Sustainable AI Regulation

TL;DR

This paper highlights the environmental sustainability challenges of AI and proposes a comprehensive regulatory framework, including transparency and restrictions, to align AI development with climate goals and extend to other high-emission technologies.

Contribution

It is the first to analyze how existing and proposed AI regulations can be adapted to promote environmental sustainability and offers a multi-faceted regulatory toolkit for this purpose.

Findings

AI contributes up to 3.9% of global GHG emissions.

Proposes transparency measures like disclosing AI GHG footprints.

Suggests regulatory tools including co-regulation and sustainability-by-design.

Abstract

Current proposals for AI regulation, in the EU and beyond, aim to spur AI that is trustworthy (e.g., AI Act) and accountable (e.g., AI Liability) What is missing, however, is a robust regulatory discourse and roadmap to make AI, and technology more broadly, environmentally sustainable. This paper aims to take first steps to fill this gap. The ICT sector contributes up to 3.9 percent of global greenhouse gas (GHG) emissions-more than global air travel at 2.5 percent. The carbon footprint and water consumption of AI, especially large-scale generative models like GPT-4, raise significant sustainability concerns. The paper is the first to assess how current and proposed technology regulations, including EU environmental law, the General Data Protection Regulation (GDPR), and the AI Act, could be adjusted to better account for environmental sustainability. The GDPR, for instance, could be interpreted to limit certain individual rights like the right to erasure if these rights significantly conflict with broader sustainability goals. In a second step, the paper suggests a multi-faceted approach to achieve sustainable AI regulation. It advocates for transparency mechanisms, such as disclosing the GHG footprint of AI systems, as laid out in the proposed EU AI Act. However, sustainable AI regulation must go beyond mere transparency. The paper proposes a regulatory toolkit comprising co-regulation, sustainability-by-design principles, restrictions on training data, and consumption caps, including integration into the EU Emissions Trading Scheme. Finally, the paper argues that this regulatory toolkit could serve as a blueprint for regulating other high-emission technologies and infrastructures like blockchain, Metaverse applications, and data centers. The framework aims to cohesively address the crucial dual challenges of our era: digital transformation and climate change mitigation.