The COVID-19 pandemic has significantly impacted global economies, prompting governments to implement social protection measures. The crisis has also limited traditional data collection methods for social protection programs, leading to a shift towards digital data sources such as digitized administrative databases and behavioural trace data. This webinar presented a report and explored novel data sources, their potential for long-term integration, and associated ethical challenges.

The report examines five novel digital data types: satellite imagery, mobile phone data, web and social media data, digital finance, and integrated digitized administrative databases. It discusses the potential applications and challenges of using these sources for social protection and offers case studies from various countries.

As temporary pandemic-related programs are phased out, it remains to be seen whether these digital data innovations will be integrated into regular social protection systems. We also address key social and ethical concerns, including digital exclusion, data access, privacy, transparency, and fairness. The report concludes with a summary and recommendations for practitioners considering the use of these data sources in social protection contexts.

Speakers

Emily Aiken, Data Science and Social Protection Expert

Tim Ohlenburg, Data Science, Machine Learning and Social Protection Expert

Alvaro Farias Velasco, Director of Climate Change and Catastrophe Risk, Prosperia

Lauro Bermeo, World Bank Social Protection Specialist, former DRC STEP-KIN Project

Joan Lopez Solano, Researcher and Policy Officer on the Global Data Justice project, Tillburg University.

Resources:

Novel digital data sources for social protection: opportunities and challenges