Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
- URL: http://arxiv.org/abs/2506.01774v2
- Date: Tue, 03 Jun 2025 08:44:31 GMT
- Title: Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
- Authors: Luís Cruz, João Paulo Fernandes, Maja H. Kirkeby, Silverio Martínez-Fernández, June Sallou, Hina Anwar, Enrique Barba Roque, Justus Bogner, Joel Castaño, Fernando Castor, Aadil Chasmawala, Simão Cunha, Daniel Feitosa, Alexandra González, Andreas Jedlitschka, Patricia Lago, Henry Muccini, Ana Oprescu, Pooja Rani, João Saraiva, Federica Sarro, Raghavendra Selvan, Karthik Vaidhyanathan, Roberto Verdecchia, Ivan P. Yamshchikov,
- Abstract summary: The "Greening AI with Software Engineering" CECAM-Lorentz workshop was held February 3-7, 2025 in Lausanne, Switzerland.<n>This report presents a research agenda emerging from the workshop.<n>It outlines open research directions and practical recommendations to guide the development of environmentally sustainable AI-enabled systems.
- Score: 70.24403396375277
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The environmental impact of Artificial Intelligence (AI)-enabled systems is increasing rapidly, and software engineering plays a critical role in developing sustainable solutions. The "Greening AI with Software Engineering" CECAM-Lorentz workshop (no. 1358, 2025) funded by the Centre Europ\'een de Calcul Atomique et Mol\'eculaire and the Lorentz Center, provided an interdisciplinary forum for 29 participants, from practitioners to academics, to share knowledge, ideas, practices, and current results dedicated to advancing green software and AI research. The workshop was held February 3-7, 2025, in Lausanne, Switzerland. Through keynotes, flash talks, and collaborative discussions, participants identified and prioritized key challenges for the field. These included energy assessment and standardization, benchmarking practices, sustainability-aware architectures, runtime adaptation, empirical methodologies, and education. This report presents a research agenda emerging from the workshop, outlining open research directions and practical recommendations to guide the development of environmentally sustainable AI-enabled systems rooted in software engineering principles.
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