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Advances in artificial intelligence (AI) have attracted great attention from researchers and practitioners and have opened up a broad range of beneficial opportunities for AI usage in the public sector. Against this background, there is an emerging need for a holistic understanding of the range and impact of AI-based applications and associated challenges. However, previous research considers AI applications and challenges only in isolation and fragmentarily. Given the lack of a comprehensive overview of AI-based applications and challenges for the public sector, our conceptual approach analyzes and compiles relevant insights from scientific literature to provide an integrative overview of AI applications and related challenges. Our results suggest 10 AI application areas, describing their value creation and functioning as well as specific public use cases. In addition, we identify four major dimensions of AI challenges. We finally discuss our findings, deriving implications for theory and practice and providing suggestions for future research.
+ ID der Publikation: hslu_55539 + Art des Beitrages: Wissenschaftliche Medien + Jahrgang: 42 + Sprache: Englisch + Letzte Aktualisierung: 2019-12-10 14:07:56 + Publisher's Statement: This is an Accepted Manuscript of an article published by Taylor & Francis in "International Journal of Public Administration" on 24.07.2018, available online: http://www.tandfonline.com/10.1080/01900692.2018.1498103.
Artificial intelligence; public sector; AI applications; AI challenges
Artificial intelligence; public sector; AI applications; AI challenges
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 776 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 0.01% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 0.1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
| views | 1K | |
| downloads | 765 |

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