Critically examine the environmental impact of Artificial Intelligence, including energy, water, and carbon footprints. Discuss sustainable practices and policy interventions that can mitigate these impacts in India.

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PocketIAS · Accepted Answer

Artificial Intelligence (AI) has transformative potential but entails substantial environmental costs. Training large AI models consumes vast energy, largely from fossil fuels, contributing to carbon emissions. For instance, a 2019 study estimated that training a single large NLP model can emit 626,000 pounds of CO₂, equivalent to the lifetime emissions of five cars. Data centres supporting AI also require millions of litres of water annually for cooling, straining resources in water-stressed Indian regions such as Rajasthan and Tamil Nadu.

Energy Footprint: High electricity demand, largely from non-renewable sources, increases India’s overall carbon load.
Water Footprint: Cooling-intensive operations can exacerbate local water scarcity.
Carbon Footprint: AI development and deployment add to greenhouse gas emissions, challenging India’s net-zero commitments.

Sustainable practices can mitigate these impacts: optimising algorithms to reduce computational load, using energy-efficient hardware, and shifting to renewable-powered data centres. Policy interventions include MeitY’s Green Data Centre guidelines, National Mission on Transformative Mobility and Battery Storage promoting renewable integration, and incentives for carbon offsets. Case studies, such as Microsoft India’s AI for Earth program, demonstrate AI integration with environmental sustainability.

Balancing AI adoption with ecological sustainability is crucial. Efficient computing, renewable energy adoption, and policy oversight can ensure India harnesses AI benefits while limiting energy, water, and carbon footprints, aligning technological growth with climate objectives.

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