Generative AI: Legal Concerns and Implications
Corresponding Author(s) : Marwa Zein Zein
Journal of Law and Emerging Technologies,
Vol. 3 No. 1 (2023)
Abstract
This research paper examines the legal implications of the widespread adoption of Artificial Intelligence (AI) and technologies emerging from it such as Generative AI, particularly in the context of the presence of advanced language models like ChatGPT. Specifically, the paper focuses on the legal challenges associated with the use of Generative AI, including issues surrounding intellectual property rights, data privacy, fair competition, and academic integrity.
The key areas of concern include potential infringements of intellectual property rights due to content generated by AI systems, the implications for data privacy given the large datasets utilized by Generative AI, and the impact on fair competition in various markets due to deceptive practices enabled by AI-generated content. By analyzing these legal issues and challenges, the aim of this research is to raise awareness and provide insights into the appropriate legal frameworks and policies needed to address them. It could be said that a balanced approach is crucial to protect intellectual property rights, ensure data privacy, foster fair competition, and maintaining academic integrity in the age of AI and Generative AI technologies.
Keywords
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References
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Copeland, Jack (ed.) (2004). 'The Essential Turing: Seminal Writings in Computing, Logic, Philosophy, Artificial Intelligence, and Artificial Life: Plus the Secrets of Enigma'. Oxford University Press, and Copeland, Jack, (1997) 'The Church-Turing Thesis' Stanford Encyclopedia of Philosophy [Online) https://plato.stanford.edu/entries/church-turing/ accessed 24 April 2023.
Turing, A.M. (1950) Computing Machinery and Intelligence. Mind, 59, 433-460. DOI: https://doi.org/10.1093/mind/LIX.236.433
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ENLETS, 'Final Synthetic Reality: Deep fakes Impact on Police Work' (2021) [PDF] Available at:
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(3) In the case of a literary, dramatic, musical or artistic work which is computer-generated, the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken.
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See Attia, A. (2021). Reflections of Artificial Intelligence on Unemployment and the Future of Work: Increased Displacement Rate or Increased Productivity?. Journal of Law and Emerging Technologies, 1(1), 159–248. https://doi.org/10.54873/jolets.v1i1.13 DOI: https://doi.org/10.54873/jolets.v1i1.13
Alexander, M., 'Are You Hung Up on That Career Path You Didn't Choose?' (2023) Harvard Business Review, March https://hbr.org/2023/03/are-you-hung-up-on-that-career-path-you-didnt-choose accessed 26 April 2023.
QAA, 'Academic Integrity Network Meeting' (16 March 2023) https://www.qaa.ac.uk/docs/qaa/members/academic-integrity-network-meeting-march-2023.pdf?sfvrsn=758ab81_6 accessed 26 April 2023.
Zhavoronkov, A. and GPT, 'Rapamycin in the context of Pascal's Wager: generative pre-trained transformer perspective' (2022) 9 Oncoscience 82-84 https://doi.org/10.18632/oncoscience.571 accessed 26 April 2023; GPT, Osmanovic Thunström, A. & Steingrimsson, S., 'Deep Reinforcement Learning for Real-Time Adaptive Traffic Signal Control: A Realistic Simulation Study' (2022) Preprint at HAL https://hal.science/hal-03701250 accessed 26 April 2023
Texas Tech University McCabe Academic Integrity Survey Report June 2010 | Office of Planning and Assessment Devin DuPree and Sabrina Sattler | (June 2010)