剖析AI灭绝风险中的不确定性，揭示传统模型的局限性
What are the odds? Risk and uncertainty about AI existential risk
- 区分风险与不确定性，指出概率评估受双重不确定性的结构性影响
- 在认知中立情境下，灭绝事件概率高于直观估计
- 批判线性风险模型，强调多层结构关系对风险判断的关键作用
本文是对Cappelen、Goldstein与Hawthorne所著《AI生存故事：人工智能灭绝风险的分类分析》的评论。不仅限于评论，更旨在提醒我们线性风险模型的哲学局限。首先，对比标准瑞士奶酪模型与本文所用模型的差异；其次，在认知中立情境下，基于层级间结构关系，认为灭绝事件发生概率P(D)高于初步预期；再次，区分风险与不确定性，指出任何对P(D)的估算均受两种不确定性影响：选项不确定性与状态空间不确定性。将这些不确定性维度纳入定性讨论，有助于更准确理解人工智能灭绝风险的可能性。
原文摘要 · Abstract (English)
This work is a commentary of the article \href{https://doi.org/10.18716/ojs/phai/2025.2801}{AI Survival Stories: a Taxonomic Analysis of AI Existential Risk} by Cappelen, Goldstein, and Hawthorne. It is not just a commentary though, but a useful reminder of the philosophical limitations of \say{linear} models of risk. The article will focus on the model employed by the authors: first, I discuss some differences between standard Swiss Cheese models and this one. I then argue that in a situation of epistemic indifference the probability of P(D) is higher than what one might first suggest, given the structural relationships between layers. I then distinguish between risk and uncertainty, and argue that any estimation of P(D) is structurally affected by two kinds of uncertainty: option uncertainty and state-space uncertainty. Incorporating these dimensions of uncertainty into our qualitative discussion on AI existential risk can provide a better understanding of the likeliness of P(D).
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