Resonance: Journal of Global Music Studies recognizes that artificial intelligence (AI) and AI-assisted technologies can contribute to scholarly research, translation, musical analysis, artistic practice, and publication workflows when used responsibly. The journal requires transparency, human intellectual accountability, respect for confidential and culturally sensitive materials, and the preservation of scholarly and artistic integrity. AI assistance must never be used to fabricate evidence, conceal plagiarism, misrepresent authorship, or replace independent human editorial judgment.

This policy applies to authors, reviewers, editors, guest editors, translators, interviewers, contributors, and editorial or production personnel involved in the preparation, assessment, and publication of content in Resonance.

It covers generative AI, large language models, machine-learning systems, automated translation and transcription, AI-assisted image and sound processing, music generation, computational analysis, and other relevant technologies. Requirements are applied according to the tool's actual function, the materials involved, and the potential effect on scholarly content, creative originality, confidentiality, and publication integrity.

1. General Principles

The journal's approach to AI is based on the following principles:

• Human Accountability: Named human contributors remain responsible for the originality, accuracy, integrity, and ethical acceptability of submitted and published content.
• Transparency: Substantive AI assistance must be disclosed in a manner that allows editors and readers to understand its role in the work.
• Independent Intellectual Judgment: AI systems must not replace the critical reasoning, research responsibility, specialist evaluation, or editorial decision-making expected of human contributors.
• Source Integrity: Sources, quotations, recordings, performances, translations, data, and research findings must be authentic and accurately represented.
• Confidentiality: Unpublished manuscripts, review materials, personal data, restricted research records, and protected creative works must not be disclosed to unauthorized AI systems.
• Copyright and Cultural Responsibility: AI use must respect relevant intellectual property, consent, privacy, archival conditions, and cultural protocols.
• Proportionate Evaluation: Editorial concerns involving AI must be assessed through evidence, context, and appropriate human review rather than relying solely on automated detection.

The journal evaluates AI use according to its effect on the work. Routine technical assistance, substantive scholarly or creative assistance, and the fabrication or misrepresentation of evidence raise different editorial considerations.

2. Human Authorship & Intellectual Responsibility

AI systems cannot be listed as authors or co-authors of submissions to Resonance. Authorship requires identifiable human intellectual contribution, approval of the submitted work, and accountability for its accuracy, originality, and ethical integrity.

Chatbots, large language models, image generators, music generators, automated translation systems, transcription software, and similar technologies do not meet these requirements.

• Human authors must make and defend the principal scholarly or artistic decisions underlying their work.
• Authors must review, verify, and appropriately revise AI-assisted material before submission.
• Authors must confirm that quotations, references, findings, interpretations, musical examples, and other substantive content are accurate and appropriately attributed.
• Authors must identify substantive AI use and clarify the contribution of relevant human collaborators.
• AI output does not itself establish originality, reliable authorship, copyright ownership, or permission to reproduce third-party materials.

AI-generated text or media may be examined as an object of research or incorporated into an appropriately disclosed creative experiment. Such use does not make the AI system an author and does not relieve human contributors of responsibility for the work's integrity.

3. Categories of AI Use by Authors

The journal distinguishes routine technical assistance from substantive uses that affect the research process, interpretation, presentation, or creative contribution.

Permitted Assistance

Subject to relevant disclosure, verification, consent, and rights requirements, authors may use AI for:

• Grammar correction, language polishing, and readability improvements.
• Translation assistance and multilingual terminology comparison.
• Title, keyword, abstract, and organizational suggestions.
• Coding assistance, data preparation, and computational analysis.
• Reference formatting and bibliographic organization, with source verification.
• Audio transcription, speech recognition, and musical notation assistance.
• Sound analysis, classification, source separation, and visualization.
• Clearly identified experimental or creative AI applications where suitable for the publication category.

Permitted assistance does not amount to automatic acceptance of the resulting content. Editors may request additional documentation where the nature of AI use affects originality, research reliability, artistic integrity, rights, or ethical compliance.

