Planetary Causal Inference - Concept
Causal insight at planetary scale is within reach. Understanding how interventions ripple through society, economy, and environment demands tools that span from individual villages to the entire globe. Traditional surveys and national statistics are costly, slow, and spatially coarse---limiting our ability to diagnose and evaluate policies where they matter most.
To address these limitations, Planetary Causal Inference (PCI) unifies Earth‐observation data with randomized and quasi-experimental studies. By aligning high-resolution satellite imagery with localized RCTs and field studies, we can identify causal processes across scales—linking pixel-level changes to human outcomes on the ground.
We launched PCI with this objective: to engineer methods, software, and data pipelines that deliver robust causal estimates from planetary-scale observations. Every research agenda, collaboration, and code repository flows from this imperative—to make causal inference as global as the problems it seeks to solve.
Just as flight only matters when it’s safe, causal insights only matter when they’re reliable and reproducible. We are committed to open-source data and tools, along with rigorous benchmarking. We prioritize ethical data use, respect for local contexts, and interdisciplinary exchange among statisticians, computer scientists, geographers, and social scientists.
We will advance methods as fast as our computational capacity grows, ensuring that each innovation is based on on-the-ground realities. Together, we can empower policymakers, practitioners, and communities with the causal knowledge needed to navigate and act on our interconnected planet.
-- Connor & Adel