Epistemic Immunodepression in the Age of AI

I am writing as a pediatric surgeon and a clinical researcher, whose works seem less likely to be affected by the AI explosion. However, the reality is totally changed and this led me to make a hypothesis that the self-correction ability of science (and of medicine, my specific domain) is eroding in the age of AI.To be honest, there is a sarcastic truth here that I completed this small paper (preprint https://doi.org/10.31222/osf.io/gqunf_v1) with significant support from AI: research for original articles, language editing (truly efficient for a non-native speaker), simulated peer review, especially when I asked where I should publish my work! That's all of the introduction, now we will follow the flow of my humble but fun reasoning process.Every day, I make decisions about operation for the children, which is based mostly on the evidence-based medicine (EBM). The question is, how this evidence is generated? Firstly, it comes from case reports or series, then from more strictly designed research (cohort, RCTs), then meta-analysis to make a conclusion or guideline for clinical practice. That chain works not because each link is perfect, but because each link can check the previous one, as listed from previous works: independent evaluation (peer-reviews and editor review), methodological plurality (many types of design help identify the truth), traceability (audit how a conclusion is made), epistemic friction between authors and critics (the huge workload/finance from a question to a conclusion).In the age of AI, all 4 of these conditions are gradually eroding. Obviously, the friction is substantially reduced that with the support from LLMs, researchers could easily synthesize hundreds of papers in several days rather than several months as before. The traceability is also challenged, while we cannot define exactly how LLMs "think or reason" to give a conclusion or a result. Plurality is decreasing, which is named in recent literature as 'monoculture' phenomenon. Mor