LLMs-Assisted Decision-making in Sustainable Contexts

Le résumé fourni par la source

Promoting sustainability through creative approaches offers a pathway to achieving sustainability goals, yet the resulting solutions often lack efficiency and effectiveness. Addressing this challenge, we introduce SAIESE, a Creativity Support Tool (CST) leveraging a Large Language Model (LLM) to support the creative process, the generation, evaluation, and selection of sustainable ideas. Our work articulates LLMs role in exploration and selection, focusing on sustainable ideas based on three metrics - Environmental Impact, Economic Benefits, and Social Effects. Our evaluation demonstrates that the prototype outperforms human evaluative tasks in usability, creative thinking, and decision-making while reducing cognitive workload. However, its effectiveness in promoting creativity depends on the clarity of ideas, underlining the importance of human collaboration in ambiguous contexts. This work articulates the potential of AI in creativity, expanding current research on CSTs by highlighting sustainability-oriented creative processes and decision-making support.

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