  Natural experiments are observational studies where the assignment of
treatment conditions to different populations occurs by chance "in the wild".
Researchers from fields such as economics, healthcare, and the social sciences
leverage natural experiments to conduct hypothesis testing and causal effect
estimation for treatment and outcome variables that would otherwise be costly,
infeasible, or unethical. In this paper, we introduce VAINE (Visualization and
AI for Natural Experiments), a visual analytics tool for identifying and
understanding natural experiments from observational data. We then demonstrate
how VAINE can be used to validate causal relationships, estimate average
treatment effects, and identify statistical phenomena such as Simpson's paradox
through two usage scenarios.
