梳理语言模型中让人格化表达的文本模式，帮助更准确讨论技术的人类化问题。
A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies
- 基于文献与用户交互案例，构建语言人格化的文本表达分类体系。
- 揭示语言本身具有人类属性，机器人格化可能引发认知偏差与伦理争议。
- 为研究者与政策制定者提供统一术语框架，推动负责任的技术设计。
近期对语言技术（如大语言模型）中人格化现象的关注，引发了关于其潜在负面影响的讨论。要有效探讨人格化的后果及其适用情境，需建立共享的语言词汇体系，以描述语言在多方面呈现人格特征的方式。本文结合现有文献并分析用户与语言技术的实际互动案例，提出一个文本表达的人格化分类框架。研究指出理解语言人格化所面临的挑战与张力，例如语言本质上是人类产物，而试图定义和改变人们对机器‘人性’的认知，也可能导致对某些人类的去人性化。该分类体系有助于实现对语言技术人格化问题更精准、有效的讨论与决策。
原文摘要 · Abstract (English)
Recent attention to anthropomorphism -- the attribution of human-like qualities to non-human objects or entities -- of language technologies like LLMs has sparked renewed discussions about potential negative impacts of anthropomorphism. To productively discuss the impacts of this anthropomorphism and in what contexts it is appropriate, we need a shared vocabulary for the vast variety of ways that language can be anthropomorphic. In this work, we draw on existing literature and analyze empirical cases of user interactions with language technologies to develop a taxonomy of textual expressions that can contribute to anthropomorphism. We highlight challenges and tensions involved in understanding linguistic anthropomorphism, such as how all language is fundamentally human and how efforts to characterize and shift perceptions of humanness in machines can also dehumanize certain humans. We discuss ways that our taxonomy supports more precise and effective discussions of and decisions about anthropomorphism of language technologies.
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