Understanding Reader Perception Shifts upon Disclosure of AI Authorship

Generative AI (Text, Image, Music, Video)Human-LLM CollaborationAI Ethics, Fairness & AccountabilityEmpathy & Emotional DesignAI-Assisted Writing & Text GenerationUI/UX DesignersAI/ML Researchers & EngineersHCI Researchers

As AI writing support becomes ubiquitous, the question of how disclosing its use affects reader perception remains critical and underexplored. We conducted a controlled study with 261 participants to examine how disclosing varying levels of AI involvement shifts perceptions of the author across six distinct communicative acts. Our analysis of 990 evaluations reveals that disclosure generally erodes perceived trustworthiness, caring, competence, and likability, with the most precipitous declines observed in social and interpersonal writing. A thematic analysis of participant feedback attributes these negative shifts to a perceived loss of human sincerity, diminished authorial effort, and the contextual inappropriateness of AI. Notably, however, we find that higher AI literacy mitigates these negative perceptions, leading to greater tolerance or even appreciation for AI assistance. Our results highlight the nuanced social dynamics of AI-mediated authorship and inform design implications for transparent, context-sensitive writing systems that better preserve trust and authenticity.

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https://hci.top/en/papers/iui/226674/2026

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IUI
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Year
2026
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5 authors
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Generative AI (Text, Image, Music, Video), Human-LLM Collaboration, AI Ethics, Fairness & Accountability, Empathy & Emotional Design
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UI/UX Designers, AI/ML Researchers & Engineers, HCI Researchers
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Abstract only
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