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This paper introduces the Value Alignment Tax (VAT), a framework to quantify how aligning LLMs to specific values impacts the broader value system. VAT measures the trade-offs between gains in target value alignment and changes in other interconnected values. Using a dataset of scenario-action pairs grounded in Schwartz value theory, the authors demonstrate that alignment interventions induce structured co-movement among values, which are often missed by target-only evaluations.
Alignment interventions in LLMs can produce uneven and structured shifts across interconnected values, creating hidden risks that target-only evaluations miss.
Existing work on value alignment typically characterizes value relations statically, ignoring how interventions - such as prompting, fine-tuning, or preference optimization - reshape the broader value system. We introduce the Value Alignment Tax (VAT), a framework that measures how alignment-induced changes propagate across interconnected values relative to achieved on-target gain. VAT captures the dynamics of value expression under alignment pressure. Using a controlled scenario-action dataset grounded in Schwartz value theory, we collect paired pre-post normative judgments and analyze alignment effects across models, values, and alignment strategies. Our results show that alignment often produces uneven, structured co-movement among values. These effects are invisible under conventional target-only evaluation, revealing systemic, process-level alignment risks and offering new insights into the dynamics of value alignment in LLMs.