Argumentation: A calculus for Human-Centric AI

This paper aims to expose and analyze the potential foundational role of Argumentation for Human-Centric AI, and to present the main challenges for this foundational role to be realized in a way that will fit well with the wider requirements and challenges of Human-Centric AI. The central idea set f...

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Detalles Bibliográficos
Autores principales: Dietz, Emmanuelle, Kakas, Antonis, Michael, Loizos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9634569/
https://www.ncbi.nlm.nih.gov/pubmed/36337143
http://dx.doi.org/10.3389/frai.2022.955579
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author Dietz, Emmanuelle
Kakas, Antonis
Michael, Loizos
author_facet Dietz, Emmanuelle
Kakas, Antonis
Michael, Loizos
author_sort Dietz, Emmanuelle
collection PubMed
description This paper aims to expose and analyze the potential foundational role of Argumentation for Human-Centric AI, and to present the main challenges for this foundational role to be realized in a way that will fit well with the wider requirements and challenges of Human-Centric AI. The central idea set forward is that by endowing machines with the ability to argue with forms of machine argumentation that are cognitively compatible with those of human argumentation, we will be able to support a naturally effective, enhancing and ethical human-machine cooperation and “social” integration.
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spelling pubmed-96345692022-11-05 Argumentation: A calculus for Human-Centric AI Dietz, Emmanuelle Kakas, Antonis Michael, Loizos Front Artif Intell Artificial Intelligence This paper aims to expose and analyze the potential foundational role of Argumentation for Human-Centric AI, and to present the main challenges for this foundational role to be realized in a way that will fit well with the wider requirements and challenges of Human-Centric AI. The central idea set forward is that by endowing machines with the ability to argue with forms of machine argumentation that are cognitively compatible with those of human argumentation, we will be able to support a naturally effective, enhancing and ethical human-machine cooperation and “social” integration. Frontiers Media S.A. 2022-10-21 /pmc/articles/PMC9634569/ /pubmed/36337143 http://dx.doi.org/10.3389/frai.2022.955579 Text en Copyright © 2022 Dietz, Kakas and Michael. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Dietz, Emmanuelle
Kakas, Antonis
Michael, Loizos
Argumentation: A calculus for Human-Centric AI
title Argumentation: A calculus for Human-Centric AI
title_full Argumentation: A calculus for Human-Centric AI
title_fullStr Argumentation: A calculus for Human-Centric AI
title_full_unstemmed Argumentation: A calculus for Human-Centric AI
title_short Argumentation: A calculus for Human-Centric AI
title_sort argumentation: a calculus for human-centric ai
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9634569/
https://www.ncbi.nlm.nih.gov/pubmed/36337143
http://dx.doi.org/10.3389/frai.2022.955579
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AT kakasantonis argumentationacalculusforhumancentricai
AT michaelloizos argumentationacalculusforhumancentricai

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