AI Training and Copyright: current status and future direction

Three recent federal court decisions split 2-1 on whether AI training constitutes copyright fair use. Judges Alsup (Bartz v. Anthropic) and Chhabria (Kadrey v. Meta) found fair use; Judge Bibas (Thomson Reuters v. ROSS Intelligence) rejected it. But these results reveal deeper complexity about AI's impact on copyright markets.

In most cases, using copyrighted works to train AI models will likely be illegal due to concerns about market dilution. As explained by Judge Chhabria in Kadrey v. Meta, copyright holders generally should be compensated for AI training use.


Market dilution: It is a specific form of market harm recognized in copyright law’s fair use analysis. AI-generated content—created using copyrighted works as training data—reduces the demand, value, or visibility of the original human-authored works, even if the AI does not directly copy or regurgitate specific passages from those works. In other words, AI models can flood the market with similar but not identical works, thereby weakening the economic footing and discoverability of the originals. AI’s outputs are made possible precisely because they were trained on, and extract value from, the copyrighted works themselves via statistical inference. This kind of competition becomes problematic when enabled by unlicensed ingestion of protected works during training.


Consider a practical example: an AI model trained on 10,000 romance novels can generate hundreds of new romance novels daily at near-zero marginal cost. Even if these AI-generated novels don't directly copy specific passages, they flood the market with substitutes that compete for reader attention, visibility, and sales, reducing both the economic returns and discoverability of the original human-authored works.


Copyright holders' compensation: This is a crucial point.  Without compensation, the system dangerously leans on eroding the very economic foundations that incentivize authorship in the first place. The erosion of income—past and prospective—fundamentally undermines the economic justification for creating new works in the first instance. Licensing and compensation restore the balance by ensuring that the value extracted from copyrighted works during AI training flows back to creators, maintaining their financial viability and thus their ability to continue producing the very content that AI systems depend upon for training data. No race to the bottom should be allowed for another reason: it creates a self-destructive technological dynamic in which AI cannibalizes its own training data. 


How are things going in the European Union?

The United States operates under a flexible "fair use" doctrine that allows courts to determine on a case-by-case basis whether a particular use of copyrighted works is fair. This creates uncertainty but also adaptability.

By contrast, the European Union follows a rigid system of specific statutory exceptions enumerated in directives. Rather than a catch-all "fair use" standard, the EU provides detailed, limited exceptions: AI training falls under two specific text and data mining (TDM) exceptions included in the 2019 Copyright in the Digital Single Market Directive. The system centers on opt-out mechanisms: copyright holders must actively reserve their rights using machine-readable means, placing the burden on creators to prevent their work from being used in AI training.


The EU approach provides greater legal certainty through specific statutory rules but raises serious concerns about effectiveness. The system's reliance on administrative compensation rather than deterrent damages mirrors the EU's weak private antitrust enforcement, where the absence of treble damages has rendered private competition litigation largely ineffective compared to the robust US model.


Conclusions

The two jurisdictions are going in two different directions: a liability-based approach with potential massive damages exposure in the US, and a statutory remuneration scheme, with legal experts and policymakers proposing mandatory licensing and compensation regimes to balance AI innovation with creator compensation in the EU. Nothing new, therefore, because this reflects the divergent legal philosophies of deterrence between the US and the EU: the EU's centralized administrative control vs. the US's decentralized private empowerment.


CILC connects clients with qualified attorneys to navigate the complexities of multiple regulatory regimes, ensuring strategic advantage in a rapidly changing digital world.

Copyright Enforcement and Market Foreclosure: The ValueLicensing/Microsoft case

ValueLicensing sells pre-owned Microsoft software licenses primarily to business and enterprise customers, including large organizations and public sector entities. Buyers typically save 30–70%, compared to new licenses, in the secondary market for pre-owned, perpetual Microsoft software licenses—especially for Windows and Office. 


