Generative AI is impacting our future. Is this our future?
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We have a major issue with artificial intelligence and its impact on water and energy consumption levels. Hence, thought I would share some key concerning facts on ChatGPT’s massive water and energy consumption that all board directors and executives need to be aware of:
ChatGPT’s
ChatGPT’s daily power usage is nearly equal to 180,000 U.S. households, each using about 29 kWh.
A ChatGPT conversation uses about 50 cl of water.
This is very concerning given the incredible growth of genAI product innovations not only from OpenAI, but also from major technology or new entrant players like: Amazon, Anthropic, Cohere, Microsoft and Nvidia.
The AI industry’s electricity consumption is already projected to increase significantly, potentially reaching between 85-134 TWh annually by 2027.
A recent OECD policy report reported that AI’s water footprint varies significantly depending on where it is trained and hosted. For example, AI consumes 1.8 – 12 litres of water for each kWh of energy usage across Microsoft’s global data centres, with Ireland and the state of Washington being the most and least water-efficient locations, respectively.
We are going to need far more efficient genAI infrastructures to compress complex AI models, but also design more energy efficient and energy friendly technology innovations. Water is our most scarcest global resource and it is the purest source of life.
Fresh water only makes up 2.5% of the world’s total volume, and more than half of that is ice. Agriculture uses 70% of what’s actually usable. By 2050, two-thirds of the world’s population is expected to suffer from water scarcity, which will affect all aspects of people’s lives.
Government leaders must get a firmer grip on these realities and risks, as well as Board Directors and CEO’s must put more pressure on technology titans to act more responsibly and ethically on sustainability matters. For more OECD insights read this newsletter as it reinforces the general public must get more involved on AI policy matters.
Another article I wrote on this same topic can be found below:
