B. Paech, P. Kaiser, P. Bambazek, I. Groher, N. Seyff: Exploring Generative Pretrained Transformers to support Sustainability, In Proceedings of the 31st International Working Conference on Requirement Engineering: Foundation for Software Quality (REFSQ 2025), April 7 - 10, 2025, Barcelona, Spain.
[Context] Sustainability is increasingly recognized as a critical aspect of software development. [Problem] However, identifying the potential sustainability effects of software systems during requirements engineering remains a complex and time-consuming task. [Principal idea] To address this challenge, we explore the use of Generative Pretrained Transformers (GPTs) to automate the generation of these effects across various sustainability dimensions. In this research preview paper, we present our research goals, key research questions, initial findings and next steps. Despite several challenges identified, our tentative conclusion is that GPTs, i.e. ChatGPT, are capable of generating relevant sustainability effects. [Contributions] Our findings aim to contribute to both research and practice by fostering AI-driven approaches for integrating sustainability considerations into requirements engineering.