AI Guidelines for Research Publication (2026)
The rapid advancement of Artificial Intelligence (AI) has significantly transformed academic research, scholarly writing, peer review, and publication practices across global research communities. In response to evolving ethical, methodological, and transparency challenges, Research Stars adopts the AI Guidelines for Research Publication (2026) to ensure responsible, transparent, and accountable use of AI-assisted technologies in scholarly communication. These guidelines emphasize human intellectual responsibility, disclosure of AI usage, originality, data integrity, ethical compliance, and research authenticity. By integrating international standards aligned with Elsevier Generative AI Policies and Scopus Publication Ethics Guidelines, Research Stars promotes ethical AI adoption while preserving academic integrity, scientific credibility, and publication quality in contemporary research environments.
- Transparency and Disclosure
Research Stars adopts the AI transparency principles recommended by Elsevier Generative AI Policies to ensure ethical, transparent, and accountable scholarly publication practices.
Guideline
Authors must clearly disclose the use of Artificial Intelligence (AI) tools and AI-assisted technologies employed during the preparation, analysis, editing, or development of research manuscripts. Transparency in AI usage is essential to maintain academic integrity, editorial trust, and scientific credibility.
Authors Must Disclose
AI-related information should be appropriately mentioned in one or more of the following sections:
- Methodology Section
- Acknowledgment Section
- Dedicated AI Disclosure Statement
Mandatory Disclosure Information
Authors must clearly specify:
- Name of the AI tool or platform used
- Version or model of the AI system
- Purpose of AI usage in the research or manuscript preparation
- Extent of human involvement, supervision, verification, and final decision-making
Research Stars Policy Statement
Research Stars recognizes that AI tools may support language refinement, data organization, literature assistance, and analytical processes; however, full intellectual responsibility for originality, accuracy, interpretation, ethical compliance, and manuscript content remains entirely with the authors. AI systems cannot be listed as authors or co-authors under Research Stars publication policies.
2. Human Accountability
Human authors remain fully responsible for the entire manuscript, even if AI tools assisted in writing or analysis.
Key Points
- Authors must verify:
- Accuracy
- Citations
- Data interpretation
- Ethical compliance
- AI-generated errors remain the responsibility of authors.
This principle is strongly emphasized in Elsevier policies and recent repository enforcement actions.
3. AI Cannot Be an Author
AI tools cannot receive authorship credit because they cannot take legal or ethical responsibility.
Key Points
- AI cannot:
- Approve manuscripts
- Take accountability
- Sign copyright agreements
- Only humans qualify as authors.
Organizations such as Elsevier and Committee on Publication Ethics support this principle.
4. Research Integrity
AI should not compromise originality, authenticity, or scientific validity.
Key Points
- Avoid:
- Fabricated references
- Hallucinated findings
- False statistics
- Fake peer reviews
- Researchers must manually validate AI-generated content.
Recent discussions in academic publishing highlight penalties for unchecked AI-generated errors.
5. Ethical Use of AI in Data Analysis
AI-assisted statistical interpretation must be transparent and reproducible.
Key Points
- Researchers should explain:
- AI-assisted coding
- AI-supported analytics
- Machine learning models used
- Human oversight is mandatory.
6. Privacy and Confidentiality
Sensitive research data should not be uploaded into public AI systems without authorization.
Key Points
- Protect:
- Participant data
- Unpublished findings
- Institutional documents
- Follow ethics committee and GDPR-style privacy standards.
7. Copyright and Intellectual Property
AI-generated material creates legal and ownership concerns.
Key Points
- Authors must ensure:
- No copyright infringement
- Proper permissions
- Original contribution
- AI-generated images and figures require disclosure.
Research Stars specifically requires disclosure if AI-generated images are part of research outputs as for guidelines of Elsevier.
8. Bias, Fairness, and Non-Discrimination
AI outputs may reflect biases present in training data.
Key Points
- Researchers should evaluate:
- Cultural bias
- Gender bias
- Language bias
- Regional imbalance
- Human review is necessary before publication.
9. Reproducibility and Traceability
AI-assisted research processes should be reproducible.
Key Points
- Maintain records of:
- Prompts
- AI outputs
- Model versions
- Editing history
- Research stars increasingly request methodological transparency.
10. Responsible Peer Review
Editors and reviewers should not upload confidential manuscripts into public AI tools.
Key Points
- Confidentiality must be protected
- AI cannot independently review manuscripts
- Human editorial judgment remains essential
11. AI Disclosure Frameworks
New frameworks in 2026 focus on structured AI reporting.
Examples include:
- Artificial Intelligence Disclosure (AID) Framework
- CANGARU Guidelines
- ERA Responsible AI Guidelines
These frameworks support standardized reporting of AI usage in research.
Common AI Disclosure Statement Example
“The authors used generative AI tools for language editing and manuscript organization. All outputs were reviewed, verified, and revised by the authors, who take full responsibility for the final content.”