Generative Artificial Intelligence Policy

Generative Artificial Intelligence (AI) tools, including large language models (LLMs) and multimodal systems, are continuously advancing and expanding in scope, with increasing adoption by both organizations and individual users.
 
Advances in Analysis and Applied Mathematics recognizes and welcomes the opportunities offered by Generative AI tools, particularly in the following areas:
  • Supporting idea generation and conceptual exploration
  • Assisting authors in improving academic expression when writing in a non-native language
  • Enhancing the efficiency of research workflows and the dissemination of scholarly knowledge
The journal provides guidance for authors, editors, and reviewers regarding the appropriate use of Generative AI tools. These guidelines may be revised over time in response to the rapid evolution of AI technologies.
 
Generative AI tools are capable of producing a wide range of outputs, including text, images, audio, and synthetic data. Examples of such tools include ChatGPT, Copilot, Gemini, Claude, NovelAI, Jasper AI, DALL·E, Midjourney, and Runway, among others.
 
While Generative AI offers substantial potential to support scholarly creativity and productivity, the current generation of these tools also presents notable risks.

Risks Associated with Current Generative AI Technologies

  • Inaccuracy and bias: Generative AI systems operate on probabilistic and statistical mechanisms rather than factual reasoning, which may result in inaccuracies, fabricated content (commonly referred to as “hallucinations”), or embedded biases that are difficult to identify and rectify.
  • Insufficient attribution: Generative AI tools often fail to adhere to established scholarly standards for accurate citation and attribution of ideas, quotations, and sources.
  • Confidentiality and intellectual property concerns: Many Generative AI tools are deployed via third-party platforms that may not provide adequate safeguards for data privacy, security, or copyright protection.
  • Unintended data usage: AI service providers may reuse user inputs or generated outputs, for example for model training purposes, potentially infringing upon the rights of authors, publishers, or other stakeholders.

Guidelines for Authors

Authors bear full responsibility for the originality, accuracy, validity, and ethical integrity of their submitted work. When choosing to employ Generative AI tools, authors are expected to do so responsibly and in compliance with the journal’s editorial policies on authorship, publishing ethics, and applicable book publishing guidelines. This includes carefully reviewing all AI-generated content and verifying its correctness.
 
Advances in Analysis and Applied Mathematics supports the responsible use of Generative AI tools that uphold high standards of confidentiality, data protection, and copyright compliance for purposes such as:
  • Idea generation and exploratory research
  • Language editing and stylistic refinement
  • Interactive online searching using LLM-enhanced search engines
  • Literature organization and classification
  • Coding and programming assistance
Authors must ensure that all submitted content meets rigorous scientific and scholarly standards of research, validation, and critical assessment, and that the intellectual contribution originates from the author. Some journals may restrict the use of Generative AI tools to language enhancement only; therefore, authors are strongly advised to consult the relevant editor prior to manuscript submission.
 
Generative AI tools must not be credited as authors. Such tools cannot assume responsibility for scholarly content, enter into copyright or licensing agreements, or provide contractual assurances regarding the integrity of a work. Authorship entails accountability, consent to publication, and ethical responsibility—obligations that are inherently human and cannot be fulfilled by AI systems.
 
Authors are required to explicitly disclose any use of Generative AI tools within their manuscript. This disclosure must include:
  • The full name of the tool used, including version number
  • A description of how the tool was applied
  • The purpose for which the tool was used
For journal articles, this statement must appear in the Methods or Acknowledgments section. Book authors must inform their editorial contact of any intended AI use at the earliest possible stage—either during proposal submission or manuscript preparation. Upon approval, the disclosure must be included in the book’s preface or introduction. This transparency enables editors to evaluate whether AI tools have been used appropriately. The journal retains full discretion regarding publication decisions to ensure compliance with ethical and editorial standards.
 
Authors intending to use Generative AI tools must ensure that the selected tools are suitable for the intended purpose and that their terms of use provide sufficient protections related to intellectual property rights, confidentiality, and data security.
 
Authors must not submit manuscripts in which Generative AI tools have been used to replace core scholarly responsibilities, including but not limited to:
  • Automated text or code generation without thorough human review and revision
  • Use of synthetic data to replace missing research data without a robust methodological framework
  • Generation of inaccurate, misleading, or unverified content, including abstracts or supplementary materials
Such cases may be subject to editorial investigation.
 
At present, Advances in Analysis and Applied Mathematics does not permit the use of Generative AI tools in the creation or modification of images, figures, or original research data intended for publication. The term “images and figures” includes photographs, charts, graphs, data tables, medical images, image fragments, computer code, and mathematical formulas. “Modification” encompasses actions such as adding, removing, concealing, relocating, or altering any element within an image or figure.
 
Any use of Generative AI or AI-assisted technologies in the research process must be accompanied by appropriate human oversight and full transparency. As research ethics standards related to AI continue to evolve, the journal will update its editorial policies accordingly.

Editors and Peer Reviewers

Advances in Analysis and Applied Mathematics is committed to maintaining the highest levels of editorial integrity and transparency. The use of unpublished manuscripts in Generative AI systems poses significant risks to confidentiality, intellectual property, and personal data protection. Consequently, editors and peer reviewers must not upload unpublished manuscripts, images, files, or associated information into any Generative AI tools.

Editors

Editors are responsible for safeguarding the quality and ethical standards of published research and must maintain strict confidentiality throughout the submission and peer review process.
 
Due to the risks associated with confidentiality breaches and proprietary rights violations, editors are prohibited from submitting unpublished manuscripts or related materials to Generative AI platforms. Unless explicitly authorized, editors should consult their designated journal contact before using any Generative AI tools. Additional guidance is available through the journal’s editorial code of conduct resources.

Peer Reviewers

Peer reviewers are selected for their subject-matter expertise and are expected to conduct independent and critical evaluations of submitted work. Generative AI tools must not be used to analyze, interpret, or summarize submitted manuscripts or proposals as part of the peer review process. Accordingly, reviewers must not upload unpublished materials into Generative AI systems.
 
Generative AI may be used solely to assist with language refinement of peer review reports. Reviewers remain fully responsible for the accuracy, objectivity, and integrity of their evaluations at all times.