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Cited by 30Creativity in Education and NeuroscienceDesign Education and PracticeAesthetic Perception and Analysis

Human‐AI Co‐Creativity: Does ChatGPT Make Us More Creative?

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Medeiros, Kelsey, Cropley, David H., Marrone, Rebecca L., Reiter‐Palmon, Roni·2025·The Journal of Creative Behavior
DOI 10.1002/jocb.70022
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Abstract

Much has been made of the apparent capacity for creativity of generative AI. However, as research expands the knowledge base regarding the capabilities and performance of this technology, the prevailing view is shifting away from “AI is creative” and towards a more balanced model of Human‐AI co‐creativity. Nevertheless, even this paradigm may be impacted by untested assumptions: for example, that generative AI will boost human performance on idea generation tasks. To test that assumption this study primed subjects with lists of words purportedly either from a human or from ChatGPT, and of varying degrees of creativity. Subjects then completed the Divergent Association Task (DAT). The results of this study found no evidence of any difference in divergent thinking resulting from either the source of priming (Human/ChatGPT) or from the level of creativity of the priming (low, typical, and high), with one exception: a low‐creativity prime, believed to be from ChatGPT, resulted in lower scores on the DAT compared to other priming conditions. A subsequent regression analysis supported this result, finding only the perceived creativity of the prime to be a weak predictor of DAT scores (in addition to the expected trait of Openness). The consequences of these findings for Human‐AI co‐creativity are discussed.

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  • Research has shown a wide range of effects of ChatGPT on creativity, including positive, adverse, and negligible or detrimental effects.

    “Additionally, research has shown a wide range of effects of ChatGPT on creativity, including positive effects (Urban et al., 2024), entirely adverse impacts (Niloy et al., 2024), and negligible or, if the AI assistance is of low quality, detrimental effects (Medeiros et al., 2025).”

    From Human Intelligence, Creativity, and Wisdom in the Age of Generative Artificial Intelligence (2025) · cites this paper as Medeiros et al., 2025

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Research works printed but not linked: 23