Prohibited Practices

• Presenting AI-generated scholarly arguments or conclusions as independently developed human reasoning without meaningful human intellectual contribution.
• Inventing, altering, or fabricating citations, quotations, archival sources, interviews, fieldnotes, data, musical examples, or research findings.
• Falsifying images, recordings, scores, performance documentation, or analytical outputs presented as authentic research evidence.
• Impersonating real authors, composers, performers, interviewees, research participants, reviewers, or editors.
• Concealing plagiarism, misleading text reuse, fabricated references, or unattributed translation through AI paraphrasing or transformation.
• Uploading confidential, restricted, unpublished, or rights-protected materials without the necessary authority and safeguards.
• Inserting hidden prompts, invisible text, deceptive metadata instructions, or machine-readable commands intended to manipulate automated screening, reviewer behavior, or editorial decisions.
• Falsely claiming that research procedures, source checks, interviews, performances, or analytical operations were carried out when they were not.

4. AI Disclosure Requirements

Authors must disclose substantive AI assistance at submission. Disclosure should be sufficiently specific to explain how AI contributed to preparing the manuscript, conducting the research, creating or processing artistic material, or generating supporting content.

Where applicable, the disclosure should identify:

1. The name of the AI tool, model, software, or service and its relevant version where known.
2. The specific purpose for which the technology was used.
3. The stages of manuscript preparation, research, analysis, translation, or artistic production affected.
4. The nature of the input materials and the resulting output, where relevant to evaluation.
5. The human verification, correction, evaluation, or other oversight performed.
6. Any important technical limitations, rights conditions, confidentiality safeguards, or reproducibility information.

The level of detail should be proportionate to the use. Routine proofreading does not ordinarily require a technical description. AI-assisted analysis of a research corpus, a substantial translation, or a synthetic musical recording requires more specific documentation.

Where AI materially contributes to research methods, data processing, or analysis, its use should be described in the Methods section or an equivalent methodological statement. Substantive writing or translation assistance may be disclosed in a dedicated AI Use Statement or other appropriate location, with identifying information separated where necessary for anonymous review.

If no generative or substantive AI assistance was used, authors may provide a corresponding declaration. The absence of an AI-use statement must not be treated as an automatic certification that the manuscript contains no errors or integrity concerns.

5. Suggested AI Use Statements

The following examples may be adapted according to the actual use of AI. Authors must not submit a statement that inaccurately describes their research or preparation process.

General AI-Assisted Preparation

During the preparation of this manuscript, the author(s) used [tool name and relevant version] for [specific purpose]. The assistance was limited to [description of tasks or manuscript components]. All substantive outputs were reviewed, corrected, and verified by the author(s), who remain fully responsible for the accuracy, originality, integrity, and final content of the manuscript.

AI-Assisted Research or Analysis

AI-assisted software [tool name and relevant version] was used for [data processing, transcription, classification, visualization, or analytical task]. The system was applied to [description of materials] under [relevant permissions or safeguards]. The author(s) verified the outputs through [verification procedure] and considered relevant methodological limitations. The research interpretations and conclusions were determined by the author(s).

AI-Assisted Creative or Musical Production

The submitted creative work incorporates AI-assisted [sound generation, composition, audio transformation, performance simulation, or other process] produced using [tool name and relevant version]. Human contributors were responsible for [creative decisions and editing]. The AI-assisted components are identified in the submission, and the author(s) have considered relevant permissions, attribution, and publication rights.

No Substantive AI Use

The author(s) declare that no generative AI or substantive AI-assisted technologies were used in the research, analysis, creative production, or preparation of this manuscript. Routine spelling or grammar tools, where used, did not materially alter its scholarly or artistic content.

If an author discovers that an earlier disclosure was incomplete or inaccurate, the Editorial Office should be informed promptly. Appropriate clarification or correction may be required before or after publication.

