The Ninth Circuit ruling acknowledges, without solving, the inequity in access to justice: “Whether the DMCA provides a sufficient remedy [...] is ultimately a question for Congress”.

How Recent Anti-Piracy Court Decisions Could Shape AI Litigation and the Pursuit of Justice for Rights Holders

by ChatGPT-4o

I. Introduction

Two recent legal developments—Cloudflare’s extensive blocking of pirate domains in the UK and the U.S. Ninth Circuit’s ruling denying the use of DMCA subpoenas to unmask infringers—reveal an evolving legal landscape where enforcement mechanisms are being both expanded and constrained. While these cases originate in the context of traditional copyright enforcement against piracy, they are highly relevant to the emerging wave of AI-related litigation. As generative AI increasingly trains on vast datasets—often without permission from rights holders—understanding the mechanisms, limitations, and avenues of enforcement explored in these cases becomes vital.

II. Relevance to AI-Related Litigation

1. Cloudflare Blocking and the Expansion of Injunctive Relief

In the UK, Cloudflare has begun implementing wide-scale site blocking of pirate domains under dynamic injunctions previously granted to Hollywood studios. Although these injunctions originally applied to internet service providers (ISPs), it appears that Cloudflare is either voluntarily complying or has been added to the orders more recently.

For AI litigation, this is instructive in several ways:

• Dynamic injunctions could become a model for addressing generative AI systems that continue to use or republish unauthorized content. Courts could authorize orders that adapt to new use cases or AI model updates without requiring new proceedings.

• The precedent of including intermediaries such as Cloudflare could be extended to AI infrastructure providers—e.g., cloud platforms, vector database hosts, or API gateway services—that facilitate AI deployment or content dissemination.

2. DMCA Subpoena Restrictions and the Limits of Identification

In the U.S., the Ninth Circuit's decision reaffirms that DMCA subpoenas cannot be used to compel “mere conduit” ISPs like Cox Communications to identify users accused of BitTorrent-based infringement. The ruling requires rights holders to file full lawsuits—typically expensive and time-consuming—if they want to identify individual infringers.

This presents a significant challenge for AI-related infringement cases:

• It restricts rights holders' ability to identify and hold accountable developers or users of AI systems who may have scraped or repurposed their content.

• The burden of proof and cost of discovery increase, disproportionately affecting smaller creators and independent publishers seeking redress from large AI firms or elusive developers.

III. Legal Avenues Still Available to Rights Owners

Despite the tightening of some enforcement mechanisms, rights holders still have several viable strategies at their disposal—some of which are particularly relevant in AI cases:

A. Dynamic Injunctions and Equitable Relief

As demonstrated in the UK case, courts may grant forward-looking injunctions against intermediaries. Rights holders can push for dynamic injunctions not only to block known AI infringers but also to preemptively cover future uses of their content.

B. John Doe Lawsuits

Although more expensive, U.S. rights holders can file “John Doe” lawsuits to pursue unknown infringers and then subpoena platforms or services that have more direct access to infringer identities (e.g., AI hosting providers or GitHub repositories).

C. Contractual Leverage and Licensing

Particularly in the scholarly and publishing sectors, content owners may embed AI-specific terms in license agreements, enabling breach-of-contract claims if content is used for AI training without authorization.

D. Copyright Management Information (CMI) Violations

When AI systems strip attribution or metadata (e.g., author names, licensing information), rights holders may sue under 17 U.S.C. §1202. These claims are easier to bring than proving traditional infringement and offer statutory damages.

E. New Legislative Tools

Some U.S. state and federal proposals, such as those concerning digital replica rights or the proposed No AI Fraud Act, may soon expand rights to control likeness, voice, or style—which could extend to AI-generated mimicry of copyrighted content.

IV. The Digital Divide in Enforcement: A Growing Problem

The Ninth Circuit ruling acknowledges, without solving, the inequity in access to justice: “Whether the DMCA provides a sufficient remedy [...] is ultimately a question for Congress”. This hints at a deeper systemic issue—a digital divide in copyright enforcement.

1. Access to Legal Remedies is Often Reserved for the Wealthy

Only large studios, major publishers, or consortiums (like the MPA or RIAA) can afford multi-jurisdictional injunctions or persistent litigation. Independent authors, musicians, or journalists lack the capital to mount such defenses—particularly against AI developers with deep pockets.

2. Transparency Gaps Amplify Asymmetries

The Cloudflare case reveals a concerning lack of transparency in enforcement—there is no public list of blocked domains, no mechanism for independent audit, and overblocking may go unnoticed. Similarly, AI firms’ lack of transparency around training data and usage logs prevents many rights holders from even identifying infringement.

3. Big Tech Benefits from Legal Ambiguity

The current patchwork of DMCA limitations, fair use ambiguity, and international enforcement gaps favors AI developers who act first and litigate later. For small rights holders, the cost of justice often outweighs the potential return.

V. Recommendations for Regulators

To ensure justice and equitable access to remedies in the age of AI, regulators must act decisively.

A. Modernize the DMCA

Congress should update the DMCA to reflect the realities of large-scale automated scraping, data mining, and generative model training. Provisions for injunctive relief, expedited discovery, and platform accountability should be added.

B. Introduce Tiered Legal Aid for Digital Creators

Regulators could create a public legal aid fund, similar to legal defense funds in journalism, to help small creators bring AI-related infringement cases to court.

C. Mandate Transparency from AI Firms

AI developers should be required to disclose datasets used in training, the provenance of their models’ outputs, and provide an opt-out mechanism for rights holders. Similar to the EU AI Act’s transparency provisions, this would lower the barrier to detection and enforcement.

D. Incentivize Industry Self-Regulation

Encourage platforms like GitHub, Hugging Face, or cloud providers to adopt terms of service that forbid unauthorized scraping or use of copyrighted content for AI training. These intermediaries can be powerful levers for compliance.

VI. Conclusion

These two legal developments—one expanding enforcement powers in the UK, and the other restricting shortcuts in the U.S.—highlight the complex, fragmented terrain that rights holders must now navigate in AI-related litigation. The absence of cheap, scalable, and transparent enforcement tools, combined with uneven access to legal remedies, exposes a widening justice gap. Left unaddressed, this divide will entrench the power of AI firms and undermine the rights of creators, especially the most vulnerable.

Regulators must step in to rebalance the equation—through legislative reform, financial support, and transparency mandates—so that copyright law remains not only enforceable but also just and inclusive in the age of artificial intelligence.