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AI And IP: Unravelling The Intellectual Property Implications Of Generative Artificial Intelligence




Rishi Pareek, National Law University, Jodhpur

Onika Arora, National Law University, Jodhpur


ABSTRACT


Generative Artificial Intelligence (AI) has transformed the landscape of creativity, produced visually striking art. Yet, alongside this remarkable progress lies a complex legal terrain where Generative AI intersects with Intellectual Property law. This paper explores legal challenges tied to the creation, ownership, and use of AI-generated content.


This paper evaluates existing legal frameworks regarding fair use, creation of derivative works, and potential intellectual property rights violations related to input data utilization. It also examines complexities surrounding ownership of content generated by generative AI, including questions of authorship and creatorship. Additionally, it highlights the need to address copyright, patent, and trademark infringement issues in the context of Generative AI.


Proposed strategies aim to enhance transparency, fairness, and ethical considerations in accessing and using training data for generative AI systems. By unravelling the complex web of IP implications, this paper provides insights for businesses navigating risks associated with Generative AI, offering a roadmap for legal compliance and protection in this rapidly evolving technological landscape.


Keywords: Generative Artificial Intelligence, Chat GPT, AI Training, Derivative Works, Ownership, Transparency, Fair Use.



Indian Journal of Law and Legal Research

Abbreviation: IJLLR

ISSN: 2582-8878

Website: www.ijllr.com

Accessibility: Open Access

License: Creative Commons 4.0

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Licensing: 

 

All research articles published in The Indian Journal of Law and Legal Research are fully open access. i.e. immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

 

Disclaimer:

The opinions expressed in this publication are those of the authors. They do not purport to reflect the opinions or views of the IJLLR or its members. The designations employed in this publication and the presentation of material therein do not imply the expression of any opinion whatsoever on the part of the IJLLR.

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