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

Johan F. Hoorn; Denice J. Tuinhof

doi:10.1016/j.cogsys.2021.10.003

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

Johan F. Hoorn^*, Denice J. Tuinhof

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

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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.

Original language	English
Pages (from-to)	116-130
Number of pages	15
Journal	Cognitive Systems Research
Volume	72
Early online date	29 Oct 2021
DOIs	https://doi.org/10.1016/j.cogsys.2021.10.003
Publication status	Published - Mar 2022

Bibliographical note

Funding Information:
This study was supported by Communicating with and Relating to Social Robots (NWO Open Competition Digitalisation, grant 406.DI.19.005). The authors wish to thank Jan Treur and Qixin Wang for reviewing the logics. We are grateful to Rick Cooper for commenting on an earlier draft of this paper. We kindly acknowledge the anonymous reviewers for their valuable comments and suggestions. Ivy S. Huang is thanked for her translation of the abstract into Chinese. The authors have no competing interests to declare.

Publisher Copyright:
© 2021

Funding

This study was supported by Communicating with and Relating to Social Robots (NWO Open Competition Digitalisation, grant 406.DI.19.005). The authors wish to thank Jan Treur and Qixin Wang for reviewing the logics. We are grateful to Rick Cooper for commenting on an earlier draft of this paper. We kindly acknowledge the anonymous reviewers for their valuable comments and suggestions. Ivy S. Huang is thanked for her translation of the abstract into Chinese. The authors have no competing interests to declare.

Keywords

Epistemics of the virtual
Logical fallacies
Maxim of quality
Metaphors
Reference
Sense
Social robots
Tableau reasoning

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10.1016/j.cogsys.2021.10.003

A robot’s sense-making of fallacies and rhetorical tropes. Creating ontologies of what humans try to sayFinal published version, 1.63 MBLicence: Article 25fa Dutch Copyright Act

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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 {\textquoteleft}forgiving{\textquoteright} and {\textquoteleft}suspending disbelief{\textquoteright} 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.",

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AB - 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.

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JO - Cognitive Systems Research

JF - Cognitive Systems Research

ER -

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

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Keywords

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