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Enactive artificial intelligence: subverting gender norms in human-robot interaction

INTRODUCTION: This paper presents Enactive Artificial Intelligence (eAI) as a gender-inclusive approach to AI, emphasizing the need to address social marginalization resulting from unrepresentative AI design. METHODS: The study employs a multidisciplinary framework to explore the intersectionality o...

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Detalles Bibliográficos
Autores principales: Hipólito, Inês, Winkle, Katie, Lie, Merete
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10285661/
https://www.ncbi.nlm.nih.gov/pubmed/37359909
http://dx.doi.org/10.3389/fnbot.2023.1149303
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author Hipólito, Inês
Winkle, Katie
Lie, Merete
author_facet Hipólito, Inês
Winkle, Katie
Lie, Merete
author_sort Hipólito, Inês
collection PubMed
description INTRODUCTION: This paper presents Enactive Artificial Intelligence (eAI) as a gender-inclusive approach to AI, emphasizing the need to address social marginalization resulting from unrepresentative AI design. METHODS: The study employs a multidisciplinary framework to explore the intersectionality of gender and technoscience, focusing on the subversion of gender norms within Robot-Human Interaction in AI. RESULTS: The results reveal the development of four ethical vectors, namely explainability, fairness, transparency, and auditability, as essential components for adopting an inclusive stance and promoting gender-inclusive AI. DISCUSSION: By considering these vectors, we can ensure that AI aligns with societal values, promotes equity and justice, and facilitates the creation of a more just and equitable society.
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spelling pubmed-102856612023-06-23 Enactive artificial intelligence: subverting gender norms in human-robot interaction Hipólito, Inês Winkle, Katie Lie, Merete Front Neurorobot Neuroscience INTRODUCTION: This paper presents Enactive Artificial Intelligence (eAI) as a gender-inclusive approach to AI, emphasizing the need to address social marginalization resulting from unrepresentative AI design. METHODS: The study employs a multidisciplinary framework to explore the intersectionality of gender and technoscience, focusing on the subversion of gender norms within Robot-Human Interaction in AI. RESULTS: The results reveal the development of four ethical vectors, namely explainability, fairness, transparency, and auditability, as essential components for adopting an inclusive stance and promoting gender-inclusive AI. DISCUSSION: By considering these vectors, we can ensure that AI aligns with societal values, promotes equity and justice, and facilitates the creation of a more just and equitable society. Frontiers Media S.A. 2023-06-08 /pmc/articles/PMC10285661/ /pubmed/37359909 http://dx.doi.org/10.3389/fnbot.2023.1149303 Text en Copyright © 2023 Hipólito, Winkle and Lie. 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 Neuroscience
Hipólito, Inês
Winkle, Katie
Lie, Merete
Enactive artificial intelligence: subverting gender norms in human-robot interaction
title Enactive artificial intelligence: subverting gender norms in human-robot interaction
title_full Enactive artificial intelligence: subverting gender norms in human-robot interaction
title_fullStr Enactive artificial intelligence: subverting gender norms in human-robot interaction
title_full_unstemmed Enactive artificial intelligence: subverting gender norms in human-robot interaction
title_short Enactive artificial intelligence: subverting gender norms in human-robot interaction
title_sort enactive artificial intelligence: subverting gender norms in human-robot interaction
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10285661/
https://www.ncbi.nlm.nih.gov/pubmed/37359909
http://dx.doi.org/10.3389/fnbot.2023.1149303
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