arXiv subjects

Jyh-An Lee

Publications and source records attributed to Jyh-An Lee.

11 recordsLinked to original sources

arXiv2026

Vocal Identity Under Siege by AI Voice Cloning Technologies

The advent of sophisticated AI-driven voice cloning has brought to the fore critical legal and ethical challenges regarding the protection of vocal identity. Prompted by recent controversies - including the striking resemblance between OpenAI's ChatGPT-4o voice and that of Scarlett Johansson - this article examines how generative AI technologies undermine the unique value of the human voice and further complicate the legal questions surrounding personality right. Through a comparative analysis, the paper evaluates three principal legal frameworks: the right of publicity, personality rights, and the personal data protection right. Each framework - rooted in different legal traditions o offers distinct strengths and limitations in addressing the threats posed by AI-generated voice cloning. By analysing these doctrines' scope, remedies, and posthumous protections, the study offers a foundation for understanding how existing legal approaches may be applied to the evolving challenges of vocal identity in the era of generative AI.

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arXiv2026

Strategic Stalemates: The Paradox of Export Controls in the U.S.-China AI Race

Export control is a policy and legal tool to protect national interests by regulating exports of sensitive goods and technology to foreign nations. It has become central to U.S.-China tech rivalry, especially in AI. Controls cover advanced chips, capital, personnel, and critical minerals for semiconductors. Since October 2022, the U.S. BIS has progressively tightened restrictions on advanced computing components to China. China responded with export curbs on critical minerals and filed a WTO complaint against the U.S. under GATT. This article argues that while export controls are strategic in U.S.-China AI competition, their long-term effectiveness is questionable. They often unintentionally boost China's self-reliance and R&D. Moreover, overly strict or arbitrary controls may violate WTO obligations, complicating dispute resolution and hindering AI progress. The study further examines legal implications of overusing export controls. It advocate for a restrained interpretation of security interests, arguing that commercial or dual-use AI models and semiconductors do not meet the security exception criteria under GATT Article XXI(b).

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arXiv2026

Unjust Enrichment as a Remedy for AI's Unauthorised Use of Protected Data

The unauthorised use of data in the training of generative AI models presents significant legal challenges, particularly under intellectual property (IP) and privacy laws. These frameworks frequently grapple with the intricate relationship between data ownership and AI innovation, resulting in ongoing debates regarding optimal protection and enforceability. This article delves into considerable potential of unjust enrichment as an alternative legal doctrine for resolving disputes arising from such unauthorised data use. We explore how the concept of unjust enrichment captures the wrongfulness of unauthorised data use in a manner distinct from IP infringement and privacy violations. Furthermore, we analyse the extent to which gain-based restitution for unjust enrichment may prove more advantageous than existing remedies, including legal, equitable, and statutory options. We content that by shifting the emphasis from establishing wrongful conduct to recovering benefits obtained unjustly, unjust enrichment offers a pragmatic and equitable framework that reconciles the rights of data owners with the interests of AI developers.

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arXiv2026

Navigating Turbulence: The Challenge of Inclusive Innovation in the U.S.-China AI Race

This chapter examines the impact of the geopolitical rivalry between the United States and China on the prospects for inclusive innovation in artificial intelligence (AI) development. We explore three critical aspects of the American and Chinese legal infrastructure that significantly impact AI innovation: data privacy, intellectual property (IP rights), and export restrictions. Through this comparative analysis, we argue that, while China's legal environment may offer certain advantage in terms of access to training data and IP protection, the United States maintains superior resources by enforcing strict export controls on semiconductor chips, AI models, as well as outbound investments in these areas. This nuanced examination helps illuminate how each country's legal framework could influence the ultimate trajectory of AI race and how the technological rivalry has led to exclusionary rulemaking on a global scale.

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arXiv2025

Tripartite Perspective on the Copyright-Sharing Economy in China

Internet and digital technologies have facilitated copyright sharing in an unprecedented way, creating significant tensions between the free flow of information and the exclusive nature of intellectual property. Copyright owners, users, and online platforms are the three major players in the copyright system. These stakeholders and their relations form the main structure of the copyright-sharing economy. Using China as an example, this paper provides a tripartite perspective on the copyright ecology based on three categories of sharing, namely unauthorized sharing, altruistic sharing, and freemium sharing. The line between copyright owners, users, and platforms has been blurred by rapidly changing technologies and market forces. By examining the strategies and practices of these parties, this paper illustrate the opportunities and challenges for China's copyright industry and digital economy. The paper concludes that under the shadow of the law, a sustainable copyright-sharing model must carefully align the interests of businesses and individual users.

