Artificial intelligence in public services: When and why citizens accept its usage
Interest in implementing artificial intelligence (AI)–based software in the public sector is growing. First implementations and research in individual public services have already been carried out; however, a better understanding of citizens' acceptance of this technology is missing in the publ...
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Veröffentlicht in: | Government information quarterly 2022-07, Vol.39 (3), p.101704, Article 101704 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Interest in implementing artificial intelligence (AI)–based software in the public sector is growing. First implementations and research in individual public services have already been carried out; however, a better understanding of citizens' acceptance of this technology is missing in the public sector, as insights from the private sector cannot be transferred directly. For this purpose, we conduct policy-capturing experiments to analyze AI's acceptance in six representative scenarios. Based on behavioral reasoning theory, we gather evidence from 329 participants. The results show that AI solutions in general public services are preferred over those provided by humans, but specific services are still a human domain. Further analyses show that the major drivers toward acceptance are the reasons against AI. The results contribute to understanding of when and why AI is accepted in public services. Public administration can use the results to identify AI-based software to invest in and communicate their usage to perceive such investments' high acceptance rates.
•The interest and use of Artificial Intelligence (AI) is growing in the public sector.•Citizens' acceptance of AI in public services is essential for a successful implementation.•We provide a unique dataset from experiments with representative public services.•Results show that AI is preferred in general public services and reasons against are most decisive.•We contribute to a better understanding of how to use AI successfully within governments. |
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ISSN: | 0740-624X 1872-9517 |
DOI: | 10.1016/j.giq.2022.101704 |