Evaluating AI-Generated Solution Ideas: A Comparative Study of AI and Human Assessments for Sustainable Process Design
Year: 2024
Type: article
Abstract: The integration of generative artificial intelligence (AI) in sustainable process design has gained substantial traction, with AI increasingly employed to generate innovative solutions. However, the efficacy of these AI-generated ideas requires rigorous evaluation to ensure their quality. This study examines the dual role of GPT-4o in generating and evaluating solution ideas for sustainable process design at the concept development stage. Focusing on process engineering, the research applies these methods to a case study involving froth flotation for nickel recovery. By comparing AI-driven assessments with those from human experts, the research aims to determine the alignment between AI and human evaluations across key criteria: novelty, feasibility, usefulness, and sustainability. The results reveal strong alignment in most areas, though notable discrepancies in novelty suggest that human expertise remains essential for nuanced judgments on uniqueness. These findings highlight GPT-4o’s potential as a preliminary evaluation tool, while also underscoring the need for a hybrid approach that combines AI insights with human expertise.
Authors: Mas'udah, Mas'udah, Livotov, Pavel, Nugroho, Saptadi
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6976612372