Review of \textitUncertain Values: an Axiomatic Approach To Axiological Uncertainty

Abstract

Expected Value Maximization offers an axiomatic framework for decision-making under axiological uncertainty, using a representation theorem based on expected-utility axioms and a Pareto condition to aggregate values across competing theories. Despite its formal rigor, the view confronts two critical theoretical challenges. First, it suffers from higher-order inconsistency: whenever an agent is not completely certain of Expected Value Maximization itself, applying the principle to resolve uncertainty at the meta-level generates second-order valuations that can directly contradict first-order recommendations, preventing the agent from satisfying both evaluative standards simultaneously. Second, the framework lacks an adequate basis for non-arbitrary intertheoretic comparisons of value. Norms intended to regulate these comparisons—such as simplicity, conservatism, and coherence—fail to resolve the arbitrariness of unit scales between theories that value fundamentally different goods, induce dynamic inconsistency across population changes, and can produce contradictory evaluations when applied across overlapping systems of value. Consequently, Expected Value Maximization fails to provide a fully coherent or non-arbitrary decision procedure under moral uncertainty. – AI-generated abstract.