South Korea has become the latest flashpoint in a rapidly globalizing conflict over artificial intelligence, creator rights and copyright. A broad coalition of Korean creator and copyright organizations—spanning literature, journalism, broadcasting, screenwriting, music, choreography, performance, and visual arts—has issued a joint statement rejecting the government’s proposed Korea AI Action Plan, warning that it risks allowing AI companies to use copyrighted works without meaningful permission or payment.
The groups argue that the plan signals a fundamental shift away from a permission-based copyright framework toward a regime that prioritizes AI deployment speed and “legal certainty” for developers, even if that certainty comes at the expense of creators’ control and compensation. Their statement is unusually blunt: they describe the policy direction as a threat to the sustainability of Korea’s cultural industries and pledge continued opposition unless the government reverses course.
The controversy centers on Action Plan No. 32, which promotes “activating the ecosystem for the use and distribution of copyrighted works for AI training and evaluation.” The plan directs relevant ministries to prepare amendments—either to Korea’s Copyright Act, the AI Basic Act, or through a new “AI Special Act”—that would enable AI training uses of copyrighted works without legal ambiguity.
Creators argue that “eliminating legal ambiguity” reallocates legal risk rather than resolves it. Instead of clarifying consent requirements or building licensing systems, the plan appears to reduce the legal exposure of AI developers while shifting enforcement burdens onto creators through opt-out or technical self-help mechanisms.
Similar policy patterns have emerged in the United Kingdom and India, where governments have emphasized legal certainty and innovation speed while creative sectors warn of erosion to prior-permission and fair-compensation norms. South Korea’s debate stands out for the breadth of its opposition and the clarity of the warning from cultural stakeholders.
The South Korean government avoids using the term “safe harbor,” but its plan to remove “legal ambiguity” reads like an effort to build one. The asymmetry is telling: rather than eliminating ambiguity by strengthening consent and payment mechanisms, the plan seeks to eliminate ambiguity by making AI training easier to defend as lawful—without meaningful consent or compensation frameworks. That is, in substance, a safe harbor, and a species of blanket license. The resulting “certainty” would function as a pass for AI companies, while creators are left to police unauthorized use after the fact, often through impractical opt-out mechanisms—to the extent such rights remain enforceable at all.
Tag: AI copyright
AI’s Legal Defense Team Looks Familiar — Because It Is
If you feel like you’ve seen this movie before, you have.
Back in the 2003-ish runup to the 2005 MGM Studios, Inc. v. Grokster, Ltd. Supreme Court case, I met with the founder of one of the major p2p platforms in an effort to get him to go legal. I reminded him that he knew there was all kinds of bad stuff that got uploaded to his platform. However much he denied it, he was filtering it out and he was able to do that because he had the control over the content that he (and all his cohorts) denied he had.
I reminded him that if this case ever went bad, someone was going to invade his space and find out exactly what he was up to. Just because the whole distributed p2p model (unlike Napster, by the way) was built to both avoid knowledge and be a perpetual motion machine, there was going to come a day when none of that legal advice was going to matter. Within a few months the platform shut down, not because he didn’t want to go legal, but because he couldn’t, at least not without actually devoting himself to respecting other people’s rights.
Everything Old is New Again
Back in the early 2000s, peer-to-peer (P2P) piracy platforms claimed they weren’t responsible for the illegal music and videos flooding their networks. Today, AI companies claim they don’t know what’s in their training data. The defense is essentially the same: “We’re just the neutral platform. We don’t control the content.” It’s that distorted view of the DMCA and Section 230 safe harbors that put many lawyers’ children through prep school, college and graduate school.
But just like with Morpheus, eDonkey, Grokster, and LimeWire, everyone knew that was BS because the evidence said otherwise — and here’s the kicker: many of the same lawyers are now running essentially the same playbook to defend AI giants.
