The School Closure Awareness System
Description
To efficiently and accurately identify and categorize unplanned school closures across the U.S. using publicly available social media data, replacing a costly and labor-intensive manual process.
Detailed example
The system processes Facebook posts from about 40,000 school or district accounts, using a large language model to categorize posts as unplanned school closures (by event type: weather, health, facility, safety) and denote status changes (full closure, virtual, hybrid, early/late dismissal). Outputs are reviewed and recoded by staff every 24 hours.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
The AI system has saved nearly $2 million in contracting fees and reduced human work hours by 200 hours. It enables faster, more comprehensive, and more detailed capture of unplanned school closure data than the previous manual process, supporting CDC’s emergency response and reporting obligations.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Publicly available Facebook posts from approximately 40,000 school or district accounts.