Growth First, Care Second? Tracing the Landscape of LLM Value Preferences in Everyday Dilemmas

• URL: http://arxiv.org/abs/2602.04456v1
• Date: Wed, 04 Feb 2026 11:41:27 GMT
• Title: Growth First, Care Second? Tracing the Landscape of LLM Value Preferences in Everyday Dilemmas
• Authors: Zhiyi Chen, Eun Cheol Choi, Yingjia Luo, Xinyi Wang, Yulei Xiao, Aizi Yang, Luca Luceri,
• Abstract summary: We examine the value trade-off structure underlying advice seeking using a curated dataset from four advice-oriented subreddits.<n>We construct value co-occurrence networks to characterize how values co-occur within dilemmas.<n>We find that, across models and contexts, LLMs consistently prioritize values related to Exploration & Growth over Benevolence & Connection.
• Score: 5.1141034187487175
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: People increasingly seek advice online from both human peers and large language model (LLM)-based chatbots. Such advice rarely involves identifying a single correct answer; instead, it typically requires navigating trade-offs among competing values. We aim to characterize how LLMs navigate value trade-offs across different advice-seeking contexts. First, we examine the value trade-off structure underlying advice seeking using a curated dataset from four advice-oriented subreddits. Using a bottom-up approach, we inductively construct a hierarchical value framework by aggregating fine-grained values extracted from individual advice options into higher-level value categories. We construct value co-occurrence networks to characterize how values co-occur within dilemmas and find substantial heterogeneity in value trade-off structures across advice-seeking contexts: a women-focused subreddit exhibits the highest network density, indicating more complex value conflicts; women's, men's, and friendship-related subreddits exhibit highly correlated value-conflict patterns centered on security-related tensions (security vs. respect/connection/commitment); by contrast, career advice forms a distinct structure where security frequently clashes with self-actualization and growth. We then evaluate LLM value preferences against these dilemmas and find that, across models and contexts, LLMs consistently prioritize values related to Exploration & Growth over Benevolence & Connection. This systemically skewed value orientation highlights a potential risk of value homogenization in AI-mediated advice, raising concerns about how such systems may shape decision-making and normative outcomes at scale.

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