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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">digitallaw</journal-id><journal-title-group><journal-title xml:lang="en">Journal of Digital Technologies and Law</journal-title><trans-title-group xml:lang="ru"><trans-title>Journal of Digital Technologies and Law</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2949-2483</issn><publisher><publisher-name>Kazan Innovative University named after V. G. Timiryasov</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21202/jdtl.2025.24</article-id><article-id custom-type="edn" pub-id-type="custom">xeltpk</article-id><article-id custom-type="elpub" pub-id-type="custom">digitallaw-592</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ARTICLES</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>СТАТЬИ</subject></subj-group></article-categories><title-group><article-title>Copyright Facing the Challenges of Generative Artificial Intelligence: Judicial Practice and Legislative Strategies in India, the United States and the European Union</article-title><trans-title-group xml:lang="ru"><trans-title>Авторское право перед вызовами генеративного искусственного интеллекта: судебная практика и законодательные стратегии в Индии, США и Европейском союзе</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0005-7023-3920</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Амит Шрирам</surname><given-names>К. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Amith Sriram</surname><given-names>K. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Ассистент преподавателя.</p><p>560054, г. Бангалор, МСР Нагар, въезд 8–10</p></bio><bio xml:lang="en"><p>Assistant Professor, Ramaiah College of Law.</p><p>Multipurpose Block, Gate No. 8 или 10, MSR Nagar, 560054 Bengaluru</p></bio><email xlink:type="simple">amithsriram.007@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Юридический колледж Рамайя</institution><country>Индия</country></aff><aff xml:lang="en"><institution>Ramaiah College of Law</institution><country>India</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>27</day><month>12</month><year>2025</year></pub-date><volume>3</volume><issue>4</issue><fpage>598</fpage><lpage>635</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Amith Sriram K.S., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Амит Шрирам К.С.</copyright-holder><copyright-holder xml:lang="en">Amith Sriram K.S.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.lawjournal.digital/jour/article/view/592">https://www.lawjournal.digital/jour/article/view/592</self-uri><abstract><sec><title>Objective</title><p>Objective: to conduct a comparative analysis of the judicial interpretation of the fair dealing and fair use doctrines in the copyright law systems of India, the United States and the European Union in the context of the challenges posed by the development of generative artificial intelligence and blockchain technologies.</p></sec><sec><title>Methods</title><p>Methods: the work uses a set of scientific methods, including a comparative legal analysis of the legislation of three jurisdictions, a systematic analysis of judicial practice in India, a dogmatic method of interpreting regulations, as well as a structural and functional approach to the study of legal institutions. Special attention was paid to over sixty years of Indian judicial practice in applying the fair dealing doctrine, to the American fair use doctrine with its four-factor test, and to the European system of legislative exceptions in text and data mining. The research methodology includes a historical and legal method for identifying evolutionary trends in the judicial interpretation of copyright exceptions, a formal legal method for analyzing the normative content of legal institutions, and a legal modeling method for developing recommendations to improve legislation for regulation of generative artificial intelligence and blockchain technologies.</p></sec><sec><title>Results</title><p>Results: the study convincingly demonstrates the structural inconsistency of the Indian closed-list system of copyright exclusions for regulating generative artificial intelligence and blockchain technologies. It was established that the Indian fair dealing doctrine is characterized by five fundamental limitations: excessively literal interpretation of the legislative text, lack of a transformative use concept, inability to adapt to digital formats, legal gap in the regulation of the artificial intelligence outputs, and significantly limited application. A comparative analysis revealed that the American system reaches structural limits when regulating the large-scale use of data, whereas the European model covers the data input but not the commercialization of artificial intelligence outputs.