The DOI matches its Crossref record; 86 of the 91 references it cites were found in a registry or an index, and 1 are not checked yet; none of the 118 sources its claims cite is checked for support yet.
Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights
Open accessAbstract
The rapid integration of generative AI (GenAI) into industries and society has prompted a re-evaluation of copyright and intellectual property rights (IPR) frameworks. GenAI's ability to produce original content using data from human-created sources raises critical ethical and legal concerns. Current copyright and IPR frameworks, designed around human authorship, are insufficient to address these challenges. This study, using a multi-perspective approach, explores GenAI's disruptive potential in replicating or transforming copyrighted materials, challenging established IPR norms. Findings highlight gaps in legislation and the opacity of GenAI platforms. To address these issues, this study presents a Dynamic Ethical Framework linked to a future global fair use policy, aiming to guide responsible GenAI development and use. By incorporating insights from domain experts, this study contextualizes emerging challenges and potential solutions within broader societal and technological trends. That said, this study calls for international collaboration and further research to reform IPR related laws and frameworks, ensuring they remain relevant and equitable in a GenAI-driven era.
Checked 2026-11-12 · 1 reference not checked yet
Overview
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TL;DR
This multi-expert paper argues that current copyright and intellectual property rights frameworks, built around human authorship, are insufficient for generative AI, and it proposes a Dynamic Ethical Framework linked to a future global fair use policy. It synthesizes legal, policy, and practice perspectives to call for international collaboration and further research on GenAI-related copyright reform.
Key findings
- The paper finds gaps in legislation and opacity in GenAI platforms, with current copyright/IPR frameworks unable to address GenAI’s use of human-created data and its generation of content that challenges authorship, ownership, and fair use.
- It reports that GenAI’s economic impact is estimated at US$2.6–$4.4 trillion in annual value added, increasing AI’s total economic impact by 40%; ChatGPT reached 100 million users in two months; and recorded music alone is a global annual market worth $26bn.
- Legal disputes illustrate the uncertainty: Getty Images accused Stability AI of using more than 12 million copyrighted images, and cases such as New York Times v. OpenAI test fair use, transformation, and market impact.
- The authors propose a Dynamic Ethical Framework and “Global Fair AI Use” policy covering GenAI platform developers, authorship, and ownership, and call for international collaboration to reform IPR laws.
Methods
- Design: a multiperspective expert-based approach, following prior work by von Foerster and Dwivedi et al., inviting specialists from academia and practice to contribute perspectives on GenAI, copyright, and IPR.
- Data/sample: eleven invited expert contributions, plus legal cases, policy documents, and literature; no primary empirical dataset is collected.
- Analysis: thematic analysis of the contributions, organized around emerging challenges, legal complexities, creativity/authorship/ownership, regulation and policy, and future adaptation; the discussion develops the Dynamic Ethical Framework and a proposed “Global Fair AI Use” policy.
Limitations
- Stated in the paper: the multi-expert format may produce overlapping narratives across perspectives; the paper’s length is a limitation; contributions were limited to eleven due to the specialised nature of the topic.
- Evident from the text: the study is conceptual/editorial rather than empirical, and the proposed Dynamic Ethical Framework is not tested or validated; legal coverage is jurisdiction-specific and not a systematic global legal review.
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Claims the paper makes
125 Own interpretation · 60 Sources not found · 26 No basis given · 17 Check pending · 12 Not checked yet · 7 No full text of the sources · 5 Own result
In the paper
“The absence of a traditional mechanism of authorship in AI-generated content creation, could potentially shift the economic benefits away from human creators towards those who own or operate the AI technologies and platforms (Israhadi, 2023).”
§ Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights > Introduction
What the sources say
- Check pendingcites Israhadi, 2023 source
hedgedstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“GenAI's ability to produce original content using data from human-created sources raises critical ethical and legal concerns.”
- Also stated in: § Introduction · plain
“This has profound legal and ethical consequences related to the protection of human creativity, authorship, and content ownership (Frosio, 2024).”
§ Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights > Abstract
What the sources say
- Check pendingcites Frosio, 2024 source
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Introduction · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Current copyright and IPR frameworks, designed around human authorship, are insufficient to address these challenges.”
§ Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption not shown here.
In the paper
“The emergence of AI as a non-human creator, directly challenges the existing legal infrastructure built around the human creator (Frosio, 2024;Liu et al., 2023).”
§ Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights > Introduction
What the sources say
- Check pendingcites Frosio, 2024 source
- Not matchedcites Liu et al., 2023
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Within the current legal frameworks, GenAI applications may be liable for copyright infringement if they both had access to the original works and GenAI generated output is substantially similar to the original works (Zirpoli, 2023).”
§ Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights > Legal Complexities
What the sources say
- Not matchedcites Zirpoli, 2023
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
- It may state two separate claims as one. 98
- Probably not a substantial claim. 175
- The quote only partly states this claim. 1
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Citations
Cites
Proceedings of the 24th international conference on Machine learning
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Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.002 · Cited by 4,611
Self-citationDwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., et al. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102642 · Cited by 4,584
Self-citationChatGPT: five priorities for research
van Dis, E. A. M., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L. (2023) · Nature · doi:10.1038/d41586-023-00288-7 · Cited by 1,842
Generative AI and ChatGPT: applications, challenges, and AI-human collaboration
Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2023.2233814 · Cited by 1,363
Organizations: A Dialectical View
Benson, J. (1977) · Administrative Science Quarterly · doi:10.2307/2391741 · Cited by 942
ChatGPT listed as author on research papers: many scientists disapprove
Stokel-Walker, C. (2023) · Nature · doi:10.1038/d41586-023-00107-z · Cited by 868
Neural Network Methods for Natural Language Processing
Goldberg, Y. (2017) · Synthesis Lectures on Human Language Technologies · doi:10.1007/978-3-031-02165-7 · Cited by 821
Art and the science of generative AI
Epstein, Z., Hertzmann, A., the Investigators of Human Creativity, Akten, M., Farid, H., Fjeld, J., Frank, M. R., Groh, M., Herman, L., Leach, N., et al. (2023) · Science · doi:10.1126/science.adh4451 · Cited by 788
Ooi, K.-B., Tan, G. W.-H., Al-Emran, M., Al-Sharafi, M. A., Capatina, A., Chakraborty, A., Dwivedi, Y. K., Huang, T.-L., Kar, A. K., Lee, V.-H., et al. (2025) · Journal of Computer Information Systems · doi:10.1080/08874417.2023.2261010 · Cited by 746
Self-citation
Research works printed but not linked: 14
- Baker, 2023, Intellectual Property and Generative AI, Deloitte AI Institute. Retrieved from
- De Mantaras, 2002, AI and music: From composition to expressive performance, AI magazine, 23
- Dornis, 2020, Artificial creativity: Emergent works and the void in current copyright doctrine, Yale Journal of Law & Technology, 22, 1
- Gans, 2024, Copyright policy options for generative artificial intelligence (No. w32106), National Bureau of Economic Research
- Jo, 2023, The promise and peril of generative AI, Nature, 614, 214
- Jodha, 2023, Copyright issues in the era of Ai-A critical analysis, Res Militaris, 13, 1737
- Metrics, PlumX. (2024). Policy Citations. Accessed on 17th November 2024. https://plu.mx/plum/a/policy_citation?doi=10.1016/j.ijinfomgt.2023.102642&theme=plum-sciencedirect-theme&hideUsage=true. · DOI · Paper page
- Metz, 2024, How tech giants cut corners to harvest data for AI, The New York Times
- MIT Technology Review (2023). The great acceleration: CIO perspectives on generative AI. Retrieved from https://www.databricks.com/sites/default/files/2023-07/ebook_mit-cio-generative-ai-report.pdf.
- Roberts, 2023, 39, 79
- Sanders, 2020, The Secret to AI is People, Harvard Business Review
- Senftleben, 2020, Robot creativity: An incentive-based neighbouring rights approach, European Intellectual Property Review, 42, 797
- Sindre, 2001, Capturing security requirements through misuse cases. NIK 2001, Norsk Informatikkonferanse, 74
- Yu, 2003, The copyright divide, Cardozo Law Review, 25, 331
Cited by
Generative AI for decision-making: A multidisciplinary perspective
Albashrawi, M. A. (2025) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2025.100751 · Cited by 82
Self-citationDwivedi, Y. K. (2025) · International Entrepreneurship and Management Journal · doi:10.1007/s11365-025-01089-2 · Cited by 79
Self-citationScholarly Discourse on GenAI’s Impact on Academic Publishing
Dwivedi, Y. K., Malik, T., Hughes, L., & Albashrawi, M. A. (2024) · Journal of Computer Information Systems · doi:10.1080/08874417.2024.2435386 · Cited by 38
Self-citationCerchione, R., Liccardo, G., & Passaro, R. (2025) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2025.100866 · Cited by 37
Zaidan, E., Truby, J., Ibrahim, I. A., & Hoppe, T. (2025) · Technology in Society · doi:10.1016/j.techsoc.2025.103159 · Cited by 19
Metadata
- Authors
- 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., Gupta, P., Gurpur, S., Hooda, A., Jurcys, P., Lim, D., Lucchi, N., Misra, T., Raman, R., Shirish, A., & Walton, P.
- Affiliations
- Sultan Qaboos University (OM)
- Edith Cowan University (AU)
- Swansea University (GB)
- King Fahd University of Petroleum and Minerals (SA)
- University of Wales Trinity Saint David (GB)
- Kyushu University (JP)
- Management Development Institute (IN)
- Symbiosis International University (IN)
- O. P. Jindal Global University (IN)
- Pennsylvania State University (US)
- Universitat Pompeu Fabra (ES)
- Université Paris-Saclay (FR)
- Capgemini (United Kingdom) (GB)
- ORCID
- Venue
- Journal of Innovation & Knowledge
- Publisher
- Elsevier BV
- Published
- 2024-10
- Volume
- 9
- Issue
- 4
- Pages
- 100630
- ISSN
- 2444-569X (ISSN-L)
- OpenAlex
- W4404867434
- Cited by
- 95
- References
- 91
- Citations by year
- 2026: 48 · 2025: 43 · 2024: 4
- FWCI
- 9.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Innovation & Knowledge (publishedVersion, cc-by-nc-nd)
- SSRN Electronic Journal (submittedVersion)
- Econstor (Econstor) (submittedVersion, cc-by-nc-nd)
- Australasian Journal of Paramedicine (submittedVersion, cc-by-nc-nd)
- HAL (submittedVersion)
- Cronfa (Swansea University) (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Institutional Research Information System University of Ferrara (University of Ferrara) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
- Social Sciences › Law › Intellectual Property Law
- Social Sciences › Law › Intellectual Property Rights and Media
- Keywords
- generative AI, copyright, intellectual property, AI-generated content, authorship, fair use, AI ethics, AI regulation, international intellectual property law
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