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).