# Suspect Your Peer Review Was AI-Generated?

> Received a peer review that feels generic, vague, or just… off? Learn how to identify the signs of an AI-generated review and the right way to respond.

Source: https://www.alfredscholar.com/blog/suspect-your-peer-review-was-ai-generated/
Published: 2026-10-27
Author: Alfred Scholar Team

## That Uncanny Feeling

You’ve waited weeks, maybe months, for feedback on your manuscript. The email from the journal finally arrives. You open the attachment, ready for the incisive, challenging, and hopefully constructive criticism of an expert in your field.

Instead, you get… this.

The comments are grammatically perfect but strangely hollow. They suggest you "enhance the clarity of the methodology" without pointing out a single confusing sentence. They recommend you "engage more deeply with the existing literature" but cite a paper that doesn’t actually exist. The prose is flawless, yet it feels like it was written by no one at all.

If this scenario feels familiar, you may have just received an AI-generated peer review. As generative AI becomes more integrated into every workflow, its presence in the confidential, expert-driven process of peer review is a growing and unsettling reality. So what do you do?

### Why This Isn't Just "Reviewer 2" Anymore

Peer review has always had its problems, from overworked volunteers to reviewers with personal biases. But the rise of AI-generated reviews introduces a fundamentally different challenge. A human reviewer, even a difficult one, is supposed to perform a core function: expert intellectual assessment.

When a reviewer outsources this task to a large language model (LLM), several critical things break:

1.  **Confidentiality Breach:** Most journal policies explicitly forbid uploading unpublished manuscripts to third-party AI tools. Doing so violates the author's intellectual property rights and the confidentiality agreement inherent in the review process.
2.  **Lack of Expertise:** An LLM does not have field-specific expertise. It generates text based on patterns in its training data, meaning it can't truly assess the novelty of your work, the validity of your methods, or the impact of your findings.
3.  **Accountability Vacuum:** Who is responsible for a flawed, AI-generated review? The reviewer who copied and pasted it? The AI? This lack of accountability erodes the foundation of trust that scholarly publishing is built on.

This isn't just about getting unhelpful feedback. It's about the integrity of the scientific validation process.

## Step 1: Identify the Red Flags of an AI Peer Review

Before you take any action, you need to move from a vague suspicion to a set of specific observations. AI-generated text has several tells. Look for a combination of these patterns in the review you received.

### The "Flawless but Empty" Prose
Human experts, even when writing carefully, have a distinct voice. Their writing has rhythm, emphasis, and occasional quirks. AI-generated text often feels unnervingly smooth and uniform.

*   **Generic and Vague Language:** Look for filler phrases that could apply to almost any paper in your field. Comments like "The authors should strengthen their argument" or "This is an important area of research" without any specific examples are a major red flag.
*   **Repetitive Phrasing and Summaries:** AI models often summarize a point they just made or use repetitive sentence structures. You might see a comment followed by a sentence that starts with, "In other words..." or "To summarize...".
*   **Excessive Hedging or Overconfidence:** The tone might swing between being overly cautious ("It might be worth considering...") and strangely definitive, without providing the reasoning an expert would.

### The Hallucination Hall of Fame
LLMs are notorious for fabricating information, a phenomenon known as "hallucination." In a peer review, this is one of the easiest signs to spot and document.

*   **Phantom Citations:** The review might suggest you cite a paper that looks plausible but, upon searching Google Scholar or your field's database, simply does not exist. It might combine a real author's name with a fake title or a real journal with a made-up article.
*   **Irrelevant References:** The review might cite real papers that are only tangentially related to your work, indicating the AI found a keyword match without understanding the context.
*   **Factual Errors About Your Own Paper:** This is the most damning evidence. The review might critique a section that isn't in your manuscript, misstate your primary finding, or comment on a figure that doesn't exist. This shows the "reviewer" didn't engage with the actual content.

### Lack of a Coherent Scientific Argument
An expert review provides a structured critique. It identifies the core strengths and weaknesses and connects them to the broader context of the field. An AI review often feels like a disconnected list of surface-level observations.

*   **No "Big Picture" View:** The review might focus on minor grammatical points or formatting issues while completely missing a major conceptual flaw, or vice versa.
*   **Contradictory Comments:** One comment might praise your novel approach, while another criticizes you for not using a standard method, with no acknowledgment of the trade-off.
*   **Failure to Engage with Nuance:** Does your research involve a complex methodology, a subtle theoretical argument, or a dataset with known limitations? A human expert will engage with that nuance. An AI review will often ignore it, offering generic advice that doesn't apply to your specific situation.

