AI for Anticipatory Action: Moving Beyond Climate Forecasting
Benjamin Q. Huynh Mathew V. Kiang
Disaster response agencies have been shifting from a paradigm of climate
forecasting towards one of anticipatory action: assessing not just what the
climate will be, but how it will impact specific populations, thereby enabling
proactive response and resource allocation. Machine learning models are
becoming exceptionally powerful at climate forecasting, but methodological gaps
remain in terms of facilitating anticipatory action. Here we provide an
overview of anticipatory action, review relevant applications of machine
learning, identify common challenges, and highlight areas where machine
learning can uniquely contribute to advancing disaster response for populations
most vulnerable to climate change.