- Шусть, Василь Володимирович (orcid.org/0000-0002-0094-1121) and Гулак, Олена Василівна (orcid.org/0000-0001-9004-0185) (2025) International experience in the protection of intellectual property rights in the era of artificial intelligence In: Законодавство України у сфері інтелектуальної власності та його правозастосування: національні, європейські та міжнародні виміри: матеріали XІІІ Міжнародної науково-практичної конференції молодих вчених та студентів з проблем інтелектуальної власності . КНУ імені Тараса Шевченка, НДІ інтелектуальної власності НАПрН України, м. Київ, Україна, pp. 130-134.
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Abstract
Relevance. In the contemporary digital environment, artificial intelligence (AI) is increasingly functioning as an autonomous source of innovation, thereby generating fundamental legal challenges in the field of intellectual property (IP). Traditional legal constructs—centred exclusively on the human person as the sole subject of authorship and inventorship—prove insufficient to regulate works and technical solutions created or substantially facilitated by AI, particularly with regard to requirements of originality, sufficient technical disclosure, lawfulness of using copyrighted works for AI training, and allocation of legal liability. Methods. The study employs a comprehensive methodology combining legal analysis of international and national normative acts—in particular, Regulation (EU) 2024/1689 on Artificial Intelligence, Directive (EU) 2019/790 on copyright in the Digital Single Market, and Ukraine’s Law “On Copyright and Related Rights” of 1 December 2022—alongside case law analysis of landmark judicial decisions, including the DABUS litigation, the Beijing Internet Court’s ruling in Li v. Liu (2023), and judgments by the German Federal Court of Justice (BGH) and the Hamburg Regional Court. A comparative legal approach is further applied to identify regulatory trends and divergences across the European Union, Germany, the United States, China, and Ukraine. Results. The analysis reveals that patent law maintains the principle that only natural persons may be recognised as inventors—a position consistently upheld by patent offices and courts in the EU, the UK, and the US. Nevertheless, inventions generated with AI assistance remain patentable provided that a human actor played a decisive role in conceiving or directing the inventive process. In copyright law, approaches diverge: while the EU adheres to a strictly anthropocentric model, Chinese jurisprudence—as evidenced by the Li v. Liu judgment—recognises copyright protection where the user has made a substantial creative contribution to the generative process (e.g., through prompt engineering, parameter tuning, and aesthetic selection). Furthermore, the Hamburg Regional Court affirmed the permissibility of using copyrighted materials for AI training under the text and data mining (TDM) exception for non-commercial scientific research, though it left unresolved the legal status of non-technical opt-out mechanisms (e.g., natural-language notices vs. machine-readable signals such as robots.txt). The study also identifies a structural tension between the transparency and documentation obligations under the EU AI Act and the need to safeguard trade secrets and patented know-how, particularly given the “black-box” nature of many deep learning systems, which impedes compliance with the requirement of sufficient technical disclosure under the European Patent Convention. Conclusions. The findings indicate that the existing IP regime requires deliberate, adaptive reform to accommodate the realities of autonomous and semi-autonomous AI-driven creation. The authors propose four priority avenues for reform: (1) refining the criteria for human creative and intellectual contribution in AI-assisted works and inventions; (2) modernising the standard of sufficient disclosure to account for opaque AI architectures; (3) harmonising TDM exceptions across jurisdictions to ensure legal certainty for researchers and developers; and (4) clarifying the legal effect of non-technical opt-out declarations in AI training contexts. For Ukraine, a phased regulatory strategy is recommended—beginning with a preparatory stage (e.g., through the White Paper on AI Regulation) and culminating in the adoption of a national law aligned with the EU AI Act—thereby fostering innovation while preserving legal coherence and international compatibility.
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