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LLMs-Assisted decision-making in sustainable contexts
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| 5.45 MB | Adobe PDF |
Orientador(es)
Resumo(s)
Promoting sustainability through creative approaches offers a path
way 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 de
pends on the clarity of ideas, underlining the importance of hu
man 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.
Descrição
Palavras-chave
Creative process Creativity support tool LLMs Sustainability . Faculdade de Ciências Exatas e da Engenharia
Contexto Educativo
Citação
Ana Rodrigues, Diogo Cabral, and Pedro Campos. 2025. LLMs-Assisted Decision-making in Sustainable Contexts. In 36th Annual Conference of the European Association of Cognitive Ergonomics (EACE) (ECCE 2025), October 07–10, 2025, Tallinn, Estonia. ACM, New York, NY, USA, 12 pages. https: //doi.org/10.1145/3746175.3746188
Editora
ACM