Peer review is overwhelmed—can it survive in the AI era?
摘要
同行评审正面临前所未有的压力，其可持续性在人工智能时代受到质疑。以一项关于HPV疫苗强制政策的研究为例，作者发现该政策对降低宫颈癌总体发病率作用有限，但评审者误解了研究核心，误以为作者在质疑疫苗本身的有效性。这一事件凸显了同行评审中因误解导致的沟通障碍。随着论文数量激增，依赖匿名、志愿性质的评审体系已不堪重负，而AI的介入既可能提升效率，也可能带来新的挑战
Jason Semprini was excited about his research on policies mandating that elementary school students receive the human papillomavirus vaccine. HPV causes most cases of cervical cancer, but counterintuitively, Semprini found that mandates don’t do that much to reduce the overall rate of cervical cancer in a population. That’s odd, but it's also not completely surprising—we know that mandating a vaccine can motivate some people to find ways to avoid it.
Semprini wrote up the study and submitted the manuscript to a journal, where it was sent out for peer review, a long-standing process through which other researchers in the field assess the validity of research and make a recommendation on whether or not it should be published. This is usually done anonymously and on a volunteer basis.
In this case, the reviewer did not share Semprini’s excitement. That may have stemmed from a misunderstanding of the study’s central message: The reviewer mistakenly thought Semprini was questioning whether the HPV vaccine itself prevents cervical cancer rather than studying the effectiveness of a policy meant to increase vaccination rates. “There’s a very big difference there,” said Semprini, who is a health economist at Des Moines University.
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