How can AI help reduce the burden of disaster management decision-making?

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.