Journals need to find a way to give guidance on what is and isn't appropriate and to let reviewers explain how they used AI tools... because like, you aren't going to nag people out of using AI to do UNPAID work 90% faster and produce results that are 90+th percentile of review quality (let's be real, there are a lot of bad flesh and blood reviewers).
I think it's interesting that AI is probably unintuitively good at spotting fraud in papers due to their ability to hold more context than majority of humans. I wish someone explored this to see if it can spot academic fraud that isn't in their training data already.
Guidance needs to be more specific. Failing to use AI for search often means you are wasting a huge amount of time, ChatGPT 5.2 Extended Thinking with search enabled speeds up research obscenely, and I'd be more concerned if reviewers were NOT making use of such tools in reviews.
Seeing the high percentage of usage of AI for composing reviews is concerning, but, also, peer review is an unpaid racket which seems basically random anyway (https://academia.stackexchange.com/q/115231), and probably needs to die given alternatives like ArXiV and OpenPeerReview and etc. I'm not sure how much I care about AI slop contaminating an area that already might be mostly human slop in the first place.
The reasons listed in TFA - "confidentiality, sensitive data and compromising authors’ intellectual property" - make sense to discourage reviewers from using cloud-based LLMs.
There are also reasons for discouraging the use LLMs in peer review at all: it defeats the purpose of peer in the peer review; hallucinations; criticism not relevant to the community; and so on.
However, I think it's high time to reconsider what scientific review is supposed to be. Is it really important to have so-called peers as gatekeepers? Are there automated checks we can introduce to verify claims or ensure quality (like CI/CD for scientific articles), and leave content interpretation to the humans?
Let's make the benefits and costs explicit: what would we be gaining or losing if we just switched to LLM-based review, and left the interpretation of content to the community? The journal and conference organizers certainly have the data to do that study; and if not, tool providers like EasyChair do.
Yes, there are often strong reasons to have peers as gatekeepers. Scientific writing is extremely information-dense. Consider a niche technical task that you work on -- now consider summarizing a day's worth of work in one or two sentences, designed to be read by someone else with similar expertise. In most scientific fields, the niches are pretty small, The context necessary to parse that dense scientific writing into a meaningful picture of the research methods is often years/decades of work in the field. Only peers are going to have that context.
There are also strong reasons why the peers-as-gatekeepers model is detrimental to the pursuit of knowledge, such as researchers forming semi-closed communities that bestow local political power on senior people in the field, creating social barriers to entry or critique. This is especially pernicious given the financial incentives (competition for a limited pool of grant money; award of grant money based on publication output) that researchers are exposed to.
> However, I think it's high time to reconsider what scientific review is supposed to be
I've been arguing for years we should publish to platforms like OpenReview and that basically we check for plagiarism and obvious errors but otherwise publish.
The old days the bottleneck was the physical sending out of papers. Now that's cheap. So make comments public. We're all on the same side. The people that will leave reviews are more likely to actually be invested in the topic rather than doing review as purely a service. It's not perfect but no system will be and we currently waste lots of time chasing reviewers
This misses the point entirely. Science is a dialogue. Peer review is just a protocol to signal that the article has been part of some dialogue.
Anyone can put anything to paper. Now more than ever - see all the vibe physics floating around. Peer review is just an assurance that what you are about to read isn't just some write-only output of some spurious thought process.
15 comments
[ 3.1 ms ] story [ 40.1 ms ] threadSeeing the high percentage of usage of AI for composing reviews is concerning, but, also, peer review is an unpaid racket which seems basically random anyway (https://academia.stackexchange.com/q/115231), and probably needs to die given alternatives like ArXiV and OpenPeerReview and etc. I'm not sure how much I care about AI slop contaminating an area that already might be mostly human slop in the first place.
There are also reasons for discouraging the use LLMs in peer review at all: it defeats the purpose of peer in the peer review; hallucinations; criticism not relevant to the community; and so on.
However, I think it's high time to reconsider what scientific review is supposed to be. Is it really important to have so-called peers as gatekeepers? Are there automated checks we can introduce to verify claims or ensure quality (like CI/CD for scientific articles), and leave content interpretation to the humans?
Let's make the benefits and costs explicit: what would we be gaining or losing if we just switched to LLM-based review, and left the interpretation of content to the community? The journal and conference organizers certainly have the data to do that study; and if not, tool providers like EasyChair do.
LLMs simply don't do science. They have no integrity.
There is no "bullshit me" step in the scientific process
There are also strong reasons why the peers-as-gatekeepers model is detrimental to the pursuit of knowledge, such as researchers forming semi-closed communities that bestow local political power on senior people in the field, creating social barriers to entry or critique. This is especially pernicious given the financial incentives (competition for a limited pool of grant money; award of grant money based on publication output) that researchers are exposed to.
The old days the bottleneck was the physical sending out of papers. Now that's cheap. So make comments public. We're all on the same side. The people that will leave reviews are more likely to actually be invested in the topic rather than doing review as purely a service. It's not perfect but no system will be and we currently waste lots of time chasing reviewers
Anyone can put anything to paper. Now more than ever - see all the vibe physics floating around. Peer review is just an assurance that what you are about to read isn't just some write-only output of some spurious thought process.