Microsoft offers discounts or incentives to enterprises to surrender or not resell perpetual licences when they move to Microsoft 365 (subscription-based cloud products), and includes contractual restrictions in enterprise agreements to prevent resale, either by conditioning support or upgrades on not transferring old licences. Microsoft’s actions, if successful, would limit or eliminate the secondary market, forcing customers toward its own direct sales and cloud-based subscriptions.


ValueLicensing claims that Microsoft, by attempting to suppress the secondary market in pre-owned licenses, violated antitrust rules in the EU and the UK. Microsoft based its defense on arguments related to copyright law.


The Legal Framework

In both EU and UK copyright law, the principle of exhaustion (also known as the first sale doctrine) says that once a copyright owner has lawfully sold a copy of a work in the EEA/UK, its exclusive right to control the distribution of that copy is “exhausted." That means the purchaser can resell or transfer that copy without further authorization from the copyright holder. For software, this principle is codified in Article 4(2) of the EU Software Directive (Directive 2009/24/EC), which was retained in UK law after Brexit. The leading EU case, UsedSoft GmbH v Oracle International Corp (C-128/11, 2012), by allowing customers who buy a perpetual license downloaded from the internet to resell the license and accompanying copy, created the market for “used software” or “pre-owned licence.”


ValueLicensing’s business model relies squarely on that case and doctrine: it buys perpetual licences from corporate customers (e.g., firms migrating to the cloud) and resells them to others at lower prices. However, the UsedSoft doctrine applies only to computer programs, meaning that other categories of works, such as e-books, music, video, or art, are governed by different EU directives and for which the resale/exhaustion principle may not apply.


Microsoft's defense relies on this atomization of copyright law in the EU. Microsoft argued that not every element of Windows or Office is a “computer program” within the meaning of the Software Directive, so exhaustion doesn’t necessarily apply to the entire bundle. In particular, parts of the suite — e.g., graphical interfaces, fonts, help systems, or templates — may be literary or artistic works, or ancillary materials, not “computer programs.” Therefore, even if the executable code is subject to exhaustion, those other elements are not. If accepted, this argument would make it nearly impossible to run or resell a fully functional “pre-owned” copy without infringing copyright — effectively nullifying the UsedSoft precedent in practice.


Why is the case so relevant?

It directly affects the scope of the right exhaustion doctrine. If Microsoft’s view prevails, large vendors could effectively eliminate the secondary market for perpetual licences. If ValueLicensing wins, the decision would reinforce UsedSoft’s principle and potentially expand the lawful resale of legacy software — a major precedent for digital property rights and competition in software licensing.


CILC connects clients with qualified attorneys to navigate the complexities of multiple regulatory regimes, ensuring strategic advantage in a rapidly changing digital world.

Digital Markets: Google’s AI Overviews within the Cross-Hairs of all major EU Digital Regulatory Tools

The European Commission's Scrutiny under the DSA, the DMA, and the Antitrust Rules

Google’s new AI Overviews search summaries are under review by the European Commission (EC) for compliance with the Digital Services Act (DSA), the European Union Copyright Law, the Digital Markets Act (DMA), and the antitrust rules.


The multi-front EU regulatory review concerns the DSA’s safety and transparency rules, the DMA’s competition obligations, and traditional antitrust law. Google argues that AI Overviews increase website diversity and engagement, and that the safeguards in place mitigate content risks. 


The Digital Service Act

The EC is examining whether the new feature complies with EU rules for “Very Large Online Search Engines” (VLOSEs) under the Digital Services Act, which applies to platforms with over 45 million monthly users in the EU.

The concern: AI-generated summaries in search results might pose systemic risks to online safety, copyright protection, media pluralism, electoral integrity, and user rights.

Possible issues are AI “hallucinations,” spread of deepfakes, automated manipulation, and misinformation that could mislead voters.

For AI Overviews, additional concerns include the implications for copyright law. Many publishers and news organizations argue that Google’s AI Overviews are built using content scraped from their websites, which is then summarized and shown to users without acquiring licenses or obtaining authorization. However, LLM developers, including Google, may lawfully crawl and ingest copyright-protected works for model training if the works are made accessible and have not been reserved (opted out) by the right-holders. Current litigation will help define future boundaries.


