在面向弱势人群的人机交互（HRI）中评估人类与大语言模型（LLM）生成的主题分析：一项比较与伦理分析
Evaluating Human and LLM-Generated Thematic Analysis in HRI for Vulnerable Populations: A Comparative and Ethical Analysis
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中文总结 AI 辅助
本研究对比分析了人类与LLM在面向弱势人群的HRI研究中生成的主题分析，评估二者的一致性，探究LLM生成主题分析的伦理风险，为相关研究者提供启示。
中文摘要 AI 辅助
主题分析（TA）长期以来被视为一种本质上属于人类的、具有反思性和解释性的过程。然而，大语言模型（LLM）生成的主题分析在涉及弱势人群的人机交互（HRI）研究中适用程度如何，在很大程度上尚未得到检验，这引发了关于有效性和伦理的关键问题，尤其是在敏感研究情境中。本文针对弱势人群的HRI场景，开展了人类与LLM生成主题分析的比较研究，评估了人类与LLM生成主题间的客观一致性和语义一致性，并检验观察到的差异是否反映出具有伦理意义的系统性解释模式。我们的分析探究了LLM生成的主题分析是否存在边缘化或错误呈现弱势参与者经历的风险，这对在HRI中采用LLM辅助主题分析的研究者具有启示意义。
英文摘要
Thematic analysis (TA) has long been regarded as an inherently human, reflexive, and interpretive process. However, the extent to which LLM-generated TA is appropriate for Human-Robot Interaction (HRI) research involving vulnerable populations remains largely unexamined and raises critical questions about validity and ethics, particularly in sensitive research contexts. This paper presents a comparative study of human- and LLM-generated TA in an HRI context with a focus on vulnerable populations. We evaluate both objective and semantic agreement between human- and LLMgenerated themes, and examine whether observed divergences reflect systematic interpretive patterns with ethical significance. Our analysis investigates whether LLM-generated TA risks marginalising or misrepresenting the experiences of vulnerable participants, with implications for researchers employing LLM-assisted TA in HRI.
发表机构
- University of Cambridge（剑桥大学）
- Faculty of Education, University of Cambridge（剑桥大学教育学院）
机构由 AI 辅助整理，请以论文原文为准。
