The Role of the Peer Reviewer in an AI-Assisted Future

AI may bring in consistency but I would trust the human to maintain the trust in the peer review process.

As part of the Peer Review Week 2026 event, we interviewed industry experts to understand their views on the AI-human partnership that is evolving in modern day peer review. Here, we present an interview of Roohi Ghosh, Ambassador for Researcher Success, CACTUS; Member, EASE Council and Co-Chair Peer Review Week 2026. The interview was conducted by Dr. Radhika Vaishnav, Managing Editor, Editage Insights.

Question 1: The Human Element

AI tools are increasingly being used to assist with manuscript screening, language assessment, and even reviewer recommendations. In your view, what aspects of peer review should always remain a human responsibility, regardless of how advanced AI becomes?

Response:
Do we undermine the role of a chartered accountant just because we built calculators? Or do we undermine the role of a teacher just because kids can learn independently online? In fact, teaching evolved with the use of digital tools. Similarly, the role of the human peer reviewer is indispensable, but it needs to evolve. Just because we have AI doesn’t make the reviewer’s role any lesser. Peer reviewers are expected to do so much more today in addition to just evaluating the science. They need to be able to spot AI hallucinations, identify papermill activities, and spot other AI introduced errors or unethical practices. But AI is getting smarter and it is not easy to spot this. Instead of spending time “being detectives”, the human peer reviewer needs to focus on the core of peer review itself. Is the paper novel? Is the research question important? Does it contribute something valuable to the existing knowledge? What is the impact that the research will have. The value of the peer reviewer cannot be argued when it comes to the role it plays in judgment and subject area expertise and contextual feedback. The detective work is just a distraction.

Question 2: Beyond Technical Evaluation

A strong peer review often involves judging novelty, significance, and the potential impact of a study on the field. Do you think AI can ever meaningfully contribute to these assessments, or are they inherently human judgments? Why/why not?

Response:
There is so much debate around this with people creating havoc when the discussion becomes even a little bit “pro AI”. I think, for me, the answer is a bit more nuanced than a simple yes or no. To be honest, I feel that AI can help with a part of the process. As a reviewer, it is not always possible to know everything about the field. How can I judge novelty if I haven’t read every single paper related to the topic I am reviewing? AI can help me explore the literature and identify related work. But it is up to the human peer reviewer to look at the evidence and judge whether the question is truly important and whether the research is novel in light of what AI found on the topic. So AI can be a contributor to the process, more like an assistant. But it cannot be the judge of whether a paper is meaningful and impactful. That is for the human to decide.

Question 3: Trust, Bias, and Accountability

Some argue that AI could make peer review more consistent and less biased, while others worry it could introduce new forms of bias and reduce accountability. How do you see the balance between human and AI involvement in maintaining trust in the peer review process?

Response:
Just because it’s AI doesn’t make it automatically more consistent and less biased. AI is trained on large data sets where there are already several biases and pre-existing assumptions. Now AI magnifies these biases by reproducing these biases at scale because it is trained on these pre-existing biased data sets. Trust in peer review, therefore, according to me, would be about transparency especially in addressing issues like what decisions were made, how did we arrive at these decisions and who is accountable for these decisions. AI may bring in consistency but I would trust the human to maintain the trust in the peer review process.

Question 4: Lessons from Experience

Think about the most valuable peer review feedback you have ever received (or provided)? Could an AI system realistically replicate that kind of contribution?

Response:
I think the most valuable feedback I have received has never been about the grammar, a statistic, or a detail in my Methods section. It has been about something deeper that has made me re-think the direction of my paper itself. For instance, a reviewer once told me, “You are trying to communicate too much. There are too many ideas. What is your main message?” It made me re-evaluate the focus of my paper. I arrived at one single idea and ensured that my paper communicated that clearly. This feedback is something I find useful irrespective of whether it’s a paper, a blog article or something else. While AI may have been able to tell me that my central message was not clear, it may not have been able to suggest which of those ideas hold merit and are of relevance to the intended audience. In fact, there are times that AI can give you so many ideas that the writing becomes messy and confusing. Sometimes what you need is not more ideas though, but for someone to remind you to focus on one central theme. In my case, the peer reviewer made me stop and asked “What is the one thing you are trying to say?”

Question 5: Looking Ahead

Imagine the peer review process ten years from now. What role would you ideally like AI to play, and what role should remain firmly in the hands of human reviewers and editors?

Response:
10 years from now I feel we won’t be discussing the pros and cons of AI. Like with the calculator, AI tools would have not just been adopted but also accepted in academia but with the aim of improving efficiency and not replacing the reviewer. The reviewer wouldn’t be focusing his energies on “were there AI hallucinations in this paper?” Decision-making and judgment would still be with the reviewer. But AI would make this process easier for the reviewer by providing the tools to help them evaluate and take these decisions more deliberately. It would help a reviewer “see more,” so they can take informed decisions.

Self-confidence would be that one quality that peer reviewers must preserve in an AI-assisted future.

Question 6: “Quick Take” 

If you had to choose just one quality that peer reviewers must preserve in an AI-assisted future, what would it be and why?

Response:

While most people would say judgement (and I agree), I feel that self-confidence would be that one quality that peer reviewers must preserve in an AI-assisted future. AI can hallucinate so confidently that there is a tendency to doubt oneself. A reviewer needs to be able to say, “I disagree.” Or “I need to look into this” even when AI sounds confident. While the mechanics may be taken care of by AI, how confident is a researcher to take that information and make an informed judgement? Decision-making and judgement without the confidence in one’s expertise will not lead to much.