Peer Review Week is here and, with it, a fascinating subject: “Rethinking Peer Review in the AI Era”.
AI is a topic that has people fascinated. Some people are all in on the idea. Others are very concerned about its implications and what it can do. Academia is no different, and there are loads of questions there too. Will it make research easier or harder? Will it be abused? Can it be helpful?
In fact, those voting on this year’s theme for Peer Review Week (PRW) overwhelmingly selected “Rethinking Peer Review in the AI Era” as the subject. This shows a real hunger to dive into this subject and to (hopefully) come away with a stronger understanding of the subject, as well as what a path forward might look like. Can AI make peer review more fair and equitable? Can it simplify the peer review process and help to reduce some of the issues that are baked into the peer review process?
Here, we’ll dive a little bit into Peer Review Week before tackling the big subject of the year.
Peer Review Week in a nutshell
Before we talk about this year’s topic, let’s quickly go over this amazing event. Started in 2015, Peer Review Week is an annual scholarly event that focuses on a different aspect related to peer review. It’s topics have ranged from “Recognizing Peer Review” (the inaugural year’s topic) to “Peer Review and The Future of Publishing” (2023). Every year, a new topic is selected using a global public poll. The 2025 topic, excitingly, is on the topic of AI and peer review.
PRW brings together different organizations, institutions, as well as people, dedicated to promoting the importance of peer review to the advancement of scholarly communication. Every year, there is a wide range of activities. Events, webinars, interviews, and more, improve awareness about the topic throughout the academic community.
As an event, it has grow both in terms of impact as well as participation.
According to the 2025 PRW press release,
Participation is open to all—publishers, academic institutions, researchers, librarians, students, and
technologists. Whether you’re hosting a panel, writing a blog, or sharing your thoughts on social
media, PRW welcomes all contributions. This is an opportunity to collaborate across borders and
disciplines to shape the future of peer review in the AI era.
It is another year and another exciting topic to discuss! So let’s dig in.
How does AI intersect with academia?
Artificial intelligence presents a very specific set of complications for academia. On the one hand, it is quite good at parsing data. Compiling information using AI can be a snap. But at the same time, it has been shown, time and time again, to be unreliable when it comes to actually presenting information. Because AI models tend to be trained on user data, if users are incorrect, then the model may also be incorrect. This means that someone attempting to have AI “do their research for them” runs the very real risk of that research being wrong.
But it’s critical to note that it can enhance learning and improve research efficiency. It can even do things like make administrative tasks simpler.
But where is the balance in the question of artificial intelligence’s use in the academic world?
Peer review and AI
Maria Machado, Co-Chair of the PRW Steering Committee for 2025 notes that,
“I believe that the most valuable outcome of integrating AI into peer review could be transforming the reviewer experience, making it more efficient and enjoyable, while increasing engagement.”
And there is a great deal of truth to this. AI could potentially improve the review process. But how does it get governed? There are different types of peer review, and some of them are very transparent processes; but what about an AI-driven model?
This year, PRW aims to answer questions like:
- How can AI enhance, rather than undermine, reviewer integrity and transparency?
- What ethical guidelines should govern the use of AI in peer review?
- How can we train and support reviewers in the responsible use of AI tools?
- What aspects of peer review must remain uniquely human?
Pros and cons of AI in academia
As with most things, there can be good and bad applications for a technology. While there are genuinely valuable applications, there are also some significant concerns that people have.
The cons of AI in academia
Artificial intelligence can have significant impacts on people’s academic careers and academia writ large. For example, at the personal level, the idea of just copying and pasting AI-generated essays and submitting them as one’s own is problematic. Plagiarism, unfortunately, has been a part of academia for as long as anyone can remember. Unfortunately, some people, for any number of reasons, might be inclined to try and cheat their way through the academic system. While plagiarism has always been present, the ease with which AI-generated content can be produced might actually make the problem worse.
If it is easier to cheat (and harder to get caught) this can have broad and far-reaching impacts on the entire academic system. Being caught cheating can have devastating and permanent impacts on your academic career.
Worse than this, however, could be the impact that this has on people learning how to do research. If “all one needs to do” is to tell AI to do something, people might never learn the important skills of patience, how to research, how to parse through different sets of information, and more.
Over-reliance on tools like AI can make it harder for people to develop creative, new ideas.
Resistance to AI
Related to this, but worth mentioning, is that a resistance to AI at the institutional (or even just instructor) level, might mean a few different things as well. For example, a strong resistance to AI might mean slow development of guidelines to control its usage.
When I was younger, there was a very strong “anti-internet” sentiment. Sources for research “couldn’t be from online sources”. This has obviously changed over time, but this slowness to adapt made research much harder to accomplish. There is an understandable resistance to AI, but as with all tools, trying to simply ban them means that it will only take longer to adjust to them. Instituting reasonable guidelines takes time and understanding.
This year, Peer Review Week’s goals include dispelling some of the concerns about AI’s application in academia—but in a clear-eyed and reasoned way.
The benefits of AI
Artificial intelligence has the potential to revolutionize many different aspects of academia.
Many have talked about the ways in which AI can free up time through its ability to parse and review datasets. It can do a great deal of data processing in a very short period of time. This, in turn, can free up researchers’ time, allowing them to focus on more novel and critical parts of their research. While AI has many benefits, it cannot create novel research.
The promise of AI has also included tools like augmented reality, which can be useful in many different ways. For example, these tools can help with immersive training in many different academic fields. In addition to this, it can also allow for tools that make learning and understanding more effective. The “gamification” of learning can lead to a more engaging academic process for many students, along with a higher retention of information.
Artificial intelligence and the peer review process
Peer Review Week’s goal this year is to shine a light on the ways in which AI impacts the peer review process. It can serve as a tool for reviewers, to more effectively review things like visual data.
Not only that, but AI can also be used to effectively improve the fact-checking process, helping peer reviewers to save time (and in turn review more research). As finding peer reviewers can sometimes be a challenge, being able to have more tools at their disposal can ease the burden of the peer review process.
It is critical to ensure that humans are in the loop. And a carefully structured peer review process, where AI has helped in the selection process of candidates, can save time. The people who have to parse peer reviewer options might find immense benefits by having a tool like AI at their disposal.
For smaller and medium-sized academic journals, AI tools can help to make up some of the staffing challenges being faced. Empowering these journals can help to grow academic research in hundreds of different fields.
AI can be a powerful tool to unlock research all over the world, but we need to make sure that we keep a watchful eye on it.