提出人类应理性对待AI判断，避免盲目服从。
Epistemic Deference to AI
- 将可靠AI视为认知权威，主张其输出应作为参考而非替代
- 指出完全听从AI会导致认知退化与失控风险
- 提倡保留人类独立判断，实现人机协同决策
在什么情况下应优先采纳AI的判断而非人类专家意见？基于社会认识论最新研究，本文论证某些具备可靠性和认知优势的AI系统可被视为人工认知权威（AEAs）。提出AI预占主义观点：当用户拥有独立认知理由时，应由AEA输出取代而非补充。然而，经典反对意见——如盲目服从、认知固化和基础瓦解——在面对这类透明度低、自我强化且缺乏失败信号的系统时会被放大。因此，本文提出一种更优方案：总证据视角下的AI信赖模式，即让AEA输出作为辅助依据，而非取代人类独立思考。该方法具有三大优势：（i）防止专业能力退化，保持人类参与；（ii）为有意义的人类监督提供认识论支持；（iii）解释为何在可靠性未满足时合理质疑AI。尽管实践要求高，但此框架为高风险场景中合理信赖AI提供了原则性依据。
原文摘要 · Abstract (English)
When should we defer to AI outputs over human expert judgment? Drawing on recent work in social epistemology, I motivate the idea that some AI systems qualify as Artificial Epistemic Authorities (AEAs) due to their demonstrated reliability and epistemic superiority. I then introduce AI Preemptionism, the view that AEA outputs should replace rather than supplement a user's independent epistemic reasons. I show that classic objections to preemptionism - such as uncritical deference, epistemic entrenchment, and unhinging epistemic bases - apply in amplified form to AEAs, given their opacity, self-reinforcing authority, and lack of epistemic failure markers. Against this, I develop a more promising alternative: a total evidence view of AI deference. According to this view, AEA outputs should function as contributory reasons rather than outright replacements for a user's independent epistemic considerations. This approach has three key advantages: (i) it mitigates expertise atrophy by keeping human users engaged, (ii) it provides an epistemic case for meaningful human oversight and control, and (iii) it explains the justified mistrust of AI when reliability conditions are unmet. While demanding in practice, this account offers a principled way to determine when AI deference is justified, particularly in high-stakes contexts requiring rigorous reliability.
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