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Public perceptions on artificial intelligence driven disaster management - Evidence from Sydney, Melbourne and Brisbane4.51 MB
Accepted VersionCC BY-NC-ND V4.0, Open Access
Journal article
Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney, Melbourne and Brisbane
Telematics and Informatics, Vol.65, pp.1-16
2021
Abstract
In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.
Details
- Title
- Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney, Melbourne and Brisbane
- Authors
- Nayomi Kankanamge - Queensland University of TechnologyTan Yigitcanlar (Corresponding Author) - Queensland University of TechnologyAshantha Goonetilleke - Queensland University of Technology
- Publication details
- Telematics and Informatics, Vol.65, pp.1-16
- Publisher
- Elsevier Ltd
- Date published
- 2021
- DOI
- 10.1016/j.tele.2021.101729
- ISSN
- 1879-324X; 0736-5853
- Organisation Unit
- School of Law and Society
- Language
- English
- Record Identifier
- 991068684302621
- Output Type
- Journal article
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