AI, Climate, and Transparency: Operationalizing and Improving the AI Act

TL;DR

Addresses the problem of AI-related climate impact and gaps in the EU AI Act's climate transparency. Applies legal and technical analysis to identify gaps, notably the exclusion of inference energy and lack of public access to disclosures. Proposes a novel interpretation to bring inference energy within the Act's scope and puts forward six policy proposals, including public disclosures and server-level energy measurement with PUE. Argues that climate reporting is a necessary first step that must be complemented by sustainability risk management, renewable energy targets, and, potentially, caps on data-center energy and water use for meaningful environmental safeguards.

Abstract

This paper critically examines the AI Act's provisions on climate-related transparency, highlighting significant gaps and challenges in its implementation. We identify key shortcomings, including the exclusion of energy consumption during AI inference, the lack of coverage for indirect greenhouse gas emissions from AI applications, and the lack of standard reporting methodology. The paper proposes a novel interpretation to bring inference-related energy use back within the Act's scope and advocates for public access to climate-related disclosures to foster market accountability and public scrutiny. Cumulative server level energy reporting is recommended as the most suitable method. We also suggests broader policy changes, including sustainability risk assessments and renewable energy targets, to better address AI's environmental impact.