Technological aspects of generative AI in the context of copyright : attribution and novelty in generative AI hypersurfaces

This in-depth analysis explains the statistical nature of generative AI and how training on copyright-protected data results in persistent functional dependencies with respect to the used data. It highlights the challenges of attribution and novelty detection in these high-dimensional models, emphasising the limitations of current methodologies. The study provides technical recommendations for traceability and output assessment mechanisms.

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Year of publication:	[2025]
Other Persons:	Brando, Axel (contributor)
Institutions:	European Parliament / Directorate-General for Citizens' Rights, Justice and Institutional Affairs (issuing body)
Publisher:	[Brussels] : European Parliament
Subject:	Urheberrecht \| Copyright law \| Generationengerechtigkeit \| Intergenerational equity \| Technischer Fortschritt \| Technological change

Extent:	1 Online-Ressource (22 p.) Illustrationen (farbig)
Type of publication:	Book / Working Paper
Language:	English
Notes:	Manuscript completed in July 2025. - Bibl. : p. 21-22
ISBN:	978-92-848-2903-3
Other identifiers:	10.2861/4727951 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10015452400