Addressing Challenges to Problem Complexity: Effectiveness of AI Assistance During the Design Process

Binyang Song, Nicolas F. Soria Zurita, H. Nolte, H. Singh, J. Cagan, Christopher McComb
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引用次数: 1

Abstract

As Artificial Intelligence (AI) assistance tools become more ubiquitous in engineering design, it becomes increasingly necessary to understand the influence of AI assistance on the design process and design effectiveness. Previous work has shown the advantages of incorporating AI design agents to assist human designers. However, the influence of AI assistance on the behavior of designers during the design process is still unknown. This study examines the differences in participants’ design process and effectiveness with and without AI assistance during a complex drone design task using the HyForm design research platform. Data collected from this study is analyzed to assess the design process and effectiveness using quantitative methods, such as Hidden Markov Models and network analysis. The results indicate that AI assistance is most beneficial when addressing moderately complex objectives but exhibits a reduced advantage in addressing highly complex objectives. During the design process, the individual designers working with AI assistance employ a relatively explorative search strategy, while the individual designers working without AI assistance devote more effort to parameter design.
解决问题复杂性的挑战:设计过程中人工智能辅助的有效性
随着人工智能辅助工具在工程设计中越来越普遍,了解人工智能辅助对设计过程和设计有效性的影响变得越来越有必要。之前的工作已经显示了将人工智能设计代理纳入辅助人类设计师的优势。然而,AI辅助在设计过程中对设计师行为的影响仍然未知。本研究使用HyForm设计研究平台,研究了在复杂的无人机设计任务中,参与者在有和没有人工智能帮助的情况下的设计过程和有效性的差异。从本研究中收集的数据进行分析,以评估设计过程和有效性使用定量方法,如隐马尔可夫模型和网络分析。结果表明,人工智能辅助在解决中等复杂的目标时是最有益的,但在解决高度复杂的目标时表现出较少的优势。在设计过程中,有人工智能辅助的个体设计师采用了相对探索性的搜索策略,而没有人工智能辅助的个体设计师则在参数设计上投入了更多的精力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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