The Digital Market Act

As a designated gatekeeper, Google must prevent self-preferencing, ensure fair access to search data, and avoid practices that could exclude competitors or disadvantage business users such as publishers. Complaints have arisen that AI Overviews have reduced referral traffic to news websites, impacting ad revenue and threatening media pluralism.

The concern is that the DMA requires business users to be able to opt out of features like AI Overviews without being delisted from Google Search altogether. European publishers and privacy groups have filed complaints, alleging that Google does not adequately enable this choice and that the integration of AI summaries unfairly shifts user attention away from original news sources.


The Antitrust Rules

The scrutiny under traditional antitrust rules primarily concerns whether Google has used its dominant position in general search to unfairly disadvantage publishers and competitors through its AI Overviews feature.

Both the DMA and traditional antitrust regimes apply to Google’s AI Overviews, but they differ fundamentally in their approach, process, and practical impact. The DMA sets out upfront, clear obligations for designated gatekeepers like Google, focusing on preventing specific unfair practices before they cause harm, which is irrelevant for the application of the rules. Antitrust operates through after-the-fact investigations based on complaints or regulators' concerns about conduct that has already occurred and caused harm.


What to expect

Burden on platform to show compliance is a central DMA/DSA feature; antitrust maintains a traditional regulator-plaintiff burden of proof. DSA and DMA both permit rapid, rules-based intervention with heavy fines and interim or structural remedies—while the antitrust process is reactive, lengthy, and focused on proven harm.

The regulatory convergence effort serves the broader goal of preserving media pluralism, consumer choice, and a level competitive digital market, as highlighted in recent EC and parliamentary statements.


Prepare for overlapping EU obligations and consider compliance strategies that cover multiple regulatory regimes.


At CILC, we provide expert legal guidance on antitrust, regulatory compliance, and intellectual property across the U.S., EU, and beyond. Our platform connects clients with qualified attorneys to navigate the complexities of multiple regulatory regimes, ensuring strategic advantage in a rapidly changing digital world.

Market Power and Digital Market Regulation: AI and Data

Comparative analysis: UK/EU, Japan, and China

In the UK, the Bank of England has raised concerns over the level of concentration and market power consolidation in AI-related service markets within the financial sector.


Approximately 75% of UK financial services firms utilize AI. The top three providers control 73% of cloud, 44% of AI models, and 33% of data services used by financial companies.


Three key conditions are under scrutiny: vendor lock-in, operational resilience, and competition:


  1. Lock-In Risks: technical and commercial barriers hinder switching and entry, prompting scrutiny under new digital markets laws. The EU aims to explicitly address vendor lock-in with its upcoming Data Act, ensuring companies can switch cloud providers — potentially at no additional cost.
  2. New rules bring "critical third parties" like major cloud providers under the Financial Conduct Authority and Prudential Regulation Authority, aiming to protect against cyber attacks and IT failures. These rules apply only after a provider receives a “critical” designation from the UK Treasury.
  3. The UK Procurement Act aims to help smaller AI companies bid for public contracts, seeking to rebalance sector concentration.


In Japan, following the enactment of the Act on Promotion of Competition for Specified Smartphone Software, the Japan Fair Trade Commission published the final rules, which target the dominance of major providers, such as Apple and Google, in mobile software ecosystems.

Modeled on the EU Digital Market Act, Japan’s regulation aims to foster competition, enhance security, and protect privacy in mobile software markets. Key provisions include rules to prevent designated companies from self-preferencing, restrictions on the use of users' data to prevent unfair competitive advantages, and a list of practices deemed anticompetitive (including anti-steering provisions).

Noncompliance can lead to investigations and fines of up to 20 percent of revenues for violations of ex-ante rules.


