AI and My Values: User Perceptions of LLMs’ Ability to Extract, Embody, and Explain Human Values from Casual Conversations

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Authors: Bhada Yun, Renn Su, April Yi Wang
Cited by: 5
References: 123

Abstract

Does AI understand human values? While this remains an open philosophical question, we take a pragmatic stance by introducing VAPT, the Value-Alignment Perception Toolkit, for studying how LLMs reflect people’s values and how people judge those reflections. 20 participants texted a chatbot over a month, then completed a 2-hour interview with our toolkit evaluating AI’s ability to extract (pull details regarding), embody (make decisions guided by), and explain (provide proof of) their values. 13 participants ultimately left our study convinced that AI can understand human values. Thus, we warn about “weaponized empathy”: a design pattern that may arise in interactions with value-aware, yet welfare-misaligned conversational agents. VAPT offers a new way to evaluate value-alignment in AI systems. We also offer design implications to evaluate and responsibly build AI systems with transparency and safeguards as AI capabilities grow more inscrutable, ubiquitous, and posthuman into the future.

Fields of Study & Subjects

AI in Service Interactions Ethics and Social Impacts of AI Explainable Artificial Intelligence (XAI)

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–38
Publication date
13 April 2026
Language
EN