  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.