## Step 2: Formulate Your Strategy (Don't Just Vent)

You've collected your evidence and you're confident the review is, at best, intellectually lazy and, at worst, a complete fabrication. Now is the time to be strategic, not emotional. Your goal is to secure a fair and expert evaluation of your work.

### First, Read for Substance (Yes, Really)
Even a broken clock is right twice a day. Before you dismiss the entire review, do a quick, dispassionate scan. Is there a single, solitary point that might actually improve your paper? Perhaps the AI’s generic comment to "clarify the limitations section" is actually a good reminder. Address any valid points. This shows the editor you are a constructive and serious scholar, not someone trying to dodge criticism.

### Privately Contact the Editor
Do **not** use your official "Response to Reviewers" document to allege AI use. This puts the editor in an awkward public position and can come across as defensive.

Instead, write a separate, polite, and private email to the journal editor.

1.  **Be Professional and Non-Accusatory:** Frame your concern around the *quality and usefulness* of the review, not just your suspicion of AI. The core issue is that the review is not helpful, regardless of how it was generated.
2.  **Provide Specific, Bulleted Evidence:** This is where your documentation from Step 1 comes in. List the most concrete examples.
    *   "Reviewer 2 suggested we cite 'Smith et al., 2024, *Journal of Obscure Studies*.' We have been unable to locate this paper and believe it may not exist."
    *   "The review states that our sample size is insufficient but offers no justification or reference to standards in our field."
    *   "The reviewer's comments on Figure 3 appear to describe a different graph, as our Figure 3 shows X while the comment discusses Y."
3.  **Reference Journal Policy (If Possible):** Briefly check the journal's website for its policy on AI in peer review. Many publishers, including Springer Nature, Elsevier, and Wiley, have clear guidelines. If the review appears to violate these (e.g., by suggesting a confidentiality breach), you can mention it. For example: "Given the journal's policy on reviewer confidentiality, we are also concerned that the manuscript may have been uploaded to an external AI service."
4.  **Make a Clear, Respectful Request:** State what you would like to happen. Your best option is to request an additional, expert review. "Given that these comments do not provide the substantive feedback needed to guide our revision, we would be grateful if the editor would consider seeking an additional review."

This approach positions you as a partner in upholding the journal's standards, not as a disgruntled author. For more on structuring this kind of communication, see our playbook on [responding to difficult reviewer comments](/blog/how-to-respond-to-difficult-reviewer-comments-without-losing-your-mind/).

## Step 3: Write the Official Response

While you await the editor's reply, you should still prepare your formal response to all reviews. How you handle the suspect review in this document matters.

### Focus on the Lack of Substance
For each problematic comment, you can politely and factually point out why it is not actionable.

*   **For a generic comment:** "We thank the reviewer for the suggestion to enhance the clarity of our methodology. In the absence of specific examples, we have carefully re-read the Methods section and made minor copyedits to improve readability."
*   **For a hallucinated citation:** "We appreciate the reviewer's suggestion to engage with additional literature. We were unable to locate the specific paper by 'Smith et al., 2024' mentioned. However, we have added a discussion of the related work by Jones et al. (2023) on page 5."
*   **For a factually incorrect comment:** "The reviewer noted a concern about X. We believe this may be a misunderstanding, as our manuscript addresses this point in Section 2.1, page 4, where we state Y. We have revised the section to make this point more prominent."

This method addresses the review without getting into a debate about its origin. You are showing the editor that you have engaged in good faith but that the feedback itself is flawed.

## The Long Game: Protecting Your Work and Your Time

Encountering an AI-generated review is frustrating. It can delay your publication and make you question the fairness of the system. But it is also a reality of the modern publishing landscape.

If the editor is unresponsive or dismisses your concerns, you have a decision to make. If the recommendation was "major revisions," you may have to proceed, addressing what you can and ignoring the rest. If your paper was rejected based on a nonsensical AI review, the most pragmatic solution is often to cut your losses. Take the opportunity to improve your paper with the feedback from any legitimate reviews and submit it to a different journal.

Ultimately, the best defense is a strong offense. Using tools like Alfred Scholar's AI chat to "pre-review" your own manuscript can help you spot weaknesses before you even submit. By asking it to "act as a critical peer reviewer and find the three biggest flaws in this paper," you can anticipate and address issues, making your manuscript more resilient to both human and machine critique.

The principles of good scholarship, rigor, novelty, and clear communication, are still your greatest assets. As the lines between human and machine writing continue to blur, focusing on the quality of your own work is the best way to navigate a changing world.