Artificial intelligence (AI) systems carry risks and opportunities for environmental sustainability. The use of AI systems, for instance, can result in both software-related (direct) as well as application-context-related (indirect) resource use. Stakeholders are expected to play a role in understanding and steering the environmental effects of AI systems. However, the processes and anticipated outcomes of stakeholder involvement in AI system lifecycles are not clear. We provide a non-exhaustive scoping review of six software and AI sustainability frameworks with respect to their recognition of environmental sustainability and the role of stakeholders in dealing with environmental sustainability. This serves to develop recommendations for future research on how stakeholder involvement can help firms and institutions design and use more sustainable AI systems.
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Kunkel, S., Schmelzle F., Niehoff S., Beier G. (2023). More sustainable artificial intelligence systems through stakeholder involvement? GAIA-Ecological Perspectives for Science and Society 2023 (32):64–70. https://doi.org/10.14512/gaia.32.S1.10 
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