6. AI in Research Methods, Data & Scholarly Analysis

AI-assisted methods may form a legitimate part of research in musicology, ethnomusicology, computational music studies, sound studies, digital humanities, and related disciplines.

When AI materially affects the research procedure or results, authors must provide sufficient information for readers and editors to understand the method and evaluate its limitations.

• Research Design: Explain why AI-assisted procedures were appropriate to the research question and how they fit within the overall methodology.
• Data Provenance: Identify the origin, selection, and relevant rights or access conditions of input data and source materials.
• Software Documentation: Identify relevant tools, versions, settings, prompts, model configurations, or processing procedures where necessary for methodological assessment.
• Validation: Explain how automated outputs were checked, including comparison with source materials, human coding, manual listening, independent analysis, or other appropriate procedures.
• Bias and Limitations: Consider language coverage, corpus representation, model bias, errors, uncertainty, and other limitations relevant to the findings.
• Reproducibility: Provide sufficient documentation for meaningful methodological evaluation, subject to confidentiality, rights, and technical limitations.
• Human Interpretation: Distinguish machine-generated classifications, predictions, or summaries from the author's own scholarly interpretations and conclusions.

AI-generated references and quotations must be verified against authentic sources. A plausible-looking citation supplied by a model is not evidence that the cited publication exists or supports the claim.

Where an AI output itself is an object of scholarly analysis, authors should document its provenance and production context rather than misrepresenting it as an independent scholarly authority.

7. AI in Music, Sound & Creative Practice

Because Resonance publishes research and creative contributions involving musical scores, lyrics, performances, recordings, poetic texts, and audiovisual materials, AI-assisted musical production requires particular care.

Permissible Research and Creative Applications

Subject to the relevant section policy and appropriate disclosure, possible applications include:

• Computational music analysis and automated feature extraction.
• Music transcription and optical music recognition.
• Audio enhancement, noise reduction, and source separation.
• AI-assisted composition, arrangement, or sound design as a documented creative practice.
• Synthetic sound or generated music used as clearly identified research material.
• Performance analysis, recording comparison, and audiovisual annotation.
• Experimental relationships between poetry, musical sound, and generative systems.

An AI-assisted creative work may be considered when it provides an identifiable human intellectual or artistic contribution and satisfies the relevant section's standards. Disclosure alone does not guarantee acceptance.

Authenticity and Representation

Synthetic or substantially altered musical material must be distinguished from authentic performances, historical recordings, field recordings, archival evidence, and documentary sources.

Authors must not fabricate a supposed live performance, traditional musical practice, historical composition, field recording, interview, or participant statement and present it as genuine evidence.

AI-assisted reconstructions of damaged or incomplete audio, notation, or archival sources must identify the reconstructed elements and relevant uncertainty. Interpretive reconstruction should not be presented as a verified original where the underlying evidence does not support that claim.

Performers, Voices and Rights

AI-generated or modified audio may involve the rights and interests of composers, lyricists, performers, recording producers, and other contributors. Voice cloning, performance simulation, and the use of identifiable artistic identities require particular scrutiny.

Authors must obtain necessary permissions and avoid misleading impersonation, unauthorized exploitation of protected materials, or false attribution. Publication under an open-access license does not override third-party rights.

Completely automated creative output without a demonstrable human contribution may be unsuitable for publication as an original authored artistic work. Such output may nevertheless be relevant to a properly contextualized scholarly investigation of AI-generated music or sound.

8. Fieldwork, Interviews, Archives & Sensitive Materials

Research involving human participants, oral histories, ethnographic records, private recordings, archives, cultural communities, or restricted musical traditions may create confidentiality and consent obligations that are incompatible with unrestricted processing by external AI services.

