Building Trust in AI: Exploring the Impact of AI Competence Framing
| dc.contributor.author | Gonzalez, Victoria | |
| dc.contributor.author | Amo, Laura | |
| dc.contributor.author | Das Smith, Sanjukta | |
| dc.date.accessioned | 2024-12-26T21:04:51Z | |
| dc.date.available | 2024-12-26T21:04:51Z | |
| dc.date.issued | 2025-01-07 | |
| dc.description.abstract | Trust in AI is crucial for its successful integration into organizations and society. Despite the increasing exposure of employees to AI-driven analyses, their adoption is not guaranteed solely by the presence of AI systems. Trust in AI is multifaceted, influenced by perceptions of its competence and accuracy. To investigate the impact of AI competence on user trust and error tolerance, we conducted an experiment using vignettes with varying AI positioning and accuracy. Our results highlight the importance of AI competence framing in shaping user trust; we found that a strong portrait of AI capabilities boosts trust and planned action. This study fills a gap in the existing literature by exploring the relationship between AI competence framing and trust in a professional context, providing insights for the implementation of AI in the workplace, and emphasizing the significance of building trust in AI for its adoption and effective use. | |
| dc.format.extent | 10 | |
| dc.identifier.doi | 10.24251/HICSS.2025.063 | |
| dc.identifier.isbn | 978-0-9981331-8-8 | |
| dc.identifier.other | 80c2676b-8fd8-43d3-af38-d3aced3419eb | |
| dc.identifier.uri | https://hdl.handle.net/10125/108900 | |
| dc.relation.ispartof | Proceedings of the 58th Hawaii International Conference on System Sciences | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Human-AI Collaborations and Ethical Issues | |
| dc.subject | ai competence, ai framing, error tolerance, trust in ai | |
| dc.title | Building Trust in AI: Exploring the Impact of AI Competence Framing | |
| dc.type | Conference Paper | |
| dc.type.dcmi | Text | |
| prism.startingpage | 521 |
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