Hype versus Historical Continuity: Situating the Rise of AI in Climate and Disaster Risk Modeling

As governments increasingly adopt Artificial Intelligence (AI) across different application sectors, advocates argue that it will create new disruptions by democratizing access, improving accuracy, and lowering costs. In practice, uncritical adoption of AI tools has been shown to cause significant harms. Our study uses a historical lens to examine the uptake of AI in climate risk management through a study of climate and disaster risk modeling. These techniques originated in the insurance industry, but are now incorporated into many climate and disaster governance processes. Using the concept of ‘insurance logics’, we demonstrate that many of the original aspects of disaster risk modeling remain despite the transfer of risk assessment tools from the insurance industry to the public sector and new techniques made possible by AI. This highlights technological continuity, rather than disruption, as a key driver of contemporary risk modeling practice. Doing so helps to unsettle problematic, though challenging to identify, aspects of supposedly disruptive technologies and create possibilities for alternatives.