The increased use of AI systems is associated with multi-faceted societal, environmental, and economic consequences. These include non-transparent decision-making processes, discrimination, increasing inequalities, rising energy consumption and greenhouse gas emissions in AI model development and application, and an increasing concentration of economic power. By considering the multi-dimensionality of sustainability, this paper takes steps towards substantiating the call for an overarching perspective on "sustainable AI". It presents the SCAIS Framework (Sustainability Criteria and Indicators for Artificial Intelligence Systems) which contains a set 19 sustainability criteria for sustainable AI and 67 indicators that is based on the results of a critical review and expert workshops. This interdisciplinary approach contributes a unique holistic perspective to facilitate and structure the discourse on sustainable AI. Further, it provides a concrete framework that lays the foundation for developing standards and tools to support the conscious development and application of AI systems.

翻译：人工智能系统的广泛应用引发了多方面的社会、环境及经济后果，包括决策过程不透明、歧视现象加剧、不平等扩大、人工智能模型开发与应用中能耗及温室气体排放增加，以及经济权力集中。本文通过考量可持续性的多重维度，为倡导"可持续人工智能"的总体视角提供了具体推进步骤。基于批判性综述与专家研讨会的成果，本文提出了人工智能系统可持续性标准与指标体系（SCAIS Framework），包含19项可持续人工智能标准及67项指标。这一跨学科方法以独特的整体性视角促进并规范了可持续人工智能领域的讨论，同时为制定支持人工智能系统有意开发与应用的标准及工具奠定了具体框架基础。