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Struggle Premium : How Human Effort and Imperfection Drive Perceived Value in the Age of AI

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arXiv:2604.15324v1 Announce Type: cross Abstract: As AI enters creative practice, audiences face growing uncertainty in judging authenticity and value. This study examines the Struggle Premium, the added value attributed to perceived human effort, by analyzing how visible effort cues influence evaluations of human- and AI-generated creative works. We surveyed 70 university students, focusing on process videos, time documentation, written explanations, and imperfections. Process-oriented cues, es

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    Computer Science > Human-Computer Interaction [Submitted on 4 Mar 2026] Struggle Premium : How Human Effort and Imperfection Drive Perceived Value in the Age of AI Nazneen Sultana, Mst Rafia Islam, Md. Tanvir Hossain, Azmine Toushik Wasi As AI enters creative practice, audiences face growing uncertainty in judging authenticity and value. This study examines the Struggle Premium, the added value attributed to perceived human effort, by analyzing how visible effort cues influence evaluations of human- and AI-generated creative works. We surveyed 70 university students, focusing on process videos, time documentation, written explanations, and imperfections. Process-oriented cues, especially videos and time spent, most strongly shaped authenticity and value judgments, while imperfections had limited impact. Participants showed a clear preference for human-made works, with 72.9% willing to pay more. Notably, effort cues also improved perceptions of AI-generated content, suggesting that process transparency can partially bridge authenticity gaps. These findings extend the effort heuristic to algorithmic creativity and inform the design of transparent human-AI creative systems. Comments: Short Paper. In Review. 12 Pages Subjects: Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Computers and Society (cs.CY) Cite as: arXiv:2604.15324 [cs.HC]   (or arXiv:2604.15324v1 [cs.HC] for this version)   https://doi.org/10.48550/arXiv.2604.15324 Focus to learn more Submission history From: Azmine Toushik Wasi [view email] [v1] Wed, 4 Mar 2026 16:02:44 UTC (2,678 KB) Access Paper: HTML (experimental) view license Current browse context: cs.HC < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.AI cs.CY References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv AI
    Category
    ◬ AI & Machine Learning
    Published
    Apr 20, 2026
    Archived
    Apr 20, 2026
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