Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/335622 
Year of Publication: 
2025
Citation: 
[Journal:] Creativity and Innovation Management [ISSN:] 1467-8691 [Volume:] 34 [Issue:] 4 [Publisher:] Wiley [Place:] Hoboken, NJ [Year:] 2025 [Pages:] 835-853
Publisher: 
Wiley, Hoboken, NJ
Abstract: 
Generative artificial intelligence (GenAI), such as ChatGPT, is increasingly recognized for its potential to drive innovation, yet questions remain about its ability to mimic human innovation. Leveraging cognitive load theory (CLT), this study explores whether humans can reliably distinguish between incremental and radical innovation ideas in text created by ChatGPT and those created by humans. In an online experiment with 689 participants and 6454 innovation ratings, results from Turing and noninferiority tests showed that participants achieved accuracy only slightly above chance level, with marginally higher accuracy for radical innovations. However, significant differences emerged across thematic clusters: Convenience and health innovations were identified more accurately than education and sustainability innovations. This research advances the understanding of how closely GenAI‐generated innovations resemble human ones, emphasizes the need for transparency in GenAI's role within creativity processes and raises questions about developing new indicators for evaluating contributions in increasingly AI‐integrated innovation environments.
Subjects: 
ChatGPT
cognitive load theory (CLT)
incremental innovation
noninferiority test
radical innovation
Turing test
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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