Conversational Implicature in Human-AI Interactions

Abstract

AI (artificial intelligence) systems should be able to talk more and more like people as the way people use computers changes. But there is still a big problem: how to understand and use verbal implicature, which is a key part of being pragmatically competent. This article looks at how implicature works between people and AI, as well as how well AI systems understand and use suggested ideas. From the point of view of Grice's Cooperative Principle and maxims, this study looks at how well chatbots like ChatGPT, Google Assistant, and Siri work in real life. There is a mix of different research methods used in this paper, such as controlled tests and qualitative speech analysis. It also looks at how people understand implicature and how AI acts in various situations, such as when it needs to be funny, polite, or use subtle language. This study utilises various aspects of language to demonstrate that AI can replicate some meanings after being trained on large datasets, but it often struggles to comprehend non-literal purposes or process contexts dynamically.

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