A robust methodology for long-term sustainability evaluation of Machine Learning models

ArXi:2511.08120v2 Announce Type: replace Sustainability and efficiency have become essential considerations in the development and deployment of Artificial Intelligence systems, but existing regulatory practices for Green AI still lack standardized, model-agnostic evaluation protocols. Recently, sustainability auditing pipelines for ML and usual practices by researchers show three main pitfalls: 1) they disproportionally emphasize epoch/batch learning settings, 2) they do not formally model the long-term sustainability cost of adapting and re.