1. Introduction
- At the International Journal of Responsible Machine Learning (IJRML), we uphold the highest standards of integrity, fairness, and ethical responsibility in the publication of scholarly work. As a journal dedicated to the social impact of machine learning, we expect all authors, reviewers, and editors to consider not only the technical soundness of submissions, but also their ethical implications.
- This policy outlines our expectations on responsible conduct in research, authorship, review, and publication.
2. Ethical Research Practices
Authors must ensure that:
- The research adheres to ethical standards in the collection, use, and sharing of data, particularly where human subjects, sensitive information, or marginalised populations are involved.
- Any use of biometric, medical, or surveillance data has received appropriate institutional ethics clearance.
- Any deployment of ML systems (even in simulation) that may influence human behaviour or wellbeing is clearly described, justified, and assessed for harm.
3. AI-Generated Content
- The use of generative AI tools (e.g., for writing, coding, image generation) must be explicitly disclosed. Authors remain fully responsible for the accuracy, originality, and integrity of all submitted content.
- We do not accept AI-generated authorship.
4. Fairness, Bias, and Societal Impact
Papers must include a section or discussion addressing:
- Potential harms or unintended consequences
- Bias in datasets or models
- Limitations in scope, fairness, and generalisability
- Impact on affected communities, especially in applied settings
- Where this is not relevant, authors should state why.
5. Conflicts of Interest
All participants in the publication process must disclose any conflicts of interest:
- Authors: Must declare any financial or personal interest that could influence their work.
- Reviewers and Editors: Must recuse themselves if they have close collaborations or relationships with the authors or their institutions.
6. Plagiarism and Duplicate Submissions
- IJRML has zero tolerance for plagiarism, falsification, or duplicate publication.
- All manuscripts are screened. Submissions found to contain uncredited work of others or recycled material without substantial new contribution will be rejected and reported.
7. Human and Animal Ethics
If your research involves human participants, authors must confirm that:
- Informed consent was obtained
- Data collection was approved by an ethics review board
- Anonymity and data protection standards were followed
- Research involving animals must comply with institutional animal welfare guidelines.
8. Post-Publication Ethics
We reserve the right to issue retractions, corrections, or expressions of concern where:
- Ethical breaches come to light after publication
- Significant undisclosed conflicts are found
- Flawed data or code undermines the findings
- Authors and readers are encouraged to notify the editorial team if such issues arise.