Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
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arXiv
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866908476421177344 |
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| author | Cruz, Luís Fernandes, João Paulo Kirkeby, Maja H. Martínez-Fernández, Silverio Sallou, June Anwar, Hina Roque, Enrique Barba Bogner, Justus Castaño, Joel Castor, Fernando Chasmawala, Aadil Cunha, Simão Feitosa, Daniel González, Alexandra Jedlitschka, Andreas Lago, Patricia Muccini, Henry Oprescu, Ana Rani, Pooja Saraiva, João Sarro, Federica Selvan, Raghavendra Vaidhyanathan, Karthik Verdecchia, Roberto Yamshchikov, Ivan P. |
| author_facet | Cruz, Luís Fernandes, João Paulo Kirkeby, Maja H. Martínez-Fernández, Silverio Sallou, June Anwar, Hina Roque, Enrique Barba Bogner, Justus Castaño, Joel Castor, Fernando Chasmawala, Aadil Cunha, Simão Feitosa, Daniel González, Alexandra Jedlitschka, Andreas Lago, Patricia Muccini, Henry Oprescu, Ana Rani, Pooja Saraiva, João Sarro, Federica Selvan, Raghavendra Vaidhyanathan, Karthik Verdecchia, Roberto Yamshchikov, Ivan P. |
| contents | 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 Européen de Calcul Atomique et Moléculaire 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_01774 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices Cruz, Luís Fernandes, João Paulo Kirkeby, Maja H. Martínez-Fernández, Silverio Sallou, June Anwar, Hina Roque, Enrique Barba Bogner, Justus Castaño, Joel Castor, Fernando Chasmawala, Aadil Cunha, Simão Feitosa, Daniel González, Alexandra Jedlitschka, Andreas Lago, Patricia Muccini, Henry Oprescu, Ana Rani, Pooja Saraiva, João Sarro, Federica Selvan, Raghavendra Vaidhyanathan, Karthik Verdecchia, Roberto Yamshchikov, Ivan P. Software Engineering Artificial Intelligence 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 Européen de Calcul Atomique et Moléculaire 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. |
| title | Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2506.01774 |