AI and Generative Tools

  1. Purpose and Scope

AMG Transcend Association recognizes that artificial intelligence and generative technologies may be used in research, manuscript preparation, data analysis, scholarly communication, and publishing workflows.

This policy establishes publisher-level principles for the responsible use of artificial intelligence, machine-learning systems, large language models, generative AI, and related AI-assisted tools across the journals published by AMG Transcend Association.

The policy applies, as relevant, to authors, reviewers, Editors-in-Chief, editors, Editorial Board members, and editorial or publishing personnel.

Individual journals may establish additional or more restrictive requirements appropriate to their disciplines, editorial processes, and types of content.

  1. Fundamental Principle of Human Responsibility

Artificial intelligence does not replace human scholarly responsibility.

Authors remain responsible for all content submitted or published under their names, including text, references, data representations, analyses, images, code, interpretations, and other material produced or modified with the assistance of AI tools.

Reviewers remain responsible for their review reports and recommendations.

Editors remain responsible for editorial assessments and decisions.

The use of an AI system does not transfer, reduce, or remove the responsibilities associated with authorship, peer review, editorial judgment, research integrity, confidentiality, or publication ethics.

Users must independently evaluate and verify AI-assisted outputs before relying on them in scholarly or editorial work.

  1. AI Systems Cannot Be Authors

Artificial intelligence systems, chatbots, language models, or other automated tools must not be listed as authors or co-authors.

Authorship requires human intellectual contribution, approval, responsibility, and accountability that an AI system cannot assume.

AI tools must not be cited or described in a manner that falsely attributes human authorship, responsibility, or accountability to the system.

Where use of an AI tool requires disclosure, that use must be described transparently rather than represented through authorship.

  1. Use of AI in Manuscript Preparation

AI-assisted tools may be used in manuscript preparation where their use is consistent with scholarly integrity, applicable journal requirements, and full human responsibility for the resulting content.

Possible uses may include:

  • language and grammar assistance;
  • stylistic or readability improvement;
  • translation;
  • organizational or structural assistance;
  • summarization used as part of an author-controlled drafting process;
  • reference-management assistance;
  • coding or computational assistance; and
  • other functions permitted by the relevant journal.

Authors must critically review and verify all AI-assisted material.

AI-generated or AI-assisted content must not introduce fabricated facts, unsupported claims, nonexistent references, false quotations, inappropriate reuse of third-party material, misleading interpretations, or other inaccuracies.

The use of AI does not relieve authors of responsibility for originality, appropriate attribution, copyright compliance, or the accuracy of references.

  1. Disclosure of AI Use

Material use of generative AI or other AI-assisted technologies in manuscript preparation must be disclosed when required by the applicable journal.

A disclosure should identify, where relevant:

  • the tool or system used;
  • the purpose for which it was used; and
  • the nature or extent of its contribution.

Routine tools whose functions are limited to spelling, grammar, reference formatting, or similarly minor technical assistance may be exempt from disclosure where the relevant journal so provides.

AI use that forms part of the research methodology, including AI-based analysis, modeling, classification, prediction, image analysis, or other substantive research procedures, must be reported in the methods or other appropriate section with sufficient detail for scientific evaluation.

Disclosure of permitted AI use does not by itself imply misconduct or diminish the scholarly value of a manuscript.

  1. AI as Part of the Research Methodology

Artificial intelligence, machine learning, computational models, or related technologies may legitimately form part of research methodology.

Where such methods materially contribute to the research, authors must report them with sufficient transparency to permit appropriate assessment.

Relevant information may include:

  • the system, model, algorithm, software, or platform used;
  • the scientific purpose of its use;
  • relevant versions or configurations;
  • data sources and preprocessing;
  • training and validation procedures, where applicable;
  • important parameters or settings;
  • evaluation methods and performance measures;
  • human oversight;
  • limitations relevant to interpretation; and
  • other information necessary to understand or reproduce the analytical approach.

AI-based research methods must be subject to the same expectations of scientific rigor, data integrity, reproducibility, ethics, and transparent reporting as other research methods.

