Intellectual property challenges in the 21st century: A study of digital piracy in the European Union

Blanca Mª Rubio Alfageme

Abstract


Purpose: This study addresses the challenges of intellectual property in the 21st century, focusing on digital piracy in the European Union and the impact of Artificial Intelligence (AI). It emphasizes the need to modernize the European copyright system to adapt to the digital era, highlighting the recent European AI regulation, a double-edged sword that can be used both as a tool to detect and curb digital piracy and to facilitate it.

Design/methodology/approach: The methodology employed in this research includes an analysis of existing literature on AI, digital piracy, and intellectual property, as well as empirical insights provided by a panel data model. A pluralist methodology is employed, starting from the "jurisprudence of interests," and an interdisciplinary approach is adopted that encompasses both a legal and an economic perspective.

Findings: The study of digital piracy from a legal perspective shows that the divergence of intellectual property laws among member states exacerbates the problem, and from an economic standpoint, the existence of a relationship between digital piracy and copyright norms is empirically demonstrated: systems that are more protective of copyrights have higher rates of digital piracy.

Originality/value: Due to the increasing importance of cultural and creative industries for the European economy, this research is essential. The European copyright system must be modernized to adapt to the digital age. Civil and criminal systems have failed in the fight against digital piracy, and administrative procedures threaten rights and freedoms. Other methods to combat it are proposed, such as raising awareness in society and investing in the development of new business models adapted to the digital economy. The study also investigates the role AI can play in this context.


Keywords


copyright, Artificial Intelligence, digital piracy, European Union, panel data

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DOI: https://doi.org/10.3926/ic.3040


Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Intangible Capital, 2004-2025

Online ISSN: 1697-9818; Print ISSN: 2014-3214; DL: B-33375-2004

Publisher: OmniaScience