Generative AI

POLICY ON THE USE OF GENERATIVE ARTIFICIAL INTELLIGENCE (GenAI LLMs)

Tazkiya Journal of Psychology, as a leading scholarly venue committed to the highest standards of academic integrity, quantitative methodological excellence, and the noble values of scholarship, hereby establishes the following comprehensive ethical framework governing the use of Generative Artificial Intelligence Large Language Models (GenAI LLMs) by all authors, reviewers, and editors.

  1. Objectives of the Policy

This policy is designed to:

  • Ensure absolute transparency, intellectual accountability, and uncompromising scientific integrity at every stage of the publication process;
  • Position GenAI LLMs as a sophisticated instrument for advancing intellectual innovation, rather than a substitute for critical thinking or the originality of research;
  • Harmonize technological advancement with the foundational scholarship principles of honesty, trustworthiness, justice, and responsibility.
  1. Scope of Application

This policy is binding upon all stakeholders involved in the publication process, including:

  • Authors
  • Reviewers
  • Editors and the Editorial Board

It applies comprehensively to any utilization of GenAI LLMs in manuscript preparation, peer review, editing, proofreading, and final publication readiness.

  1. Fundamental Principles of Use

The deployment of GenAI LLMs must be grounded in the following principles:

  • Honesty and Transparency: Every contribution of AI must be explicitly and fully disclosed.
  • Trustworthiness and Accountability: Authors, reviewers, and editors retain full and undivided responsibility for the validity, accuracy, and originality of all content.
  • Fairness and Academic Integrity: Any form of plagiarism is strictly prohibited, including the submission of GenAI-generated output as original work without substantial human modification and profound critical analysis.
  • Alignment with scholarship Values: Content generated or assisted by GenAI LLMs must not contravene any religious teachings, academic ethical norms, or universal human values.
  1. Permitted Uses (with Mandatory Disclosure)

GenAI LLMs may be employed ethically and responsibly for:

  • Deepening understanding of complex theoretical concepts and quantitative methodological frameworks;
  • Supporting literature identification, hypothesis development, and preliminary data analysis — subject to comprehensive and critical human validation;
  • Idea brainstorming, manuscript structuring, and linguistic refinement (grammar, clarity, and readability) without altering the scientific substance;
  • For reviewers and editors: assisting in consistency evaluation, methodological enhancement, and overall quality improvement of manuscripts.
  1. Prohibited Uses

The following practices are strictly prohibited:

  • Submitting a manuscript (in whole or in substantial part) generated by GenAI LLMs as original work without significant intellectual contribution from the author(s);
  • Utilizing GenAI LLMs in the peer-review process to produce review comments or assessments without independent critical analysis;
  • Generating or promoting content that violates any religious values (including pornography, extreme violence, hate speech, discrimination, or provocation of SARA issues);
  • Employing GenAI LLMs to manipulate data, statistical results, or empirical findings.
  1. Obligations of Disclosure and Referencing
  • Authors must transparently and comprehensively declare the use of GenAI LLMs in the Methods section or Author Note, specifying the tool(s), version, access date, and precise nature of their contribution.
  • References to GenAI LLMs must adhere to prevailing academic citation standards (APA 7th edition or the journal’s recommended style), as stipulated in the Appendix to the Rector’s Decree.
  • Reviewers and editors who employ GenAI LLMs during review or editing must formally notify the Editorial Board through the journal’s editorial management system.
  1. Responsibilities of Each Party
  • Authors: Bear full responsibility for the validity of data, statistical analyses, interpretation of findings, and overall originality of the manuscript.
  • Reviewers: Must uphold complete objectivity and intellectual independence; GenAI LLMs serve solely as supportive tools, never as replacements for professional judgment.
  • Editors: Ensure strict compliance with this policy prior to manuscript acceptance and publication.