Using AI to achieve renewable goals like stabilising grid connections and improving water storage is becoming more common. But its contribution towards fossil fuel pollution outweighs the results of these practices.
A study has become the first to model AI’s climate impact across the whole power sector.
Researchers tested the potential for AI to boost clean power generation along with projecting how it can help produce coal, oil and gas. In 64 scenarios they found net yearly carbon pollution rose by 0.47-1.8 gigatonnes, which is around 1-5% of the energy sector’s annual emissions.
Net emissions only fell in scenarios where the technology did not increase productivity in the fossil fuel sector.
The study found that if clean and dirty energy facilities were to adopt AI at similar rates, the productivity gains for renewables would have to surpass fossil fuels gains by more than four times for emissions to break even.
The researchers say that AI is a bidirectional productivity amplifier, meaning that the same capabilities that optimise renewables generation and efficiency also sustain and expand the economic viability of fossil fuels.
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