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伴随着多重社会、环境和经济影响，包括决策过程不透明、歧视加剧、不平等扩大、模型开发与应用中的能耗及温室气体排放上升，以及经济权力日益集中。本文通过考量可持续性的多维度特性，为落实“可持续人工智能”的全局性视角迈出实质性步骤。研究提出了SCAIS框架（人工智能系统可持续性标准与指标体系），该框架基于批判性文献综述与专家研讨会的成果，包含19项可持续人工智能标准及67项具体指标。这一跨学科方法提供了独特的整体视角，有助于促进和构建可持续人工智能领域的系统性讨论；同时，该框架为制定规范与开发工具奠定了基础，从而支持人工智能系统的有意识开发与应用。