Artificial creativity in design: A theory-based framework for implementation

Qihao Zhu; Jianxi Luo

doi:10.1017/pds.2025.10076

Artificial creativity in design: A theory-based framework for implementation

Qihao Zhu^*
, Jianxi Luo

^*Corresponding author for this work

Department of Systems Engineering

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

4 Downloads (CityUHK Scholars)

Abstract

This paper presents a novel framework for Artificial Creativity (AC) in design, emphasizing the co-development of problem and solution spaces. Grounded in cognitive psychology and design theories, the framework leverages advancements in artificial intelligence (AI), particularly generative AI models, to augment human creativity in design. The study identifies four key design spaces—Solution-Knowledge, Solution-Concept, Problem-Knowledge, and Problem-Concept—and defines operators that automate reasonings within and across these spaces. By enabling simultaneous divergence and convergence of problem and solution spaces, it fosters creativity while balancing novelty and effectiveness. This work bridges AI capabilities with cognitive processes of design creativity, laying a foundation for advancing artificial creativity and human-AI collaboration in design. © The Author(s) 2025.

Original language	English
Pages (from-to)	621-630
Number of pages	10
Journal	Proceedings of the Design Society
Volume	5
Online published	27 Aug 2025
DOIs	https://doi.org/10.1017/pds.2025.10076
Publication status	Published - Aug 2025
Event	25th International Conference on Engineering Design (ICED 25) - Dallas, United States Duration: 11 Aug 2025 → 14 Aug 2025

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Research Keywords

artificial intelligence
collaborative design
conceptual design
creativity
process modelling

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This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

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abstract = "This paper presents a novel framework for Artificial Creativity (AC) in design, emphasizing the co-development of problem and solution spaces. Grounded in cognitive psychology and design theories, the framework leverages advancements in artificial intelligence (AI), particularly generative AI models, to augment human creativity in design. The study identifies four key design spaces—Solution-Knowledge, Solution-Concept, Problem-Knowledge, and Problem-Concept—and defines operators that automate reasonings within and across these spaces. By enabling simultaneous divergence and convergence of problem and solution spaces, it fosters creativity while balancing novelty and effectiveness. This work bridges AI capabilities with cognitive processes of design creativity, laying a foundation for advancing artificial creativity and human-AI collaboration in design. {\textcopyright} The Author(s) 2025.",

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author = "Qihao Zhu and Jianxi Luo",

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T2 - 25th International Conference on Engineering Design (ICED 25)

AU - Zhu, Qihao

AU - Luo, Jianxi

N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

PY - 2025/8

Y1 - 2025/8

N2 - This paper presents a novel framework for Artificial Creativity (AC) in design, emphasizing the co-development of problem and solution spaces. Grounded in cognitive psychology and design theories, the framework leverages advancements in artificial intelligence (AI), particularly generative AI models, to augment human creativity in design. The study identifies four key design spaces—Solution-Knowledge, Solution-Concept, Problem-Knowledge, and Problem-Concept—and defines operators that automate reasonings within and across these spaces. By enabling simultaneous divergence and convergence of problem and solution spaces, it fosters creativity while balancing novelty and effectiveness. This work bridges AI capabilities with cognitive processes of design creativity, laying a foundation for advancing artificial creativity and human-AI collaboration in design. © The Author(s) 2025.

AB - This paper presents a novel framework for Artificial Creativity (AC) in design, emphasizing the co-development of problem and solution spaces. Grounded in cognitive psychology and design theories, the framework leverages advancements in artificial intelligence (AI), particularly generative AI models, to augment human creativity in design. The study identifies four key design spaces—Solution-Knowledge, Solution-Concept, Problem-Knowledge, and Problem-Concept—and defines operators that automate reasonings within and across these spaces. By enabling simultaneous divergence and convergence of problem and solution spaces, it fosters creativity while balancing novelty and effectiveness. This work bridges AI capabilities with cognitive processes of design creativity, laying a foundation for advancing artificial creativity and human-AI collaboration in design. © The Author(s) 2025.

KW - artificial intelligence

KW - collaborative design

KW - conceptual design

KW - creativity

KW - process modelling

UR - https://www.scopus.com/pages/publications/105022812726

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-105022812726&origin=recordpage

U2 - 10.1017/pds.2025.10076

DO - 10.1017/pds.2025.10076

M3 - RGC 21 - Publication in refereed journal

SN - 2732-527X

VL - 5

SP - 621

EP - 630

JO - Proceedings of the Design Society

JF - Proceedings of the Design Society

Y2 - 11 August 2025 through 14 August 2025

ER -

Artificial creativity in design: A theory-based framework for implementation

Abstract

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Research Keywords

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