The P2P Parallel: “We Don’t Control Uploads… Except We Clearly Do”
In the 2000s, platforms like Kazaa and LimeWire were like my little buddy–magically they never had illegal pornography or extreme violence available to consumers, they prioritized popular music and movies, and filtered out the worst of the web
That selective filtering made it clear: they knew what was on their network. It wasn’t even a question of “should have known”, they actually knew and they did it anyway. Courts caught on.
In Grokster, the Supreme Court side stepped the hosting issue and essentially said that if you design a platform with the intent to enable infringement, you’re liable.
The Same Playbook in the AI Era
Today’s AI platforms — OpenAI, Anthropic, Meta, Google, and others — essentially argue:
“Our model doesn’t remember where it learned [fill in the blank]. It’s just statistics.”
But behind the curtain, they:
– Run deduplication tools to avoid overloading, for example on copyrighted books
– Filter out NSFW or toxic content
– Choose which datasets to include and exclude
– Fine-tune models to align with somebody’s social norms or optics
This level of control shows they’re not ignorant — they’re deflecting liability just like they did with p2p.
Déjà Vu — With Many of the Same Lawyers
Many of the same law firms that defended Grokster, Kazaa, and other P2P pirate defendants as well as some of the ISPs are now representing AI companies—and the AI companies are very often some, not all, but some of the same ones that started screwing us on DMCA, etc., for the last 25 years. You’ll see familiar names all of whom have done their best to destroy the creative community for big, big bucks in litigation and lobbying billable hours while filling their pockets to overflowing.
The legal cadre pioneered the ‘willful blindness’ defense and are now polishing it up for AI, hoping courts haven’t learned the lesson. And judging…no pun intended…from some recent rulings, maybe they haven’t.
Why do they drive their clients into a position where they pose an existential threat to all creators? Do they not understand that they are creating a vast community of humans that really, truly, hate their clients? I think they do understand, but there is a corresponding hatred of the super square Silicon Valley types who hate “Hollywood” right back.
Because, you know, information wants to be free—unless they are selling it. And your data is their new oil. They apply this “ethic” not just to data, but to everything: books, news, music, images, and voice. Copyright? A speed bump. Terms of service? A suggestion. Artist consent? Optional. Writing a song is nothing compared to the complexities of Biggest Tech.
Why do they do this? OCPD Much?
Because control over training data is strategic dominance and these people are the biggest control freaks that mankind has ever produced. They exhibit persistent and inflexible patterns of behavior characterized by an excessive need to control people, environments, and outcomes, often associated with traits of obsessive-compulsive personality disorder.
So empathy will get you nowhere with these people, although their narcissism allows them to believe that they are extremely empathetic. Pathetic, yes, empathetic, not so much.
Pay No Attention to that Pajama Boy Behind the Curtain
The driving force behind AI is very similar to the driving force behind the Internet. If pajama boy can harvest the world’s intellectual property and use it to train his proprietary AI model, he now owns a simulation of the culture he is not otherwise part of, and not only can he monetize it without sharing profits or credit, he can deny profits and credit to the people who actually created it.
So just like the heyday of Pirate Bay, Grokster & Co. (and Daniel Ek’s pirate incarnation) the goal isn’t innovation. The goal is control over language, imagery, and the markets that used to rely on human creators. This should all sound familiar if you were around for the p2p era.
Why This Matters
Like p2p platforms, it’s just not believable that the AI companies do know what’s in their models. They may build their chatbot interface so that the public can’t ask the chatbot to blow the whistle on the platform operator, but that doesn’t mean the company can’t tell what they are training on. These operators have to be able to know what’s in the training materials and manipulate that data daily.
They fingerprint, deduplicate, and sanitize their datasets. How else can they avoid having multiple copies of books, for example, that would be a compute nightmare. They store “embeddings” in a way that they can optimize their AI to use only the best copy of any particular book. They control the pipeline.
It’s not about the model’s memory. It’s about the platform’s intent and awareness.
