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DMCA Abuse, Deleted Evidence and Damaged Credibility

In C21 Pty Ltd (Trustee) v Hou (No 6) [2025] FedCFamC2G 927, Judge Manousaridis handed down a strongly worded decision marking the latest chapter in a copyright enforcement saga — and it’s not one Mr Hou will be pleased with.

The case delivers a clear warning about the misuse of takedown procedures, destruction of evidence, and strategic dishonesty in IP disputes.

The Story So Far

C21, a real estate agency and video producer, had previously succeeded in proving that Mr Hou had infringed copyright in a range of marketing videos and photographs. The current decision dealt with the consequences: what additional orders should flow from the infringements — and how Mr Hou’s subsequent conduct should influence those outcomes.

DMCA Misuse

One of the key issues was Mr Hou’s deliberate use of DMCA takedown notices to get C21’s legitimately owned videos removed from YouTube. Despite prior court findings that C21 owned the copyright in those materials, Mr Hou sent notices claiming infringement — knowingly and falsely asserting he was the rights holder.

Judge Manousaridis held that these takedown notices were issued:

  • With no lawful basis;

  • In a continuing effort to damage C21’s business;

  • And in knowing contradiction to the findings in earlier proceedings.

Deleted Evidence

Equally concerning was Mr Hou’s deletion of thousands of emails, including emails that may have contained information relevant to the proceedings. The Court accepted that this was done:

  • After the proceedings had commenced;

  • With knowledge of the likely relevance of those materials;

  • And without any acceptable explanation for their destruction.

This led to adverse inferences being drawn about the deleted material.

Additional Damages and Costs

Given the flagrancy of the infringement and the subsequent conduct:

  • The Court awarded additional damages under s 115(4) of the Copyright Act;

  • Compensatory damages were set at $4,200;

  • Additional damages were calculated at $17,000, taking into account Mr Hou’s conduct and the need for deterrence;

  • Full costs were awarded to C21 on a standard basis.

Main Takeaways

The decision is a powerful reminder that:

  • Copyright enforcement tools like DMCA notices must not be weaponised — false claims are not just unethical, they’re legally risky;

  • Deleting relevant evidence mid-litigation can be just as damaging to your case as the infringement itself;

  • Courts take reputational harm and procedural abuse seriously, and will respond with enhanced penalties.

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Fair Use or Free Ride? The Case for an AI Blanket Licence

What if AI companies had to pay for the content they train on? Welcome to the next frontier in copyright law — where inspiration meets ingestion.

When AI companies train their models — whether for music, image generation, writing or video — they don’t do it in a vacuum. They train on us. Or more precisely: on our songs, our blogs, our art, our tweets, our books, our interviews.

They harvest it at scale, often scraped from the open web, with or without permission — and certainly without compensation.

This has prompted an increasingly vocal question from creators and content owners:

Shouldn’t we get paid when machines learn from our work?

The proposed answer from some corners: a blanket licensing regime.

What’s a Blanket Licence?

Nothing to do with bedding – a blanket licence is a pre-agreed system for legal reuse. It doesn’t ask for permission each time. Instead, it says:

You can use a defined pool of material for a defined purpose — if you pay.

We already see this in:

  • Music royalties (e.g. APRA, ASCAP, BMI)

  • Broadcast and public performance rights

  • Compulsory licensing of cover songs in the US

Could the same apply to AI?

What the Law Says (or Doesn’t)

AI companies argue that training their models on public material is “fair use” (US) or doesn’t involve “substantial reproduction” (Australia), since no exact copy of the work appears in the output.

However, copies are made during scraping, and substantial parts are almost certainly reproduced during the training process or embedded in derivative outputs — either of which could pose problems under both US and Australian copyright law.

But courts are still catching up.

Pending or recent litigation:

  • The New York Times v OpenAI: scraping articles to train GPT

  • Sarah Silverman v Meta: use of copyrighted books

  • Getty Images v Stability AI: image training and watermark copying

None of these cases have yet resolved the underlying issue:

Is training AI on copyrighted works a use that requires permission — or payment?

