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Employees’ Appraisals and Trust of Artificial Intelligences’ Transparency and Opacity

Artificial intelligence (AI) is being increasingly used as a decision agent in enterprises. Employees’ appraisals and AI affect the smooth progress of AI–employee cooperation. This paper studies (1) whether employees’ challenge appraisals, threat appraisals and trust in AI are different for AI trans...

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Detalles Bibliográficos
Autores principales: Yu, Liangru, Li, Yi, Fan, Fan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10135857/
https://www.ncbi.nlm.nih.gov/pubmed/37102857
http://dx.doi.org/10.3390/bs13040344
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author Yu, Liangru
Li, Yi
Fan, Fan
author_facet Yu, Liangru
Li, Yi
Fan, Fan
author_sort Yu, Liangru
collection PubMed
description Artificial intelligence (AI) is being increasingly used as a decision agent in enterprises. Employees’ appraisals and AI affect the smooth progress of AI–employee cooperation. This paper studies (1) whether employees’ challenge appraisals, threat appraisals and trust in AI are different for AI transparency and opacity. (2) This study investigates how AI transparency affects employees’ trust in AI through employee appraisals (challenge and threat appraisals), and (3) whether and how employees’ domain knowledge about AI moderates the relationship between AI transparency and appraisals. A total of 375 participants with work experience were recruited for an online hypothetical scenario experiment. The results showed that AI transparency (vs. opacity) led to higher challenge appraisals and trust and lower threat appraisals. However, in both AI transparency and opacity, employees believed that AI decisions brought more challenges than threats. In addition, we found the parallel mediating effect of challenge appraisals and threat appraisals. AI transparency promotes employees’ trust in AI by increasing employees’ challenge appraisals and reducing employees’ threat appraisals. Finally, employees’ domain knowledge about AI moderated the relationship between AI transparency and appraisals. Specifically, domain knowledge negatively moderated the positive effect of AI transparency on challenge appraisals, and domain knowledge positively moderated the negative effect of AI transparency on threat appraisals.
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spelling pubmed-101358572023-04-28 Employees’ Appraisals and Trust of Artificial Intelligences’ Transparency and Opacity Yu, Liangru Li, Yi Fan, Fan Behav Sci (Basel) Article Artificial intelligence (AI) is being increasingly used as a decision agent in enterprises. Employees’ appraisals and AI affect the smooth progress of AI–employee cooperation. This paper studies (1) whether employees’ challenge appraisals, threat appraisals and trust in AI are different for AI transparency and opacity. (2) This study investigates how AI transparency affects employees’ trust in AI through employee appraisals (challenge and threat appraisals), and (3) whether and how employees’ domain knowledge about AI moderates the relationship between AI transparency and appraisals. A total of 375 participants with work experience were recruited for an online hypothetical scenario experiment. The results showed that AI transparency (vs. opacity) led to higher challenge appraisals and trust and lower threat appraisals. However, in both AI transparency and opacity, employees believed that AI decisions brought more challenges than threats. In addition, we found the parallel mediating effect of challenge appraisals and threat appraisals. AI transparency promotes employees’ trust in AI by increasing employees’ challenge appraisals and reducing employees’ threat appraisals. Finally, employees’ domain knowledge about AI moderated the relationship between AI transparency and appraisals. Specifically, domain knowledge negatively moderated the positive effect of AI transparency on challenge appraisals, and domain knowledge positively moderated the negative effect of AI transparency on threat appraisals. MDPI 2023-04-20 /pmc/articles/PMC10135857/ /pubmed/37102857 http://dx.doi.org/10.3390/bs13040344 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yu, Liangru
Li, Yi
Fan, Fan
Employees’ Appraisals and Trust of Artificial Intelligences’ Transparency and Opacity
title Employees’ Appraisals and Trust of Artificial Intelligences’ Transparency and Opacity
title_full Employees’ Appraisals and Trust of Artificial Intelligences’ Transparency and Opacity
title_fullStr Employees’ Appraisals and Trust of Artificial Intelligences’ Transparency and Opacity
title_full_unstemmed Employees’ Appraisals and Trust of Artificial Intelligences’ Transparency and Opacity
title_short Employees’ Appraisals and Trust of Artificial Intelligences’ Transparency and Opacity
title_sort employees’ appraisals and trust of artificial intelligences’ transparency and opacity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10135857/
https://www.ncbi.nlm.nih.gov/pubmed/37102857
http://dx.doi.org/10.3390/bs13040344
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