Expected value, to a point: Moral decision‐making under background uncertainty

Noûs Pub Date : 2025-02-26 DOI:10.1111/nous.12544
Christian Tarsney
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Abstract

Expected value maximization gives plausible guidance for moral decision‐making under uncertainty in many situations. But it has unappetizing implications in ‘Pascalian’ situations involving tiny probabilities of extreme outcomes. This paper shows, first, that under realistic levels of ‘background uncertainty’ about sources of value independent of one's present choice, a widely accepted and apparently innocuous principle—stochastic dominance—requires that prospects be ranked by the expected value of their consequences in most ordinary choice situations. But second, this implication does not hold when differences in expected value are driven by tiny probabilities of extreme outcomes. Stochastic dominance therefore lets us draw a surprisingly principled line between ‘ordinary’ and ‘Pascalian’ situations, providing a powerful justification for de facto expected value maximization in the former context while permitting deviations in the latter. Drawing this distinction is incompatible with an in‐principle commitment to maximizing expected value, but does not require too much departure from decision‐theoretic orthodoxy: it is compatible, for instance, with the view that moral agents must maximize the expectation of a utility function that is an increasing function of moral value.
预期值,到一定程度:背景不确定情况下的道德决策
在许多情况下,期望值最大化为不确定性下的道德决策提供了合理的指导。但在出现极端结果可能性极小的“帕斯卡利亚式”情况下,它的含义令人生厌。本文首先表明,在独立于当前选择的价值来源的“背景不确定性”的现实水平下,一个被广泛接受且显然无害的原则——随机优势——要求在大多数普通选择情况下,根据其结果的期望值对前景进行排序。但其次,当期望值的差异是由极端结果的微小概率驱动时,这种暗示就不成立了。因此,随机优势让我们在“普通”和“帕斯卡利安”情况之间划出一条令人惊讶的原则性界限,为前者的实际期望值最大化提供了有力的理由,同时允许后者的偏差。这种区分与期望价值最大化的原则上承诺是不相容的,但并不需要过多地偏离决策理论的正统:例如,它与道德行为者必须最大化效用函数的期望的观点是相容的,而效用函数是道德价值的一个递增函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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