Intellectual Property Challenges in the Era of Big Data and Large Language Models
Keywords:
Intellectual Property, Big Data, Large Language Model, Artificial Intelligence.Abstract
This research explores the intricate landscape arising from the integration of big data and large language models (LLMs) across sectors, unveiling intellectual property (IP) challenges requiring careful scrutiny. The transformative impact of big data and the ascendancy of LLMs in artificial intelligence have precipitated complex inquiries into data ownership, copyright law, and privacy. Central to these challenges is the ownership of datasets, especially those crucial in LLM training, reflecting the ambiguous nature of data as a contemporary digital asset. LLMs, proficient in generating content akin to their training materials, introduce nuances challenging traditional copyright boundaries. Privacy concerns escalate due to the pivotal role of personal data in both big data analytics and LLM functionality. This research aims for a comprehensive examination of these IP challenges by scrutinizing existing legal frameworks, evaluating their adequacy in the context of big data and LLMs, and unraveling the intricate relationship between technological innovation and IP law. The ultimate goal is to propose legal solutions or frameworks adept at tackling these emergent challenges. The significance of this research lies in its potential to shape robust legal and ethical standards in the digital age, providing valuable insights for policymakers, technologists, and legal experts to navigate the evolving nexus of technology and intellectual property.
Downloads
References
M. Abdallah and M. Salah, "Artificial Intelligence and Intellectual properties: legal and ethical considerations," International Journal of Intelligent Systems and Applications in Engineering, vol. 12, no. 1, pp. 368-376, 2024.
L. Barqawi and M. Abdallah, "Copyright and generative AI," Journal of Infrastructure, Policy and Development, vol. 8, no. 8, p. 6253, 2024.
E. Kasneci et al., "ChatGPT for good? On opportunities and challenges of large language models for education," Learning and Individual Differences, vol. 103, p. 102274, 2023/04/01/ 2023, doi: https://doi.org/10.1016/j.lindif.2023.102274.
K. Taylor, "The patentability of inventions with artificial intelligence listed as an inventor following Thaler v. Hirshfeld," IPCLJ, vol. 6, p. 1, 2021.
M. Abdallah, K. Jaber, M. Salah, and A. Omayah, "Impact of Big Data Analytics and Large Language Model on Intellectual Property," Al-Zaytoonah University of Jordan Journal for Legal studies, vol. 5, no. Special Issue, pp. 1039-1047, 2024.
[S. Ghayyur, J. Averitt, E. Lin, E. Wallace, A. Deshpande, and H. Luthi, "Panel: Privacy Challenges and Opportunities in {LLM-Based} Chatbot Applications," 2023.
S. Tripathi and C. Ghatak, "Artificial intelligence and intellectual property law," Christ ULJ, vol. 7, p. 83, 2018.
C. M. Correa and A. A. Yusuf, Intellectual Property and International Trade: The TRIPS Agreement: The TRIPS Agreement. Kluwer Law International BV, 2016.
S. Ricketson and J. Ginsburg, "International copyright and neighbouring rights: The Berne Convention and beyond," 2022.
J. Clizer, "Exploring the Abstract: Patent Eligibility Post Alice Corp v. CLS Bank," Mo. L. Rev., vol. 80, p. 537, 2015.
C. Schmit, M. Doerr, and J. Wagner, "Leveraging IP for AI governance," Science, vol. 379, no. 6633, pp. 646-648, 2023.
L. Barqawi and S. Al-Arasi, "Intellectual Property Protection through University Innovation Centres: Jordan’s Approach to Sustainable Development," International Journal of Religion, vol. 5, no. 5, pp. 542-548, 2024.
I. Abdikhakimov, "Legal aspects of AI generated content," in International Conference on Legal Sciences, 2023, vol. 1, no. 5, pp. 1-17.
P. Jandrić, "On The Hyping of Scholarly Research (With A Shout-Out to ChatGPT)," Postdigital Science and Education, pp. 1-8, 2023.
C. G. Merritt, "A Compulsory Solution to the Machine Problem: Recognizing Artificial Intelligence as Inventors in Patent Law," Vand. J. Ent. & Tech. L., vol. 25, p. 211, 2023.
