Environmental Impacts of AI
Context
The sudden rush in the use of AI has raised considerable environmental issues by contributing significantly to carbon footprints, in terms of greenhouse gas (GHG) emissions, energy consumption, and e-waste generation.
Relevance:
GS-03 (Conservation)
Environmental Impacts of AI
- Rising Carbon Emissions
- AI models require massive computational power, leading to high electricity consumption.
- AI-related emissions account for 1% of global GHG emissions, expected to double by 2026.
- Soaring Energy Demands
- Advanced AI models consume 10–100 times more power than earlier versions.
- Growing E-Waste Crisis
- AI hardware, particularly GPUs and processors, contributes to substantial e-waste, including hazardous materials like lead and mercury.
- Projection: By 2030, AI-driven industries could generate 5 million metric tons of e-waste globally.
- Natural Resource Depletion
-
- AI chips require rare earth elements (REEs), leading to destructive mining activities.
- AI data centers consume large volumes of water for cooling, impacting water availability in vulnerable regions.
Global Actions to Curb AI’s Environmental Impact
- Climate Agreements & Global Summits
- COP29 (2024, Baku, Azerbaijan): The International Telecommunication Union (ITU) stressed the need for sustainable AI practices.
- AI Action Summit 2025: The UN Secretary-General urged nations to design low-energy AI algorithms and integrate AI into smart grids.
- Regulatory Measures by Countries
- EU AI Act (2024): Enforces energy efficiency norms for AI-based industries.
- US Artificial Intelligence Environmental Impacts Act (2024): Focuses on reducing AI-related emissions and promoting green AI practices.
- Ethical AI Frameworks
- UNESCO’s AI Ethics Guidelines (2024): Adopted by 190+ countries, encouraging AI development with reduced carbon footprint and energy consumption.
- UNEP’s Sustainability Roadmap
- The United Nations Environment Programme (UNEP) has proposed key strategies to limit AI’s ecological damage, including:
Way Forward
- Sustainable AI Development: Governments and industries must focus on green AI models that minimize energy use and emissions.
- Renewable Energy Integration: AI data centers should shift towards solar, wind, and other green energy sources.
- Public Awareness & Industry Accountability: Tech companies must be held accountable for the environmental consequences of AI, ensuring transparency and compliance with sustainability standards.
Related Posts
