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AI Gone Rogue: The Dangers Of Deepfake Technology In The Digital Age


Vikas Kabeer, LLM, MVN University, Palwal


ABSTRACT


Deepfake technology, which combines artificial intelligence (AI) and machine learning is an emerging technology that allows the creation of hyper realistic, fabricated audio, video and image content in the digital age. Deepfakes have the ability to provide creative opportunities in the entertainment and virtual reality fields, but they also pose enormous threats to political stability, personal privacy and economic security. This paper examines the perils of deepfake technology, such as privacy invasion, manipulation and economic fraud, and explores the evolution and mechanics of this technology in depth. The paper also conducts a comprehensive analysis of current and proposed regulatory responses that are intended to moderate these risks. It also tackles the forthright issues of biased algorithm and accountability in terms of the social effect of biased deepfakes and ethic responsibilities of the AI creator. In an effort to contribute to the debate on how to mitigate the risks of AI driven media manipulation this paper, investigates the multifaceted risks of deepfakes and proposes ways to regulate and publicize about deepfake technology.


Keywords: Deepfake Technology, Artificial Intelligence (AI), AI Bias and Accountability, Digital Privacy.



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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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​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.

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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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