In China, new judicial guidelines on data-property protection instruct courts to handle AI-related disputes by avoiding overly restrictive interpretations of data ownership that might stifle innovation. The guidelines have two key objectives: to create predictability for AI developers and investors, and to strengthen China’s global tech position. Significantly, the new rules expand IP protection.


Each jurisdiction's approach reflects a nuanced variation of the same objective: to prevent market power abuse. 

The regulatory (UK/EU, Japan) and judicial/administrative (China) approaches converge, viewing data as a fundamental economic asset in the digital economy that may disadvantage smaller firms or limit innovation. The interesting news is China's clear opening to IP development as an engine for high-tech growth and global competitiveness, suggesting a more innovation-centric approach compared to the past.


At CILC, we provide expert legal guidance on antitrust, regulatory compliance, and intellectual property across the U.S., EU, and beyond. Our platform connects clients with qualified attorneys to navigate the complexities of multiple regulatory regimes, ensuring strategic advantage in a rapidly changing digital world.

The widening strategic gap between Chinese and U.S. approaches to Large Language Models

Open Source vs. Proprietary Models

Recent AI developments underscore a widening strategic gap between Chinese and U.S. approaches to advanced large language models (LLMs).


Notably:

  • Moonshot AI (Beijing) released Kimi K2, a trillion-parameter Mixture-of-Experts (MoE) model, reportedly surpassing GPT-4.1 in coding and math benchmarks, and crucially, making it open source.
  • OpenAI (San Francisco) postponed the release of its anticipated “open-weight” model, attributing the delay to extended safety reviews.


Chinese firms are leaning aggressively into open releases, sharing model weights freely to encourage rapid adoption and enable broad experimentation. This tactic is intended to grow developer ecosystems and accelerate both innovation and feedback cycles.

 Leading U.S. AI companies are showing increased hesitation, tightening access to model weights and intellectual property. OpenAI’s latest delay follows broader industry reticence to release high-performing models without restrictive licensing or additional vetting.


Impact on competition

The tradition of proprietary “AI moats” may be eroding as China’s open-weight models gain traction. Open release models can dilute incumbents' moats by reducing barriers to parity and enabling collective improvement. Ready access to state-of-the-art models enables more actors to experiment, build, and deploy novel use cases, potentially accelerating the AI adoption curve worldwide.


(New ?) Barriers

With model weights more widely available, the limiting factor shifts to access to computational resources. This is especially true as high-end GPUs and accelerators face supply constraints, in part due to escalating chip export restrictions targeting China. Thus, even as models proliferate, only those with sufficient compute can fully leverage them.


Conclusion

The immediate gains in model quality and access by Chinese labs challenge U.S. incumbents’ dominance. Open-source pushes can foster ecosystems richer and more diverse than those around closed models, influencing who shapes the next generation of applications and research. Export controls and hardware limitations now risk becoming the primary choke point for global AI progress, overshadowing the previous focus on model secrecy. These trends signal a reconfiguration of the AI competitive landscape, elevating open-source momentum and forcing U.S. firms to rethink their approaches to IP, safety, and collaboration. The trajectory will depend on how each side navigates the compute challenge and the rapidly evolving regulatory climate.


At CILC, we provide expert legal guidance on antitrust, regulatory compliance, and intellectual property across the U.S., EU, and beyond. Our platform connects clients with qualified attorneys to navigate the complexities of multiple regulatory regimes, ensuring strategic advantage in a rapidly changing digital world

AI and the Regulatory Framework: U.S./EU Compare

As ChatGPT falls under the European Commission lens, the Commission has launched an AI-on-Demand platform

ChatGPT is about to be considered for designation as a "systemic digital service" under the EU Digital Services Act (DSA). Specifically, the European Commission is actively considering designating ChatGPT as a "very large online platform" or "very large online search engine" (VLOP/VLOSE), which are the official terms for systemic digital services under the DSA. ChatGPT’s web search feature in Europe has rapidly grown to an average of 41.3 million monthly active users as of the first quarter of 2025, up from 11.2 million in the previous period. The DSA’s threshold for such designation is 45 million average monthly users, so ChatGPT is now very close to triggering this status.


