Artificial Intelligence (AI) Policy

Research in the Mathematical and Natural Sciences (RMNS) requires responsible, transparent, and accountable use of Artificial Intelligence (AI) in research and scholarly publishing.

1. AI Use by Authors

Authors may use AI-assisted tools when scientific originality, accuracy, methodological validity, confidentiality, and human accountability are maintained.

Substantive generative AI use must be disclosed, including the tool and its specific purpose.

Authors must independently verify AI-assisted analyses, mathematical formulations, scientific findings, references, and conclusions.

AI-generated fabricated references, unsupported findings, and misleading scientific content are prohibited.

AI tools cannot be listed as authors or co-authors.

Routine spelling correction, conventional grammar checking, reference management, and non-generative formatting generally do not require disclosure.

2. AI Declaration

When substantive generative AI was used:

“The authors used [AI tool and version, if available] for [specific purpose]. All AI-assisted content was independently reviewed and verified by the authors, who take full responsibility for the manuscript.”

When generative AI was not used:

“The authors declare that no generative AI tools were used in the preparation of this manuscript.”

3. AI Use by Reviewers

Reviewers must not use generative AI to evaluate manuscripts, generate scientific review reports, or formulate editorial recommendations.

Confidential manuscripts must not be uploaded to external generative AI platforms.

Conventional mathematical and computational tools may be used for independent verification when confidentiality is maintained.

4. AI Use by Editors

Editors must exercise independent human judgment and protect confidential manuscripts and review materials.

Generative AI must not independently determine manuscript acceptance or rejection.

5. AI as Research Methodology

AI, machine learning, deep learning, and related computational approaches may be used as legitimate research methods when scientifically justified and adequately documented.

Relevant datasets, algorithms, parameters, training procedures, validation methods, and performance measures must be reported as appropriate.