What a Blanket Licence Would Do

Under a blanket licence system:

  • Training (and copying or development of derivatives for that purpose) would be lawful, as long as the AI provider paid into a fund

  • Creators and rights holders would receive royalty payments, either directly or via a collecting society

  • A legal baseline would be established, reducing lawsuits and uncertainty

This would mirror systems used in broadcasting and streaming, where revenue is pooled and distributed based on usage data.

Challenges Ahead

1. Who Gets Paid?

Not all data is traceable or attributed. Unlike Spotify, which tracks each song streamed, AI models ingest billions of unlabeled tokens.

How do you determine who owns what — and which parts — of material abstracted, fragmented, and stored somewhere in the cloud?

2. How Much?

Rates would need to reflect:

  • The extent of use

  • The importance of the material to the training corpus

  • The impact on the original market for the work

This is tricky when a model is trained once and then used forever.

3. Which Countries?

Copyright laws vary. A licence in Australia might mean nothing in the US.

A global licence would require multilateral cooperation — and likely WIPO involvement.

Legal Precedent: Australia’s Safe Harbour and Statutory Licensing Models

Australia’s own statutory licensing schemes (e.g. educational copying under Part VB of the Copyright Act) show that:

  • Lawmakers can mandate payment for certain uses,

  • Even if individual rights holders never negotiated the terms,

  • Provided it’s reasonable, transparent, and compensatory.

But those systems also brought:

  • Bureaucratic collection processes

  • Contentious allocation models

  • Endless legal wrangling over definitions (What is “reasonable portion”? What qualifies as “educational purpose”?)

Expect the same for AI.

Creators and Innovation: A Balancing Act

For creators:

  • A blanket licence offers recognition and payment

  • It helps avoid the current “scrape now, settle later” model

  • It could fund new creative work rather than hollowing out industries

For innovators:

  • It provides legal certainty

  • Encourages investment in AI tools

  • Reduces the risk of devastating retroactive litigation

But if set up poorly, it could:

  • Be exclusionary (if licensing fees are too high for small players)

  • Be ineffective (if rights aren’t properly enforced or distributed)

  • Or be too slow to match AI’s pace

What’s Next?

Australia’s Copyright Act doesn’t currently recognise training as a specific form of use. But policy reviews are under way in multiple countries, including by:

  • The UK IPO

  • The European Commission

  • The US Copyright Office

  • And here in Australia, the Attorney-General’s Department is conducting consultations through 2024–25 on how copyright law should respond to AI

Creators, platforms, and governments are all watching the courts. But if consensus forms around the need for structured compensation, a statutory blanket licence might just be the solution.

Bottom Line

We’ve built AI on the backs of human creativity. The question isn’t whether to stop AI — it’s how to make it fair.

A blanket licence won’t solve every problem. But it could be the start of a system where creators aren’t left behind — and where AI learns with permission, not just ambition.

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Whose Work Is It Anyway? The Remix War, AI, Coffee Plungers and Swimsuits

From Elton John to anonymous meme-makers, a battle is raging over what it means to be “creative” — and whether it starts with permission.

Two stories made waves in copyright circles last week:

  • In the UK, Sir Elton John, Sir Paul McCartney and other musical heavyweights called for stronger rules to stop AI from “scraping” their songs without a licence.

  • In India, news agency ANI drew criticism for aggressively issuing YouTube copyright claims — even for sub-10 second clips — triggering takedown threats against creators.

At first glance, these might seem worlds apart. But they highlight the same question:

At what point does using someone else’s work become exploitation, not inspiration?

And who decides?

Creators vs Reusers: Two Sides of the Copyright Culture Clash

On one side: Creators — musicians, writers, filmmakers, photographers — frustrated by tech platforms and algorithms ingesting their work without permission. Whether it’s AI training data or news footage embedded in political commentary, their message is the same:
“You’re building on our backs. Pay up.”

