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With the growing popularity of conversational agents based on large languagemodels (LLMs), we need to ensure their behaviour is ethical and appropriate.Work in this area largely centres around the 'HHH' criteria: making outputsmore helpful and honest, and avoiding harmful (biased, toxic, or inaccurate)statements. Whilst this semantic focus is useful when viewing LLM agents asmere mediums or output-generating systems, it fails to account for pragmaticfactors that can make the same speech act seem more or less tactless orinconsiderate in different social situations. With the push towards agentic AI,wherein systems become increasingly proactive in chasing goals and performingactions in the world, considering the pragmatics of interaction becomesessential. We propose an interactional approach to ethics that is centred onrelational and situational factors. We explore what it means for a system, as asocial actor, to treat an individual respectfully in a (series of)interaction(s). Our work anticipates a set of largely unexplored risks at thelevel of situated social interaction, and offers practical suggestions to helpagentic LLM technologies treat people well.

Should agentic conversational AI change how we think about ethics? Characterising an interactional ethics centred on respect