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The Fourth Industrial Revolution. The Functions and Impacts of Copyright and Related Rights on Artificial Intelligence and Machine Learning (ML).

White, B., 2026. The Fourth Industrial Revolution. The Functions and Impacts of Copyright and Related Rights on Artificial Intelligence and Machine Learning (ML). Doctoral Thesis (Doctoral). Bournemouth University.

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Abstract

This thesis addresses the question of the extent to which the contours of copyright law, and in Europe sui generis database rights, affect the adoption of machine learning in four different jurisdictions – namely the EU, Japan, the United Kingdom and the United States of America. Furthermore, it explores how the answer to this question has influenced recent e-commerce developments in international trade law. It approaches this analysis through the traditional framework of copyright law and related rights by evaluating the application of both permitted and restricted acts. First, the thesis examines how these four jurisdictions frame limitations and exceptions to exclusive rights that facilitate data analysis undertaken on copyrighted works. After this, existing legal doctrines that apply to exclusive rights in traditional computer programs are outlined before evaluating their applicability to AI model software. The research employs doctrinal and comparative research methodologies grounded in an economic and innovation policy perspective on law. Such an approach serves to highlight not only the strengths and weaknesses of data analysis exceptions across the four jurisdictions examined, but how copyright law contributes to both economic imbalances in AI markets and recent geo-political developments in Preferential Trade Agreements and at the WTO. This research makes an original contribution to knowledge through the doctrinal and comparative legal analysis adopted, including inter alia an in-depth analysis of Japanese copyright law’s regulation of AI, and a doctrinal exploration of the extent to which copyright and sui generis database rights inhere in a range of different trained AI models, including but not limited to neural networks, SVM models, decision trees and random forests. The conclusion presented forms a concrete legal justification to explain recent developments in international trade law concerning software and algorithm disciplines, highlighting the potential role of copyright law as a mechanism to facilitate greater competition within artificial intelligence markets.

Item Type:Thesis (Doctoral)
Additional Information:If you feel that this work infringes your copyright, please contact the BURO Manager.
Uncontrolled Keywords:Intellectual property law; Trade law; Copyright; Sui Generis database rights; Artificial Intelligence; Machine learning; Text and data mining
Group:Faculty of Business and Law
ID Code:42288
Deposited By: Symplectic RT2
Deposited On:03 Aug 2026 12:52
Last Modified:04 Aug 2026 10:57

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