When first drafted, this Article predicted that litigants would ask courts to broaden the derivative work right either to prevent the use of, or to claim protection for, literary and artistic productions made by Artificial Intelligence (AI) systems. The prediction has come true: plaintiffs have pleaded that generative models and their outputs are infringing derivative works, and courts have begun to cabin the right in ways this Article prescribes. The Article considers the normative valence of, and the (significant) doctrinal pitfalls associated with, such attempts. It also considers a possible legislative alternative, namely attempts to introduce a new sui generis right in AI productions. Finally, the Article explains how, whether such attempts succeed or not, the debate on rights (if any) in productions made by AI machines is distinct from the debate on text and data mining exceptions.

The principle of territoriality under which intellectual property (IP) rights exist and are enforced only within national borders sits uneasily alongside the global nature of standard-essential patent (SEP) licensing disputes. In recent years, courts in Brazil, China, Colombia, Germany, India, the United Kingdom, and now the Unified Patent Court have asserted authority, directly or indirectly, to determine worldwide fair, reasonable, and non-discriminatory (FRAND) licensing terms, often without both parties’ consent. These practices, ranging from injunction-driven leverage to comprehensive judicial rate-setting, raise difficult questions about jurisdiction, comity, competition norms, and the coherence of international IP law. This article provides a systematic and comparative analysis of the principle of territoriality in international IP law and its tension with non-consensual global FRAND determinations. It traces the origins and enduring role of territoriality in treaties such as the Paris Convention and TRIPS Agreement, examines its implications for jurisdiction and choice of law, and explains why territoriality remains a cornerstone of global IP governance. It then turns to the distinctive case of SEPs, highlighting the role of standard-setting organizations and the unique licensing challenges they generate. Against this backdrop, the article maps national approaches across key jurisdictions, identifying functional categories (adjudicators, regulators, and leverage providers) and analyzing how their practices interact in transnational disputes. Drawing on recent case law, WTO findings, and comparative treatment of other IP rights, the article argues that non-consensual global FRAND rate-setting undermines the territorial foundation of international IP law and risks destabilizing global markets. At the same time, it acknowledges arguments for efficiency and uniformity, and considers how these objectives might be pursued within a framework that respects sovereignty and due process. The article concludes by proposing both short-term and longer-term solutions, ranging from national court strategies and WTO enforcement to a possible role for WIPO, the US Congress, and the EU, designed to reconcile innovation incentives, market access, and the legitimacy of international dispute resolution.

The Encyclopedia of Intellectual Property Law is quite simply the definitive reference work in the field. Bringing together over 350 authors from across the world, the Encyclopedia sheds light on the current global state of Intellectual Property Law, providing unique insights into the discipline and how it is affected by globalization and increased regional integration. New entries will be added every month and PDF downloads will be available once the Encyclopedia is complete.

The Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS Agreement) was negotiated between 1986 and 1994 during the Uruguay Round of the General Agreement on Tariffs and Trade (GATT), which led to the establishment of the World Trade Organization (WTO). The TRIPS Agreement sets minimum levels of several types of intellectual property (IP) protection, including copyright, trademarks, patents, industrial design, and trade secrets protection. Membership in the WTO includes an obligation to comply with the TRIPS Agreement. According to the WTO, the Agreement attempts to strike a balance between long-term social benefits to society of increased innovations and short-term costs to society from the lack of access to inventions (World Trade Organization (n.d.) Intellectual property: protection and enforcement. Retrieved from understanding the WTO: the agreements: http://wto.org/english/thewto_e/whatis_e/tif_e/agrm7_e.htm).This entry considers this balance by looking at the two poles of intellectual property policy: providing incentives to increase innovation and optimizing access to inventions both for consumptive use and for potentially innovation-increasing experimentation. This entry also surveys the notion of calibration, the idea that every country or region should adapt its regulatory framework to reflect its own strengths and weaknesses in optimizing what one might refer to as its innovation policy. A calibration approach suggests that providing innovation incentives and optimizing access are not mutually exclusive objectives.

