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Challenging presumed technological superiority when working with (artificial) colleagues
Technological advancements are ubiquitously supporting or even replacing humans in all areas of life, bringing the potential for human-technology symbiosis but also novel challenges. To address these challenges, we conducted three experiments in different task contexts ranging from loan assignment o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8904495/ https://www.ncbi.nlm.nih.gov/pubmed/35260683 http://dx.doi.org/10.1038/s41598-022-07808-x |
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author | Rieger, Tobias Roesler, Eileen Manzey, Dietrich |
author_facet | Rieger, Tobias Roesler, Eileen Manzey, Dietrich |
author_sort | Rieger, Tobias |
collection | PubMed |
description | Technological advancements are ubiquitously supporting or even replacing humans in all areas of life, bringing the potential for human-technology symbiosis but also novel challenges. To address these challenges, we conducted three experiments in different task contexts ranging from loan assignment over X-Ray evaluation to process industry. Specifically, we investigated the impact of support agent (artificial intelligence, decision support system, or human) and failure experience (one vs. none) on trust-related aspects of human-agent interaction. This included not only the subjective evaluation of the respective agent in terms of trust, reliability, and responsibility, when working together, but also a change in perspective to the willingness to be assessed oneself by the agent. In contrast to a presumed technological superiority, we show a general advantage with regard to trust and responsibility of human support over both technical support systems (i.e., artificial intelligence and decision support system), regardless of task context from the collaborative perspective. This effect reversed to a preference for technical systems when switching the perspective to being assessed. These findings illustrate an imperfect automation schema from the perspective of the advice-taker and demonstrate the importance of perspective when working with or being assessed by machine intelligence. |
format | Online Article Text |
id | pubmed-8904495 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89044952022-03-09 Challenging presumed technological superiority when working with (artificial) colleagues Rieger, Tobias Roesler, Eileen Manzey, Dietrich Sci Rep Article Technological advancements are ubiquitously supporting or even replacing humans in all areas of life, bringing the potential for human-technology symbiosis but also novel challenges. To address these challenges, we conducted three experiments in different task contexts ranging from loan assignment over X-Ray evaluation to process industry. Specifically, we investigated the impact of support agent (artificial intelligence, decision support system, or human) and failure experience (one vs. none) on trust-related aspects of human-agent interaction. This included not only the subjective evaluation of the respective agent in terms of trust, reliability, and responsibility, when working together, but also a change in perspective to the willingness to be assessed oneself by the agent. In contrast to a presumed technological superiority, we show a general advantage with regard to trust and responsibility of human support over both technical support systems (i.e., artificial intelligence and decision support system), regardless of task context from the collaborative perspective. This effect reversed to a preference for technical systems when switching the perspective to being assessed. These findings illustrate an imperfect automation schema from the perspective of the advice-taker and demonstrate the importance of perspective when working with or being assessed by machine intelligence. Nature Publishing Group UK 2022-03-08 /pmc/articles/PMC8904495/ /pubmed/35260683 http://dx.doi.org/10.1038/s41598-022-07808-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Rieger, Tobias Roesler, Eileen Manzey, Dietrich Challenging presumed technological superiority when working with (artificial) colleagues |
title | Challenging presumed technological superiority when working with (artificial) colleagues |
title_full | Challenging presumed technological superiority when working with (artificial) colleagues |
title_fullStr | Challenging presumed technological superiority when working with (artificial) colleagues |
title_full_unstemmed | Challenging presumed technological superiority when working with (artificial) colleagues |
title_short | Challenging presumed technological superiority when working with (artificial) colleagues |
title_sort | challenging presumed technological superiority when working with (artificial) colleagues |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8904495/ https://www.ncbi.nlm.nih.gov/pubmed/35260683 http://dx.doi.org/10.1038/s41598-022-07808-x |
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