Big data for development: bridging the gap between machine learning and human learning
Big data presents new opportunities for innovative research in international development. In this webinar, a panel of experts drew on real-world applications in this area to reflect on key questions for the field, such as: Is the term "big data" even useful? When do the benefits of big data outweigh its blind spots? Will low-touch measurement become the new normal?
Time: 14:45 – 16:00 GMT
- Alessandra Garbero, IFAD;
- Maria Ruth Jones, DIME, World Bank;
- Michael Bamberger, Independent Consultant;
- Douglas Glandon, 3ie
- Tom Wilkinson, Head of Data Science, International Development, FCDO
As the buzz around using big data to measure development effectiveness and guide decision-making continues to build, a growing number of examples of real-world applications add nuance to our understanding of opportunities and limitations. Increasingly sophisticated and accessible tools and methods provide new options and new blind spots in data-informed decision-making. This panel discussion focused on the use of big data in impact evaluation, program targeting and monitoring, and predictive analytics in international development. Each panellist brought a different perspective to this discussion, which focused on several key themes: 1) Innovations in big data for development 2) Practical applications in the context of time urgency and resource scarcity; 3) Research uptake and use for policy, programming; 4) Future direction - forecasts and forewarnings.