Climate Implications of Diffusion-based Generative Visual AI Systems and their Mass Adoption

TL;DR

This paper examines how the widespread adoption of diffusion-based visual AI systems could significantly impact global energy consumption and climate change, highlighting the need for careful consideration and solutions.

Contribution

It provides an analysis of the growth, usage patterns, and climate implications of diffusion-based AI art systems, emphasizing their potential environmental impact.

Findings

Mass adoption of diffusion AI art tools may substantially increase energy use

Current data on AI system energy consumption is limited and hard to access

The paper discusses potential solutions and future research directions

Abstract

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.