Generative AI Use Ethics

RULES FOR THE USE OF ARTIFICIAL INTELLIGENCE TOOLS IN THE WRITING OF SCIENTIFIC ARTICLES

 

This document establishes the rules for the use of artificial intelligence (AI) tools in the preparation and writing of scientific articles, aimed at ensuring transparency, ethics, and reliability in scientific activity.

Modern AI technologies provide researchers with new opportunities for data analysis, process automation, and increased productivity of scientific work. However, their use requires strict adherence to academic standards and the principles of scientific integrity.

These rules serve as guidelines for the responsible use of AI, minimization of potential risks, and maintenance of high-quality scientific publications, thereby strengthening confidence in research results and ensuring compliance with international and national standards of scientific ethics.

Purpose of the document: To ensure transparency, ethics, and scientific accuracy in the use of AI tools during the preparation, writing, and publication of scientific articles, as well as to establish recommendations aimed at maintaining high standards of research quality.

Authors, the editorial board, and reviewers share joint responsibility for complying with these rules. The present rules are subject to periodic review and update in accordance with the development of AI technologies and the emergence of new challenges in scientific practice.

  1. Ethical principles of AI use

1.1. The fact of using AI tools must be clearly indicated in the article if they were employed for data analysis, text generation, or other research-related tasks.
1.2. The use of AI does not exempt authors from responsibility for the originality, accuracy, and quality of the submitted material.
1.3. The use of AI for data manipulation, result falsification, or distortion of information with the aim of exaggerating the significance of scientific conclusions is strictly prohibited.
1.4. The use of AI must not violate copyright laws, ethical norms, or principles of scientific integrity, including cases of unintentional text duplication generated by AI systems.

  1. Transparency in AI use

2.1. Authors are required to specify which AI tools were used during article preparation and at which stage (e.g., text generation, data processing and analysis, image creation, etc.).
2.2. The publication must clearly distinguish which parts of the work were performed manually by the authors and which were carried out using AI tools.
2.3. The contribution of AI to the research must be explicitly mentioned in the article text (for example, in the “Acknowledgments” section).
2.4. Any content created using AI must be additionally reviewed and verified by the authors to avoid errors, misinterpretations of data, or contextual distortions.

  1. Authors’ responsibility in using AI

3.1. Authors bear full responsibility for all aspects of their publication (quality, accuracy, and ethical compliance), including materials created with the assistance of AI.
3.2. AI tools must be used solely as auxiliary instruments and should not replace the author’s intellectual contribution.
3.3. Results obtained with AI assistance must be appropriately adapted and refined by the authors to ensure the originality and authenticity of the research.
3.4. Authors must comply with all licensing agreements and copyright regulations associated with the use of AI technologies.
3.5. The use of AI must not violate the laws of the Republic of Kazakhstan, including intellectual property protection norms and the internal regulatory documents of the University.

  1. Verification of publication originality

4.1. The editorial board of the scientific journal reserves the right to use specialized systems to verify the originality of the text, including analysis of data and findings generated using AI.

4.2. The editorial board may request additional information from the authors regarding the use of AI in the process of preparing the publication.

4.3. The editorial board reserves the right to reject an article if the use of AI tools is not properly disclosed.

4.4. If violations of AI use rules are identified, the editorial board may return the article for revision or refuse its publication.

  1. Authorship of scientific publications

5.1. Authorship must belong exclusively to individuals who have made an intellectual contribution to the research and bear responsibility for its content.

5.2. AI tools cannot be listed as authors, as they lack the rights and obligations inherent to individuals and cannot interpret or take responsibility for scientific outcomes.

  1. Data confidentiality

6.1. When using AI, authors must comply with data protection regulations, especially when handling personal or confidential information.

6.2. The use of AI must conform to international and national standards for data protection.

  1. Recommendations for authors

7.1. AI tools may be used at the following stages of scientific publication preparation:

- Literature search (automated search, structuring and analysis of publications, generation of summaries and annotations on the topic);

- Data analysis (processing of large data sets, identification of patterns and trends, application of ML and DL for visualization and interpretation);

- Description and interpretation of results (creation of figures, graphs, tables, assistance in formulating conclusions and defining directions for future research);

- Formatting (automation of references, bibliographies, verification of publication structure and templates);

- Translation and editing (translation of scientific articles with preservation of terminology, unification of formulations, correction of grammatical errors, improvement of text readability).

7.2. The use of AI for forming scientific hypotheses, conclusions, or interpretation of scientific results is strictly prohibited.

7.3. AI must not be used to circumvent ethical, methodological, or academic standards.

7.4. Examples of AI tools permitted for use in preparing publications:

- ChatGPT, Jasper AI — text generation and editing;

- EndNote, Zotero — bibliographic management;

- Tableau, Python (pandas, matplotlib) — data analysis and visualization;

- Grammarly, DeepL — text checking and translation.