Artificial Intelligence in Local Governments: Perceptions of City Managers on Prospects, Constraints and Choices
Yigitcanlar, Tan, Agdas, Duzgun, & Degirmenci, Kenan (2023) Artificial Intelligence in Local Governments: Perceptions of City Managers on Prospects, Constraints and Choices. AI and Society, 38(3), pp. 1135-1150.
|
Published Version
(PDF 3MB)
100182332. Available under License Creative Commons Attribution 4.0. |
Open access copy at publisher website
Description
Highly sophisticated capabilities of artificial intelligence (AI) have skyrocketed its popularity across many industry sectors globally. The public sector is one of these. Many cities around the world are trying to position themselves as leaders of urban innovation through the development and deployment of AI systems. Likewise, increasing numbers of local government agencies are attempting to utilise AI technologies in their operations to deliver policy and generate efficiencies in highly uncertain and complex urban environments. While the popularity of AI is on the rise in urban policy circles, there is limited understanding and lack of empirical studies on the city manager perceptions concerning urban AI systems. Bridging this gap is the rationale of this study. The methodological approach adopted in this study is two-fold. First, the study collects data through semi-structured interviews with city managers from Australia and the US. Then, the study analyses the data using the summative content analysis technique with two data analysis software. The analysis identifies the following themes and generates insights into local government services: AI adoption areas, cautionary areas, challenges, effects, impacts, knowledge basis, plans, preparedness, roadblocks, technologies, deployment timeframes, and usefulness. The study findings inform city managers in their efforts to deploy AI in their local government operations, and offer directions for prospective research.
Impact and interest:
Citation counts are sourced monthly from Scopus and Web of Science® citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads:
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
| ID Code: | 214111 | ||||||
|---|---|---|---|---|---|---|---|
| Item Type: | Contribution to Journal (Journal Article) | ||||||
| Refereed: | Yes | ||||||
| ORCID iD: |
|
||||||
| Additional Information: | Open Access funding enabled and organized by CAUL and its Member Institutions. This research was funded by the Australian Research Council Discovery Grant Scheme, grant number DP220101255. | ||||||
| Measurements or Duration: | 16 pages | ||||||
| Keywords: | AI, artificial intelligence, urban AI, local government AI, technology adoption, technology perception, local government, city manager, smart city | ||||||
| DOI: | 10.1007/s00146-022-01450-x | ||||||
| ISSN: | 0951-5666 | ||||||
| Pure ID: | 100182332 | ||||||
| Divisions: | Current > Research Centres > Centre for Future Enterprise Current > Research Centres > Centre for the Environment Current > QUT Faculties and Divisions > Faculty of Business & Law Current > QUT Faculties and Divisions > Faculty of Science Current > Schools > School of Information Systems Current > QUT Faculties and Divisions > Faculty of Engineering Current > Schools > School of Architecture & Built Environment Current > Schools > School of Civil & Environmental Engineering |
||||||
| Funding: | |||||||
| Copyright Owner: | The Author(s) 2022 | ||||||
| Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||||
| Deposited On: | 26 Oct 2021 16:18 | ||||||
| Last Modified: | 26 Sep 2026 23:15 |
Export: EndNote | Dublin Core | BibTeX
Repository Staff Only: item control page