A robot's sense-making of fallacies and rhetorical tropes. Creating ontologies of what humans try to say

TL;DR

This paper develops a novel framework enabling robots to interpret human communication beyond literal meaning by analyzing fallacies, metaphors, and rhetorical tropes using logical and psychological principles.

Contribution

It introduces an ontology-based protocol that allows robots to understand and respond politely to metaphorical and fallacious human utterances, bridging gaps in communication understanding.

Findings

Robots can interpret non-literal human statements more effectively.

The protocol improves robot politeness and understanding in human-robot interactions.

Enhanced comprehension of metaphors and fallacies in communication.

Abstract

In the design of user-friendly robots, human communication should be understood by the system beyond mere logics and literal meaning. Robot communication-design has long ignored the importance of communication and politeness rules that are 'forgiving' and 'suspending disbelief' and cannot handle the basically metaphorical way humans design their utterances. Through analysis of the psychological causes of illogical and non-literal statements, signal detection, fundamental attribution errors, and anthropomorphism, we developed a fail-safe protocol for fallacies and tropes that makes use of Frege's distinction between reference and sense, Beth's tableau analytics, Grice's maxim of quality, and epistemic considerations to have the robot politely make sense of a user's sometimes unintelligible demands. Keywords: social robots, logical fallacies, metaphors, reference, sense, maxim of quality, tableau reasoning, epistemics of the virtual