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How good is ChatGPT? An exploratory study on ChatGPT's performance in engineering design tasks and subjective decision-making

Published online by Cambridge University Press:  16 May 2024

Wanyu Xu ,
Maulik Chhabilkumar Kotecha  and
Daniel A. McAdams
Wanyu Xu*
Affiliation:
Texas A&M University, United States of America
Maulik Chhabilkumar Kotecha
Affiliation:
Texas A&M University, United States of America
Daniel A. McAdams
Affiliation:
Texas A&M University, United States of America
*
*[email protected]

Abstract

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This study explores how large language models like ChatGPT comprehend language and assess information. Through two experiments, we compare ChatGPT's performance with humans', addressing two key questions: 1) How does ChatGPT compare with human raters in evaluating judgment-based tasks like speculative technology realization? 2) How well does ChatGPT extract technical knowledge from non-technical content, such as mining speculative technologies from text, compared to humans? Results suggest ChatGPT's promise in knowledge extraction but also reveal a disparity with humans in decision-making.

Keywords

artificial intelligence (AI)design knowledgedesign researchdesign theory
Type
Artificial Intelligence and Data-Driven Design
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 2307 - 2316
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

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