Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/8412
Title: | Public perceptions on application areas and adoption challenges of AI in urban services |
Authors: | Yigitcanlar, Tan Prof. LI Yi Man, Rita Inkinen, Tommi Paz, Alexander |
Issue Date: | 2022 |
Source: | Emerging Science Journal, 2022, Vol. 6(6), pp. 1199-1236. |
Journal: | Emerging Science Journal |
Abstract: | Artificial intelligence (AI) deployment is exceedingly relevant to local governments, for example, in planning and delivering urban services. AI adoption in urban services, however, is an understudied area, particularly because there is limited knowledge and hence a research gap on the public's perceptions-users/receivers of these services. This study aims to examine people’s behaviors and preferences regarding the most suited urban services for application of AI technology and the challenges for governments to adopt AI for urban service delivery. The methodological approach includes data collection through an online survey from Australia and Hong Kong and statistical analysis of the data through binary logistic regression modeling. The study finds that: (a) Attitudes toward AI applications and ease of use have significant effects on forming an opinion on AI; (b) initial thoughts regarding the meaning of AI have a significant impact on AI application areas and adoption challenges; (c) perception differences between the two countries in AI application areas are significant; and (d) perception differences between the two countries in government AI adoption challenges are minimal. The study consolidates our understanding of how the public perceives the application areas and adoption challenges of AI, particularly in urban services, which informs local authorities that deploy or plan to adopt AI in their urban services. |
Type: | Peer Reviewed Journal Article |
URI: | http://hdl.handle.net/20.500.11861/8412 |
ISSN: | 2610-9182 |
DOI: | 10.28991/ESJ-2022-06-06-01 |
Appears in Collections: | Economics and Finance - Publication |
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