Materials requiring special protection may include:

• Unpublished interviews, oral histories, and identifiable participant statements.
• Private fieldnotes, ethnographic records, and non-public research data.
• Recordings of performances, rituals, ceremonies, rehearsals, lessons, or private events.
• Unpublished compositions, scores, arrangements, translations, and restricted archival documents.
• Materials concerning minors, vulnerable participants, or identifiable private individuals.
• Sacred, ceremonial, community-restricted, or culturally sensitive knowledge and artistic practices.

These materials must not be uploaded to external AI systems unless the researcher has the necessary authority, relevant consent or other lawful basis, and safeguards appropriate to the information and service involved.

Researchers should consider the service's retention practices, permitted data uses, access controls, confidentiality commitments, security arrangements, and possible transfers of data to third parties. An assertion that a tool is private is not sufficient by itself to establish that a particular use is ethically or legally permissible.

De-identification may reduce certain risks but does not automatically eliminate the possibility of identifying a speaker, performer, community, location, or participant. Audio recordings, distinctive musical practices, and contextual details may contain identifying information even when names are removed.

AI-assisted transcription and translation must be checked against the original materials, with particular attention to culturally specific terminology, speakers, names, musical concepts, and potentially consequential errors.

Authors must also comply with the journal's Fieldwork & Interview Ethics Policy.

9. AI Use by Reviewers

Manuscripts under review are confidential scholarly communications. Reviewers must protect manuscripts, associated media, author information, review correspondence, and other non-public materials entrusted to them.

• No Unauthorized Manuscript Processing: Reviewers must not upload or enter manuscripts, abstracts, excerpts, figures, tables, scores, recordings, datasets, supplementary files, or manuscript-derived summaries into external AI systems without prior authorization from the journal and the necessary confidentiality safeguards and permissions.
• Human Evaluation: A reviewer must personally assess the manuscript's scholarly contribution, evidence, methods, interpretation, and ethical issues.
• Limited Language Support: AI tools may be used to polish the reviewer's own independently prepared comments only where the use does not disclose confidential manuscript information and is consistent with journal instructions.
• Transparency: Material AI assistance in preparing a review should be reported to the handling editor.
• No Delegated Judgment: Reviewers must not use AI-generated assessments or recommendations as a substitute for their own scholarly judgment.
• Source Verification: Reviewers remain responsible for any references, factual assertions, or technical criticisms included in their reports.

The journal may disregard a review report that relies on unauthorized AI processing, discloses confidential information, contains fabricated observations, or fails to represent an independent human assessment.

Reviewers who are uncertain whether a particular technology is permissible should obtain guidance from the handling editor before using it.

See the journal's How to Review and Review Criteria.

10. AI Use by Editors, Guest Editors & Editorial Staff

Editors and editorial personnel may use appropriately authorized AI-assisted tools for limited administrative, technical, or production functions. The use of such systems must remain consistent with manuscript confidentiality, editorial independence, the journal's privacy obligations, and applicable data-protection requirements.

Appropriate uses may include:

• Formatting and metadata checks.
• Language polishing of non-confidential administrative communications.
• Workflow organization and technical quality checks.
• Assistance with production tasks where appropriate authorization and safeguards exist.

Editors, guest editors, and staff must not upload confidential manuscripts, reviewer identities, unpublished research materials, personal correspondence, or internal editorial records to unauthorized AI platforms.

AI tools may assist authorized checks but must not independently determine editorial screening outcomes, reviewer selection, research quality, revision requirements, acceptance, rejection, corrections, expressions of concern, or retractions.

Final editorial authority remains with responsible human editors. AI-generated summaries, risk indicators, classification results, or recommendations must be verified and cannot substitute for evidence-based editorial judgment.

Where the journal uses AI assistance in manuscript production, translation, accessibility preparation, or other substantive publication activities, the relevant use should be appropriately disclosed to affected contributors and documented according to its significance.

Guest editors and external production partners are subject to the same confidentiality and independence requirements as other authorized editorial personnel.

11. Data Protection, Tool Authorization & Confidentiality

The responsible use of AI requires an assessment of both the purpose of the tool and the information to which it will be given access.

