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Artificial Intelligence And Environmental Accountability: A Legal Analysis Of Energy Use, Carbon Debt And Ecological Governance




Anushka Singh, Christ (Deemed to be University), Delhi NCR


ABSTRACT


Artificial Intelligence (AI), the most pivotal revolution of the 21st century, presents a severe environmental and energy crisis. This book chapter explores, in various stages, the ecological impacts led by AI across its lifecycle- mineral extraction, use, and waste disposal. The utilisation of rare earth minerals in AI hardware exposes ecosystems to radioactive by- products, soil contamination, and dangerous rays. Big data centres, the foundation of AI, exert pressures on biodiversity, water, and air through land conversion, overwater withdrawal for cooling, and fossil-fuel-powered electricity usage. These operations result in carbon debt, the long-term climate policy implications of which are unknown. Case studies of Congo's cobalt mines, Oregon and Ireland's data centres, and GPT-3's carbon debt document the extent to which biodiversity and human settlements are displaced or threatened by uncontrolled AI infrastructural growth. Moreover, manufacturing and usage of electronic equipment lead to massive e-waste production, which is harmful to soil and water quality. Against this backdrop, the chapter makes a case for climate-sensitive governing frameworks, carbon-sensitive AI innovation, and deployment of clean energy technologies. AI remains a threat to the larger landscape of environmental sustainability; technological development needs to be in check for the conservation and maintenance of the ecological balance.


Keywords: Artificial Intelligence, Data Centres, Carbon Debt, Loss of Biodiversity, Water Stress, Air Pollution, Climate Governance, Sustainable AI.



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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