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Weaponised Intelligence - From Deepfakes To Smart Glasses: AI-Enabled Gender Violence And The Crisis Of Legal Protection For Women In India

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Dimple A. Parmar, Marwadi University


ABSTRACT


Artificial Intelligence was developed by human intelligence to make life simple and efficient, but today it is also being weaponised against women. This paper explains three weapons of AI-enabled gender violence: deepfakes, voice cloning and sextortion, and smart glasses such as the Ray- Ban Meta glasses. These tools are cheap, easy to use and anonymous, and they can harm a woman without her knowledge and without anyone touching her. The paper then examines whether Indian law protects women from this harm. It finds that although Articles 14, 15 and 21 of the Constitution promise equality, dignity and privacy, the IT Act, 2000, the Bharatiya Nyaya Sanhita, 2023, the Digital Personal Data Protection Act, 2023 and the IT Amendment Rules, 2026 are fragmented, focus on obscenity rather than consent, and regulate platforms rather than punish perpetrators. The paper calls these problems the Authenticity Paradox and remedial fragmentation. It compares the laws of the United Kingdom, the European Union, the United States and Australia, and suggests a way forward for India: a consent-based offence, regulation of AI tools and smart glasses, and a single authority where victims can seek help.


Keywords: Deepfakes, Non-Consensual Intimate Imagery, Voice Cloning, Sextortion, Smart Glasses, Consent, Right to Privacy.



Indian Journal of Law and Legal Research

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Abbreviation: IJLLR

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ISSN: 2582-8878

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Website: www.ijllr.com

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Accessibility: Open Access

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License: Creative Commons 4.0

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Submit Manuscript: Click here

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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:

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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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