  1. AI-Generated and Synthetic Data

AI or computational methods may be used to generate synthetic, simulated, augmented, or modeled data where such use is scientifically justified and appropriate to the research design.

Such data must be clearly identified as generated, synthetic, simulated, augmented, or modeled and must not be presented as directly observed experimental or clinical data.

Authors must describe the method of generation and the role of the generated data with sufficient transparency for readers and reviewers to understand their provenance and purpose.

AI must not be used to fabricate research observations, experimental results, participant data, measurements, or other evidence and present them as genuine empirical findings.

  1. Data, Images, Figures, and Other Research Outputs

AI-assisted processing of data, images, figures, audio, video, spectra, graphical outputs, or other research materials must not misrepresent the underlying evidence.

Authors must distinguish legitimate scientific processing or analysis from alterations that create a false or misleading representation of research findings.

Where AI-assisted image or data processing materially affects the reported research, the relevant methodology must be described transparently.

AI tools must not be used to:

  • fabricate experimental images or data;
  • introduce or remove scientifically meaningful features without legitimate methodological justification;
  • conceal manipulation;
  • create misleading representations of observations; or
  • falsify the provenance of research materials.

Applicable requirements in the Data Integrity and Reproducibility and other relevant policies remain in force.

  1. References and Source Verification

AI systems may generate inaccurate, incomplete, inappropriate, or nonexistent references.

Authors are responsible for verifying every reference included in a manuscript, regardless of how it was identified or generated.

Authors must ensure that:

  • cited works exist;
  • bibliographic information is accurate;
  • references support the statements for which they are cited;
  • sources have been consulted sufficiently to support their use; and
  • citations are not fabricated or included merely because they were suggested by an AI system.

AI-generated output should not be treated as an authoritative substitute for the underlying scholarly or primary source.

  1. Confidentiality and Sensitive Information

AI tools must not be used in ways that compromise the confidentiality, privacy, intellectual property, or security of unpublished or restricted information.

Authors must exercise particular caution when AI systems are used with:

  • confidential research data;
  • personal or identifiable participant information;
  • sensitive datasets;
  • unpublished proprietary information;
  • material subject to contractual restrictions; or
  • information protected by ethical or legal obligations.

Use of an external AI service must be compatible with applicable consent, ethics approval, data-protection requirements, contractual obligations, and intellectual-property rights.

Information must not be uploaded to an AI service where doing so would expose it to unauthorized retention, reuse, training, disclosure, or third-party access contrary to applicable requirements.

  1. Use of AI by Peer Reviewers

Peer review is a confidential process based on the reviewer’s independent expertise and judgment.

Reviewers must not upload submitted manuscripts, figures, supplementary files, confidential data, or substantive unpublished manuscript content to external AI systems where confidentiality cannot be assured.

AI tools must not replace the reviewer’s own critical scientific assessment.

Where permitted by the relevant journal and compatible with confidentiality requirements, reviewers may use limited AI-assisted tools for functions such as language or organizational assistance. The reviewer remains fully responsible for the accuracy, substance, tone, and recommendation contained in the review.

Any material AI use in peer review must be handled according to the disclosure requirements of the relevant journal.

  1. Use of AI by Editors and Editorial Personnel

Editorial decisions must remain under human authority and accountability.

AI tools may support appropriate administrative, technical, or workflow functions, such as:

  • organization of editorial information;
  • technical compliance checks;
  • workflow assistance;
  • administrative communications;
  • similarity or integrity screening; and
  • other non-decisional support functions.

AI-generated assessments, rankings, scores, or recommendations must not independently determine whether a manuscript is accepted, rejected, sent for review, or otherwise evaluated.

Editors must independently assess relevant information and remain accountable for editorial decisions.

Unpublished manuscripts and confidential peer-review materials must not be submitted to external AI systems where confidentiality cannot be assured.

  1. AI Detection and Automated Screening

Automated tools may assist editors in identifying potential issues requiring further examination, but their outputs must not be treated as conclusive evidence of misconduct or policy violation.

This principle applies to tools intended to detect:

  • AI-generated text;
  • plagiarism or textual similarity;
  • image manipulation;
  • fabricated or unusual references;
  • statistical anomalies; or
  • other potential integrity concerns.

