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How Can AI Help Reduce the Burden of Disaster Management Decision-Making?

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Advances in Human Factors and Systems Interaction (AHFE 2018)

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Abstract

Disaster management is a decision-making scenario where humans are faced with the assessment and prioritization of a large number of conflicting courses of action and the pressing need to take difficult trade-offs (e.g., ethical, technical, cost-benefit) for selecting and assigning often very scarce resources in response to overwhelming humanitarian crises. The paper discusses the contribution of Artificial Intelligence methodologies for the development of Intelligent Systems that support decision-makers in the context of disaster management, providing examples of alternative methodologies for collecting and representing imprecise information, modeling the inference processes, and to convey naturalistically formulated recommendations and explanations to system users, also encompassing a User Experience perspective, addressing users’ needs and requirements, the decision-making environment, equipment and task while using an Intelligent System that provides the support to their functions.

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References

  1. Vohs, K.D., Baumeister, R.F., Schmeichel, B.J., Twenge, J.M., Nelson, N.M., Tice, D.M.: Making choices impairs subsequent self-control: a limited-resource account of decision making, self-regulation, and active initiative. J. Pers. Soc. Psychol. 94(5), 883–898 (2008)

    Article  Google Scholar 

  2. Inzlicht, M., Schmeichel, B.J.: Beyond limited resources: self-control failure as the product of shifting priorities. In: Vohs, K.D., Baumeister, R.F. (eds.) The Handbook of Self-Regulation: Research, Theory, and Applications (3rd Edition), pp. 165–181. Guilford Press, New York (2016)

    Google Scholar 

  3. Baumeister, R.F., Vohs, K.D., Tice, D.M.: The strength model of self-control. Curr. Dir. Psychol. Sci. 16(6), 351–355 (2007)

    Article  Google Scholar 

  4. Oxford University Press. https://en.oxforddictionaries.com/definition/artificial_intelligence

  5. Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach, 3rd edn. Prentice Hall Press, Upper Saddle River (2010)

    MATH  Google Scholar 

  6. Tversky, A., Kahneman, D.: Judgment under uncertainty: heuristics and biases. Science 185(4157), 1124–1131 (1974)

    Article  Google Scholar 

  7. Simon, H.A.: Theories of bounded rationality. In: McGuire, C.B., Radner, R. (eds.) Decision and Organization, pp. 161–176. North-Holland Publishing Company (1972)

    Google Scholar 

  8. Bossaerts, P., Murawski, C.: Computational complexity and human decision-making. Trends Cogn. Sci. 21(12), 917–929 (2017)

    Article  Google Scholar 

  9. Correia, A., Severino, I., Nunes, I.L., Simões-Marques, M.: Knowledge management in the development of an intelligent system to support emergency response. In: Nunes, I. (ed.) Advances in Human Factors and Systems Interaction. AHFE 2017. Advances in Intelligent Systems and Computing, vol. 592, pp. 109–120. Springer, Cham (2018)

    Google Scholar 

  10. Simões-Marques, M.J.: Facing disasters—trends in applications to support disaster management. In: Nunes, I.L. (ed.) Advances in Human Factors and System Interactions. Advances in Intelligent Systems and Computing, vol. 497, pp. 203–215. Springer, Cham (2017)

    Google Scholar 

  11. NAS: Facing hazards and disasters - understanding human dimensions. In: Kreps, G.A., Berke, P.R., et al. (eds.) National Academy of Sciences. National Academies Press, Washington, D.C. (2006)

    Google Scholar 

  12. UNISDR Terminology. https://www.unisdr.org/we/inform/terminology

  13. Turban, E., Sharda, R., Delen, D.: Decision Support and Business Intelligence Systems, 9th edn. Prentice Hall Press, Upper Saddle River (2011)

    Google Scholar 

  14. Turban, E., Aronson, J.E., Liang, T.P.: Decision Support Systems and Intelligent Systems, 7th edn. Prentice-Hall of India, Inc., New Delhi (2007)

    Google Scholar 

  15. Zimmermann, H.-J.: Fuzzy Set Theory—and Its Applications. Springer, Netherlands, Dordrecht (2001)

    Book  Google Scholar 

  16. Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning - I. Inform. Sci. 8(3), 199–249 (1975)

    Article  MathSciNet  Google Scholar 

  17. Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning - II. Inform. Sci. 8(4), 301–357 (1975)

    Article  MathSciNet  Google Scholar 

  18. Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning - III. Inform. Sci. 9(1), 43–80 (1975)

    Article  MathSciNet  Google Scholar 

  19. Zimmermann, H.-J., Zysno, P.: Latent connectives in human decision making. Fuzzy Sets Syst. 4(1), 37–51 (1980)

    Article  Google Scholar 

  20. Werners, B.M.: Aggregation models in mathematical programming. In: Mathematical Models for Decision Support, vol. 48, pp. 295–305, Springer, Berlin (1988)

    Chapter  Google Scholar 

  21. ISO 9241-210:2010: Ergonomics of human-system interaction – Part 210: human-centred design for interactive systems. ISO (2010)

    Google Scholar 

  22. Simões-Marques, M., Correia, A., Teodoro, M.F., Nunes, I.L.: Empirical studies in user experience of an emergency management system. In: Nunes I. (ed.) Advances in Human Factors and Systems Interaction. AHFE 2017. Advances in Intelligent Systems and Computing, vol. 592, pp. 97–108. Springer, Cham (2018)

    Google Scholar 

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Acknowledgments

The work was funded by the Portuguese Ministry of Defense and by the Portuguese Navy.

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Correspondence to Mário Simões-Marques .

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Simões-Marques, M., Figueira, J.R. (2019). How Can AI Help Reduce the Burden of Disaster Management Decision-Making?. In: Nunes, I. (eds) Advances in Human Factors and Systems Interaction. AHFE 2018. Advances in Intelligent Systems and Computing, vol 781. Springer, Cham. https://doi.org/10.1007/978-3-319-94334-3_14

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