Before processing confidential or restricted material through an AI-assisted system, the responsible person should consider:

1. Whether the intended use is necessary and authorized.
2. Whether the material is confidential, unpublished, copyrighted, personally identifying, or culturally restricted.
3. Whether the service retains inputs, uses them for model development, or shares them with other parties.
4. Whether appropriate access controls, contractual terms, confidentiality safeguards, and lawful processing arrangements are in place.
5. Whether the required consents and third-party permissions permit the proposed processing.
6. Whether a less intrusive or locally controlled method can accomplish the task.
7. Whether the use should be recorded or disclosed to the relevant editorial or research participants.

A private account, paid subscription, enterprise label, or promise that an AI system does not train on user data does not by itself establish that all confidentiality, copyright, consent, or data-protection obligations have been satisfied.

Confidential editorial material must only be processed through systems authorized for the relevant purpose. Authorization for one administrative task does not automatically permit the use of the same tool to evaluate unpublished manuscripts or process sensitive research evidence.

12. AI Detection, Screening & Editorial Assessment

The journal may examine whether a manuscript's AI use is consistent with its publication standards. Relevant checks may involve editorial reading, examination of disclosures, source verification, comparison with original materials, technical review, or additional specialist assessment.

AI-detection software cannot independently establish that particular text was generated by AI, that a disclosure is false, or that publication misconduct has occurred. Automated scores and classifications are indicators that may warrant further consideration, not conclusive findings.

Editorial assessment may consider:

• Whether the declared AI use is consistent with the actual materials and research procedures.
• Whether references, quotations, recordings, datasets, and other evidence can be verified.
• Whether relevant human intellectual or artistic contributions are identifiable.
• Whether confidential or rights-protected information was processed without authorization.
• Whether synthetic or altered material has been misrepresented as authentic evidence.
• Whether metadata, hidden text, or machine-readable instructions were inserted to manipulate editorial or automated systems.
• Whether additional explanations or verification are necessary to establish the work's integrity.

The Editorial Office may request a revised AI Use Statement, technical documentation, source verification, an explanation of analytical methods, correction of inaccurate material, or other reasonable supporting information.

Authors should normally be given an appropriate opportunity to respond to substantive concerns before a final adverse determination. Immediate interim measures may be taken when necessary to protect confidential information or prevent further harm.

The journal must not treat an author's writing style, language background, use of conventional academic expressions, or an automated detection score as sufficient proof of undisclosed AI use.

13. Non-Compliance & Editorial Actions

Suspected violations are assessed according to their nature, seriousness, supporting evidence, and effect on scholarly or creative integrity. The journal may seek clarification and advice from qualified specialists or relevant institutions where necessary.

Depending on the circumstances, possible actions include:

• Clarification: Request an explanation or correction of incomplete or unclear disclosure.
• Additional Verification: Request relevant sources, methodological details, permissions, or documentation.
• Revision: Require correction, removal, or replacement of problematic AI-assisted material.
• Suspension: Pause editorial consideration while a substantial integrity or confidentiality concern is examined.
• Rejection: Reject a submission when serious or unresolved violations make it unsuitable for publication.
• Institutional Communication: Contact relevant institutions or competent parties when serious concerns warrant further investigation or action.
• Post-Publication Action: Issue a correction, expression of concern, retraction, or other appropriate notice where necessary to protect the scholarly record.
• Reviewer or Editorial Action: Disregard compromised review reports, reassign editorial responsibilities, or take other proportionate measures where confidentiality or professional independence has been violated.

Minor disclosure errors should not automatically be treated as equivalent to deliberate fabrication, serious misappropriation, or unauthorized disclosure of sensitive information. At the same time, significant violations may justify rejection or formal post-publication action.

A confirmed violation does not automatically require retraction. The appropriate response depends on whether the problem can be corrected and whether the reliability or integrity of the published contribution has been materially undermined.