The internet was never designed with a native layer of trust. As deepfakes, AI-generated misinformation, and engagement-driven algorithms flood the information ecosystem, traditional cues of authenticity have collapsed. This paper argues that rebuilding credibility online requires a systemic response—a “trust stack” that reintroduces verifiable provenance and semantic assessment into digital infrastructure. Drawing on behavioral science and design principles, it outlines how machine-readable trust indicators, modeled on security standards like HTTPS, could allow users to assess authenticity at a glance. The first layer would certify provenance through cryptographic metadata, as in emerging initiatives like the Coalition for Content Provenance and Authenticity (C2PA). A second, semantic layer would use AI and knowledge graphs to evaluate factual consistency and sourcing, translating complex verification into intuitive user signals. The paper compares this approach to labeling systems such as Nutri-Score and Creative Commons, identifying both their behavioral power and their vulnerability to industry capture. It concludes that trust must become an opt-out default of the digital ecosystem, driven by open standards, independent governance, and interoperable “trust-as-a-service” tools. The internet’s integrity, it suggests, depends not on censorship but on transparency engineered into its very code.

Sustainability markets naturally implies a major environmental dimension. It also includes cultural sustainability, and in particular the creation, dissemination and availability of Socially Responsible News (SRN) and of literary and artistic creations that contribute to human progress. This chapter examines the situation of current markets for SRN and literary and artistic productions, and in particular the disruption caused by the shift to a few major digital platforms, and suggests reforms to one important policy level: copyright, including a possible overhaul of the norms contained in the most important copyright treaty, the Berne Convention, which was last revised on substance in 1967.

This article explores the intricate relationship between copyright law and artificial intelligence, including large language models (LLMs). It begins with a detailed technical overview of LLM functionality, including tokenization, word embeddings, and the various stages of LLM development. The authors then delve into the copyright implications of using protected works for both training LLMs and generating outputs. The paper argues that the training process likely constitutes prima facie copyright infringement through the reproduction and adaptation of copyrighted works. This occurs at multiple levels, including the creation of temporary copies during training and the embedding of numerical representations of training data within the LLMitself. The authors draw parallels between these AI processes and established legal concepts, such as the translation of computer code into executable formats. A thorough evaluation of potential copyright exceptions and limitations across various jurisdictions is presented. This includes an in-depth analysis of the fair use doctrine in the United States, with particular attention to how AI companies are attempting to draw parallels with previous cases like the Google Books cases. The paper also examines the text and data mining provisions in the European Union's Digital Single Market Directive and their applicability to AI training. The authors discuss emerging legislation, such as the EU AI Act, and its potential global impact on AI development and copyright law. They also address the complexities arising from the borderless nature ofAI technology and the territorial limitations of copyright laws, which may lead to issues like forum shopping for AI training. Given the legal uncertainties surrounding AI and copyright, the paper proposes licensing as a key solution to balance innovation with copyright protection. The authors argue that global licensing agreements could harmonize practices and provide a consistentframework for responsible use of copyrighted works inAI development. The article concludes by reflecting on how copyright law has historically adapted to technological changes. However, it emphasizes thatAI presents unprecedented challenges that may require novel legal and market-based approaches. The authors stress the importance of finding solutions that foster both technological innovation and respect for intellectual property rights in the rapidly evolving AI landscape.

Law could recognize nonhuman AI-led corporate entities.

Abstract The seemingly interminable discussions under the aegis of the World Trade Organization (WTO), on a possible conditional waiver of certain obligations under the TRIPS Agreement, ostensibly aim to increase access to vaccines and treatments to help WTO members address the public health emergency created by the novel coronavirus, the Covid-19 pandemic. While much of the discussions concerning a possible waiver focused on patents, the thorniest legal issues were not about patents, because removing patent protection means that information disclosed in a patent application can then be used, but rather the protection of confidential information, such as trade secrets, because removing that protection does not provide access to such information. Its disclosure must be coerced if not made voluntarily. This chapter examines the legal issues concerning coerced disclosure and discusses whether such disclosure would be effective. It then draws additional lessons from the Covid-19 pandemic on the future of vaccine and other pharmaceutical research.

This short chapter reviews the application of patent incentives to inventions made by AI machines. It discusses two policy goals of patents in this space, namely acceleration of innovation with the help of AI but also the need to continue human progress. It reviews decisions by several courts, most of which have (correctly) decided that, as the law now stands, machines cannot be "inventors". Moreover, financial incentives apply to humans and legal persons (managed by humans), not machines. Patent law should continue to promote human ingenuity.

This Article predicts that there will be attempts to use courts to try to broaden the derivative work right in litigation either to prevent the use of, or claim protection for, literary and artistic productions made by Artificial Intelligence (AI) machines. The Article considers the normative valence and the (significant) doctrinal pitfalls associated with such attempts. It also considers a possible legislative alternative, namely attempts to introduce a new sui generis right in AI productions. Finally, the Article explains how, whether such attempts succeed or not, the debate on rights (if any) in productions made by AI machines is distinct from the debate on text and data mining exceptions.