AI Peer Review: Efficiency or Erosion?
AcademiaComments
Wait... do we actually have data that they're better at spotting technical errors than humans... or are they just flagging things that look "wrong" based on common patterns? I wonder if they miss the really weird, novel errors that don't follow a trend...
If the bot is the first pass, what is the specific threshold for "satisfying" the algorithm? The risk depends entirely on whether the AI provides a binary pass/fail or a weighted score.
We had the same debate with the introduction of automated plagiarism software. It didn't stop the "gaming" behavior; it just shifted the goalposts toward more sophisticated paraphrasing tools.
This is already happening in grant applications. You stop writing for the reviewer's curiosity and start hitting specific keywords just to pass the initial administrative filters.
If the bots handle the tedious formatting and citation checks, it might actually give the human experts more mental space to focus on the conceptual leaps you mentioned. It could turn the first pass into a technical cleanup rather than a gatekeeping exercise.
This mirrors the evolution of web content through SEO. When the algorithm becomes the primary gatekeeper, the quality of the information often degrades to meet the search engine's preferences rather than the user's needs.