</p></sec><sec><title>Scientific novelty</title><p>Scientific novelty: the research presents a comprehensive comparative legal analysis of the application of the fair dealing and fair use doctrines to generative artificial intelligence and blockchain technologies. The study systematizes more than sixty years of judicial practice in three legal systems, which allowed identifying the structural limitations of both open and closed models of copyright exceptions and justifying the need to comprehensively regulate full cycle of the creation and commercialization of artificial intelligence content.</p></sec><sec><title>Practical significance</title><p>Practical significance: the results can be used to develop national strategies for regulating artificial intelligence; reform the system of copyright exceptions; introduce technologically neutral standards for text and data mining; create disclosure mechanisms for training datasets and registers of copyright holders’ opt-outs; and modernize the system of collective rights management using blockchain.</p></sec></abstract><trans-abstract xml:lang="ru"><sec><title>Цель</title><p>Цель: проведение сравнительного анализа судебной интерпретации доктрин добросовестного ведения сделок и добросовестного использования в системах авторского права Индии, Соединенных Штатов и Европейского союза в контексте вызовов, порождаемых развитием генеративного искусственного интеллекта и технологий блокчейна.</p></sec><sec><title>Методы</title><p>Методы: в работе использован комплекс научных методов, включающий сравнительно-правовой анализ законодательства трех юрисдикций, систематический анализ судебной практики Индии, догматический метод толкования нормативных актов, а также структурно-функциональный подход к исследованию правовых институтов. Особое внимание уделено изучению индийской судебной практики применения доктрины добросовестного ведения сделок за более чем 60 лет, анализу американской доктрины добросовестного использования с ее четырехфакторным критерием и исследованию европейской системы законодательных исключений для интеллектуального анализа текстов и данных. Методологическая основа исследования включает историко-правовой метод для выявления эволюционных тенденций судебного толкования исключений из авторского права, формально-юридический метод для анализа нормативного содержания правовых институтов, а также метод правового моделирования для разработки рекомендаций по совершенствованию законодательства в области регулирования генеративного искусственного интеллекта и блокчейн-технологий.</p></sec><sec><title>Результаты</title><p>Результаты: проведенное исследование убедительно демонстрирует структурное несоответствие индийской системы исключений из авторского права по принципу закрытых списков для регулирования генеративного искусственного интеллекта и блокчейн-технологий. Установлено, что индийская доктрина добросовестного ведения сделок характеризуется пятью фундаментальными ограничениями: чрезмерной привязанностью к буквальному толкованию законодательного текста, отсутствием концепции трансформирующего использования, неспособностью адаптироваться к цифровым форматам, правовым пробелом в регулировании результатов работы искусственного интеллекта и существенно ограниченным применением. Сравнительный анализ выявил, что американская система достигает структурных пределов при регулировании масштабного использования данных, тогда как европейская модель ограничивается этапом ввода данных и не охватывает коммерциализацию результатов работы искусственного интеллекта.</p></sec><sec><title>Научная новизна</title><p>Научная новизна: впервые проведен комплексный сравнительно-правовой анализ применения доктрин добросовестного ведения сделок и добросовестного использования к генеративному искусственному интеллекту и блокчейн-технологиям на основе систематизации более чем шестидесятилетней судебной практики трех правовых систем, позволивший выявить структурные ограничения как открытых, так и закрытых моделей исключений из авторского права и обосновать необходимость перехода к комплексному регулированию полного жизненного цикла создания и коммерциализации контента, генерируемого искусственным интеллектом.</p></sec><sec><title>Практическая значимость</title><p>Практическая значимость: результаты исследования могут быть использованы при разработке национальных стратегий регулирования искусственного интеллекта, реформировании системы исключений из авторского права, внедрении технологически нейтральных норм для интеллектуального анализа данных, создании механизмов раскрытия информации об обучающих наборах данных и реестров отказа правообладателей, а также при модернизации системы коллективного управления правами с применением инструментов блокчейна.