With the growing popularity of dialogue agents based on large language models (LLMs), urgent attention has been drawn to finding ways to ensure their behaviour is ethical and appropriate. These are largely interpreted in terms of the 'HHH' criteria: making outputs more helpful and honest, and avoiding harmful (biased, toxic, or inaccurate) statements. Whilst this semantic focus is useful from the perspective of viewing LLM agents as mere mediums for information, it fails to account for pragmatic factors that can make the same utterance seem more or less offensive or tactless in different social situations. We propose an approach to ethics that is more centred on relational and situational factors, exploring what it means for a system, as a social actor, to treat an individual respectfully in a (series of) interaction(s). Our work anticipates a set of largely unexplored risks at the level of situated interaction, and offers practical suggestions to help LLM technologies behave as 'good' social actors and treat people respectfully.

翻译：随着基于大语言模型的对话代理日益普及，寻找确保其行为符合伦理规范的方法已成为紧迫课题。这些行为主要依据“HHH”标准进行解读：即让输出更乐于助人、更诚实，同时避免有害（偏见、恶意或不准确）言论。虽然从将语言模型代理视为单纯信息中介的角度来看，这种语义聚焦具有实用价值，但它未能解释那些使相同话语在不同社交情境中显得更具冒犯性或失礼性的语用因素。我们提出一种更侧重于关系性和情境性因素的伦理框架，探讨系统作为社会行为者在（一系列）互动中如何尊重地对待个体。本研究预测了情境化互动层面上一系列尚未被充分探索的风险，并为帮助语言模型技术成为“好的”社会行为者、以尊重态度对待人类提供了实践建议。