Understanding Reader Perception Shifts upon Disclosure of AI Authorship
Hiroki Nakano, Jo Takezawa, Fabrice Matulic, Chi-Lan Yang, Koji Yatani

TL;DR
This study investigates how revealing AI authorship affects reader perceptions, showing that disclosure often reduces trust and likability, but higher AI literacy can mitigate these effects, informing better transparent writing system design.
Contribution
It provides empirical insights into how AI disclosure impacts reader perceptions and highlights the moderating role of AI literacy, informing design of transparent AI writing tools.
Findings
Disclosure reduces trustworthiness, caring, competence, and likability.
Negative perception shifts are strongest in social and interpersonal writing.
Higher AI literacy correlates with more positive or tolerant perceptions.
Abstract
As AI writing support becomes ubiquitous, how disclosing its use affects reader perception remains a critical, underexplored question. We conducted a study with 261 participants to examine how revealing varying levels of AI involvement shifts author impressions across six distinct communicative acts. Our analysis of 990 responses shows that disclosure generally erodes perceptions of trustworthiness, caring, competence, and likability, with the sharpest declines in social and interpersonal writing. A thematic analysis of participants' feedback links these negative shifts to a perceived loss of human sincerity, diminished author effort, and the contextual inappropriateness of AI. Conversely, we find that higher AI literacy mitigates these negative perceptions, leading to greater tolerance or even appreciation for AI use. Our results highlight the nuanced social dynamics of AI-mediated…
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