Artificial Intelligence (AI) Policy
Policy on the Use of Artificial Intelligence (AI) in Scholarly Activities
Axis Journal of Medical and Biosocial Sciences (AJMBS)
1.0 Preamble and Purpose
The Axis Journal of Medical and Biosocial Sciences (AJMBS), published by Axis Academics Limited (UK), acknowledges the rapidly evolving role of Artificial Intelligence (AI) as a transformative tool in scientific research and academic publishing. While AI technologies offer significant potential to enhance efficiency and discovery, particularly in analysing complex medical and biosocial datasets, their use must be governed by a clear ethical framework to preserve the fundamental principles of academic integrity, transparency, and human accountability that are the cornerstone of scholarly work. This policy establishes mandatory guidelines for the responsible use of AI tools by all contributors to AJMBS, including authors, reviewers, and editors.
2.0 Scope and Definitions
This policy applies to all stages of the manuscript lifecycle, from initial research and writing to peer review and editorial decision-making.
Artificial Intelligence (AI): For the purpose of this policy, AI refers to machine-based systems that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. This includes but is not limited to: large language models (LLMs), generative AI, machine learning, natural language processing, and AI-assisted data analysis tools.
AI-Generated Content: Any text, image, data, analysis, or interpretation that is primarily created by an AI tool without substantial human intellectual direction and oversight.
AI-Assisted Content: Content where AI tools are used to support, refine, or enhance human-generated work (e.g., for grammar checking, language polishing, formatting references, or preliminary data exploration in biosocial research).
3.0 Author Responsibilities and Transparency
Mandatory Disclosure: Authors must transparently disclose any use of AI or AI-assisted technologies in the preparation of their manuscript. This disclosure must be made within the 'Methods' section or a dedicated 'AI Use Statement'.
Prohibition of AI Authorship: AI tools and large language models cannot be listed as an author or co-author on a manuscript. Authorship requires legal personhood and the ability to be accountable for the work, which AI systems cannot provide.
Human Accountability: Authors are entirely responsible and accountable for the entire content of their manuscript, including any portions developed with the assistance of AI. This includes ensuring the accuracy, originality, and validity of all information, ensuring proper citation of sources, and verifying that AI use does not constitute plagiarism or introduce errors into medical or biosocial analyses.
Data Privacy and Security: Authors must not input confidential, sensitive, or proprietary information into publicly available AI systems. This includes unpublished research data, confidential peer-review information, patient health data, or any human participant information protected under applicable data protection regulations.
4.0 Quality, Originality, and Ethical Compliance
Plagiarism Screening Policy: As stated in the journal's Submission and Editorial Evaluation Pathway, all submissions undergo plagiarism screening. Additionally, the use of AI to circumvent originality requirements is strictly prohibited. Manuscripts found to contain unethical use of AI-generated content will be rejected or returned for correction.
The Axis Journal of Medical and Biosocial Sciences (AJMBS) screens all submitted manuscripts for plagiarism prior to peer review using professional plagiarism detection software. 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.
5.0 Peer Reviewer and Editor Responsibilities
Confidentiality: Reviewers and editors must not upload any part of a submitted manuscript, or any related confidential materials, into generative AI tools. This constitutes a severe breach of confidentiality and will result in immediate removal from the process and potential future exclusion from reviewing for AJMBS.
AI in Review: While reviewers may use AI tools for administrative tasks (e.g., checking references or formatting), the core intellectual work of evaluation, critique, and recommendation must be performed by the human reviewer. The journal may employ AI-based screening tools to assist editors in initial checks for plagiarism or formatting, but final editorial decisions will always rest with human editors employed by Axis Academics Limited (UK).
6.0 Research Involving AI as a Methodology
For manuscripts where the development or application of an AI algorithm is the primary subject of the research, particularly in medical diagnostics, biological data analysis, or social modelling:
Methodological Rigour: The manuscript must provide a complete and reproducible description of the AI methodology, including details of the algorithm, training data, validation methods, and code availability (where possible). For clinical or biosocial applications, validation must be performed on independent datasets.
Bias and Limitations: A dedicated discussion of potential biases within the training data, the algorithm's limitations, and the steps taken to mitigate them is required, with specific attention to how biases might affect medical or social outcomes.
7.0 Enforcement and Compliance
Non-compliance with this policy will be treated as a serious breach of publishing ethics. Consequences may include, but are not limited to:
Rejection of the manuscript.
Retraction of a published article.
Prohibition on future submissions for all involved authors.
Notification of institutional bodies or employers in cases of severe misconduct involving patient data or ethical violations.
8.0 Policy Review
Given the rapid pace of AI development, this policy will be subject to formal review on an annual basis to ensure its continued relevance and effectiveness. AJMBS is committed to adapting its guidelines in line with emerging community standards, technological advancements, and updates to ICMJE Recommendations.
By implementing this comprehensive policy, AJMBS aims to harness the benefits of AI technology while steadfastly upholding the values of academic rigour, transparency, and human intellectual leadership that define our scholarly community in medical and biosocial sciences.