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What is new with Artificial Intelligence? Human–agent interactions through the lens of social agency
In this article, we suggest that the study of social interactions and the development of a “sense of agency” in joint action can help determine the content of relevant explanations to be implemented in artificial systems to make them “explainable.” The introduction of automated systems, and more bro...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559368/ https://www.ncbi.nlm.nih.gov/pubmed/36248519 http://dx.doi.org/10.3389/fpsyg.2022.954444 |
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author | Pagliari, Marine Chambon, Valérian Berberian, Bruno |
author_facet | Pagliari, Marine Chambon, Valérian Berberian, Bruno |
author_sort | Pagliari, Marine |
collection | PubMed |
description | In this article, we suggest that the study of social interactions and the development of a “sense of agency” in joint action can help determine the content of relevant explanations to be implemented in artificial systems to make them “explainable.” The introduction of automated systems, and more broadly of Artificial Intelligence (AI), into many domains has profoundly changed the nature of human activity, as well as the subjective experience that agents have of their own actions and their consequences – an experience that is commonly referred to as sense of agency. We propose to examine the empirical evidence supporting this impact of automation on individuals’ sense of agency, and hence on measures as diverse as operator performance, system explicability and acceptability. Because of some of its key characteristics, AI occupies a special status in the artificial systems landscape. We suggest that this status prompts us to reconsider human–AI interactions in the light of human–human relations. We approach the study of joint actions in human social interactions to deduce what key features are necessary for the development of a reliable sense of agency in a social context and suggest that such framework can help define what constitutes a good explanation. Finally, we propose possible directions to improve human–AI interactions and, in particular, to restore the sense of agency of human operators, improve their confidence in the decisions made by artificial agents, and increase the acceptability of such agents. |
format | Online Article Text |
id | pubmed-9559368 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95593682022-10-14 What is new with Artificial Intelligence? Human–agent interactions through the lens of social agency Pagliari, Marine Chambon, Valérian Berberian, Bruno Front Psychol Psychology In this article, we suggest that the study of social interactions and the development of a “sense of agency” in joint action can help determine the content of relevant explanations to be implemented in artificial systems to make them “explainable.” The introduction of automated systems, and more broadly of Artificial Intelligence (AI), into many domains has profoundly changed the nature of human activity, as well as the subjective experience that agents have of their own actions and their consequences – an experience that is commonly referred to as sense of agency. We propose to examine the empirical evidence supporting this impact of automation on individuals’ sense of agency, and hence on measures as diverse as operator performance, system explicability and acceptability. Because of some of its key characteristics, AI occupies a special status in the artificial systems landscape. We suggest that this status prompts us to reconsider human–AI interactions in the light of human–human relations. We approach the study of joint actions in human social interactions to deduce what key features are necessary for the development of a reliable sense of agency in a social context and suggest that such framework can help define what constitutes a good explanation. Finally, we propose possible directions to improve human–AI interactions and, in particular, to restore the sense of agency of human operators, improve their confidence in the decisions made by artificial agents, and increase the acceptability of such agents. Frontiers Media S.A. 2022-09-29 /pmc/articles/PMC9559368/ /pubmed/36248519 http://dx.doi.org/10.3389/fpsyg.2022.954444 Text en Copyright © 2022 Pagliari, Chambon and Berberian. 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 | Psychology Pagliari, Marine Chambon, Valérian Berberian, Bruno What is new with Artificial Intelligence? Human–agent interactions through the lens of social agency |
title | What is new with Artificial Intelligence? Human–agent interactions through the lens of social agency |
title_full | What is new with Artificial Intelligence? Human–agent interactions through the lens of social agency |
title_fullStr | What is new with Artificial Intelligence? Human–agent interactions through the lens of social agency |
title_full_unstemmed | What is new with Artificial Intelligence? Human–agent interactions through the lens of social agency |
title_short | What is new with Artificial Intelligence? Human–agent interactions through the lens of social agency |
title_sort | what is new with artificial intelligence? human–agent interactions through the lens of social agency |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559368/ https://www.ncbi.nlm.nih.gov/pubmed/36248519 http://dx.doi.org/10.3389/fpsyg.2022.954444 |
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