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dc.contributor.authorStasjuka, Tatjana
dc.contributor.otherRiga Graduate School of Law
dc.date.accessioned2025-07-29T10:05:13Z
dc.date.available2025-07-29T10:05:13Z
dc.date.issued2025
dc.identifier.urihttps://dspace.lu.lv/dspace/handle/7/71616
dc.description.abstractThis thesis addresses the growing interest to legal uncertainty surrounding the recognition control and commercialization of instrumental music generated by artificial intelligence. Despite the increasing use of generative AI in creative industries, for instance music industry, and its transformative influence, copyright law remains grounded in the concept of human authorship and has yet to adequately adapt to emerging realities. The study explores the conditions under which AI-generated music may qualify for legal protection, the minimum threshold of human involvement required for authorship recognition, and the risks associated with the use of copyrighted training data. A three-tier regulatory model – legal, technological, and economic – is proposed to enhanced transparency and enable effective rights management. This model includes modular licensing, value-based revenue allocation, and provenance verification through blockchain technologies. The research also considers the potential application of NFTs, smart contracts, and platform-based regulation of monetization purposes. A comparative analysis of EU and US approaches highlights the current lack of harmonization and underscores the need for flexible, coordinated solutions. The findings of this study may serve as a foundation for developing a legal infrastructure for AI-generated content.en_US
dc.language.isoengen_US
dc.publisherRiga Graduate School of Lawen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectResearch Subject Categories::LAW/JURISPRUDENCE::Private law::Intellectual property lawen_US
dc.subjectResearch Subject Categories::LAW/JURISPRUDENCE::Other law::European lawen_US
dc.subjectAI-generated musicen_US
dc.subjectcopyright lawen_US
dc.subjectauthorshipen_US
dc.titleLegal recognition, control and monetization of AI-generated instrumental music content: EU and US approachesen_US
dc.typeinfo:eu-repo/semantics/masterThesisen_US


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