Can Social Concepts Support Value Conflict Resolution in Language Models?

Abstract

Language models (LMs) have demonstrated a persistent value-action gap: while they can identify and endorse human values, they frequently fail to select actions consistent with those values in decision scenarios. We hypothesize that this gap is partly attributable to missing psychological context, and investigate whether conditioning LMs on Maslow-based needs profiles improves value-aligned action prediction in value-conflict situations. We construct a reproducible dataset of human-validated value-conflict scenarios combining Schwartz values with social contexts, each paired with candidate actions spanning an ordinal alignment scale. We evaluate open-source LMs under baseline and needs-conditioned prompting conditions, measuring alignment strength and prediction stability. Results show that needs profiles can influence model predictions, though effects are modest overall. These findings suggest that LMs can incorporate psychological context when reasoning about value conflicts, but that value representations remain the dominant factor in action selection.