Human-AI Interactions Through A Gricean Lens
Laura Panfili, Steve Duman, Andrew Nave, Katherine Phelps Ridgeway,, Nathan Eversole, Ruhi Sarikaya

TL;DR
This study evaluates human-AI interactions through Grice's Cooperative Principle, revealing that humans apply these maxims to AI conversations, which can inform better AI design and understanding of interaction dynamics.
Contribution
It demonstrates that humans use Gricean maxims in AI interactions and proposes adding a human Priority principle to better describe human-AI communication.
Findings
Participants identified violations of Grice's maxims in AI interactions.
Relevance violations were most frequent and frustrating.
Participants disliked unsolicited AI suggestions.
Abstract
Grice's Cooperative Principle (1975) describes the implicit maxims that guide conversation between humans. 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? The present study addresses this question by evaluating human-AI interactions using Grice's four maxims; we demonstrate 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…
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