The Covid-19 pandemic pushed many countries to employ novel methods for distributing aid to impacted communities, including new data-driven technological approaches. Using social impact scenarios, Zoe Kahn and Joshua Blumenstock’s research examines the unanticipated dynamics that may arise from data-driven technical policies. Looking at Togo’s scheme to provide aid via a data-driven system based on recipients’ mobile money accounts, they reveal 3 unanticipated dynamics in this approach that would potentially negatively impact who receives aid as well as how the target community perceives this policy.
