Project Resilience was initiated under the Global Initiative on AI and Data Commons to build a public AI utility where a global community of innovators and thought leaders can enhance and utilize a collection of data and AI approaches to help with better preparedness, intervention, and response to environmental, health, information, or economic threats to our communities, and contribute the general efforts towards meeting the Sustainable Development Goals (SDGs). More info about Project Resilience here.
The goal of the Minimum Viable Product (MVP) track is to develop an MVP platform that will enable collaborative AI models to accelerate the United Nations sustainable development goals.
The MVP working group works in two tracks, Data and Architecture, to produce the following deliverables:
The collaboration between XPRIZE, Cognizant, ITU, and Oxford University via the Pandemic Response Challenge demonstrated how we could convene a group of experts – data scientists, epidemiologists, public health officials, to build a useful set of tools to advise us on how to cope with and plan around a health disruption to society. Have a look at the competition's GitHub repo for an example of APIs and architecture that were used for the challenge.
Find us on Slack at: bit.ly/project-resilience
The UN currently has 17 Sustainable Development Goals. The goal of the MVP track is to focus on a few of them to demonstrate how AI models can help.
Please read Project Resilience Data Requirements and Tips for a description of how to assemble a Project Resilience dataset.
Goal 13 - Climate Action - Take urgent action to combat climate change and its impacts
One approach can be: what can countries, or regions, do to transition to clean energy?
Please have a look at the draft dataset description and help gather the data.
Proposed architecture for Project Resilience: PDF