从软件工程角度提出可持续AI系统的研究路线
Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
- 结合软件工程方法，构建绿色AI系统开发框架
- 识别出能源评估、基准测试等六大核心挑战
- 适合关注碳足迹与可持续性的研发团队参考
人工智能系统环境影响日益加剧，软件工程在开发可持续解决方案中扮演关键角色。由欧洲原子与分子计算中心（CECAM）和洛伦兹中心资助的「以软件工程推动AI绿色化」研讨会（第1358号，2025年）于2025年2月3日至7日在瑞士洛桑举行，汇聚了29位来自产业界与学术界的参与者，涵盖实践者与研究者。通过主旨报告、快速演讲与协作讨论，与会者共同识别并优先排序了该领域的关键挑战，包括能源评估与标准化、基准测试实践、可持续架构设计、运行时自适应、实证方法论及教育培养。本报告呈现了由此衍生的研究议程，明确了开放性研究方向与实践建议，旨在推动基于软件工程原则的环境友好型AI系统发展。
原文摘要 · Abstract (English)
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.
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