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Can text and data mining exceptions and synthetic data training mitigate copyright-related concerns in generative AI?
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“It should be noted, however, that increasing the cost or difficulty of accessing data may diminish AI technological progress (Kowala, 2024;Manteghi, 2024).”
From Generative AI and intellectual property: a systematic literature review of possible issues and mitigations (2026) · cites this paper as Manteghi, 2024
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“Matching the licences for a huge amount of digital data, the ownership of which is usually difficult to reconstruct, is a complex task (Manteghi, 2024).”
From Generative AI and intellectual property: a systematic literature review of possible issues and mitigations (2026) · cites this paper as Manteghi, 2024
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“Furthermore, it is argued that the quality, reliability and diversity of GenAI models could degrade over generations if training datasets consist only of synthetic data without fresh real-world data (Manteghi, 2024).”
From Generative AI and intellectual property: a systematic literature review of possible issues and mitigations (2026) · cites this paper as Manteghi, 2024
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“Alongside licensing agreements between AI developers and copyright owners, one proposed solution for the legal use of copyright-protected works in training is to pay royalties to copyright owners (Manteghi, 2024).”
From Generative AI and intellectual property: a systematic literature review of possible issues and mitigations (2026) · cites this paper as Manteghi, 2024
In the citing paper
“While copyright protects ideas rather than expression, GenAI training technically requires making digital copies to analyse the data, which triggers copyright restrictions (Manteghi, 2024).”
From Generative AI and intellectual property: a systematic literature review of possible issues and mitigations (2026) · cites this paper as Manteghi, 2024
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Research works printed but not linked: 16
- Jonathan Griffiths, and Tuomas Mylly (eds), Global Intellectual Property Protection and New Constitution- alism: Hedging Exclusive Rights (Oxford, 2021; online edn, Oxford Academic, 23 Dec. 2021);
- Christophe Geiger and Elena Izyumenko, 'From Internal to External Balancing, and Back? Copyright Limitations and Fundamental Rights in the Digital Environment' in Julian Lopez and Conception Saiz Garcia (eds.) Digitalización, acceso a conteni- dos y propiedad intelectual (Madrid, Dykinson, 2022) 103, 105;
- Tito Rendas, 'Fundamental rights in EU copyright law: An overview' in Eleonora Rosati (ed.), The Routledge Handbook of EU Copyright Law (1 ed., Taylor and Francis - Balkema) 18, 23; Christophe Geiger (n 40) 32; Case C-469/17 Funke Medien NRW GmbH v Bundesrepublik Deutschland para 72; Case C-476/17 Pelham GmbH and Others v Ralf Hütter and Florian Schneider- Esleben para 32; Case C-314-12, UPC Telekabel Wien GmbH v. Constantin Film Verleih GmbH, Wega Film- produktionsgesellschaft mbH [2014], Judgment of the Court (Fourth Chamber) of 27 March 2014, para. 61;
- Christophe Geiger and Bernd Justin Juẗte (n 18) 142; for a general overview of TDM techniques and methods see, for instance, Jiawei Han et al., Data Mining: Concepts and Techniques (3rd edn, Elsevier 2012).
- Kalpana Tyagi, 'Copyright, text & data mining and the innovation dimension of generative AI' Forth- coming in Journal of Intellectual Property Law & Practice, 2024 < https://academic.oup.com/jiplp/ advance-article/doi/10.1093/jiplp/jpae028/7624901 > accessed 27 March 2024, 17. See also CJEU, Judgment in Funke Medien NRW GmbH v. Bundesrepublik Deutschland, C-469/17, 29 July 2019, EU: C:2019:623; CJEU, Judgment in Pelham GmbH and Others v. Ralf Huẗter and Florian Schneider- Esleben, C-476/17, 29 July 2019, EU: C:2019:624; and CJEU, Judgment in Spiegel Online GmbH v. Volker Beck, C-516/17, 29 July 2019, EU: C:2019:625. For commentary on these decisions, see also Thomas Dreier, 'The CJEU, EU Fundamental Rights and the Limitations of Copyright' (2020) 69 GRUR International 223-224; Tito Rendas (n 48) 25. · DOI
- Oreste Pollicino et al., 'Cultural Rights, Cultural Diversity and the EU's Copyright Regime: the Battlefield of Exceptions and Limitations to Protected Content' in Oreste Pollicino (ed.) Copyright and Fundamental Rights in the Digital Age (Edward Elgar Publishing Limited, 2020) 124, 141-142. 82 Recital 6 of the CDSM Directive; Andres Guadamuz, 'A Scanner Darkly: Copyright Liability and Excep- tions in Artificial Intelligence Inputs and Outputs' (2024) 73(2) GRUR International 111, 120.
