About

PlanetaryCausalInference.org was created by Connor T. Jerzak to showcase the work of researchers, many in the AI & Global Development Lab, involved in work related to Planetary Causal Inference, as well as to provide information about a book project (with Adel Daoud) of the same name. This work has been funded by, among others, the Swedish National Space Agency and the Swedish Research Council.

Mission

Listen
Listen 1:47

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


Contact

Connor T. Jerzak, Assistant Professor
Department of Government, University of Texas at Austin, connor.jerzak@austin.utexas.edu
[Bio] [CV]
[Website Feedback] [PCI Narrative]

Adel Daoud, Senior Associate Professor
Institute for Analytical Sociology, Linköping University; Affiliated Associate Professor in Data Science & AI, Chalmers University of Technology, Sweden, adel.daoud@liu.se
[Bio]

Adel

PCI logo (light) PCI logo (dark)

Connor

Posts

Scaling Laws for Multi-scale Dynamics

Policymakers and researchers analyzing randomized controlled trials (RCTs) increasingly harness satellite imagery to capture the geographical, socioeconomic, or environmental covariates believed to moderate an intervention’s impact. Some of those moderating factors might be locally confined—such as...Continue reading

New Directions in Planetary Causal Inference

Planetary causal inference (PCI) is a field where we draw on experimental, observational, or natural experimental data from social, natural, and environmental sciences and link those sources to satellite imagery or other Earth Observation (EO) data....Continue reading

Earth Observation Meets Adam Smith

Satellite imagery is contributing to how we measure and understand global poverty. From miles above Earth, high-resolution photographs capture details of villages, farms, and cities that conventional surveys might have a hard time capturing. By analyzing these...Continue reading

Introducing the PCI RCT Repo

Randomized controlled trials (RCTs) long ago proved themselves as workhorses of rigorous social science, medical research, and policy evaluation. Yet, they can struggle to account for the spatial and contextual heterogeneity of real-world settings: there are so many factors....Continue reading

Connect

[Return to Home]