On the other side: Remixers, meme-makers, educators, and critics argue that strict copyright regimes chill creativity. “How can we critique culture,” they ask, “if we’re not allowed to reference it?”

This isn’t new — hip hop, collage art, satire, and even pop music are full of samples and nods. But AI has industrialised the scale of reuse. It doesn’t borrow one beat or a single shot. It eats the entire catalogue — then spits out something “new.”

So what counts as originality anymore?

Australian Lens: Seafolly, Bodum, and the Meaning of “Original”

Seafolly v Madden [2012] FCA 1346

In this high-profile swimwear spat, designer Leah Madden accused Seafolly of copying her designs. She posted comparison images on social media implying that Seafolly had engaged in plagiarism. Seafolly sued for misleading and deceptive conduct under ss 52 and 53 of the Trade Practices Act 1974 (predecessors to s18 of the Australian Consumer Law – which had by then commenced but the relevant conduct being sued for took place before it had commenced).

The Federal Court found that Madden’s claims were not only misleading but also unsubstantiated, because the design similarities were not the result of actual copying. The case reinforced that:

  • Independent creation is a valid defence, even if the resulting works are similar

  • Superficial resemblance isn’t enough — there must be a causal connection

It’s a reminder that derivation must be substantial and material, not speculative or assumed.

Bodum v DKSH [2011] FCAFC 98

This case involved Bodum’s iconic French press coffee plunger — the Chambord — and whether a rival product sold by DKSH under the “Euroline” brand misled consumers or passed off Bodum’s get-up as its own.

Bodum alleged misleading or deceptive conduct and passing off, based not on name or logo, but on the visual appearance of the product: a clear glass beaker, metal band, and distinctive handles, which had come to be strongly associated with Bodum.

At trial, the Federal Court rejected Bodum’s claims. But on appeal, the Full Federal Court reversed that decision, holding that:

  • Bodum had a substantial reputation in the get-up alone;

  • The Euroline plunger was highly similar in appearance; and

  • DKSH’s failure to adequately differentiate its product through branding or design gave rise to a misleading impression.

Both passing off and misleading/deceptive conduct (also under the old s52) were found. The Court emphasised that reputation in shape and design can be enough — and differentiation must be meaningful, not tokenistic.

The AI Angle: Who Trains Whom?

AI tools like ChatGPT, Midjourney, and Suno don’t just copy works. They learn patterns from thousands of inputs. But in doing so, they arguably absorb creative expression — chord progressions, phrasing, brushstroke styles — and then make new outputs in that same vein.

AI developers claim this is fair use or transformative. Artists argue it’s a form of invisible appropriation — no different from copying and tweaking a painting, but with zero attribution or compensation.

It’s the Seafolly and Bodum problem, scaled up: if AI’s “original” work was trained on 10,000 human ones, is it really original? Or just a remix with plausible deniability?

The Bottom Line

Copyright law is meant to balance:

  • Encouraging creativity

  • Rewarding labour

  • Allowing critique and cultural dialogue

But that balance is breaking under the weight of machine learning models and automated copyright bots. As Seafolly and Bodum show, the law still values intention, process, and context — not just resemblance.

Yet in a world of remix and AI, intention is opaque, and process is synthetic.

So where do we draw the line?

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Who Owns the Music? Taylor Swift and the Master Rights Nobody Talks About

She might be Swift, but she wasn’t quick enough to catch the Scooter back in the day.  But now all has changed …

It’s the music industry story that refuses to fade: Taylor Swift may finally have the chance to buy back her original masters — the recordings that launched her global superstardom. If the deal happens, it would close a saga that began in 2019, when her former label sold those recordings to private equity giant Shamrock Capital, following an earlier sale by Scooter Braun’s Ithaca Holdings.

For Swift fans, it’s a long-awaited victory. But for lawyers — and especially those in IP — the story is a masterclass in what most people don’t understand about music rights.

Let’s break it down.

