Case Study

The Carbon Footprint of AI


Dive deep into the environmental impact of AI and discover actionable strategies to enhance AIs sustainability.

The rise of artificial intelligence (AI) has risen exponentially in recent years. It has the potential to revolutionise various industries and overall make life easier for many people. Despite this, AI emerges as a solution and a challenge when it comes to climate change and sustainable practices. 

This blog post will be exploring the sustainability of AI and discussing actions businesses must consider if they are wanting to implement AI into their daily operations. 

Artificial Intelligence and its potential:

As stated by a multitude of sources, AI has been cited as a potential tool for combating climate change. AI has the potential to revolutionise various sectors and reduce carbon emissions from a variety of business sectors.

Examples of this include: 

  • AI self-driving cars could reduce carbon emissions since they will use the most efficient routes. 
  • AI can also create more sustainable agriculture as it can minimise reliance on harmful pesticides and fertilisers. Providing sustainable food production.

The environmental impact of Artificial Intelligence:

While AI offers hope for environmental sustainability, its creation and deployment process itself contributes to carbon emissions.

Developing AI models and training them requires extensive computing power and energy consumption. The infrastructure and data centres that power AI operations consume significant amounts of electricity, predominantly derived from fossil fuels. 

This energy-intensive process leads to a substantial carbon footprint, raising concerns about the environmental impact of AI technologies.

Despite this, AI uses an enormous amount of energy. The MIT Technology Review reported that training just one AI model can emit more than 626,00 pounds of carbon dioxide equivalent – which is nearly five times the lifetime emissions of an average  car.

This is a cause for concern because as AI develops, they will be using bigger models to store more data to ensure accuracy of AI, meaning the carbon emissions from AI will only grow. 

Data and statistics as discussed by Dr Van Rijmenam suggest the following:

  • AI carbon emissions are equivalent to the entire airline industry emissions
  • In the next five years, energy consumption of AI will increase up to 300%

How can we make AI more sustainable and why is it important? 

AI has the potential to become revolutionary in the climate crisis. However, there needs to be sustainable practices in play from both the developers and those who implement AI into their daily life. 

  • Using only renewable energy to power AIs data centres is vital. Companies like Google are already committed to this promise. Meaning this will be reducing AIs carbon footprint. 
  • When researching, researchers should collaborate and share data and best practices, this will use less data in the development of AI and will accelerate AIs progress. 
  • Impact assess regularly on the environmental impact on AI systems. Monitor energy usage, carbon emissions and resource consumption. Use insights gained to identify areas for improvement. 
  • Businesses that utilise AI into their strategy must develop sustainability strategies to maximise environmentally friendly practices. This could include tree planting, using eco conscious transport and becoming as digital as possible. 
  • Make sustainable choices in line with the development of AI. Start your own forest and plant trees as these trees absorb carbon. This could be through Carma’s tree planting subscription or through our corporate tree planting days. 

To conclude, while AI shows great promise for improving the environment, its creation is not environmentally conscious. We must strive for a greener future, so investment into AI needs to also become as energy efficient as possible. 

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