Data Responsibility and Digital Remote Targeting During COVID-19

Challenges due to the pandemic have led to all kinds of innovations and adaptations focused on remote targeting, enrolment, verification and delivery. While required for the ongoing COVID-19 crisis, these new approaches might be useful in future responses that require remote targeting and delivery, such as in fragile contexts. 

This case study explores digital remote targeting approaches that GiveDirectly is using for cash assistance, and ways that the organization is addressing data responsibility. Early results indicate that the approach they have taken has been effective at quickly delivering COVID-19-related cash transfers to a large number of individuals living in extreme poverty in record time. 

The World Bank predicts that COVID-19 could push up to 150 million people into poverty by the end of 2021, depending on how severely the pandemic affects the world economy. This would be the first time that global poverty has risen in the past 20 years. This unprecedented situation has brought new challenges: how to deliver CVA at huge scale; as quickly, inclusively and accurately as possible; to previous recipients and to a rapidly increasing number of people who are now eligible due to COVID-19, and all without physical contact? The pandemic has made standard CVA processes impossible in some contexts. The scale of the crisis has led to discussions, collaboration and cross-learning between humanitarian organizations and those working on social protection programming. While social protection programming is normally done in partnership with governments, humanitarian CVA tends to be directed towards populations that government social protection programmes do not cover. COVID-19 has blurred some of these lines, and many in the CVA sector are calling for closer collaboration and learning.

In the case study, we discuss how one of GiveDirectly’s COVID-19 response programmes leverages machine-learning technology to complement an existing government run social safety net.