The difference between artificial intelligence implicatures and human implicatures in conversation
TL;DR
The analysis reveals that while artificial intelligence can simulate implicature-like meanings, these implicatures often lack intentionality, contextual sensitivity, and shared socio-cultural grounding, in contrast, human implicatures are deeply rooted in communicative intention, contextual awareness, and social norms.
Abstract
This research investigates the pragmatic differences between conversational implicatures produced by artificial intelligence systems and those generated by humans in everyday conversation. Grounded in Grice’s Cooperative Principle and its four conversational maxims—quantity, quality, relation, and manner—the study analyzes how implicatures emerge, function, and are interpreted in human–human and human–AI "chat GPT" interactions. Adopting a qualitative descriptive-analytical approach, the study examines ten conversational exchanges: five human conversations and five AI-based conversations. The analysis reveals that while artificial intelligence can simulate implicature-like meanings, these implicatures often lack intentionality, contextual sensitivity, and shared socio-cultural grounding. In contrast, human implicatures are deeply rooted in communicative intention, contextual awareness, and social norms. The findings contribute to pragmatic studies and human–AI "chat GPT" communication by highlighting the fundamental pragmatic gap between artificial and human conversational behavior.