Artificial Intelligence (AI) Usage Policy

Authors may use generative AI or AI-assisted technologies to support activities such as language improvement, literature organization, idea development, coding assistance, software documentation, data exploration, data preprocessing support, system-design ideation, or manuscript preparation. AI tools must not replace the authors' critical thinking, scholarly judgment, systems analysis, technical validation, interpretation, or original contribution.

Authors are responsible for:

• verifying factual accuracy and checking references generated by AI;
• reviewing and substantially editing AI-assisted content;
• checking for bias, hallucination, fabricated citations, insecure code, or misleading technical information;
• protecting confidential datasets, personal information, credentials, source code, system configurations, organizational records, copyrighted material, and unpublished data;
• independently validating AI-assisted code, algorithms, classifications, models, calculations, system recommendations, or interpretations; and
• ensuring that the final manuscript represents the authors' own scholarly work.

Meaningful use of generative AI in manuscript preparation must be disclosed in a separate AI Declaration. The declaration should identify the tool used, its purpose, and the extent of human review and oversight.

Basic spelling, grammar, or punctuation checks do not normally require disclosure. If AI forms part of the research method, software development, information-system design, data preprocessing, machine-learning pipeline, database analysis, predictive modeling, decision-support process, cybersecurity analysis, or data analysis, its use must be described in sufficient detail in the Methods section.

AI tools, chatbots, code assistants, and language models must not be listed as authors or co-authors. Authorship requires human responsibility for the integrity of the work, approval of the final manuscript, accountability for its content, and the ability to respond to questions regarding the research, system design, methods, and findings.

Generative AI must not be used to create, manipulate, obscure, remove, or introduce features in research figures, system diagrams, dashboards, screenshots, interface images, architecture diagrams, data visualizations, or other visual evidence in a manner that misrepresents the underlying research or system output.

An exception may apply when AI-assisted visualization, image generation, interface generation, synthetic-data visualization, or automated diagramming is part of the research design or methodology. In such cases, authors must describe the tool, model/version, procedure, inputs, validation process, and its role in generating or interpreting research data in the Methods section.

Submitted manuscripts are confidential documents. Reviewers must not upload manuscripts, manuscript excerpts, source code, system configurations, datasets, credentials, supporting files, proprietary algorithms, or review reports into public generative AI systems.

Peer review is a human scholarly responsibility. AI tools must not be used to generate scientific assessments, independently evaluate system quality, assess methodological validity, determine software correctness, or determine review recommendations. Reviewers remain personally responsible for the content, accuracy, fairness, technical soundness, and integrity of their reports.

Editors must not upload submitted manuscripts, confidential correspondence, reviewer reports, source code, unpublished datasets, system documentation, proprietary technical information, or editorial decision letters into public generative AI systems.

AI must not replace human editorial judgment or be used to determine acceptance, revision, or rejection. Editors remain fully responsible for editorial evaluation, reviewer selection, confidentiality management, communication, conflict-of-interest management, and final publication decisions.