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>авторское право</kwd><kwd>анализ данных</kwd><kwd>блокчейн</kwd><kwd>генеративный искусственный интеллект</kwd><kwd>искусственный интеллект</kwd><kwd>право</kwd><kwd>правовое регулирование</kwd><kwd>сравнительное правоведение</kwd><kwd>судебная практика</kwd><kwd>цифровые технологии</kwd></kwd-group><kwd-group xml:lang="en"><kwd>artificial intelligence</kwd><kwd>blockchain</kwd><kwd>comparative legal studies</kwd><kwd>copyright</kwd><kwd>data analysis</kwd><kwd>digital technologies</kwd><kwd>generative artificial intelligence</kwd><kwd>judicial practice</kwd><kwd>law</kwd><kwd>legal regulation</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Al-Busaidi, A. S. (2024). Investigating the impact of generative artificial intelligence on copyright law: A comparative analysis. Computer Law &amp; Security Review, 54, 105928. https://doi.org/10.1016/j.clsr.2024.105928sciencedirect</mixed-citation><mixed-citation xml:lang="en">Al-Busaidi, A. S. (2024). Investigating the impact of generative artificial intelligence on copyright law: A comparative analysis. Computer Law &amp; Security Review, 54, 105928. https://doi.org/10.1016/j.clsr.2024.105928sciencedirect</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Balganesh, S. (2013). The constitutionalization of fair use. Oxford University Press.</mixed-citation><mixed-citation xml:lang="en">Balganesh, S. (2013). The constitutionalization of fair use. Oxford University Press.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Balganesh, S. (2017). Fair use and fair dealing: Two approaches to limitations and exceptions in copyright law. In I. A. Calboli, &amp; G. F. Dinwoodie (Eds.), The Cambridge handbook of international and comparative copyright law (pp. 286–305). Cambridge University Press.</mixed-citation><mixed-citation xml:lang="en">Balganesh, S. (2017). Fair use and fair dealing: Two approaches to limitations and exceptions in copyright law. In I. A. Calboli, &amp; G. F. Dinwoodie (Eds.), The Cambridge handbook of international and comparative copyright law (pp. 286–305). Cambridge University Press.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Bonadio, E., &amp; McDonagh, L. (2025). Modernising EU copyright in the generative AI era: Text and data mining, transparency, and authors’ rights. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5523838</mixed-citation><mixed-citation xml:lang="en">Bonadio, E., &amp; McDonagh, L. (2025). Modernising EU copyright in the generative AI era: Text and data mining, transparency, and authors’ rights. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5523838</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Buick, A. (2025). Copyright and AI training data—Transparency to the rescue? Journal of Intellectual Property Law &amp; Practice, 20(3), 182–192. https://doi.org/10.1093/jiplp/jpae102</mixed-citation><mixed-citation xml:lang="en">Buick, A. (2025). Copyright and AI training data—Transparency to the rescue? Journal of Intellectual Property Law &amp; Practice, 20(3), 182–192. https://doi.org/10.1093/jiplp/jpae102</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Chauhan, K. (2025). Artificial intelligence and copyright in India. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5096997</mixed-citation><mixed-citation xml:lang="en">Chauhan, K. (2025). Artificial intelligence and copyright in India. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5096997</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Chopra, P. (2025). Generative AI, copyright and personality rights. Library and Information Discourse Analysis, 16(2), 243–266. https://doi.org/10.17323/2658-3253.2025.16.2.243-266</mixed-citation><mixed-citation xml:lang="en">Chopra, P. (2025). Generative AI, copyright and personality rights. Library and Information Discourse Analysis, 16(2), 243–266. https://doi.org/10.17323/2658-3253.2025.16.2.243-266</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Dornis, T. W. (2025). Generative AI training and copyright law: Fair use, fair dealing, and the EU’s new regime. arXiv. https://arxiv.org/pdf/2502.15858.pdfarxiv</mixed-citation><mixed-citation xml:lang="en">Dornis, T. W. (2025). Generative AI training and copyright law: Fair use, fair dealing, and the EU’s new regime. arXiv. https://arxiv.org/pdf/2502.15858.pdfarxiv</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Grodzinsky, F. S., Tavani, H. T., &amp; Wolf, M. J. (2007). Private use as fair use: Is it fair? ACM SIGCAS Computers and Society, 37(3), 8–13. https://doi.org/10.1145/1327325.1327326acm</mixed-citation><mixed-citation xml:lang="en">Grodzinsky, F. S., Tavani, H. T., &amp; Wolf, M. J. (2007). Private use as fair use: Is it fair? ACM SIGCAS Computers and Society, 37(3), 8–13. https://doi.org/10.1145/1327325.1327326acm</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Hauck, R. (2021). Blockchain, smart contracts and intellectual property: Using distributed ledger technology to protect, license and enforce intellectual property rights. Legal Issues in the Digital Age, 1(1), 17–41. https://doi.org/10.17323/2713-2749.2021.1.17.41lida.hse</mixed-citation><mixed-citation xml:lang="en">Hauck, R. (2021). Blockchain, smart contracts and intellectual property: Using distributed ledger technology to protect, license and enforce intellectual property rights. Legal Issues in the Digital Age, 1(1), 17–41. https://doi.org/10.17323/2713-2749.2021.1.17.41lida.hse</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Li, K. (2024). Copyright