A robot's sense-making of fallacies and rhetorical tropes. Creating ontologies of what humans try to say
This addresses the challenge of improving human-robot interaction for social robots by handling metaphorical and fallacious speech, though it appears incremental in applying existing theories to a specific domain.
The paper tackled the problem of robots misunderstanding human communication that is illogical or non-literal, by developing a fail-safe protocol that enables robots to politely interpret such utterances using philosophical and logical frameworks.
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