AI Boom Raises Environmental Concerns: Are Carbon Taxes the Answer?

Is AI Going Green? The Hidden Environmental Cost of Artificial Intelligence.. Saurabh Rai, CEO of Arahas discusses the hidden environmental costs of Artificial Intelligence (AI).

Aanchal Ghatak
New Update
Hidden Environmental Cost of Artificial Intelligence


A new white paper by Saurabh Rai, CEO of Arahas, dives into the hidden environmental costs of Artificial Intelligence (AI). While AI is revolutionizing industries, its energy demands and carbon footprint are cause for concern.

The report highlights the high energy consumption of training complex AI models, particularly those using image generation. Hugging Face and Carnegie Mellon University's research reveals that a small AI project can consume enough electricity to release significant amounts of carbon dioxide, equivalent to several trees working for a year to absorb.

The paper uses NVIDIA's H100 GPUs as an example. These powerful processors are crucial for AI tasks but consume a lot of power. With projected sales of millions in 2024, the combined energy usage is comparable to entire countries.

Energy Consumption Challenges in AI and GPU Technologies

  • NVIDIA's H100 GPUs are estimated to use up to 700W each. If sales projections of 2 million units in 2024 are met, the total annual power consumption could reach 13,091.82 GWh by late 2024. This amount equals the electricity consumption of entire countries like Georgia, Lithuania, or Guatemala.
  • Generating a single image with a sophisticated AI model can use as much electricity as charging a smartphone multiple times. When scaled up to the billions of AI operations performed globally each day, the cumulative environmental impact is significant. Studies also show varying energy consumption levels across different AI tasks, with image generation being notably high in carbon emissions.

India: A Case Study

The report explores India's booming AI sector as a case study. While India embraces AI advancements, the high energy consumption of GPUs poses a challenge. Training AI models using large language models (LLMs) and synthetic data significantly impacts energy usage.

The report estimates that the power consumed by AI operations in India could illuminate the Taj Mahal for millennia, and annual emissions could exceed the lifetime carbon footprint of millions of cars. Water scarcity is another concern, with AI data centers potentially draining resources.

Solutions and The Carbon Tax Debate

The paper proposes solutions to mitigate these impacts, including:

  • Developing energy-efficient AI chips
  • Utilizing renewable energy and innovative cooling systems in data centers
  • Designing efficient AI algorithms
  • Encouraging consumers to adopt energy-saving devices
  • Implementing policies that incentivize energy efficiency and international collaboration on sustainable technologies

The report also explores the contentious issue of carbon taxes on AI companies. While a carbon tax could incentivize sustainable practices, creating a fair and effective framework is challenging.

The Path Forward

The report emphasizes the need for balance. The global tech industry, including giants like Google, Meta, and Microsoft, must prioritize both innovation and environmental responsibility. Consumers and policymakers also have a role to play in advocating for sustainable practices.

The paper concludes that a multi-pronged approach is necessary. Carbon taxes, regulations on data center efficiency, and voluntary corporate initiatives can all contribute to a more sustainable future for AI. As AI continues to evolve, ensuring its development doesn't come at the expense of the environment is crucial.