It’s Her Song, But Not Her Recording

When people say “Taylor Swift owns her music,” they’re often talking about copyright in the song/composition itself — comprised of the lyrics, melodies and chord structure. And yes, she owns or co-owns the copyright in many of her compositions, particularly the later albums.

But that’s not the same as owning the recordings. The actual sound recordings of her early music — the studio masters — were owned by her former label, Big Machine Records. That’s standard in the music industry. Unless you’re a major independent artist or had rare contract leverage, your label usually controls the master rights from day one.

So even though the voice on those original albums is Taylor’s, and even though the songs are her words and melodies, the master recordings were never hers to begin with.

Why Master Ownership Matters

Owning the masters means controlling how the recordings are used, licensed, sold, or synced in media. If someone wants to use the originally recorded “Love Story” in a film, the master rights holder — not Taylor — says yes or no and collects the licensing fee.

It also means revenue. Master owners collect royalties from streaming, downloads, radio play, and physical sales. For a catalogue like Swift’s, we’re talking tens of millions of dollars per year.

In fairness, so does Taylor as the songwriter – but not as many as she’d collect if she owned the masters too.

When Swift lost control of her masters, she didn’t just lose licensing rights — she lost influence over how those recordings were represented commercially, something she’s made clear she cares deeply about.

The Re-Recording Strategy — and What This Offer Means

Swift’s response was bold: she began re-recording her albums (as “Taylor’s Versions”) to reclaim both control and commercial value. Because copyright law allows the same songwriter to create a new recording of their own work, she’s been able to rebuild her catalogue under her own terms.

But this new offer — to buy back the original recordings — is different. It’s about reconciling emotional legacy and legal control. For Swift, it could mean regaining ownership of the original audio associated with her rise to fame … and far more royalties.  For Shamrock Capital, it could mean cashing out at a high watermark while retaining goodwill.

The Legal Lesson

Here’s the IP truth every artist — and every lawyer advising creators — should remember:

  • Songs and recordings are separate IP assets with separate ownership structures.

  • A performer can own either, neither, or both.

  • Contract terms set at the start of a career can shape or strangle an artist’s control for decades.

For artists, the Swift story is a cautionary tale — but also a blueprint. For lawyers, it’s a reminder to explain the difference between composition rights, performance rights, and master rights clearly — preferably before the artist becomes a household name.

And for Swifties? It’s one more reason to stream the hell out of 1989 (Taylor’s Version).

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Sad Bot, Caged Thought: The Global Crackdown on AI

We’re living through the Great AI Whiplash. After a few years of “move fast and break things” AI hype, the regulators have woken up — and they’re looking a little nervous.

Around the globe, lawmakers are scrambling to rein in artificial intelligence, fearing a digital Frankenstein’s monster. But the problem? No one can quite agree on which monster they’re dealing with — or how to shackle it without killing the spark that brought it to life.

Europe: The AI Act is Here, and It Means Business

The EU has locked in its AI Act, the world’s first major attempt at a cross-sector regulatory framework for artificial intelligence. It’s classic Brussels: tiered risk models, sweeping definitions, and enough compliance paperwork to make your chatbot cry. High-risk systems — think facial recognition or algorithmic credit scoring — face tight controls, while general-purpose models like ChatGPT must disclose training data, provide documentation, and prevent unlawful output.

It’s bold, it’s bureaucratic, and it’s already making developers nervous. The result? A brain drain of AI startups testing the waters elsewhere — or geofencing Europe altogether. You can regulate risk, but you can’t regulate innovation into existence.

UK: “Light Touch” with a Side of Confusion

Meanwhile, across the Channel, the UK wants to be the Goldilocks of AI regulation: not too hot, not too cold. The approach is “context-specific” — no overarching law, just guidance for existing regulators. But insiders say the result feels like regulatory hopscotch. Now, the House of Lords is up in arms over data mining for AI training. An amendment that would’ve required consent to scrape copyrighted works was shot down — despite a Beatles-backed campaign. A softer version might still pass.

