AI Disclosure with DAISY

TL;DR

This paper introduces DAISY, a structured tool for AI disclosure in research, which improves disclosure completeness without reducing author comfort, addressing transparency challenges.

Contribution

Development and evaluation of DAISY, a form-based tool that enhances AI disclosure clarity and completeness in research reporting.

Findings

DAISY disclosures met more completeness criteria.

Authors' comfort with disclosures was not reduced by DAISY.

Structured disclosure improves transparency in AI use reporting.

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.