New Global Coalition Aims To Help Policymakers Leverage AI Against COVID-19

A new coalition, backed by US-based think tanks and UN agencies, announced on Thursday a new effort to help policymakers around the globe leverage AI in the battle against the COVID-19 pandemic. The newly-formed Collective and Augmented Intelligence Against Covid-19 (CAIAC) is building a platform that relies on both AI and human expertise to guide COVID-19 decision-making. 

The group plans to leverage data sets spanning health, social and economic data related to COVID-19, "to make sure we can actually make sense of this vast amount of data" being generated, according to Cyrus Hodes, chair of the AI Initiative at the nonprofit think tank the Future Society.  

"I don't think we'll be able to solve this without the help of various data sets and AI tools," Hodes said to ZDNet. "Pretty much the whole world understands this."

The Future Society is establishing CAIAC along with the Stanford Institute for Human-Centered Artificial Intelligence, with support from UNESCO (an agency within the UN) and the Patrick J. McGovern Foundation. The alliance will establish an advisory group that includes UNESCO and other UN entities, including UN Global Pulse (an initiative of the United Nations that attempts to "bring real-time monitoring and prediction to development and aid programs"). 

The group is working closely with private sector partners to get the platform off the ground, including C3.ai, stability.ai, Element AI, Axis, GLG and Planet. 

The idea behind the alliance, and the platform they're building, is anchored in the Global Data Access Framework (GDAF), a UN initiative to use the power of big data and AI to achieve the UN's 17 Sustainable Development Goals (SDGs).

Initially, the alliance is focusing on three uses cases for the platform, zeroing in on use cases that are especially relevant for multilateral organizations: 

• Tracking and tracing of contagion chains via mobility data and artificial intelligence  
• Identifying and addressing inaccurate information on COVID-19

• Finding marginalized areas most affected by second and third order pandemic impacts to deploy the appropriate interventions needed.

"We are basing this on pretty much all data sets that can be available," Hodes said. For instance, for the third use case -- helping marginalized communities -- the alliance could tap into mobility data and telco data, transaction data, or even satellite data. The group will try to "think outside the box," he said. 

The effort joins a number of other initiatives focused on using AI and big data to respond to the ongoing COVID-19 crisis. In May, Microsoft announced it's partnering with a Seattle-based biotechnology firm to launch a virtual clinical study to map the immune response to COVID-19. IBM, meanwhile, unveiled a new, open-source toolkit designed for developers and data scientists that want to help spot trends in the ongoing COVID-19 pandemic. Back in March, a unique cooperative effort between academic, government and industry researchers unveiled structured data set that the worldwide machine learning community can use to advance COVID-19 research.