliferate and their popularity increases, whether the these are is fit for purpose.

Two of the most debated issues when discussing the regulation of the digital economy — not just AI — is the lack of transparency underpinning how technologies and applications work and the limited accountability of their providers. In the EU, the main instruments that (will) establish rules seeking to promote and transparency and accountability in the digital economy are the Digital Services Act and the AI Act.

This is happening as the industry pushes for regulations. Michael Nash, chief digital officer for Universal Music Group, tells Winston Cho at The Hollywood Reporter that AI programs training machine learning models by feeding them copyrighted works without permission from or payment to UMG’s artists “enables us to have a very important seat at the table around the evolution and use of these models, particularly with respect to developing new licensing opportunities.”

He underscores the adoption of AI is to “put these tools in the hands of artists” to see “how far their vision can take this technology.”

The Society of Composers and Lyricists, with creators of scores and song for film, TV and theater as members, maintains that AI firms should have to secure consent by creators for the use of their works to train AI programs and compensate them at fair market rates for the subsequent creation of any new work that’s created on top of providing the proper credit, Cho reports. The SCL stresses that any regulatory framework should not grant copyright protection to AI-generated works since doing so could flood the market with them, diluting the value of original pieces.

According to THR, UMG has been sending requests to take down AI-generated songs, but is fighting “an entire online community dedicated to making, sharing and teaching others how to create AI music.”

On Discord, members of a server called AI Hub released an album in April called UTOP-AI — a play on an upcoming project from Travis Scott — featuring the AI-generated voices of the rapper along with Drake, Playboy Carti and Baby Keem. It got nearly 200,000 views on YouTube and Soundcloud in just three hours before it was flagged for copyright infringement by Warner Music Group.

READ MORE: “I Have a Problem With the Stealing of My Material”: A Common Rallying Cry Emerges On AI (The Hollywood Reporter)

Tech companies entrenched in the M&E industry are taking a cautious approach. Some studios, Pixar among them, are building their own generative AI models but training them on their own back catalog of films. Others like Shutterstock, Valve and Adobe are flagging copyright concerns as a selling point.

Like Disney and other large studios, however, Adobe and Shutterstock are in the fortunate position of owning databanks of images, concept art and videos to train new AI models. Because they can be absolutely sure where the assets used come from, they can offer indemnification against any copyright lawsuits brought against their users.

READ MORE: Inside the big promise Adobe is making to advertisers with its generative AI tool (The Drum)

“It is an extremely smart marketing technique for the companies, as they are both highlighting a fundamental issue with AI and highlighting how, by their nature, that issue will never arise for its users,” says Chris Sutcliffe at The Drum.

READ MORE: How tech companies are approaching generative AI copyright (The Drum)

Valve, meanwhile, said it would not be hosting games that use AI-generated assets on its Steam platform. The company clarified to Victory Kennedy at Eurogamer that its decision to delist a game created by a solo developer due to its use of AI-generated assets was not simply its opinion on the tech, but a reflection of how it interprets the current copyright laws.

READ MORE: Valve says AI-generated content policy goal is “not to discourage the use of it on Steam” (Eurogamer)

A team of 14 legal experts across disciplines has just published a paper on generative AI in Science magazine. One of the key questions that emerged was whether copyright laws can adequately deal with the unique challenges of generative AI.

“Generative AI might seem unprecedented, but history can act as a guide,” three of the paper’s authors conclude in an essay written for The Conversation. For example, the US Copyright Office has stated unequivocally that only humans can hold copyrights.

Matters are more complicated when outputs resemble works in the training data. If the resemblance is based only on general style or content, it is unlikely to violate copyright, because style is not copyrightable.

Even here there could be a solution. Since copyright law tends to favor an all-or-nothing approach, scholars at Harvard Law School have proposed new models of joint ownership that allow artists to gain some rights in outputs that resemble their works.

The issue is complex in the extreme but writer’s and actors (possibly directors and producers and production designers and concept artists and costume and make-up designers down the line) understandably want some assurance now that they are not going to be taken for a ride in future.

It almost requires an AI to compute all the possible consequences of how the technology might be used, and that use is being interpreted by humans with feelings and emotions and fears and values which in some ways are not predictable and not consistent with binary logic.

READ MORE: Generative AI is a minefield for copyright law (The Conversation)

Back to Goldman. Would an AI really have devised the sparse but brilliant script for Butch Cassidy and the Sundance Kid, the film that set the template for every buddy movie since?

“Kid, the next time I say, ‘Let’s go some place like Bolivia,’ let’s go some place like Bolivia.”

Jennifer Wolfe

A Los Angeles-based content producer and media strategist with 15+ years of experience in Media & Entertainment, I bring a broad-scope knowledge of M&E business and technologies spanning visual storytelling, creative post production, and digital content creation and delivery. Fluent across digital publishing platforms, including development and back-end management, I am highly skilled at translating technical workflows into narratives that showcase product features and capabilities.