The impact of labeling automotive AI as trustworthy or reliable on user evaluation and technology acceptance
Abstract This study explores whether labeling AI as either “trustworthy” or “reliable” influences user perceptions and acceptance of automotive AI technologies. Utilizing a one-way between-subjects design, the research presented online participants (N = 478) with a text presenting guidelines for eit...
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| Format: | Article |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-85558-2 |
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| author | John Dorsch Ophelia Deroy |
| author_facet | John Dorsch Ophelia Deroy |
| author_sort | John Dorsch |
| collection | DOAJ |
| description | Abstract This study explores whether labeling AI as either “trustworthy” or “reliable” influences user perceptions and acceptance of automotive AI technologies. Utilizing a one-way between-subjects design, the research presented online participants (N = 478) with a text presenting guidelines for either trustworthy or reliable AI, before asking them to evaluate 3 vignette scenarios and fill in a modified version of the Technology Acceptance Model which covers different variables, such as perceived ease of use, human-like trust, and overall attitude. While labeling AI as “trustworthy” did not significantly influence people’s judgements on specific scenarios, it increased perceived ease of use and human-like trust, namely benevolence, suggesting a facilitating influence on usability and an anthropomorphic effect on user perceptions. The study provides insights into how specific labels affect adopting certain perceptions of AI technology. |
| format | Article |
| id | doaj-art-cd4847ecbeb945ce8b4cabad4a3bd456 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-cd4847ecbeb945ce8b4cabad4a3bd4562025-01-12T12:23:12ZengNature PortfolioScientific Reports2045-23222025-01-0115111410.1038/s41598-025-85558-2The impact of labeling automotive AI as trustworthy or reliable on user evaluation and technology acceptanceJohn Dorsch0Ophelia Deroy1Faculty of Philosophy, Philosophy of Science and the Study of Religion, Ludwig-Maximilians-Universität MünchenFaculty of Philosophy, Philosophy of Science and the Study of Religion, Ludwig-Maximilians-Universität MünchenAbstract This study explores whether labeling AI as either “trustworthy” or “reliable” influences user perceptions and acceptance of automotive AI technologies. Utilizing a one-way between-subjects design, the research presented online participants (N = 478) with a text presenting guidelines for either trustworthy or reliable AI, before asking them to evaluate 3 vignette scenarios and fill in a modified version of the Technology Acceptance Model which covers different variables, such as perceived ease of use, human-like trust, and overall attitude. While labeling AI as “trustworthy” did not significantly influence people’s judgements on specific scenarios, it increased perceived ease of use and human-like trust, namely benevolence, suggesting a facilitating influence on usability and an anthropomorphic effect on user perceptions. The study provides insights into how specific labels affect adopting certain perceptions of AI technology.https://doi.org/10.1038/s41598-025-85558-2Trustworthy AIEthics of AIHuman–machine interfaceTechnology acceptanceAlgorithm aversion |
| spellingShingle | John Dorsch Ophelia Deroy The impact of labeling automotive AI as trustworthy or reliable on user evaluation and technology acceptance Scientific Reports Trustworthy AI Ethics of AI Human–machine interface Technology acceptance Algorithm aversion |
| title | The impact of labeling automotive AI as trustworthy or reliable on user evaluation and technology acceptance |
| title_full | The impact of labeling automotive AI as trustworthy or reliable on user evaluation and technology acceptance |
| title_fullStr | The impact of labeling automotive AI as trustworthy or reliable on user evaluation and technology acceptance |
| title_full_unstemmed | The impact of labeling automotive AI as trustworthy or reliable on user evaluation and technology acceptance |
| title_short | The impact of labeling automotive AI as trustworthy or reliable on user evaluation and technology acceptance |
| title_sort | impact of labeling automotive ai as trustworthy or reliable on user evaluation and technology acceptance |
| topic | Trustworthy AI Ethics of AI Human–machine interface Technology acceptance Algorithm aversion |
| url | https://doi.org/10.1038/s41598-025-85558-2 |
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