An experimental study of public trust in AI chatbots in the public sector
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Much of the existing AI research is technical in nature, studying specific technological problems and solutions in the computer science domain.
“Third, much of the existing AI research is technical in nature, studying specific technological problems and solutions in the computer science domain (Aoki, 2020).”
From Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda (2021) · cites this paper as Aoki, 2020
Compared to the private sector, there is less knowledge concerning AI challenges specifically associated with the public sector.
“Compared to the private sector, there is less knowledge concerning AI challenges specifically associated with the public sector (Aoki, 2020;Wang & Siau, 2018;Wirtz, Weyerer, & Sturm, 2020).”
From Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda (2021) · cites this paper as Aoki, 2020
It is not common in AI research today to contribute to empirical testing, as confirmed by our research.
“Although considerable attention has been paid to AI technologies and speculations about the societal impacts of AI, it is not common in AI research today to contribute to empirical testing (Aoki, 2020), as confirmed by our research.”
From Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda (2021) · cites this paper as Aoki, 2020
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“are widely speculated about, and empirical evidence remains rare [58].”
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“…surveys and interviews can capture how public officials perceive their discretionary autonomy, fairness, and accountability, providing insight into the subjective and interpretive dimensions of discretion (for example, Aoki, 2020 ; de Boer & Raaphorst, 2023 Nagtegaal, 2021 ; Wang et al., 2022 ).”
Influential
- Authors
- Aoki, N.
- Affiliations
- The University of Tokyo (JP)
- Corresponding author
- Aoki, Naomi
- ORCID
- Aoki, Naomi
- Venue
- Government Information Quarterly
- Publisher
- Elsevier BV
- Published
- 2020-10
- Volume
- 37
- Issue
- 4
- Pages
- 101490
- ISSN
- 0740-624X (ISSN-L)
- OpenAlex
- W3064053140
- Cited by
- 350
- References
- 51
- Citations by year
- 2026: 72 · 2025: 84 · 2024: 76 · 2023: 56 · 2022: 40 · 2021: 21 · 2020: 1
- FWCI
- 101.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Government Information Quarterly (publishedVersion)
- Funders
- National University of Singapore
- Topics
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- public trust in AI, AI chatbots, public sector, trust in machines, parental support, waste sorting, government communication
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