PURPOSE

The increasing use of AI tools, particularly large language models like ChatGPT, in academic research has raised significant questions about authorship and transparency. This commentary emphasizes the need for a standardized AI contributions taxonomy to clarify AI's role in producing and publishing research outputs, ensuring ethical standards and maintaining academic integrity.

APPROACH

We propose adapting the NIST AI Use Taxonomy and incorporating categories that reflect AI's use in tasks such as hypothesis generation, data analysis, manuscript preparation, and ethical oversight. Findings: Establishing an AI contributions taxonomy for the production and publication of research output would address inconsistencies in AI disclosure, enhance transparency, and uphold accountability in research. It would help differentiate between AI-assisted and human-led tasks, providing more explicit attribution of contributions.

FINDINGS

Establishing an AI contributions taxonomy for the production and publication of research output would address inconsistencies in AI disclosure, enhance transparency, and uphold accountability in research. It would help differentiate between AI-assisted and human-led tasks, providing more explicit attribution of contributions.

PRACTICAL IMPLICATIONS

The proposed taxonomy would offer researchers and journals a standardized method for disclosing AI's role in academic work, promoting responsible and transparent reporting aligned with ethical guidelines from COPE and ICMJE.

VALUE

A well-defined AI contributions taxonomy for the production and publication of research output would foster transparency and trust in using AI in research, ensuring that AI's role is appropriately acknowledged while preserving academic integrity.