Automated indicators must be interpreted in context and, where necessary, followed by human assessment and appropriate clarification.

Authors must not be accused of inappropriate AI use solely on the basis of an automated detection score.

  1. Prohibited Uses

AI and generative tools must not be used to:

  • fabricate or falsify data, results, references, ethical approvals, consent statements, reviewer reports, or other scholarly information;
  • disguise plagiarism or inappropriate reuse;
  • misrepresent generated content as empirical evidence;
  • conceal material alterations of data or images;
  • fabricate reviewer identities or manipulate peer review;
  • generate false declarations concerning authorship, funding, competing interests, data availability, research ethics, or clinical-trial registration;
  • compromise confidential manuscripts or peer-review information;
  • impersonate another person in scholarly or editorial communication;
  • circumvent legitimate editorial, ethical, or integrity controls; or
  • transfer responsibility for scholarly or editorial decisions from accountable human participants to automated systems.

Use of AI in connection with fraudulent or deceptive conduct may also be addressed under the Publication Ethics and Research Integrity policy.

  1. Intellectual Property, Attribution, and Third-Party Rights

Users of AI tools remain responsible for ensuring that resulting content complies with applicable copyright, licensing, attribution, confidentiality, and intellectual-property requirements.

The use of an AI system does not guarantee that an output is original or free from third-party rights.

Authors must verify that material included in a manuscript can lawfully and ethically be published and licensed under the terms applicable to the article.

AI tools must not be used to conceal the origin of copyrighted, licensed, confidential, or otherwise protected material.

  1. Bias, Limitations, and Scientific Interpretation

AI systems may produce incomplete, inaccurate, biased, inconsistent, or apparently plausible but unsupported outputs.

Researchers must critically evaluate such limitations where AI materially contributes to research methods, analyses, or interpretation.

Where relevant to the validity or generalizability of the study, authors should report important limitations associated with:

  • training data;
  • model performance;
  • validation;
  • representativeness;
  • bias;
  • uncertainty;
  • generalizability; or
  • other characteristics of the AI method.

AI-generated outputs must not substitute for appropriate scientific validation.

  1. Concerns and Non-Compliance

Concerns about AI use must be assessed according to their nature, seriousness, transparency, and effect on the reliability or integrity of the work.

Editors may request:

  • clarification of how an AI tool was used;
  • an updated disclosure statement;
  • methodological information;
  • original or supporting data;
  • relevant source files;
  • confirmation of references;
  • additional expert review; or
  • other information necessary to evaluate the concern.

Failure to disclose required AI use, provision of materially misleading information, fabricated content, confidentiality breaches, or other misuse may result in appropriate editorial action.

Not every undisclosed or inappropriate use of an AI tool constitutes research misconduct. Actions must be evidence-based and proportionate to the effect of the issue on authorship, transparency, confidentiality, research integrity, and the scholarly record.

  1. Post-Publication Issues

Credible concerns concerning AI-assisted or AI-generated content identified after publication must be evaluated in the same manner as other publication-integrity concerns.

Where the underlying work remains reliable and the primary problem concerns incomplete disclosure or reporting, clarification or correction may be sufficient.

Where AI-related practices materially undermine the authenticity, validity, provenance, or reliability of the published work, an expression of concern, retraction, or other appropriate action may be required.

Post-publication action must be taken in accordance with the Publication Ethics and Research Integrity and Corrections, Retractions and Expressions of Concern policies.

  1. Relationship with Other Policies

This policy should be read together with applicable AMG Transcend Association and journal policies concerning:

  • Authorship and Contributor Responsibilities;
  • Publication Ethics and Research Integrity;
  • Data Integrity and Reproducibility;
  • Peer Review Principles;
  • Research Ethics;
  • Human and Animal Research Ethics;
  • Conflict of Interest and Competing Interests;
  • Editorial Independence and Governance; and
  • Corrections, Retractions and Expressions of Concern.

Individual journals may establish additional or more restrictive requirements concerning the use and disclosure of AI and generative tools.