Experts argue that the carbon intensity of the energy source used by tech firms is a key factor in determining the environmental cost of AI. However, the increasing demand for renewable energy by tech firms is pushing other users towards fossil fuels. The International Energy Agency (IEA) has warned that the world may only double its renewable energy by 2030 under current government plans, despite the rapid growth in renewable energy capacity. The solution may lie in tech companies investing more in building new renewable energy projects to meet their growing power demand. However, the continuous demand for electricity by AI and the industry's unique nature could lead to increased energy costs and more fossil fuel consumption.
Key takeaways:
- AI technology is threatening tech companies' environmental targets, with Google admitting that datacentres, a key piece of AI infrastructure, have increased its greenhouse gas emissions by 48% since 2019.
- Datacentres, which are crucial for operating AI models, require large amounts of electricity, contributing to CO2 emissions. They are expected to use 4.5% of global energy generation by 2030.
- While tech firms are investing in renewable energy contracts to meet their environmental goals, there are concerns that there is not enough clean energy to meet the increasing demand, pushing other energy users into fossil fuels.
- Despite breakthroughs in AI technology that allow for more efficient use of electricity, the phenomenon known as “Jevons’ paradox” suggests that improvements in efficiency may lead to increased consumption, as the same amount of electricity is used to create more advanced AI systems.