Can Generative AI Help Improve the Wording of Peer-Review Comments?

Can AI Make Peer-Review Comments More Constructive Without Changing Their Meaning?

You have finished evaluating a manuscript and identified several concerns about its methodology, interpretation, and reporting. Your observations are justified, but the comments you drafted are rather direct.

One sentence reads, "The authors clearly do not understand the limitations of their research design." Another says, "The statistical analysis is poorly explained and needs to be fixed."

You want to communicate the same concerns without unnecessarily antagonizing the authors. Generative AI seems useful for making the language more precise, professional, and constructive.

Yet peer-review comments are not ordinary writing. They may contain confidential information about an unpublished manuscript, and even seemingly minor language changes can alter the severity or substance of a methodological criticism.

Can AI help improve the wording while leaving the reviewer's scientific judgment intact?

Yes, but Language Editing Must Be Authorized and Carefully Verified

How AI Can Improve Reviewer Communication Without Replacing Scholarly Judgment

Constructive Peer Review Is More Than Polite Writing

A constructive review identifies a concern, explains why it matters, and provides sufficient direction for the authors to respond.

Professional language is important, but politeness alone does not make a comment useful. A courteous statement that offers no identifiable methodological concern may be less helpful than a direct criticism supported by clear evidence.

For example, telling authors that their discussion "could benefit from further development" may sound diplomatic but provides little guidance. Explaining that their causal interpretation exceeds what an observational design can establish is more specific and actionable.

Generative AI may help refine the presentation of a criticism, but the underlying assessment must originate from and remain defensible by the reviewer.

Which Aspects of Reviewer Comments Can AI Potentially Improve?

When permitted, AI assistance may be useful for editorial tasks that do not require the model to make independent scientific judgments.

These benefits should be regarded as possibilities rather than guaranteed outcomes. AI may improve fluency while weakening a necessary qualification or introducing a statement the reviewer never intended.

Why Tone Matters in Peer Review

Peer review can be intellectually demanding for authors, particularly when comments question the validity of a study's central claims.

Reviewers should be candid about substantive weaknesses without making unnecessary judgments about the authors' competence, motives, or character.

For example, "The authors do not understand causal inference" attributes a deficiency to the researchers. "The manuscript's causal interpretation is not sufficiently supported by the observational design" identifies a problem in the work itself.

The second formulation is more appropriate because it directs attention to the evidence and the claim being evaluated.

Generative AI may help remove unnecessarily personal language, but reviewers should not mistake an agreeable tone for a scientifically adequate review.

AI Can Accidentally Strengthen a Criticism

Language editing is not always substantively neutral.

Suppose a reviewer writes, "The manuscript does not clearly explain how missing observations were handled."

An AI system might rewrite this as, "The authors failed to address missing data, compromising the validity of the findings."

The revised sentence is more forceful, but it introduces a claim that the original comment did not establish. Incomplete reporting is not necessarily evidence that the analysis was conducted incorrectly.

Reviewers should therefore examine whether AI-assisted editing changes the evidentiary strength, certainty, or implications of a criticism.

Substantive changes require independent scholarly evaluation. They should not be accepted merely because the generated wording appears more polished.

AI Can Also Weaken a Necessary Criticism

The opposite problem is equally important. A request to make comments more polite may cause AI to soften a serious methodological concern until its significance becomes unclear.

For example, a reviewer may identify that the authors used an analysis that does not account for the clustering of students within classrooms, potentially affecting uncertainty estimates.

An overly softened rewrite might say, "The authors may wish to consider discussing classroom differences."

This no longer communicates the actual analytical concern.

Constructive peer review does not require avoiding difficult judgments. It requires expressing them accurately, proportionately, and respectfully.

Confidentiality Applies to Reviewer Comments, Not Just Manuscripts

A reviewer may assume that their own comments are safe to enter into an AI system because they wrote them independently.

However, comments may reveal unpublished findings, methodological details, editorial assessments, or information about the manuscript's status.

Even a sentence written by the reviewer can contain confidential information obtained through the review assignment.

Removing author names does not necessarily resolve this concern.

The relevant issue is whether the material being processed is confidential and whether the journal has authorized its disclosure to the particular AI service.