So far, the UK’s trying to play tech cheerleader and cautious referee. But if everyone’s a stakeholder, who’s actually accountable?

US: States vs Feds, and the Lobbyists Are Winning

In Washington, it’s chaos as usual. President Biden’s Executive Order on AI was a decent start — calling for safeguards around national security and discrimination. But Congress? Still dithering. House Republicans recently tried to sneak a 10-year ban on state-level AI regulation into a tax bill (!), prompting a bipartisan outcry from attorneys general across 40 states. Why? Because the states are the ones doing the real work — regulating facial recognition, policing AI in employment, and pushing back on Big Tech’s black boxes.

Then there’s copyright: The U.S. Copyright Office is in a full existential crisis over whether AI-generated content can be protected and whether training data sourced from creative works amounts to fair use or industrial-scale infringement.

The Rest of Us

Australia, Canada, Singapore — all watching and waiting. Some are rolling out AI ethics frameworks. Others are updating privacy laws or leaning on competition watchdogs. Everyone’s talking transparency, risk, and bias. No one’s solved the training data problem. And no country has yet nailed a working model for how AI intersects with IP rights — especially when the training data is your music, your writing, or your likeness.

Author’s View – The Risk of Overcorrection

AI is scary, sure. But if you treat every algorithm like a grenade, you end up regulating fear, not function. Good regulation shouldn’t make developers hide or flee — it should set standards that encourage safe, creative, accountable use. The IP world knows this better than most: you can reward innovation and protect creators. But try to do both with clumsy laws or reactive bans, and you get what we’re seeing now — paralysis dressed as progress.

And so, here we are: a sad little AI bot, behind bars. Not because it committed a crime. But because the grown-ups can’t agree on the rules.

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Caramel slice of heaven, or recipe for disaster?  There has been calamity in the kitchen (or at least, all over social media) as two cooks have a donnybrook over a cookbook – and it’s not a good look.

The rich buffet of available cooking puns aside, various plagiarism accusations have been flung by Nagi Maehashi (author of RecipeTin Eats) at Brooke Bellamy (author of Bake With Brooki), including about a caramel slice recipe Ms Bellamy has published in her Bake with Brooki book.

Ms Maehashi says she wrote that recipe and that Ms Bellamy has plagiarised it in her book – which of course Ms Bellamy denies.  To demonstrate her “evidence”, Ms Maehashi posted the below on her Instagram page:

Maehashi has compared her caramel slice recipe with Bellamy's as 'evidence' of copying. Picture: Instagram

Interesting (and tasty) … but … it’s caramel slice – even this author can make caramel slice.  So, what rights have been infringed?

Well, original works expressed in a material form may be protected by copyright – so if Maehashi’s recipe is original and she published it first then perhaps she has a point against Bellamy.

The bigger problem is whether the recipe Maehashi published is actually sufficiently “original”.  While those measurements might at first glance seem oddly specific (which might support an argument that it was original), they are individually very common measurement amounts.  Maehashi would need to be able to prove (if she was going to pursue the argument) not only that those measurements in that combination were her original works, but also that the rest of the recipe (such as the ingredients and the method) were also originally hers, and not just some slight tweaks on her part of other well-known recipes and methods.

Maybe this is why there is a cry of “plagiarism” instead of “breach of copyright” – plagiarism is not a legal claim as such, but is often more loosely referred to when there has been apparently copying of some parts of a work that might not actually amount to a breach of copyright (which seems to be the case here).

The biggest challenge for cooks in Maehashi’s position to make a legal claim for breach of copyright, even if those precise measurement combinations are hers, is that the rest of the recipe and that method are in fairness pretty well known – that’s simply how you make caramel slices.

Copyright does not protect “ideas” – not even really tasty ones.  Copyright only protects the original expression of those ideas.

If I like my Corn Flakes with precisely 425 mls of milk of a morning, that doesn’t mean I can publish that as my own original Corn Flakes recipe and have copyright protect me.

Perhaps the plagiarism claim has been overbaked?