Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane |
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| Affiliation: | 1. School of Architecture and Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia;2. School of Civil and Environmental Engineering, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia;1. Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, OH 43210, USA;2. Department of Physics, The Ohio State University, Columbus, OH 43210, USA;3. Brookhaven National Laboratory, Bldg 510, Upton, NY 11973, USA;4. Fermi National Accelerator Laboratory, P. O. Box 500, Batavia, IL 60510, USA;5. Kavli Institute for Particle Astrophysics & Cosmology, P. O. Box 2450, Stanford University, Stanford, CA 94305, USA;6. SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA;7. Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, Casilla 603, La Serena, Chile;8. Department of Physics & Astronomy, University College London, Gower Street, London, WC1E 6BT, UK;9. Department of Physics and Electronics, Rhodes University, PO Box 94, Grahamstown, 6140, South Africa;10. CNRS, UMR 7095, Institut d’Astrophysique de Paris, F-75014, Paris, France;11. Sorbonne Universités, UPMC Univ Paris 06, UMR 7095, Institut d’Astrophysique de Paris, F-75014, Paris, France;12. Laboratório Interinstitucional de e-Astronomia - LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ - 20921-400, Brazil;13. Observatório Nacional, Rua Gal. José Cristino 77, Rio de Janeiro, RJ - 20921-400, Brazil;14. Department of Astronomy, University of Illinois, 1002 W. Green Street, Urbana, IL 61801, USA;15. National Center for Supercomputing Applications, 1205 West Clark St., Urbana, IL 61801, USA;16. Institut de Ciències de l’Espai, IEEC-CSIC, Campus UAB, Carrer de Can Magrans, s/n, 08193 Bellaterra, Barcelona, Spain;17. Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, 08193 Bellaterra (Barcelona), Spain;18. Institute of Cosmology & Gravitation, University of Portsmouth, Portsmouth, PO1 3FX, UK;19. School of Physics and Astronomy, University of Southampton, Southampton, SO17 1BJ, UK;20. Excellence Cluster Universe, Boltzmannstr. 2, 85748 Garching, Germany;21. Faculty of Physics, Ludwig-Maximilians University, Scheinerstr. 1, 81679 Munich, Germany;22. Department of Astronomy, University of Michigan, Ann Arbor, MI 48109, USA;23. Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA;24. Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA;25. Max Planck Institute for Extraterrestrial Physics, Giessenbachstrasse, 85748 Garching, Germany;26. Universitäts-Sternwarte, Fakultät für Physik, Ludwig-Maximilians Universität München, Scheinerstr. 1, 81679 München, Germany;27. Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA;28. Australian Astronomical Observatory, North Ryde, NSW 2113, Australia;29. George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, and Department of Physics and Astronomy, Texas A&M University, College Station, TX 77843, USA;30. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA;31. Department of Physics and Astronomy, Pevensey Building, University of Sussex, Brighton, BN1 9QH, UK;32. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain;33. Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, USA |
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| 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. |
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| Keywords: | artificial intelligence (AI) Disaster management Disaster preparedness Disaster response Disaster recovery Public perception |
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