HCApr 3

AI Disclosure with DAISY

arXiv:2604.0276050.21 citationsh-index: 5
Predicted impact top 41% in HC · last 90 daysOriginality Incremental advance
AI Analysis

This addresses the need for transparent AI use reporting in research, though it is incremental as it builds on existing disclosure practices with a new tool.

The paper tackled the problem of inconsistent and rare AI disclosure in research by developing DAISY, a form-based tool for generating disclosure statements, which resulted in disclosures meeting more completeness criteria and maintaining author comfort.

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.

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