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Who Owns the Knowledge? Copyright, GenAI, and the Future of Academic Publishing

Published: November 24, 2025 | arXiv ID: 2511.21755v1

By: Dmitry Kochetkov

Potential Business Impact:

Protects artists' work from being used to train AI.

Business Areas:
Machine Learning Artificial Intelligence, Data and Analytics, Software

The integration of generative artificial intelligence (GenAI) and large language models (LLMs) into scientific research and higher education presents a paradigm shift, offering revolutionizing opportunities while simultaneously raising profound ethical, legal, and regulatory questions. This study examines the complex intersection of AI and science, with a specific focus on the challenges posed to copyright law and the principles of open science. The author argues that current regulatory frameworks in key jurisdictions like the United States, China, the European Union, and the United Kingdom, while aiming to foster innovation, contain significant gaps, particularly concerning the use of copyrighted works and open science outputs for AI training. Widely adopted licensing mechanisms, such as Creative Commons, fail to adequately address the nuances of AI training, and the pervasive lack of attribution within AI systems fundamentally challenges established notions of originality. This paper issues a call to action, contending that AI training should not be shielded under fair use exceptions. Instead, the author advocates for upholding authors' rights to refuse the use of their works for AI training and proposes that universities assume a leading role in shaping responsible AI governance. The conclusion is that a harmonized international legislative effort is urgently needed to ensure transparency, protect intellectual property, and prevent the emergence of an oligopolistic market structure that could prioritize commercial profit over scientific integrity and equitable knowledge production.

Page Count
21 pages

Category
Computer Science:
Digital Libraries