Human-AI interactions through a Gricean lens

Abstract

Grice’s Cooperative Principle (1975), which describes the implicit maxims that guide effective conversation, has long been applied to conversations between humans. However, as humans begin to interact with non-human dialogue systems more frequently and in a broader scope, an important question emerges: what principles govern those interactions? In the present study, this question is addressed, as human-AI interactions are categorized using Grice’s four maxims. In doing so, it demonstrates the advantages and shortcomings of such an approach, ultimately demonstrating that humans do, indeed, apply these maxims to interactions with AI, even making explicit references to the AI’s performance through a Gricean lens. Twenty-three participants interacted with an American English-speaking Alexa and rated and discussed their experience with an in-lab researcher. Researchers then reviewed each exchange, identifying those that might relate to Grice’s maxims: Quantity, Quality, Manner, and Relevance. Many instances of explicit user frustration stemmed from violations of Grice’s maxims. Quantity violations were noted for too little but not too much information, while Quality violations were rare, indicating high trust in Alexa’s responses. Manner violations focused on speed and humanness. Relevance violations were the most frequent of all violations, and they appear to be the most frustrating. While the maxims help describe many of the issues participants encountered with Alexa’s responses, other issues do not fit neatly into Grice’s framework. For example, participants were particularly averse to Alexa initiating exchanges or making unsolicited suggestions. To address this gap, we propose the addition of human Priority to describe human-AI interaction. Humans and AIs are not (yet?) conversational equals, and human initiative takes priority. Moreover, we find that Relevance is of particular importance in human-AI interactions and suggest that the application of Grice’s Cooperative Principles to human-AI interactions is beneficial both from an AI development perspective as well as a tool for describing an emerging form of interaction.