If they’re smart enough to remove illegal content and prioritize clean data, they’re smart enough to be held accountable.
We’re not living through the first digital content crisis — just the most powerful one yet. The legal defenses haven’t changed much. But the stakes — for copyright, competition, and consumer protection — are much higher now.
Courts, Congress, and the public should recognize this for what it is: a recycled defense strategy in service of unchecked AI power. Eventually Grokster ran into Grokster— and all these lawyers are praying that there won’t be an AI version of the Grokster case.
Steve’s Not Here–Why AI Platforms Are Still Acting Like Pirate Bay
In 2006, I wrote “Why Not Sell MP3s?” — a simple question pointing to an industry in denial. The dominant listening format was the MP3 file, yet labels were still trying to sell CDs or hide digital files behind brittle DRM. It seems kind of incredible in retrospect, but believe me it happened. Many cycles were burned on that conversation. Fans had moved on. The business hadn’t.
Then came Steve Jobs.
At the launch of the iTunes Store — and I say this as someone who sat in the third row — Jobs gave one of the most brilliant product presentations I’ve ever seen. He didn’t bulldoze the industry. He waited for permission, but only after crafting an offer so compelling it was as if the labels should be paying him to get in. He brought artists on board first. He made it cool, tactile, intuitive. He made it inevitable.
That’s not what’s happening in AI.
Incantor: DRM for the Input Layer
Incantor is trying to be the clean-data solution for AI — a system that wraps content in enforceable rights metadata, licenses its use for training and inference, and tracks compliance. It’s DRM, yes — but applied to training inputs instead of music downloads.
It may be imperfect, but at least it acknowledges that rights exist.
What’s more troubling is the contrast between Incantor’s attempt to create structure and the behavior of the major AI platforms, which have taken a very different route.
AI Platforms = Pirate Bay in a Suit
Today’s generative AI platforms — the big ones — aren’t behaving like Apple. They’re behaving like The Pirate Bay with a pitch deck.
– They ingest anything they can crawl.
– They claim “public availability” as a legal shield.
– They ignore licensing unless forced by litigation or regulation.
– They posture as infrastructure, while vacuuming up the cultural labor of others.
These aren’t scrappy hackers. They’re trillion-dollar companies acting like scraping is a birthright. Where Jobs sat down with artists and made the economics work, the platforms today are doing everything they can to avoid having that conversation.
This isn’t just indifference — it’s design. The entire business model depends on skipping the licensing step and then retrofitting legal justifications later. They’re not building an ecosystem. They’re strip-mining someone else’s.
What Incantor Is — and Isn’t
Incantor isn’t Steve Jobs. It doesn’t control the hardware, the model, the platform, or the user experience. It can’t walk into the room and command the majors to listen with elegance. But what it is trying to do is reintroduce some form of accountability — to build a path for data that isn’t scraped, stolen, or in legal limbo.
That’s not an iTunes power move. It’s a cleanup job. And it won’t work unless the AI companies stop pretending they’re search engines and start acting like publishers, licensees, and creative partners.
What the MP3 Era Actually Taught Us
The MP3 era didn’t end because DRM won. It ended because someone found a way to make the business model and the user experience better — not just legal, but elegant. Jobs didn’t force the industry to change. He gave them a deal they couldn’t refuse.
Today, there’s no Steve Jobs. No artists on stage at AI conferences. No tactile beauty. Just cold infrastructure, vague promises, and a scramble to monetize other people’s work before the lawsuits catch up. Let’s face it–when it comes to Elon, Sam, or Zuck, would you buy a used Mac from that man?
If artists and AI platforms were in one of those old “I’m a Mac / I’m a PC” commercials, you wouldn’t need to be told which is which. One side is creative, curious, collaborative. The other is corporate, defensive, and vaguely annoyed that you even asked the question.
Until that changes, platforms like Incantor will struggle to matter — and the AI industry will continue to look less like iTunes, and more like Pirate Bay with an enterprise sales team.
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