Generative AI Policy

Generative AI Policy

Generative Artificial Intelligence (GenAI) is a powerful technology that offers significant opportunities to enhance research, creativity, and academic publishing.  We acknowledge the transformative impact of GenAI tools such as OpenAI's GPT-4 and successors, Google Gemini, Meta’s LLaMA 3, and other advanced multimodal and domain-specific AI models emerging in 2025. This policy sets forth our principles and guidelines to ensure responsible, transparent, and ethical use of GenAI in manuscript preparation, review, and publication, safeguarding the integrity and trustworthiness of scholarly communication.

  1. Transparency and Disclosure

Authors must explicitly disclose any use of GenAI tools in their manuscripts, including text generation, data analysis, visualization, or language enhancement. This disclosure should appear in the Acknowledgments section or a dedicated footnote, specifying the tool used and its specific purpose.

  • Example Disclosure: "This manuscript utilized GPT-4 (OpenAI) for language refinement and initial drafting of the literature review introduction. All content was thoroughly reviewed and validated by the authors."
  • Non-disclosure will be treated as a violation of publishing ethics and may lead to rejection or retraction.
  1. Author Responsibility and Accountability

The use of GenAI does not diminish the authors’ responsibility for the originality, accuracy, and ethical standards of their work. GenAI tools cannot be credited as authors because they cannot take accountability for the published work, nor can they legally hold copyrights. Authors are strictly required to verify that any AI-generated content is accurate, unbiased, and ethically sound.

  1. Ethical Use of Content
  1. Data Integrity: GenAI must not be used to fabricate or manipulate data, research results, statistical output, or crucial data visualizations (e.g., charts, models, conceptual diagrams).
  2. Source Verification: References and citations generated by GenAI must be carefully checked and authenticated manually by the authors to prevent the inclusion of non-existent or incorrect sources (known as "AI hallucinations").
  3. Plagiarism and Originality
  • AI-generated text used in the manuscript is considered non-original content and must be treated similarly to paraphrased text from other sources.
  • Authors must ensure that the final submitted manuscript adheres to the journal's acceptable similarity index threshold (e.g., maximum 20% total similarity, excluding bibliography).
  • The use of GenAI for text generation should only serve as a supplementary tool for drafting or editing. The core intellectual contribution (e.g., methodology, results interpretation, discussion) must be entirely the authors' own work and judgment.
  1. Peer Review Process

Jurnal Konsep Bisnis dan Manajemen relies exclusively on qualified human reviewers for manuscript evaluation. Reviewers are strongly discouraged from using GenAI tools to analyze or summarize manuscripts under review to ensure assessments reflect their independent, professional expertise and judgment, and to protect the confidentiality of the submitted work.

  1. Editorial Use

The editorial team may use GenAI tools for auxiliary tasks such as grammar checking, similarity detection, or summarization of accepted articles. However, all critical editorial decisions including acceptance, rejection, and requests for revision remain human-driven.

  1. Technical Guidance for Authors
  1. Disclose GenAI use clearly and specify its limited role.
  2. Verify all AI-generated content for factual accuracy and originality.
  3. Use plagiarism detection tools to avoid unintended duplication of public or AI-generated texts.
  4. Avoid relying on GenAI for critical intellectual contributions like hypothesis development, complex data interpretation, or drawing novel conclusions.
  5. Manually check all references and citations generated by AI.
  1. Policy Review

This policy will be periodically updated to reflect technological advances and evolving best practices and ethical standards in generative AI and academic publishing.