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Research Paper Volume 8 Issue 1 1087 - 1099 February 7, 2025

Protecting Artificial Intelligence through Patent and Copyright Laws: An Ethico-Legal Dilemma

Lead author · Corresponding
Gunjan Deshpande
Ph.D. Candidate at Maharashtra National Law University, Auranagabd, India
Co-author
Priya Gondhalekar
Ph.D. Candidate at Maharashtra National Law University, Auranagabd, India
View PDF Full text DOIhttps://doij.org/10.10000/IJLMH.119003
Abstract

Artificial Intelligence (AI) is an autonomous system that imitates human intelligence and mimics human actions. This system works mostly without any human intervention. The advancement in AI has reached such a height that automated content generation is not fiction but a commercial reality. The legislative intent behind the IPRs laws is to foster creativity and innovation. Traditionally, IPRs are given to the ideas expressed through human creativity. The introduction of AI in the copyright, patent, and designs has changed the dimensions of the protection of IPRs. While discussing IP rights and AI the most important question that arises is whether AI creativity needs to be incentivized separately. The authors will discuss the ethico-legal dilemma surrounding the ownership (including authorship for copyright and inventorship for innovation) of AI and the legal liability (including tortious) attached to it. The authors argue that the future of AI will be determined by the legal and ethical dimensions governing the working of AI. The aspect includes IP ownership, incentivization, and liability of IP ownership and ethical dilemmas governing the same. Considering this, and the United Nations Educational, Scientific, and Cultural Organization’s Ethics of Artificial Intelligence (UNESCO), the authors will analyse and put a way forward by balancing the rights of AI and human creativity.

Type
Research Paper
Information
International Journal of Law Management and Humanities, Volume 8, Issue 1, Page 1087 - 1099
DOI: https://doij.org/10.10000/IJLMH.119003
Creative Commons
CC BY-NC 4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.
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Copyright © IJLMH 2026
Disclaimer
The views and opinions expressed in this manuscript are those of the author(s) alone and do not reflect the views, policies, or position of the Journal.

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