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Copyright as an obstacle or an enabler? A European perspective on text and data mining and its role in the development of AI creativity
Abstract
Text and data mining (TDM) may be performed in a variety of fields and for different purposes. Among other things, TDM techniques may be used to ‘train’ Artificial Intelligence (AI), also for the purpose of AI-driven creativity. In this context, copyright restrictions might be in place, even if copies made of pre-existing content are only used internally and are instrumental to the creation of something ‘new’. Recently, in the context of the Directive 2019/790 on Copyright in the Digital Single Market (DSM Directive), the European Union (EU) legislature introduced two new mandatory exceptions for TDM. This article discusses the interplay between TDM and AI creativity by focusing, first, on the potential and technicalities of TDM and the interplay with legal restrictions. Second, it reviews the copyright-related issues facing TDM and the debate underlying the adoption of this new piece of EU legislation. Third, it reflects on the future of AI creativity in Europe. This article concludes that, even despite the adoption of two new mandatory TDM exceptions in the DSM Directive which are now to be transposed by individual EU Member States, copyright restrictions might continue affecting and restricting significantly the possibility of undertaking TDM activities in Europe.
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“In an EU context, some argue that the emerging approach to regulation of Text and Data Mining (TDM) positions copyright law as a potential obstacle rather than an enabler for the learning required by commercial GenAI (Rosati, 2019).”
From Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights (2024) · cites this paper as Rosati, 2019
Citations
Cited by
Al-Busaidi, A. S., Raman, R., Hughes, L., Albashrawi, M. A., Malik, T., Dwivedi, Y. K., Al- Alawi, T., AlRizeiqi, M., Davies, G., Fenwick, M., et al. (2024) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2024.100630 · Cited by 95
Metadata
- Authors
- Rosati, E.
- Affiliations
- Law Department, Stockholm University, Stockholm, Sweden
- ORCID
- Rosati, Eleonora
- Venue
- Asia Pacific Law Review
- Publisher
- Informa UK Limited
- Published
- 2019-07-03
- Volume
- 27
- Issue
- 2
- Pages
- 198-217
- ISSN
- 1019-2557
- 1875-8444
- Cited by
- 31
- References
- 0
- Language
- en
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