Select Your Preferred Language

Please choose your language to continue.

AI has an environmental problem | Current Affairs | Vision IAS

Daily News Summary

Get concise and efficient summaries of key articles from prominent newspapers. Our daily news digest ensures quick reading and easy understanding, helping you stay informed about important events and developments without spending hours going through full articles. Perfect for focused and timely updates.

News Summary

Sun Mon Tue Wed Thu Fri Sat

AI has an environmental problem

2 min read

Artificial Intelligence: Transformation and Environmental Concerns

Artificial Intelligence (AI) has become integral to modern life, significantly influencing work, lifestyle, and business practices. Defined as technologies that emulate human cognition and decision-making, AI has advanced swiftly due to improved computing power and increased data availability.

Economic Impact and Developments

  • The global AI market is valued at $200 billion, with projections to contribute up to $15.7 trillion to the global economy by 2030.
  • The Stargate Project in the U.S. involves over $500 billion in AI infrastructure investments over four years.
  • Reliance Industries in India plans to construct the world’s largest data centre in Jamnagar, in collaboration with Nvidia.
  • India aims to build its own large language model (LLM) to compete with existing models like DeepSeek and ChatGPT.

Environmental Implications

While the economic prospects of AI are promising, its rapid expansion poses significant environmental challenges, notably:

  • Data centres, crucial for AI operations, contribute to 1% of global greenhouse gas emissions. This figure is likely to increase as electricity demand is projected to double by 2026.
  • Generative AI models require significantly more computing power, intensifying the environmental impact.
  • AI software life cycle processes like data collection and model training contribute to substantial emissions.
  • Training advanced models like GPT-3 can emit up to 552 tonnes of CO2 equivalent.

Strategies for Mitigation

Governments and businesses must integrate sustainability into AI design:

  • Invest in clean energy and transition to renewable sources.
  • Locate data centres in areas rich in renewable resources.
  • Optimize energy grids using AI, such as Google's DeepMind improving wind energy forecasting.
  • Develop energy-efficient hardware and maintain regular equipment checks to reduce emissions.
  • Create smaller, domain-specific models to decrease processing power needs.
  • Adapt pre-trained models to new tasks instead of starting from scratch.

The Importance of Transparency

Transparency is crucial for sustainability efforts:

  • Organizations should measure and disclose AI systems' environmental impact.
  • Establish standardized frameworks to track and compare emissions across the industry.

Incorporating sustainability into AI's ecosystem design is essential to balancing innovation with environmental stewardship, ensuring AI's transformative potential does not compromise the planet's future.

  • Tags :
  • Artificial Intelligence (AI)
Subscribe for Premium Features

Quick Start

Use our Quick Start guide to learn about everything this platform can do for you.
Get Started