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Robot occupations affect the categorization border between human and robot faces
The Uncanny Valley hypothesis implies that people perceive a subjective border between human and robot faces. The robot–human border refers to the level of human-like features that distinguishes humans from robots. However, whether people’s perceived anthropomorphism and robot–human borders are cons...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630393/ https://www.ncbi.nlm.nih.gov/pubmed/37935780 http://dx.doi.org/10.1038/s41598-023-46425-0 |
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author | Shen, Junyi Tang, Guyue Koyama, Shinichi |
author_facet | Shen, Junyi Tang, Guyue Koyama, Shinichi |
author_sort | Shen, Junyi |
collection | PubMed |
description | The Uncanny Valley hypothesis implies that people perceive a subjective border between human and robot faces. The robot–human border refers to the level of human-like features that distinguishes humans from robots. However, whether people’s perceived anthropomorphism and robot–human borders are consistent across different robot occupations remains to be explored. This study examined the robot–human border by analyzing the human photo proportion represented by the point of subjective equality in three image classification tasks. Stimulus images were generated by morphing a robot face photo and one each of four human photos in systematically changed proportions. Participants classified these morphed images in three different robot occupational conditions to explore the effect of changing robot jobs on the robot–human border. The results indicated that robot occupation and participant age and gender influenced people’s perceived anthropomorphism of robots. These can be explained by the implicit link between robot job and appearance, especially in a stereotyped context. The study suggests that giving an expected appearance to a robot may reproduce and strengthen a stereotype that associates a certain appearance with a certain job. |
format | Online Article Text |
id | pubmed-10630393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106303932023-11-07 Robot occupations affect the categorization border between human and robot faces Shen, Junyi Tang, Guyue Koyama, Shinichi Sci Rep Article The Uncanny Valley hypothesis implies that people perceive a subjective border between human and robot faces. The robot–human border refers to the level of human-like features that distinguishes humans from robots. However, whether people’s perceived anthropomorphism and robot–human borders are consistent across different robot occupations remains to be explored. This study examined the robot–human border by analyzing the human photo proportion represented by the point of subjective equality in three image classification tasks. Stimulus images were generated by morphing a robot face photo and one each of four human photos in systematically changed proportions. Participants classified these morphed images in three different robot occupational conditions to explore the effect of changing robot jobs on the robot–human border. The results indicated that robot occupation and participant age and gender influenced people’s perceived anthropomorphism of robots. These can be explained by the implicit link between robot job and appearance, especially in a stereotyped context. The study suggests that giving an expected appearance to a robot may reproduce and strengthen a stereotype that associates a certain appearance with a certain job. Nature Publishing Group UK 2023-11-07 /pmc/articles/PMC10630393/ /pubmed/37935780 http://dx.doi.org/10.1038/s41598-023-46425-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Shen, Junyi Tang, Guyue Koyama, Shinichi Robot occupations affect the categorization border between human and robot faces |
title | Robot occupations affect the categorization border between human and robot faces |
title_full | Robot occupations affect the categorization border between human and robot faces |
title_fullStr | Robot occupations affect the categorization border between human and robot faces |
title_full_unstemmed | Robot occupations affect the categorization border between human and robot faces |
title_short | Robot occupations affect the categorization border between human and robot faces |
title_sort | robot occupations affect the categorization border between human and robot faces |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630393/ https://www.ncbi.nlm.nih.gov/pubmed/37935780 http://dx.doi.org/10.1038/s41598-023-46425-0 |
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