A high-wire balancing act? Technology advancements vs environmental impact

Two of the ‘big ticket’ items on many corporate agendas currently are leveraging technology advancements such as Gen AI alongside environmental responsibility and an aspiration for net zero. But are these aspirations paradoxical and if so, what can we do to minimize impacts?

Artificial Intelligence (AI) is hailed as a game-changer but beneath its transformative potential, lies a pressing concern: its environmental impact. The development, maintenance, and disposal of AI technology all come with a carbon footprint.

I asked Copilot, Microsoft's conversational chat interface - How does AI advancements impact the environment?

It gave me both sides of the argument:

Negative Environmental Impact of AI:

• Energy Consumption: The rapid growth of AI, especially generative AI systems, has led to increased energy consumption. For instance, ChatGPT, created by OpenAI, already consumes as much energy as 33,000 homes.
• Water Usage: Generative AI systems require substantial amounts of fresh water for cooling their processors and generating electricity. Data centers supporting large AI models can strain local water resources significantly.
• Electronic Waste: At the end of their lifecycle, AI technologies contribute to electronic waste, containing hazardous materials that can pollute the environment.

Positive Role of AI in Addressing Climate Change:

• Predictive Models: AI systems can predict weather patterns, track icebergs, and identify pollution sources, aiding climate research and disaster management.
• Agriculture Optimization: AI helps improve agriculture practices, optimize resource allocation, and reduce environmental impact.
• Environmental Governance: By assisting research and promoting effective environmental governance, AI can contribute to solving environmental challenges.

Earth.Org comments that other concerns are functions such as automated advertising which may result in greater consumption as well as increasing waste in certain sectors, such as the e-commerce industry, which has normalized the rapid and frequent delivery of goods; or the rising use of AI in agriculture which could result in the overuse of pesticides and fertilizers, contaminating the soil and water, and harming biodiversity.

Behind the scenes of AI’s brilliance lies an energy-intensive process with a staggering carbon footprint.

Training of AI models can produce about 626,000 pounds of carbon dioxide, or the equivalent of around 300 round-trip flights between New York and San Francisco – nearly 5 times the lifetime emissions of the average car.

Therefore, as businesses focus not only on their technical landscape but their EVP and Environmental reputation, they must also consider building sustainable practices and make educated decisions by considering the potential environmental effects of AI adoption. Such actions as prioritizing energy efficiency, designing more sustainable models, and rethinking data center practices.

Copilot concludes: Balancing AI’s potential with ecological responsibility is crucial for a sustainable future.