Modernizing DC’s Emergency Communications
Thane Douglass, Anuoluwapo Soneye · Team AI-CAD
Submitted to AI Policy Hackathon at Johns Hopkins University. Sprint projects are early-stage work by participants, not Apart Research publications.
The District of Columbia proposes implementing an AI-enabled Computer-Aided Dispatch (CAD) system to address critical deficiencies in our current emergency alert infrastructure. This policy establishes a framework for deploying advanced speech recognition, automated translation, and intelligent alert distribution capabil- ities across all emergency response systems. The proposed system will standardize incident reporting, eliminate jurisdictional barriers, and ensure equitable access to emergency information for all District residents. Implementation will occur over 24 months, requiring 9.2 million dollars in funding, with projected outcomes including forty percent community engagement and seventy-five percent reduction in misinformation incidents.
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Cite this project
@misc{douglass2024modernizing,
title = {{Modernizing DC’s Emergency Communications}},
author = {Thane Douglass and Anuoluwapo Soneye},
year = {2024},
month = nov,
note = {Submitted to AI Policy Hackathon at Johns Hopkins University, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/modernizing-dc-s-emergency-communications}},
url = {https://apartresearch.com/sprints/projects/modernizing-dc-s-emergency-communications}
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