A faceted model based on Form, Generation, Evaluation with extensions for Intent, Control, and Traceability is proposed as a minimal baseline for representing AI-assisted text production at multiple document scales.
AI Disclosure with DAISY
2 Pith papers cite this work. Polarity classification is still indexing.
abstract
The use of AI tools in research is becoming routine, alongside growing consensus that such use should be transparently disclosed. However, AI disclosure statements remain rare and inconsistent, with policies offering limited guidance and authors facing social, cognitive, and emotional barriers when reporting AI use. To explore how structured disclosure shapes what authors report and how they experience disclosure, we present DAISY (Disclosure of AI-uSe in Your Research), a form-based tool for generating AI disclosure statements. DAISY was developed from literature-derived requirements and co-design (N =11), and deployed in a user study with authors (N=31). DAISY-supported disclosures met more completeness criteria, offering clearer breakdowns of AI use across research and writing than unsupported disclosures. Surprisingly, despite concerns about how transparently disclosed AI use might be perceived, the use of DAISY did not reduce author comfort with the disclosure statements. We discuss design implications and a research agenda for AI disclosure as a sociotechnical practice.
citation-role summary
citation-polarity summary
years
2026 2roles
background 1polarities
support 1representative citing papers
Hiding generative AI use to signal expertise reduces knowledge sharing and transparency among workplace colleagues.
citing papers explorer
-
A Faceted Proposal for Transparent Attribution of AI-Assisted Text Production
A faceted model based on Form, Generation, Evaluation with extensions for Intent, Control, and Traceability is proposed as a minimal baseline for representing AI-assisted text production at multiple document scales.
-
"If You're Very Clever, No One Knows You've Used It": The Social Dynamics of Developing Generative AI Literacy in the Workplace
Hiding generative AI use to signal expertise reduces knowledge sharing and transparency among workplace colleagues.