How can the human dimensions of disaster impacts be more accurately captured and represented in the analysis, modeling and simulation of disasters?
First; I would recommend enhancing “social sensing” technologies to capture and understand impacts on social and human activities. It is obviously impossible to directly monitor an individual's activities; how each of us is impacted; what support does each of us require. By many means and forms; our activities can be observed/interpreted through lifeline; traffic and economic data. Besides; we even send signals of our activities using our mobile phones; SNS. But all these data are incomplete; heterogeneous; inconclusive and sparse. The key technology will be “multi-source data fusion”; the process of integrating multi-data sources to gain more consistent; reliable; and useful information than that provided by any individual data source. Second; “Digital Twin”; the fusion of data-interpretation-inference; to capture the real physical world from various sensors and simulations; creating a copy (or twin) in the virtual world (on a computer); running simulations with the copied data to find out optimal solutions for enhancing disaster resilience; and provide the insights into the physical world’s policy or decision. AI (Artificial Intelligence) is one of the key elements of Digital Twin; but the goal is a deployment of a mixed-initiative of human and machine (computer) systems as the emergence of collective intelligence (see answer to Q3). I believe that it emerged from the convergence of disaster science research from multiple disciplines with a deep understanding of physical and social systems.
What type of data and supporting research infrastructure would be necessary to enable novel, transdisciplinary approaches to answering these and other human-centered disaster questions?
I strongly emphasize the importance of “evidence” in disaster science. The process to gain scientific evidence is similarly discussed as a process to gain knowledge. One could argue that the so-called ”data-information-knowledge- wisdom(DIKW) pyramid” has been widely used to demonstrate how the deep understanding of the subject emerges; passing through the 4 qualitative stages. Disaster science needs a concrete structure to gain knowledge based on evidence. Considering what constitutes Collective Intelligence (see the answer to Q3) in disaster science; those can be human minds; computers; models and AI derived by data; information; more to say things derived from ”evidences”. Inspired by Prof. Alexander of UCL discussing the importance of evidence in disaster science; my proposal sets out the following critical questions from the belief that evidence are the essential members of collective intelligence; Q1 What exactly is evidence in disaster management; and how can (should) disaster science provide evidence? Q2 How much evidence should be derived from direct experience or from indirect sources? Q3 How disaster resilience can be quantified and discussed in an evidence-based manner? Q4 How much evidence is enough for decision making towards a resilient society?
In what ways can US-Japan collaborations advance these questions in new and important ways?
I propose a project that will develop an advanced studies initiative to pursue ”Emergence of Collective Intelligence in Disaster Science (ECI-DS)” that emerges as a consequence of collaborations; collective efforts; and competition of many individuals and appears in policy making of enhancement of disaster resilience. Collective intelligence emerges from the collaboration; collective efforts; and competition of many individuals and appears as intelligence in consensus decision making. Prof. Malone of MIT identifies novel forms of collective intelligence to be created that are larger and more sophisticated than any that have previously existed. He uses the term ”supermind” which means ”a group of individuals acting together in ways that seem intelligent”. It is important to note that ”individual” includes not only humans; but also computers; models; and AI (Artificial Intelligence).Disaster science; which aims to solve social problems; is probably believed to most utilize ”convergence of knowledge”; a fusion of knowledge in the humanities and social sciences and in the natural sciences. Is this proposition true? This research proposal has a hypothesis that ”convergence of knowledge” in disaster science is NOT enough. Certainly; research that claims to be a fusion of the humanities and natural sciences has been conducted for a long time. But the scientific framework and discipline have depended on the respective fields since we say ”multi- or interdisciplinary”. In other words; there is possibly a lack of common discipline for disaster science. This is my hypothesis; and I will try to convince the disaster science community through this great challenge.