Next-Gen AI-Enhanced Epidemic Intelligence
Axby Loh, Waikit Fung, Anthony Li · Team SmartNation
Submitted to AI Policy Hackathon at Johns Hopkins University. Sprint projects are early-stage work by participants, not Apart Research publications.
Policies for Equitable, Privacy-Preserving, Sustainable & Groked Innovations for AI Applications in Infectious Diseases Surveillance
Reviews
Relevance is clearly address and ethical concerns, impact isn't fully elaborated and policy feasibility is lacking
On layout: generally follows template although densely packed; On content: while certainly of relevance and with the potential for high impact, not clear how any of the highlighted AI infrastructure needs, oversight measures, and ethical issues would all be feasible and cooridinated amongst the various stakeholders.
Overall, really good. Liked how specific it was and how relevant it was. Unfortunately, it was less feasible and did not have a solid impact
Very polished idea and presentation.
Cite this project
@misc{loh2024nextgen,
title = {{Next-Gen AI-Enhanced Epidemic Intelligence}},
author = {Axby Loh and Waikit Fung and Anthony Li},
year = {2024},
month = oct,
note = {Submitted to AI Policy Hackathon at Johns Hopkins University, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/next-gen-ai-enhanced-epidemic-intelligence}},
url = {https://apartresearch.com/sprints/projects/next-gen-ai-enhanced-epidemic-intelligence}
}More from AI Policy Hackathon at Johns Hopkins University
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