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Artificial Intelligence In Climate Litigation: Bridging The Evidentiary Gap While Confronting Transnational Legal Challenges




Romil Aryan & Ritul Aryan, Vignan Institute of Law, VFSTR


ABSTRACT


The entire world is facing climate crisis and there is a rise in climate litigation. The use of artificial intelligence is also growing at the same in time in the field of environmental litigation. Artificial intelligence is helpful in environmental litigation and protecting environmental rights, but also create many legal risks. Law still has gaps to treat artificial intelligence plus transnational climate harms. This paper examines the use of artificial intelligence in climate litigation. AI is playing an important role in environmental litigation by providing evidence, predicting the risks and monitoring the implementation, but it is not free from the problem of bias opacity, exclusion, and accountability. At the same time it also has the transnational challenges of jurisdiction, liability, and fragmented law. If artificial intelligence has to be used meaningfully in environmental litigation, then going forward it is important to have right-based framework, transparency, accountability, inclusion of the vulnerable community in decision making and global regulation. Technology alone cannot ensure justice and law must regulate artificial intelligence to protect rights, and use artificial intelligence in such a manner that it progresses the cause of environmental protection rather than hindering it.



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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