Microsoft AI for Good Lab – Introduction to HASTE

  • Juan M. Lavista Ferres, Microsoft; Caleb Robinson, Microsoft; Cameron Birge; Kevin White

The Microsoft AI for Good Lab introduces HASTE, its open-source rapid building-damage assessment tool that turns post-disaster satellite, aerial, or drone imagery into building-by-building damage classifications in minutes. Through live demonstrations from real responses, the team shows both the interactive in-browser labeling workflow and the original semantic-segmentation approach, along with built-in validation tooling. The session also covers accuracy and validation, imagery sources, hard cases like flooding, and how results are activated and shared—with HASTE now fully open source for humanitarian and disaster-response organizations to run on their own infrastructure and build on via GitHub.

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