Towards Green AI: Current status and future research

TL;DR

This paper reviews the current state of Green AI, emphasizing the importance of sustainable practices in AI development, and proposes a life-cycle approach to assess and reduce environmental impact, advocating for AI to help mitigate its own ecological footprint.

Contribution

It introduces a comprehensive life-cycle-based framework for evaluating and promoting Green AI, highlighting the need for further research and adoption of sustainable AI practices.

Findings

Estimated carbon footprint of compute hardware

Identified need for methods to facilitate Green AI adoption

Proposed AI to mitigate its own environmental challenges (AI4greenAI)

Abstract

The immense technological progress in artificial intelligence research and applications is increasingly drawing attention to the environmental sustainability of such systems, a field that has been termed Green AI. With this contribution we aim to broaden the discourse on Green AI by investigating the current status of approaches to both environmental assessment and ecodesign of AI systems. We propose a life-cycle-based system thinking approach that accounts for the four key elements of these software-hardware-systems: model, data, server, and cloud. We conduct an exemplary estimation of the carbon footprint of relevant compute hardware and highlight the need to further investigate methods for Green AI and ways to facilitate wide-spread adoption of its principles. We envision that AI could be leveraged to mitigate its own environmental challenges, which we denote as AI4greenAI.