protection during the training stage of generative AI: A comparative study of US and EU law. Computer Law &amp; Security Review, 54, 105983. https://doi.org/10.1016/j.clsr.2024.105983sciencedirect</mixed-citation><mixed-citation xml:lang="en">Li, K. (2024). Copyright protection during the training stage of generative AI: A comparative study of US and EU law. Computer Law &amp; Security Review, 54, 105983. https://doi.org/10.1016/j.clsr.2024.105983sciencedirect</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Li, Y., &amp; Wang, S. (2024). A copyright-aware blockchain framework for digital content licensing. Computers &amp; Security, 134, 103539. https://doi.org/10.1016/j.cose.2024.103539sciencedirect</mixed-citation><mixed-citation xml:lang="en">Li, Y., &amp; Wang, S. (2024). A copyright-aware blockchain framework for digital content licensing. Computers &amp; Security, 134, 103539. https://doi.org/10.1016/j.cose.2024.103539sciencedirect</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Lund, D. S., &amp; Samuelson, P. (2024). Tiered copyrightability for generative artificial intelligence. AI and Ethics, 4(2), 201–220. https://doi.org/10.1002/aaai.70018onlinelibrary.wiley</mixed-citation><mixed-citation xml:lang="en">Lund, D. S., &amp; Samuelson, P. (2024). Tiered copyrightability for generative artificial intelligence. AI and Ethics, 4(2), 201–220. https://doi.org/10.1002/aaai.70018onlinelibrary.wiley</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Mohammed, A. F. (2025). Fair dealing or unfair system? Copyright enforcement, Content ID, and user rights in India’s platform economy. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5367971papers.ssrn</mixed-citation><mixed-citation xml:lang="en">Mohammed, A. F. (2025). Fair dealing or unfair system? Copyright enforcement, Content ID, and user rights in India’s platform economy. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5367971papers.ssrn</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Rosati, E. (2025a). Copyright exceptions and fair use defences for AI training: EU, US and beyond. European Journal of Risk Regulation, 16(3), 421–446. https://doi.org/10.1017/err.2025.15cambridge</mixed-citation><mixed-citation xml:lang="en">Rosati, E. (2025a). Copyright exceptions and fair use defences for AI training: EU, US and beyond. European Journal of Risk Regulation, 16(3), 421–446. https://doi.org/10.1017/err.2025.15cambridge</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Rosati, E. (2025b). The development of generative AI from a copyright perspective: EU text and data mining, opt-outs, and fundamental rights. European Parliamentary Research Service Study. https://doi.org/10.2861/GENAI.2025europarl.europa</mixed-citation><mixed-citation xml:lang="en">Rosati, E. (2025b). The development of generative AI from a copyright perspective: EU text and data mining, opt-outs, and fundamental rights. European Parliamentary Research Service Study. https://doi.org/10.2861/GENAI.2025europarl.europa</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Sood, P. (2024). Fair dealing in India: An analysis vis-à-vis fair use in the United States. Journal of Intellectual Property Rights, 28, 560–568. https://doi.org/10.56042/jipr.v29i6.7528niscpr</mixed-citation><mixed-citation xml:lang="en">Sood, P. (2024). Fair dealing in India: An analysis vis-à-vis fair use in the United States. Journal of Intellectual Property Rights, 28, 560–568. https://doi.org/10.56042/jipr.v29i6.7528niscpr</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Volkovа, K. Y. (2021). Comparison of fair use and fair dealing concepts in copyright law. Scientific and Technical Libraries, 6, 57–69. https://doi.org/10.33186/1027-3689-2021-6-57-69ntb.gpntb</mixed-citation><mixed-citation xml:lang="en">Volkovа, K. Y. (2021). Comparison of fair use and fair dealing concepts in copyright law. Scientific and Technical Libraries, 6, 57–69. https://doi.org/10.33186/1027-3689-2021-6-57-69ntb.gpntb</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Xie, R., Zhang, J., &amp; Liu, H. (2024). A digital resource copyright protection scheme based on blockchain cross-chain technology. Heliyon, 10(5), e228617. https://doi.org/10.1016/j.heliyon.2024.e228617sciencedirect</mixed-citation><mixed-citation xml:lang="en">Xie, R., Zhang, J., &amp; Liu, H. (2024). A digital resource copyright protection scheme based on blockchain cross-chain technology. Heliyon, 10(5), e228617. https://doi.org/10.1016/j.heliyon.2024.e228617sciencedirect</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Yu, F., Li, Z., &amp; Wang, J. (2023). A copyright-preserving and fair image trading scheme based on blockchain. IEEE Transactions on Industrial Informatics, 19(7), 9321–9332.</mixed-citation><mixed-citation xml:lang="en">Yu, F., Li, Z., &amp; Wang, J. (2023). A copyright-preserving and fair image trading scheme based on blockchain. IEEE Transactions on Industrial Informatics, 19(7), 9321–9332.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