Key Business Impacts of VLOP/VLOSE Designation

The EC Increased Regulatory Compliance and Oversight will cause:

- Stricter Obligations: robust risk management systems, publish transparency reports, and annual audits to assess and mitigate systemic risks such as misinformation, illegal content, and threats to fundamental rights.

Data Access for Researchers: Provide researchers and regulators with access to internal data, which could expose operational details and require new data-sharing infrastructure.

- Algorithmic Transparency:  Explain how its algorithms rank and present results, which could impact proprietary technology and competitive advantage

- Higher Compliance Costs

- Penalties for Non-Compliance

- Potential Slowdown in Innovation

- Precedent for AI Regulation: This designation could set a precedent for how other AI-driven platforms are regulated, potentially influencing global standards and increasing scrutiny for similar services.

- Competitive Pressure: Increased regulatory scrutiny could level the playing field, making it harder for dominant players to stifle competition and fostering a more diverse digital market


Designating ChatGPT as a VLOP or VLOSE under the DSA would bring challenges for OpenAI. It would require significant investments in compliance and transparency, potentially slow innovation, and increase operational costs.

At the same time, the European Commission has launched its AI-on-Demand platform. The EU prioritizes ethical development, regulatory compliance, and digital sovereignty, often resulting in slower deployment but higher trust and transparency. Once again, the EU shows that its approach to innovation is collaborative, involving universities, research centers, and industry. This sharply contrasts with the competitive U.S., where the initiatives focus more on feature-rich, user-friendly products with companies vying for market share and technological leadership.


Is This Protectionism or a Push for Broader Objectives?

The EU is pursuing a dual strategy: building up its AI ecosystem and infrastructure while regulating powerful foreign platforms (like ChatGPT) to ensure a level playing field, user safety, and compliance with EU law. It is also true that the DSA and AI Act are designed to apply to all relevant actors, regardless of origin, ensuring that both European and non-European platforms meet the same standards for transparency, accountability, and risk management. However, the regulatory environment does create a higher barrier to entry for non-EU firms, which must invest heavily in compliance. This can be seen as a form of regulatory protectionism, especially if the compliance burden disproportionately affects foreign companies with large user bases in Europe. Yet, the EU’s stated goal is to ensure that all platforms, whether European or not, meet the same standards for safety, transparency, and accountability.


Conclusion

Back to the future. It is undeniable that two distinct economic philosophies influence the approach to digital markets in two of the world's largest economies.  The U.S. model is strongly influenced by Schumpeterian competition, emphasizing innovation and market dynamism.  The U.S. legal and regulatory environment is seen as sufficiently adaptable to accommodate this competitive dynamism, fostering a virtuous cycle of innovation and entry by both startups and large incumbents. This reflects the classic Schumpeterian view, where market leadership is constantly contested and technological change drives progress; that is, economic progress is propelled by entrepreneurs who disrupt existing industries and technologies, continuously destroying old structures to make way for new, more efficient ones. This process is inherently dynamic and often results in both winners and losers, but it is considered essential for long-term economic growth and increased productivity. Google, Apple, and Microsoft have transformed markets through aggressive innovation, displacing older technologies and business models. The EU model is shaped by ordoliberal ideas that emphasize the importance of legal frameworks in ensuring fair competition, market contestability, and the protection of fundamental rights. The EU is not explicitly or solely ordoliberal, but these ideas are deeply embedded in its regulatory approach to digital markets and AI.  Strict regulatory oversight and the need to comply with detailed rules could slow down the pace of innovation. If we examine the current debate in Europe, many have observed that Europe is lagging behind the U.S. in AI and digital innovation.


At CILC, we provide expert legal guidance on antitrust, regulatory compliance, and intellectual property across the U.S., EU, and beyond. Our platform connects clients with qualified attorneys to navigate the complexities of both regulatory regimes, ensuring strategic advantage in a rapidly changing digital world