The journal will manage relevant conflicts of interest and consider appropriate opportunities for explanation or appeal. Decisions concerning corrections, expressions of concern, and retractions follow the Corrections and Retractions Policy.

14. Application Across Publication Categories

The journal publishes original research, reviews, interviews, translations, musical scores, performance reflections, poetry, scholarly exchanges, and other forms of music-related work. AI-related requirements are applied in relation to the publication category and the claims made by the contribution.

• Original Research Articles: AI-assisted research methods, data processing, analysis, or writing must be disclosed and documented with sufficient detail for scholarly evaluation. Human authors remain responsible for all findings and conclusions.
• Translations & Source Texts: AI translation must be verified against authentic source material, with relevant textual and cultural limitations acknowledged. Original authorship and translation rights must be respected.
• Dialogues & Interviews: AI-assisted transcription, translation, summarization, or editing must respect participant consent and preserve the accuracy of the original statements.
• Musical Scores & Performance Contributions: AI-generated or transformed music, notation, recordings, or performance simulations must be identified and supported by relevant documentation and rights.
• Poetry & Creative Writing: Substantive generative assistance must be disclosed, and the submission must demonstrate appropriate human creative contribution and artistic integrity.
• Reviews, Forum Contributions & Reflective Essays: AI may assist limited preparation tasks, but the author's evaluation, interpretation, critical position, and substantive claims must remain independently developed and verified.

AI-assisted creative work should be evaluated according to the purpose and standards of the relevant artistic or editorial section. It must not be misclassified as original empirical research solely because it incorporates technical experimentation.

All content types remain subject to appropriate editorial oversight and the journal's Special Issues & Non-Research Content Review Policy.

15. Author AI Compliance Checklist

Before submission, authors should confirm that:

1. All named authors are human contributors who have approved the manuscript and accept responsibility for its content.
2. Substantive AI use has been disclosed accurately and with sufficient detail.
3. AI-assisted passages, translations, references, analytical outputs, or other materials have been independently verified.
4. All cited sources, quotations, datasets, interviews, archival records, and musical examples are authentic and appropriately attributed.
5. No generated or altered material is presented misleadingly as authentic documentary or research evidence.
6. Relevant methodological information is documented where AI materially affects data processing, analysis, or findings.
7. Necessary consent, copyright, confidentiality, and data-protection conditions have been respected.
8. AI-assisted musical or creative elements are clearly identified where relevant.
9. No hidden instructions or deceptive metadata have been inserted to manipulate editorial or automated review processes.
10. The final manuscript complies with the journal's originality, ethics, and publication requirements.

16. Policy Interpretation & Review

The Editorial Office is responsible for interpreting and applying this policy in conjunction with the journal's other publication requirements. Complex or novel AI applications may require case-specific editorial or specialist consideration.

This policy may be revised periodically in response to developments in AI technologies, scholarly publishing standards, music and sound research practices, copyright, privacy, research ethics, and the technical conditions of AI-assisted creative work.

Material policy changes should be communicated clearly to authors, reviewers, and editors. Revisions should identify their effective date and should not be represented as having been in force before formal adoption.

Editorial Statement: Resonance: Journal of Global Music Studies welcomes responsible technological innovation in scholarly and artistic practice. The journal recognizes AI as a potentially valuable instrument for research, translation, musical analysis, accessibility, and creative experimentation. Its use must remain transparent, critically evaluated, ethically responsible, and subject to human intellectual accountability. The protection of genuine evidence, confidential research, cultural knowledge, artistic attribution, and independent editorial judgment remains essential to the journal's publication standards.

Contributors should also consult the journal's Publication Ethics, Plagiarism Policy, Fieldwork & Interview Ethics Policy, and Corrections and Retractions Policy.

Contact: Questions concerning the interpretation of this policy or disclosure of AI use may be directed to the Resonance Editorial Office: [email protected].

Original effective date: May 28, 2026. Last updated: October 28, 2026.