The relation between humans and LLMs in the creative act

Can Large Language Models (LLMs) be creative? Existing research into the creativity of LLMs frames the debate as if the construct of creativity is limited to our conception of human creativity and fails to articulate the opportunity for human and LLM creativity to co-exist and contribute to the creative act in different manners. The objective of this article is to provide a new viewpoint for reflecting on the capabilities of LLMs in the domain of creativity and to enable us to acknowledge the relative strengths and weaknesses of LLMs compared to humans. A framework is proposed that builds on existing creativity frameworks (4Ps, 5As, and 5Cs) and articulates four perspectives (Entity, Proposition, Process, and Environment) for exploring the relation between LLMs and (human) creativity. Within each perspective, empirical and theoretical research on the creativity of LLMs is positioned into a broader landscape of theoretical creativity literature from the fields of psychology, philosophy, design, and computational creativity. In the discussion section, a framework is proposed that highlights how LLMs should be regarded as complementary amplifiers of the human cognition in the domain of natural language instead of ‘on par’ in terms of nature and capacities. For researchers, the insights provide a theoretical foundation for designing empirical research. For practitioners in the creative domain, the article introduces the vocabulary to articulate how humans and LLMs relate in the creative act.

Authors

Institutions

Publication Details

Journal
Journal of Creativity
Published
2025-11-12
DOI
https://doi.org/10.1016/j.yjoc.2025.100114
Primary Topic
Creativity in Education and Neuroscience
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The relation between humans and LLMs in the creative act

Yuan Yin, Rebecca Anne Price, Milene Gonçalves, Pan Wang et al.
Journal of Creativity
Creativity in Education and Neuroscience
article

The relation between humans and LLMs in the creative act

Yuan Yin, Rebecca Anne Price, Milene Gonçalves, Pan Wang, Tom Kortenbach
article en

Abstract

Can Large Language Models (LLMs) be creative? Existing research into the creativity of LLMs frames the debate as if the construct of creativity is limited to our conception of human creativity and fails to articulate the opportunity for human and LLM creativity to co-exist and contribute to the creative act in different manners. The objective of this article is to provide a new viewpoint for reflecting on the capabilities of LLMs in the domain of creativity and to enable us to acknowledge the relative strengths and weaknesses of LLMs compared to humans. A framework is proposed that builds on existing creativity frameworks (4Ps, 5As, and 5Cs) and articulates four perspectives (Entity, Proposition, Process, and Environment) for exploring the relation between LLMs and (human) creativity. Within each perspective, empirical and theoretical research on the creativity of LLMs is positioned into a broader landscape of theoretical creativity literature from the fields of psychology, philosophy, design, and computational creativity. In the discussion section, a framework is proposed that highlights how LLMs should be regarded as complementary amplifiers of the human cognition in the domain of natural language instead of ‘on par’ in terms of nature and capacities. For researchers, the insights provide a theoretical foundation for designing empirical research. For practitioners in the creative domain, the article introduces the vocabulary to articulate how humans and LLMs relate in the creative act.

Journal of CreativityVol. 36(1)
Bureau of Land Management (US), Kensington College of Business (GB)
Openalex Percentile: Top 64%
Creativity in Education and Neuroscience
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.