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arXiv2025

FRT Regulation in China

This paper first introduces China's legal framework regulating facial recognition technology (FRT) and analyzes the underlying problems. Although current laws and regulations have restricted the development of FRT under some circumstances, these restrictions may function poorly when the technology is installed by the government or when it is deployed for the purpose of protecting public security. We use two cases to illustrate this asymmetric regulatory model, which can be traced to systematic preferences that existed prior to recent legislative efforts advancing personal data protection. Based on these case studies and evaluation of relevant regulations, this paper explains why China has developed this distinctive asymmetric regulatory model towards FRT specifically and personally data generally.

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arXiv2025

Licensing Open Government Data

This article focuses on the legal issues associated with open government data licenses. This study compares current open data licenses and argues that licensing terms reflect policy considerations, which are quite different from those contemplated in business transactions or shared in typical commons communities. This article investigates the ambiguous legal status of data together with the new wave of open government data, which concerns some fundamental intellectual property (IP) questions not covered by, or analyzed in depth in, the current literature. Moreover, this study suggests that government should choose or adapt open data licenses according to their own IP regimes. In the end, this article argues that the design or choice of open government data license forms an important element of information policy; government, therefore, should make this decision in accordance with their policy goals and in compliance with their own jurisdictions' IP laws.

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arXiv2025

Copyright in AI-generated works: Lessons from recent developments in patent law

In Thaler v The Comptroller-General of Patents, Designs and Trade Marks (DABUS), Smith J. held that an AI owner can possibly claim patent ownership over an AI-generated invention based on their ownership and control of the AI system. This AI-owner approach reveals a new option to allocate property rights over AI-generated output. While this judgment was primarily about inventorship and ownership of AI-generated invention in patent law, it has important implications for copyright law. After analysing the weaknesses of applying existing judicial approaches to copyright ownership of AI-generated works, this paper examines whether the AI-owner approach is a better option for determining copyright ownership of AI-generated works. The paper argues that while contracts can be used to work around the AI-owner approach in scenarios where users want to commercially exploit the outputs, this approach still provides more certainty and less transaction costs for relevant parties than other approaches proposed so far.

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arXiv2025

Algorithmic Bias and the New Chicago School

AI systems are increasingly deployed in both public and private sectors to independently make complicated decisions with far-reaching impact on individuals and the society. However, many AI algorithms are biased in the collection or processing of data, resulting in prejudiced decisions based on demographic features. Algorithmic biases occur because of the training data fed into the AI system or the design of algorithmic models. While most legal scholars propose a direct-regulation approach associated with the right of explanation or transparency obligation, this article provides a different picture regarding how indirect regulation can be used to regulate algorithmic bias based on the New Chicago School framework developed by Lawrence Lessig. This article concludes that an effective regulatory approach toward algorithmic bias will be the right mixture of direct and indirect regulations through architecture, norms, market, and the law.

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arXiv2025

Unwinding NFTs in the Shadow of IP Law

Amid the surge of intellectual property (IP) disputes surrounding non-fungible tokens (NFTs), some scholars have advocated for the application of personal property or sales law to regulate NFT minting and transactions, contending that IP laws unduly hinder the development of the NFT market. This Article counters these proposals and argues that the existing IP system stands as the most suitable regulatory framework for governing the evolving NFT market. Compared to personal property or sales law, IP laws can more effectively address challenges such as tragedies of the commons and anticommons in the NFT market. NFT communities have also developed their own norms and licensing agreements upon existing IP laws to regulate shared resources. Moreover, the IP regimes, with both static and dynamic institutional designs, can effectively balance various policy concerns, such as innovation, fair competition, and consumer protection, which alternative proposals struggle to provide.

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arXiv2024

Interoperability of the Metaverse: A Digital Ecosystem Perspective Review

The Metaverse is at the vanguard of the impending digital revolution, with the potential to significantly transform industries and lifestyles. However, in 2023, skepticism surfaced within industrial and academic spheres, raising concerns that excitement may outpace actual technological progress. Interoperability, recognized as a major barrier to the Metaverse's full potential, is central to this debate. CoinMarketCap's report in February 2023 indicated that of over 240 metaverse initiatives, most existed in isolation, underscoring the interoperability challenge. Despite consensus on its critical role, there is a research gap in exploring the impact on the Metaverse, significance, and developmental extent. Our study bridges this gap via a systematic literature review and content analysis of the Web of Science (WoS) and Scopus databases, yielding 74 publications after a rigorous selection process. Interoperability, difficult to define due to varied contexts and lack of standardization, is central to the Metaverse, often seen as a digital ecosystem. Urs Gasser's framework, outlining technological, data, human, and institutional dimensions, systematically addresses interoperability complexities. Incorporating this framework, we dissect the literature for a comprehensive Metaverse interoperability overview. Our study seeks to establish benchmarks for future inquiries, navigating the complex field of Metaverse interoperability studies and contributing to academic advancement.

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