For this reason, peer-review confidentiality obligations extend beyond complete manuscript uploads.

What Do Journal and Publisher Policies Allow?

Policies vary across publishers and journals, and reviewers should consult the current instructions governing their assignment.

The International Committee of Medical Journal Editors (ICMJE) recommends that reviewers follow the journal's AI policy or request permission before using AI to facilitate their review. Reviewers should disclose AI assistance and ensure that any resulting content is appropriate and valid.

Elsevier's generative AI policies distinguish certain supportive activities, including language improvement, from prohibited disclosure of confidential manuscript content. Any permitted assistance remains subject to the publisher's conditions and the journal's instructions.

These policies should not be generalized into a universal permission to paste reviewer reports into external AI services.

A journal may prohibit AI assistance even for editing, or permit it only within an approved environment.

Can Reviewers Ask AI for General Writing Guidance Without Sharing Their Comments?

Potentially, if the journal permits the intended use.

A reviewer might ask for general advice on structuring a constructive report or distinguishing major methodological concerns from minor editorial observations.

Such requests need not contain manuscript-specific information.

For example, a generic question about how to phrase methodological uncertainty respectfully is different from submitting a detailed criticism that reveals an unpublished study's results.

However, even generic assistance should comply with applicable journal restrictions. The absence of confidential content does not automatically override a prohibition on AI use during review.

Why AI-Generated Politeness Can Become Excessive

Generative AI systems often produce diplomatic language when asked to make feedback constructive.

Excessive qualification can make comments unnecessarily long or obscure the requested action. Phrases such as "The authors may perhaps wish to consider the possibility of potentially clarifying" add politeness without improving precision.

A more useful formulation would identify the problem and state what clarification is needed.

For example, "Please clarify whether the regression accounted for classroom-level clustering" is courteous, direct, and methodologically specific.

Reviewers should prefer clarity over elaborate diplomatic language. Academic courtesy does not require a paragraph of hedging before every methodological question.

Should AI Be Allowed to Add New Reviewer Comments?

A request to improve wording should not become an invitation for AI to generate additional scientific criticisms.

New concerns may be incorrect, irrelevant, or based on assumptions that do not apply to the manuscript.

If an AI system introduces a new issue, the reviewer should treat it as an unverified suggestion rather than an established weakness.

The reviewer must independently determine whether the concern is supported by the manuscript and whether it warrants inclusion.

This distinction is central to using AI to identify potential methodological problems without delegating the reviewer's scientific judgment.

What Should Reviewers Check After AI-Assisted Editing?

The reviewer should compare the edited text against the original comments and the manuscript.

Each concern should retain its intended meaning, evidentiary basis, degree of certainty, and requested revision.

Reviewers should also check whether the AI introduced new statistical claims, fabricated references, exaggerated deficiencies, or contradictory instructions.

Finally, the reviewer should verify that the use complied with the journal's policy and that any required disclosure has been completed.

The final report should represent the reviewer's independent scholarly assessment, not merely the most fluent version produced by the AI system.

Making a Methodological Criticism Constructive Without Changing Its Meaning

The example illustrates that improving tone does not mean reducing every criticism to a suggestion. A constructive comment should remain sufficiently precise for the authors to understand the concern and respond appropriately.

Misconceptions About AI-Assisted Reviewer Comment Editing

How to Use AI for Clearer Reviewer Comments Without Compromising the Review

The safest approach is to separate the scientific evaluation from any permitted writing assistance.

Reviewers should establish their concerns independently, determine whether AI assistance is authorized, and verify that the edited text preserves the original assessment.

Preserve the Reviewer's Original Judgment

Where AI editing is authorized, retaining the original draft until the final report is verified can help reviewers identify unintended changes.

The reviewer should examine not only grammar but also qualifiers, causal language, numerical statements, and the severity assigned to each concern.

The final report should communicate what the reviewer actually concluded after evaluating the manuscript.

Generative AI may make authorized reviewer comments easier to read, but the quality of peer review ultimately depends on whether those comments are accurate, relevant, and supported by the research evidence.

Checklist for AI-Assisted Peer-Review Language Editing

Frequently Asked Questions About AI-Edited Peer-Review Comments

Improve the Language Without Rewriting the Scientific Judgment

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