- Gina Maria Ziaja, 'The Text and Data Mining Opt-out in Article 4(3) CDSMD: Adequate Veto Right for Rightholders or a Suffocating Blanket for European Artificial Intelligence Innovations?' (2024) 19(5) Journal of Intellectual Law and Practice 453, 454-453. Maryna Manteghi (n 28) 454. 86 Ibid 87 Maryna Manteghi (n 28) 40; Maryna Manteghi (n 28) 449;
- Christophe Geiger et al., 'Crafting a Text and Data Mining Exception for Machine Learning and Big Data in the Digital Single Market' in Xavier Seuba, Christophe Geiger and Julien Pénin (eds.), Intellectual Property and Digital Trade in the Age of Artificial Intelligence and Big Data (A CEIPI-ICTSD, Issue 5, 2018) 95; Bernt Hugenholtz, 'The New Copyright Directive: Text and Data Mining (Articles 3 and 4)' (Kluwer Copyright Blog, 24 July 2019) < http://copyrightblog.kluweriplaw. com/2019/07/24/the-new-copyright-directive-text-and-data-mining-articles-3-and-4/ > accessed 20 February 2024;
- Christophe Geiger and Vncenzo Iaia, 'The Forgotten Creator: Towards a Statutory Remuneration Right for Machine Learning of Genera- tive AI' (2023) 52 Computer Law & Security Review (forthcoming, 2024) < https://papers.ssrn.com/sol3/ papers.cfm?abstract_id=4594873 > accessed 23 March 2024.
- Christophe Geiger and Elena Izyumenko, 'Towards a European 'Fair Use' Grounded in Freedom of Expression' (2019) 35(1) American University International Law Review 1, 58; Christophe Geiger (n 38) 1.
- Péter Mezei, 'A saviour or a dead end? Reservation of rights in the age of generative AI' (2024) SSRN < https://papers.ssrn.com/sol3/ papers.cfm?abstract_id=4695119 > accessed 20 March 2024, 3.
- James Jordon et al., 'Synthetic Data -What, Why and How?' (2022) < https://arxiv.org/abs/2205.03257 > accessed 23 February 2024, 6, 30. 136 Sina Alemohammad et al (n 32) 2. 137 Tshilidzi Marwala et al (n 30), 5; For more discussions see, for example, Fida K. Dankar and Mahmoud Ibrahim (n 34) 2159; · arXiv
- Peter Lee, 'Synthetic Data and the Future of AI' (2024) 110 Cornell Law Review (forthcoming) < https:// papers.ssrn.com/sol3/papers.cfm?abstract_id=4722162 > accessed 12 March 2024, 15;
- Fordham Law Review 1887; See also famous US cases which hold that TDM constitute fair use: Authors Guild v. HathiTrust, 755 F.3d 87 (2d Cir. 2014) and Authors Guild v. Google, Inc., 804 F.3d 202 (2d Cir. 2015). 158 Peter Lee (n 155) 24; In this sense, see also GenAI pending cases (n 43). 159 Peter Lee (n 155) 24. 160
- Katherine Lee et al (n 15) 51; In this sense, it is argued that accessing and using different variations of synthetic data for training would require less time, money and effort than obtaining 'lawful access' to real-world data every time when AI developers need to develop new GenAI models, see, for instance, Aryan Jadon and Shashank Kumar, (n 30) 3; James Jordon et al (n 135) 7; Adam Zewe (n 144). 161 For technical aspects see Daniele Panfilo et al., 'A Deep Learning-Based Pipeline for the Generation of Synthetic Tabular Data' (2016) 11 IEEE < https://www.researchgate.net/publication/371828083_A_ Deep_Learning-based_Pipeline_for_the_Generation_of_Synthetic_Tabular_Data > access 162
- Yuxi Ma et al., 'Brain in a Vat: On Missing Pieces Towards Artificial General Intelligence in Large Language Models' (2023) < https://arxiv.org/abs/2307.03762 > accessed 12 February 2024, 4; · arXiv
Cited by
Arnaudo, A., Coppola, R., Morisio, M., Vetrò, A., Borghi, M., Raso, R., & Khan, B. (2026) · PeerJ Computer Science · doi:10.7717/peerj-cs.3928 · Cited by 2
Metadata
- Authors
- Manteghi, M.
- Affiliations
- Faculty of Law, University of Turku, Turku, Finland
- Venue
- Law, Innovation and Technology
- Publisher
- Informa UK Limited
- Published
- 2024-07-02
- Volume
- 16
- Issue
- 2
- Pages
- 663-686
- ISSN
- 1757-9961
- 1757-997X
- Cited by
- 9
- References
- 0
- Language
- en
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