Applications of artificial intelligence and cognitive science in design
File(s)
Author(s)
Han, Ji
Childs, Peter RN
Luo, Jianxi
Type
Journal Article
Abstract
Artificial intelligence and cognitive science are two core research areas in design. Artificial intelligence shows the capability of analysing massive amounts of data which supports making predictions, uncovering patterns and generating insights in varying design activities, while cognitive science provides the advantage of revealing the inherent mental processes and mechanisms of humans in design. Both artificial intelligence and cognitive science in design research are focused on delivering more innovative and efficient design outcomes and processes. Therefore, this thematic collection on “Applications of Artificial Intelligence and Cognitive Science in Design” brings together state-of-the-art research in artificial intelligence and cognitive science to showcase the emerging trend of applying artificial intelligence techniques and neurophysiological and biometric measures in design research. Three promising future research directions: 1) human-in-the-loop AI for design, 2) multimodal measures for design, and 3) AI for design cognitive data analysis and interpretation, are suggested by analysing the research papers collected. A framework for integration of artificial intelligence and cognitive science in design, incorporating the three research directions, is proposed to inspire and guide design researchers in exploring human-centred design methods, strategies, solutions, tools and systems.
Date Issued
2024
Date Acceptance
2024-05-01
Citation
Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2024, 38
ISSN
0890-0604
Publisher
Cambridge University Press
Journal / Book Title
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Volume
38
Copyright Statement
Copyright © The Author(s), 2024. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy).
License URL
Identifier
http://dx.doi.org/10.1017/s0890060424000052
Publication Status
Published
Article Number
e6
Date Publish Online
2024-05-03