  1. Beaty, R. E., D. R. Johnson, D. C. Zeitlen, and B. Forthmann. 2022. "Semantic Distance and the Alternate Uses Task: Recommendations for Reliable Automated Assessment of Originality." Creativity Research Journal 34, no. 3: 245-260. https:// doi. org/ 10. 1080/ 10400 419. 2022. 2025720. · DOI
  2. Chen, H., and N. Ding. 2023. In Findings of the Association for Computational Linguistics: EMNLP 2023, 12881-12888. Association for Computational Linguistics.
  3. Cropley, D. H. 2023. "Is Artificial Intelligence More Creative Than Humans?" Learning Letters 2: 13.
  4. Cropley, D. H., K. Medeiros, and A. Damadzic. 2022. "Creativity and Artificial Intelligence: The Integration of Human and Artificial Cognition." In Creative Provocations: Speculations on the Future of Creativity, Technology & Learning, edited by D. Henriksen and P. Mishra, 19-34. Springer.
  5. Davidson, O. B., and D. Eden. 2000. "Remedial Self-Fulfilling Prophecy: Two Field Experiments to Prevent Golem Effects Among Disadvantaged Women." Journal of Applied Psychology 85, no. 3: 386-398. https:// doi. org/ 10. 1037// 0021-9010. 85.3. 386. · DOI
  6. Farmer, S., P. Tierney, and K. Kung-McIntyre. 2003. "Employee Creativity in Taiwan: An Application of Role Identity Theory." Academy of Management Journal 46: 618-630. https:// doi. org/ 10. 5465/ 30040653. · DOI
  7. Giannuzzo, A. 2023. "Creativity, Intentions, and Self-Narratives: Can AI Really be Creative?" Paper presented at the EPIA Conference on Artificial Intelligence. https:// doi. org/ 10. 1007/ 978-3-031-49011 -8_ 5. · DOI
  8. Guilford, J. P. 1967. The Nature of Human Intelligence. McGraw-Hill.
  9. Guzik, E. E., C. Byrge, and C. Gilde. 2023. "The Originality of Machines: AI Takes the Torrance Test." Journal of Creativity 33, no. 3: 100065.
  10. Haase, J., and P. H. Hanel. 2023. "Artificial Muses: Generative Artificial Intelligence Chatbots Have Risen to Human-Level Creativity." Journal of Creativity 33, no. 3: 100066.
  11. Happle, K. M. 2024. "Cre-AI-Tivity: The Intersection of Human Ingenuity and AI Collaboration in Scriptwriting With ChatGPT 4.0." (Master's thesis, Utrecht University). https:// stude ntthe ses. uu. nl/ bitst ream/ handle/ 20. 500. 12932/ 46352/ Happl eK_ 16983 97_ Maste rThes is. pdf? seque nce= 1.
  12. Hwang, A. H. C., and A. S. Won. 2021. "IdeaBot: Investigating Social Facilitation in Human-Machine Team Creativity." In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems.
  13. Kaufman, J. C., and R. A. Beghetto. 2009. "Beyond Big and Little: The Four-c Model of Creativity." Review of General Psychology 13: 1-12.
  14. Marmolejo-Ramos, F. 2023. "Trust in Algorithms. An Experimental Approach." PsyArXiv. https:// doi. org/ 10. 31234/ osf. io/ 9wh2f . · DOI
  15. Marrone, R., D. H. Cropley, and K. E. Medeiros. 2024. "How Does Narrow AI Impact Human Creativity?" Creativity Research Journal 2: 1-11. https:// doi. org/ 10. 1080/ 10400 419. 2024. 2378264. · DOI · Paper page
  16. Merritt, S. 2011. "Affective Processes in Human-Automation Interactions." Human Factors 53: 356-370. https:// doi. org/ 10. 1177/ 00187 20811 411912. · DOI · Paper page
  17. Olson, J. A., J. Nahas, D. Chmoulevitch, S. J. Cropper, and M. E. Webb. 2021. "Naming Unrelated Words Predicts Creativity." Proceedings of the National Academy of Sciences 118, no. 25: 2635.
  18. Powers, A., S. Kielser, S. Fussell, and C. Torrey. 2007. "Comparing a Computer Agent With a Humanoid Robot." Proceedings of the ACM/ IEEE International Conference on Human-Robot Interaction.
  19. Romney, A., J. T. Harrison, and S. Benson. 2024. "Looking Back to Predict the Future: A Review of Empirical Support for the Self-Fulfilling Prophecy." Management Research Review 47, no. 2: 245-260.
  20. Runco, M. A., and S. Acar. 2019. "Divergent Thinking." In The Cambridge Handbook of Creativity, edited by J. C. Kaufman and R. J. Sternberg, 2nd ed., 224-254. Cambridge University Press.
  21. Soto, C. J., and O. P. John. 2017. "The Next Big Five Inventory (BFI- 2): Developing and Assessing a Hierarchical Model With 15 Facets to Enhance Bandwidth, Fidelity, and Predictive Power." Journal of Personality and Social Psychology 113, no. 1: 117-143. https:// doi. org/ 10. 1037/ pspp0 000096. · DOI · Paper page
  22. Stevenson, C., I. Smal, M. Baas, R. Grasman, and H. van der Maas. 2022. Putting GPT-3's Creativity to the (Alternative Uses) Test arXiv:2206.08932. · arXiv
  23. Zhou, E., and D. Lee. 2023. "Generative Ai, Human Creativity, and Art." SSRN. https:// doi. org/ 10. 1093/ pnasn exus/ pgae052. · DOI · Paper page

Cited by

Sorted by citations

Authors
Medeiros, K., Cropley, D. H., Marrone, R. L., & Reiter‐Palmon, R.
Affiliations
  • University of Nebraska at Omaha (US)
  • University of South Australia (AU)
Corresponding author
Cropley, David H.
ORCID
Venue
The Journal of Creative Behavior
Publisher
Wiley
Published
2025-04-18
Volume
59
Issue
2
ISSN
  • 0022-0175 (ISSN-L)
  • 2162-6057
DOI
10.1002/jocb.70022
OpenAlex
W4409589475
Cited by
30
References
9
Citations by year
2026: 22 · 2025: 8
FWCI
31.42
Type
journal article
Language
en
Open access
Licence
Locations
  • The Journal of Creative Behavior (publishedVersion, cc-by-nc-nd)
  • Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by-nc-nd)
Funders
University of South Australia
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Creativity in Education and Neuroscience
  • Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Aesthetic Perception and Analysis
Keywords
human-AI co-creation, ChatGPT, generative AI, divergent thinking, idea generation, priming, openness to experience, creativity

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