P. Cummings, A. Balazer, and C. Worrel, "Who is an Inventor?," 2023.
K. Hristov, "Artificial intelligence and the copyright dilemma," Idea, vol. 57, p. 431, 2016.
O. Taha, "Intellectual Property Rights in Jordanian Legislation A Comparative Study with Islamic Jurisprudence a New Endowment Formula " Al-Zaytoonah University of Jordan Journal for Legal studies, vol. 2, no. 3, pp. 133-153, 2021, doi: 10.15849/ZUJJLS.211130.06.
B. J. Keele and H. Alcasid, "Copyright and Non-Humans," 2018.
J. Oster, "Code is code and law is law—the law of digitalization and the digitalization of law," International Journal of Law and Information Technology, vol. 29, no. 2, pp. 101-117, 2021.
J. Chen et al., "Copy, right? a testing framework for copyright protection of deep learning models," in 2022 IEEE Symposium on Security and Privacy (SP), 2022: IEEE, pp. 824-841.
T. D. Haley, "Illusory Privacy," Ind. LJ, vol. 98, p. 75, 2022.
S. Unit, "The General Data Protection Regulation (GDPR)," 2022.
C. Radsch, "Weaponizing Privacy and Copyright Law For Censorship," CIGI Papers No, 2023.
L. Barqawi, "The access to medicine puzzle: scaling back the negative effects of the Jordan–US Free Trade Agreement," Journal of Intellectual Property Law & Practice, vol. 14, no. 9, pp. 678-686, 2019, doi: 10.1093/jiplp/jpz080.
J. Luo, "Data-driven innovation: What is it?," IEEE Transactions on Engineering Management, vol. 70, no. 2, pp. 784-790, 2022.
P. Samuelson, "Generative AI meets copyright," Science, vol. 381, no. 6654, pp. 158-161, 2023.
P. Mezei, "‘You AIn't seen nothing yet’: Arguments against the protectability of AI-generated outputs by copyright law," in Law, Regulation and Governance in the Information Society: Routledge, 2022, pp. 126-143.
T. Awad, "Universalizing Copyright Fair Use: To Copy, or Not to Copy?," J. Intell. Prop. L., vol. 30, p. 1, 2022.
L. A. DiMatteo, C. Poncibò, and M. Cannarsa, The Cambridge handbook of artificial intelligence: global perspectives on law and ethics. Cambridge University Press, 2022.
K. Muehlfeld and M. Wang, "Intellectual Property Rights in China—A Literature Review on the Public's Perspective," Frontiers in Sociology, vol. 7, p. 793165, 2022.
M. T. Messina, "Thaler v. Vidal, 43 F. 4th 1207 (Fed. Cir. 2022)," DePaul J. Art Tech. & Intell. Prop. L, vol. 33, p. 67, 2023.
M. Lavrichenko, "Thaler v. Vidal: Artificial Intelligence-Can the Invented Become the Inventor," Cardozo L. Rev., vol. 44, p. 699, 2022.
I. Buzu, "The DABUS Affair," Available at SSRN 4175009, 2022.
R. Moufang, "Artificial Intelligence and the Technicality Requirement of Patent Law," in A Critical Mind: Hanns Ullrich’s Footprint in Internal Market Law, Antitrust and Intellectual Property: Springer, 2023, pp. 471-488.
A. Drake et al., "Legal contestation of artificial intelligence-related decision-making in the United Kingdom: reflections for policy," International Review of Law, Computers & Technology, vol. 36, no. 2, pp. 251-285, 2022.
E. Bonadio, L. McDonagh, and P. Dinev, "Artificial intelligence as inventor: exploring the consequences for patent law," Intellectual Property Quarterly, vol. 1, pp. 48-66, 2021.
S. Kokane, "The Intellectual Property Rights of Artificial Intelligence-based Inventions," Journal of Scientific Research, vol. 65, no. 2, 2021.
K. Wills, "Ai around the world: Intellectual property law considerations and beyond," J. Pat. & Trademark Off. Soc'y, vol. 102, p. 186, 2021.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
