Context:
Artificial Intelligence (AI) is emerging as a powerful tool to address climate change by improving energy efficiency, reducing emissions, and advancing environmental monitoring and sustainability.
How AI Contributes to Climate Action
Climate Forecasting & Disaster Preparedness
- AI strengthens the accuracy of climate models and extreme weather predictions, enabling early alerts for floods, cyclones, and heatwaves.
- Example: Google’s AI-powered flood forecasting system operational in India and Bangladesh enhances community preparedness.
Energy Sector Transformation
- AI manages smart grids for real-time balancing of renewable energy sources and demand.
- Optimizes integration of solar and wind energy, reducing dependence on fossil fuels.
Sustainable Resource Management
- AI supports precision agriculture by monitoring soil moisture, irrigation patterns, and pest outbreaks, reducing input wastage.
- Example: Project Drawdown uses AI for regenerative agriculture to improve carbon sequestration.
Biodiversity Protection
- AI applications like Google’s coral reef monitoring detect coral bleaching early through underwater image analysis, aiding marine ecosystem conservation.
Waste & Recycling Efficiency
- AI-driven robotic waste sorters significantly improve recycling accuracy—over 90% efficiency in segregation.
Disaster Monitoring
- Combined with IoT, AI enables live tracking of wildfires, deforestation, and pollution levels.
- Example: IBM’s Green Horizons in China uses AI to forecast and manage air quality.
Emission Reduction
- Smart Transportation: Google Maps uses AI for fuel-efficient routing.
- Industrial Use: Predictive maintenance and energy-efficient AI systems help reduce carbon emissions in manufacturing.
Key Challenges
High Energy Consumption
- Training large AI models generates significant carbon emissions—comparable to the lifetime emissions of five vehicles.
- AI data centers currently consume 1–1.3% of global electricity, projected to rise to 2–3% by 2026.
Water Stress
- Cooling systems in AI-powered data centers require large volumes of water, raising concerns in water-scarce regions.
Ethical & Social Concerns
- Biased datasets may result in unfair outcomes in climate policy.
- Automation can displace workers in sectors like agriculture and waste management.
Digital Inequality
- Unequal access to AI and computing infrastructure could exclude developing countries from climate-tech benefits, widening the global digital divide.
Global & National Policy Frameworks
- India’s Responsible AI Framework: Drafted by MeitY to ensure that AI is inclusive, ethical, and aligned with sustainable development goals.
- EU AI Act (2024): Categorizes AI systems based on risk and mandates environmental safeguards, transparency, and human accountability.
- UNESCO AI Ethics Recommendation (2021): The first global standard advocating for energy-efficient, equitable, and eco-conscious AI development.
Way Forward
- Promote Green AI:
- Use low-energy models (e.g., model pruning, quantization) to reduce AI’s carbon footprint.
- Mandate Carbon Disclosure:
- Require AI developers to publish carbon footprint data as part of ESG reporting.
- Green Infrastructure:
- Shift AI data centers to renewable energy sources.
- Collaborative Innovation:
- Facilitate partnerships between climate scientists, tech experts, and ecologists.
- Environmental Regulation:
- Introduce Environmental Impact Assessments (EIA) and carbon scoring for large-scale AI projects.