[2603.00068] The Global Landscape of Environmental AI Regulation: From the Cost of Reasoning to a Right to Green AI

Computer Science > Computers and Society arXiv:2603.00068 (cs) [Submitted on 10 Feb 2026] Title:The Global Landscape of Environmental AI Regulation: From the Cost of Reasoning to a Right to Green AI Authors:Kai Ebert, Boris Gamazaychikov, Philipp Hacker, Sasha Luccioni View a PDF of the paper titled The Global Landscape of Environmental AI Regulation: From the Cost of Reasoning to a Right to Green AI, by Kai Ebert and 3 other authors View PDF HTML (experimental) Abstract:Artificial intelligence (AI) systems impose substantial and growing environmental costs, yet transparency about these impacts has declined even as their deployment has accelerated. This paper makes three contributions. First, we collate empirical evidence that generative Web search and reasoning models - which have proliferated in 2025 - come with much higher cumulative environmental impacts than previous generations of AI approaches. Second, we map the global regulatory landscape across eleven jurisdictions and find that the manner in which environmental governance operates (predominantly at the facility-level rather than the model-level, with a focus on training rather than inference, with limited AI-specific energy disclosure requirements outside the EU) limits its applicability. Third, to address this, we propose a three-pronged policy response: mandatory model-level transparency that covers inference consumption, benchmarks, and compute locations; user rights to opt out of unnecessary generative AI in...