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When people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution?

Given that artificial intelligence (AI) has been predicted to eventually take on human tasks demanding logical thinking, it makes sense that we should examine psychological responses of humans when their performance is inferior to AI. Research has demonstrated that after people fail a task, whether...

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Detalles Bibliográficos
Autores principales: Yokoi, Ryosuke, Nakayachi, Kazuya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758208/
https://www.ncbi.nlm.nih.gov/pubmed/35043036
http://dx.doi.org/10.1007/s12144-021-02559-w
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author Yokoi, Ryosuke
Nakayachi, Kazuya
author_facet Yokoi, Ryosuke
Nakayachi, Kazuya
author_sort Yokoi, Ryosuke
collection PubMed
description Given that artificial intelligence (AI) has been predicted to eventually take on human tasks demanding logical thinking, it makes sense that we should examine psychological responses of humans when their performance is inferior to AI. Research has demonstrated that after people fail a task, whether they reorient their behavior towards success depends on what they attribute the failure to. This study investigated the causal attributions people made in a competition task requiring such thinking. We also recorded whether they wanted to re-challenge the games after they were defeated by AI. Experiments 1 (N = 74) and 2 (N = 788) recruited Japanese participants, while Experiment 3 (N = 500) comprised American participants. There were two conditions: in the first, participants competed against an AI opponent and in the other, they believed they were competing against a human. The results of the three experiments showed that participants attributed the loss to their own and their opponent’s abilities more than any other factor, irrespective of the opponent type. The number of participants choosing to re-challenge the game did not differ significantly between the AI and human conditions in Experiments 1 and 3, although the number was lower in the AI condition than in the human condition in Experiment 2. Besides providing fresh insight on how people make causal attributions when competing against AI, our findings also predict how people will respond after their jobs are replaced by AI. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12144-021-02559-w.
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spelling pubmed-87582082022-01-14 When people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution? Yokoi, Ryosuke Nakayachi, Kazuya Curr Psychol Article Given that artificial intelligence (AI) has been predicted to eventually take on human tasks demanding logical thinking, it makes sense that we should examine psychological responses of humans when their performance is inferior to AI. Research has demonstrated that after people fail a task, whether they reorient their behavior towards success depends on what they attribute the failure to. This study investigated the causal attributions people made in a competition task requiring such thinking. We also recorded whether they wanted to re-challenge the games after they were defeated by AI. Experiments 1 (N = 74) and 2 (N = 788) recruited Japanese participants, while Experiment 3 (N = 500) comprised American participants. There were two conditions: in the first, participants competed against an AI opponent and in the other, they believed they were competing against a human. The results of the three experiments showed that participants attributed the loss to their own and their opponent’s abilities more than any other factor, irrespective of the opponent type. The number of participants choosing to re-challenge the game did not differ significantly between the AI and human conditions in Experiments 1 and 3, although the number was lower in the AI condition than in the human condition in Experiment 2. Besides providing fresh insight on how people make causal attributions when competing against AI, our findings also predict how people will respond after their jobs are replaced by AI. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12144-021-02559-w. Springer US 2022-01-14 /pmc/articles/PMC8758208/ /pubmed/35043036 http://dx.doi.org/10.1007/s12144-021-02559-w Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Yokoi, Ryosuke
Nakayachi, Kazuya
When people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution?
title When people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution?
title_full When people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution?
title_fullStr When people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution?
title_full_unstemmed When people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution?
title_short When people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution?
title_sort when people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution?
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758208/
https://www.ncbi.nlm.nih.gov/pubmed/35043036
http://dx.doi.org/10.1007/s12144-021-02559-w
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