AI and Disaster Risk: A Practitioner Perspective

Abstract

Emerging techniques developed by AI researchers promise to offer the capacity to support disaster risk management (DRM), through making data collection or analysis practices faster, less costly, or more accurate. However, in every socially consequential domain in which AI tools have been applied, these technologies have been demonstrated to have some degree of negative consequences. This paper explores an attempt to convene technical experts in the area of DRM to discuss potential negative impacts, their approaches toward mitigating these impacts as well as identifying some of the overarching challenges. In doing so, we contribute new findings about a domain that has received relatively little attention from critical and ethical AI researchers, and the opportunities and limitations that are presented by working with domain experts to evaluate the social consequences of emerging technologies.