Why AI’s present and future bring some serious environmental concerns
- July 26, 2024
- Posted by: OptimizeIAS Team
- Category: DPN Topics
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Why AI’s present and future bring some serious environmental concerns
Sub: Sci
Sec: AWARENESS IN IT and computer
Context:
- Google reported a 13% increase in emissions in 2023 compared to 2022.
- The rise was mainly due to increased electricity consumption in data centres and supply chains.
- Data centres used 17% more electricity in 2023, largely due to the growing deployment of AI tools.
Energy Consumption by AI:
- AI tools, such as those used in chatbots, consume significantly more energy than regular Google searches.
- Studies show that an AI query can use 10 to 33 times more energy than a typical search, with image-based AI searches consuming even more.
- Reasons for Higher Emissions
- AI models process and sift through more data, requiring more electrical signals and generating more heat.
- The increased heat demands more powerful cooling systems in data centres, further increasing energy consumption.
Global Impact of AI on Energy Consumption:
- The widespread use of AI is expected to sharply increase global energy consumption.
- Data centres currently account for 1-1.3% of global electricity demand, potentially rising to 1.5-3% by 2026.
- In countries like Ireland and the United States, data centres already consume significant portions of national electricity demand.
Concerns for India:
- In India, the environmental impact of AI and data centres is expected to grow.
- The increased demand for water resources for cooling data centres, noting a lack of adequate data on water consumption.
- The need for efficient planning and measures to minimize the environmental impact as AI and data centres expand in India.
Potential Positive Impact of AI:
- Some estimates suggest that large-scale AI deployment could reduce global emissions by 5-10% by 2030.
- AI can help monitor and optimize existing processes to reduce wastage and inefficiencies, potentially generating significant economic value.