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Summary
Artificial intelligence and data-science techniques can help improve the ability of developing countries to respond to future epidemics.

Across the world, artificial intelligence (AI) and data-science research is showing promise for early COVID-19 detection, timely communications with the public, new diagnostic tools, and informed policy and public health responses that can be automated, implemented and scaled affordably. AI and data-science methodologies are particularly well suited to pattern recognition, forecasting, and automation.  

Despite the positive potential of AI and data innovations, it is important to understand the potential ethical, legal, and socio-economic ramifications that could emerge from their misuse in emergency contexts, especially to safeguard rights and ensure inclusive approaches to response and recovery. For example, while citizens might be more willing to forgo their civil liberties in the short term to address the COVID-19 challenge, most low- and middle-income countries lack strong privacy legislation and data-protection laws.

Funded by the Swedish International Development Cooperation Agency (Sida) and IDRC, with support from Pulse Lab Jakarta of the United Nations Global Pulse network, the CA$12.65-million Global South AI4COVID Response program supports nine multidisciplinary research projects across Asia, Latin America, and sub-Saharan Africa to combat the negative impacts of COVID-19 and strengthen health systems to improve pandemic response.

The initiative is structured around three major approaches:  

  • deepening understanding of how to develop and scale responsible, evidence-based, and proven AI and data-science approaches that support COVID-19 response and recovery in developing countries 

  • informing policies and implementation, both organizationally and nationally, that support and build trust in AI and data-science responses to epidemics, and mitigating potential social and economic harms

  • strengthening research capacity and the capacity of health systems in developing countries to respond to epidemics through the use of AI and data-science techniques.   

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