Climate Implications of Diffusion-based Generative Visual AI Systems and their Mass Adoption
This highlights a climate problem for AI developers and policymakers, but it is incremental as it extends known concerns from other digital technologies to AI art systems.
The paper tackles the climate impact of diffusion-based generative visual AI systems by estimating their energy consumption from mass adoption, showing they potentially contribute considerably to global energy use.
Climate implications of rapidly developing digital technologies, such as blockchains and the associated crypto mining and NFT minting, have been well documented and their massive GPU energy use has been identified as a cause for concern. However, we postulate that due to their more mainstream consumer appeal, the GPU use of text-prompt based diffusion AI art systems also requires thoughtful considerations. Given the recent explosion in the number of highly sophisticated generative art systems and their rapid adoption by consumers and creative professionals, the impact of these systems on the climate needs to be carefully considered. In this work, we report on the growth of diffusion-based visual AI systems, their patterns of use, growth and the implications on the climate. Our estimates show that the mass adoption of these tools potentially contributes considerably to global energy consumption. We end this paper with our thoughts on solutions and future areas of inquiry as well as associated difficulties, including the lack of publicly available data.