Artificial Intelligence (AI) Policy

Axis Journal of Medical and Biosocial Sciences (AJMBS)

Purpose

The Axis Journal of Medical and Biosocial Sciences (AJMBS) recognizes the transformative potential of Artificial Intelligence (AI) in improving research quality, editorial efficiency, and scientific innovation. This policy establishes ethical, transparent, and accountable guidelines governing the responsible use of AI technologies across all stages of the publication process — from manuscript preparation to peer review and editorial decision-making.

By implementing this policy, AJMBS ensures that AI tools are used to enhance human judgment, not replace it, preserving academic integrity and accountability in scientific publishing.

1. Scope

This policy applies to all individuals involved in the publication process, including authors, reviewers, editors, and the editorial office staff.
Covered AI applications include, but are not limited to:

Machine Learning (ML) models for data analysis and statistical interpretation.
Natural Language Processing (NLP) tools for text refinement, summarization, or grammar correction.
AI-assisted image or data analysis in medical, biological, or social science research.
AI-supported editorial and peer review systems used to enhance efficiency and detect research integrity concerns.

This policy is particularly relevant to manuscripts involving or utilizing AI methodologies, datasets, or analytical tools within the medical, clinical, and biosocial sciences.

2. Definitions

Artificial Intelligence (AI): Computational systems capable of performing tasks that typically require human intelligence, such as learning, reasoning, and decision-making.
AI-Generated Content: Any text, image, data, or analysis wholly or partially produced by AI software.
AI-Assisted Decision-Making: The application of AI tools to support, but not substitute, editorial or peer review judgments.

3. Transparency and Disclosure

Transparency is central to ethical AI integration in publishing.

Mandatory Disclosure: Authors, reviewers, and editors must declare the use of any AI tool at any stage of manuscript creation, review, or editorial processing.
Statement of Use: Authors must include a clear statement describing the AI tool(s) used, their purpose, and the extent of their contribution (e.g., “AI language assistance was provided using [tool name] for grammar improvement”).
AI Contribution Distinction: The role of AI tools must be clearly distinguished from human intellectual input. Human authors retain full accountability for the accuracy and integrity of all AI-assisted content.

4. Authorship and Accountability

AI Cannot Be an Author: AI systems do not meet the criteria for authorship established by the ICMJE and therefore cannot be listed as co-authors.
Acknowledgment: When AI tools contribute meaningfully to data processing, text drafting, or analysis, this must be acknowledged in the manuscript’s “Acknowledgment” section.
Human Responsibility: All content generated or refined by AI tools remains the sole responsibility of the human authors, who must verify its accuracy, originality, and compliance with ethical standards.

5. Ethical Integrity and Data Protection

Fairness and Non-Bias: Authors and editors must ensure that AI tools used in research or review processes are implemented ethically, without reinforcing gender, racial, or social biases.
Data Privacy Compliance: All AI applications must comply with GDPR and relevant data protection laws, ensuring that personal, clinical, or sensitive data are handled securely and anonymized before processing.
Ethical Review: Any research involving AI in data collection or patient care must include institutional ethics approval and disclose the ethical safeguards adopted.

6. Quality, Originality, and Verification

Standards for AI Content: Any AI-assisted text, data visualization, or analysis must meet AJMBS’s editorial standards for clarity, originality, and scientific validity.
Plagiarism Screening Policy: The Axis Journal of Medical and Biosocial Sciences screens all submitted manuscripts for plagiarism prior to peer review using professional plagiarism detection software (e.g., Turnitin / iThenticate). Manuscripts found to contain significant plagiarism, redundant publication, or unethical use of AI-generated content will be rejected outright or returned to authors for correction, depending on severity. The journal follows COPE guidelines in handling suspected cases of plagiarism and academic misconduct.
Factual Verification: Authors must validate factual information, references, and analytical outputs generated by AI tools before submission.

7. AI in Peer Review and Editorial Decision-Making

Supportive Role Only: AI tools may assist editors and reviewers in identifying plagiarism, image manipulation, or statistical inconsistencies, but cannot independently determine acceptance or rejection.
Transparency in AI-Use: If AI aids in reviewer matching or similarity checks, this must be disclosed internally within editorial workflows.
Human Oversight: All final editorial and publication decisions must be made by qualified human editors, not automated systems.

8. Research Involving AI

For manuscripts that involve the use or development of AI systems as part of the study design:

Methodological Description: Authors must describe the AI methodology, including data sources, algorithms, validation methods, and potential limitations.
Algorithmic Transparency: If feasible, datasets and code used for AI models should be made available in public repositories for reproducibility.
Ethical Reporting: Studies must report how algorithmic bias, data quality, and validation were managed.

9. Documentation, Traceability, and Version Control

AI Revision Tracking: Any AI-generated or AI-modified content must be traceable through a documented revision history.
Auditability: Editors may request access to logs or version records showing how AI tools contributed to manuscript development.
Transparency in Updates: If significant AI-driven modifications are made after acceptance, these must be disclosed in the publication history or corrigenda.

10. Bias Identification and Error Management

Bias Mitigation: Authors should actively test for and mitigate algorithmic biases in AI models or datasets.
Error Disclosure: Any detected errors resulting from AI use must be transparently acknowledged and corrected, either during review or post-publication.
Responsible Correction: The editorial office reserves the right to issue corrections or retractions if AI misuse or unacknowledged AI content is discovered.

11. Implementation, Training, and Oversight

Editorial Training: AJMBS provides periodic training for editors, reviewers, and staff on the ethical use of AI tools in scholarly publishing.
Policy Monitoring: The journal continuously monitors advancements in AI technology and updates this policy annually to ensure compliance with global standards.
Governance: The Axis Exploration & Academics (Pvt) Ltd oversight committee ensures policy enforcement and addresses any ethical breaches related to AI usage.

12. Enforcement and Consequences

Mandatory Compliance: Adherence to this AI policy is a condition of submission and publication.
Violation Response: Failure to disclose AI use or misuse of AI tools may result in:
- Manuscript rejection or withdrawal during review.
- Retraction or correction after publication.
- Notification of the author’s affiliated institution for investigation.

13. Policy Review and Updating

This policy will be reviewed annually or as necessitated by rapid developments in AI technologies, ethical frameworks, or global publishing standards. Revisions will be publicly documented and implemented under the guidance of the AJMBS editorial board.

Conclusion

By enforcing this comprehensive Artificial Intelligence Policy, the Axis Journal of Medical and Biosocial Sciences (AJMBS) ensures that AI is used ethically, transparently, and responsibly across all aspects of academic publishing. This commitment preserves the authenticity, accountability, and scientific integrity of every published work, while embracing innovation as a driving force for advancement in medical and biosocial research.