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Over the past decade, major advancements in transparency and reproducibility, from data and code sharing to pre-analysis plans and replication efforts, have reshaped empirical research. But the field is now at a turning point: AI and increasingly complex computational methods are transforming how we analyze ever-larger, often confidential datasets. These advances promise more timely and granular insights, but also raise new questions: How can we ensure research remains trustworthy and reproducible? How do we balance openness with privacy and security? And how do we keep up with the pace of technological change?
The World Bank’s Development Impact Group (DECDI), Development Data Group (DECDG), and Data Academy, the Center for Effective Global Action (CEGA), and the University of Chicago’s Becker Friedman Institute for Economics are excited to explore these questions at the 12th annual Measuring Development (MeasureDev) Conference, “Open Science in the Age of AI: Balancing Privacy and Transparency.”
MeasureDev 2026 will bring together policymakers, researchers, and practitioners who are shaping the future of transparent, credible, and privacy-aware evidence generation. The event will reflect on a decade of progress in open science, spanning data and code sharing, pre-analysis plans, replication initiatives, and more, while charting a path forward for transparency and replicability in research in light of rapid changes in technology, data access, and computational methods.